Multi-source data fused infectious disease epidemic situation wave monitoring and early warning method, system and equipment

Abstract

The invention provides an infectious disease epidemic situation wave monitoring and early warning method, system and device fused with multi-source data, and the method comprises the steps: building an epidemic situation wave monitoring and early warning concept and a technical mode graph based on the normal distribution of a new case number histogram in unit time of an infectious disease monitoring region, accumulating three boundary points and four stages of the concave-convex features of a case number curve graph, and carrying out the early warning of the epidemic situation wave. Determining epidemic situation wave nodes, inflection points and natural histories of epidemic situation wave start, rise, mitigation, decline and the like; based on epidemic situation wave multi-source data information types and concepts, definitions and indexes of monitoring circulation, effective monitoring, staged measurement, subject measurement, effective early warning, key node early warning, key prevention, key control and the like, epidemiological causes, etiological causes, propagation modes, warning conditions and mitigation conditions of epidemic situation wave natural history are determined; and formulating and executing prevention and control strategies and measures in corresponding stages. The method can more effectively study and judge the situation and consequence of the epidemic situation, determine the natural history and mechanism of the epidemic situation and implement prevention and control strategies and measures.

Description

Technical Field

[0001] This invention relates to the field of infectious disease prevention and control technology, and in particular to a method, system and equipment for monitoring and early warning of infectious disease outbreaks by integrating multi-source data. Background Technology

[0002] Currently, in the field of infectious disease outbreak monitoring and early warning, a universally standardized methodology or technical system has not yet been established. Existing technologies reveal numerous problems. First, there is a serious lack of clear definitions at the conceptual and definitional level. Key concepts such as infectious disease outbreak waves, outbreak wave change nodes and inflection points, early detection and monitoring, effective monitoring and early warning, critical node early warning, key prevention and control, as well as outbreak wave staging measurement, epidemiological etiology, and virological etiology measurement lack clear definitions. This results in a lack of a unified theoretical foundation and technical framework for related research and practice. Second, there is a lack of systematic and collaborative methods or technologies to cover the entire process of infectious disease outbreak wave detection, monitoring, early warning, response, prevention, control, and assessment. Effective connections and collaboration between these stages are lacking, making it difficult to form a cohesive force for prevention and control. Third, there is no systematic and collaborative technical framework and roadmap to achieve the goals of comprehensive monitoring, effective monitoring, staging measurement, virological measurement, effective early warning, critical node early warning, and key prevention and control of infectious disease outbreak waves. This results in a lack of overall planning and scientific guidance for epidemic prevention and control. These problems ultimately led to a state of disorder, superficiality, and inefficiency in the monitoring and early warning of infectious disease outbreaks, with the results and conclusions often being vague and unclear, failing to meet actual prevention and control needs.

[0003] Therefore, there is an urgent need for a method, system, and equipment for monitoring and early warning of infectious disease outbreaks that integrates multi-source data to solve the above problems. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a method, system, and device for monitoring and early warning of infectious disease outbreaks by integrating multi-source data.

[0005] This invention provides a method for monitoring and early warning of infectious disease outbreaks by fusing multi-source data, comprising: Based on historical data of infectious disease cases in the region under infectious disease surveillance, epidemic wave nodes or turning points are identified, and epidemic wave staging is measured according to the epidemic wave nodes or turning points to dynamically construct an infectious disease epidemic wave trend map. Based on the real-time data of infectious disease cases in the infectious disease monitoring area during the current period and the infectious disease epidemic wave trend map, determine the target infectious disease epidemic wave multi-source data information type index corresponding to the infectious disease monitoring area during the current period; Based on the multi-source data information type indicators, monitoring and prevention effectiveness indicators, and effective monitoring targets of the target infectious disease epidemic wave, effective monitoring of infectious disease epidemic waves is carried out in the infectious disease monitoring area to obtain key data for effective monitoring. Based on the effective monitoring key data and the infectious disease epidemic wave trend map, the target epidemic wave turning point corresponding to the infectious disease monitoring area is determined, and based on the target epidemic wave turning point, key prevention and control strategies and measures for infectious diseases are implemented in the infectious disease monitoring area.

[0006] According to the present invention, a method for monitoring and early warning of infectious disease outbreak waves by fusing multi-source data includes determining outbreak wave nodes or outbreak wave turning points based on historical infectious disease case data of an infectious disease monitoring area over a historical period, and performing outbreak wave staging measurement based on the outbreak wave nodes or outbreak wave turning points to dynamically construct an infectious disease outbreak wave trend map, comprising: Based on the historical data of infectious disease cases in the monitored area during the historical period, the characteristics of the growth rate of cases and the trend of infectious disease epidemic fluctuations are obtained; Based on a preset unit time, the epidemic wave nodes corresponding to each time point in the historical period of the infectious disease monitoring area are constructed, and based on the fluctuation characteristics of the increase in the number of cases and the fluctuation process of the trend of the infectious disease epidemic, the epidemic wave turning point is determined from multiple epidemic wave nodes, wherein the epidemic wave turning point includes at least the turning point of the increase in the number of cases, the inflection point of the number of cases, and the turning point of the number of cases. Based on the historical number of infectious disease cases at the time points corresponding to the turning points of the epidemic wave, a cumulative case count curve of the infectious disease epidemic wave per unit time is generated; based on the historical number of new infectious disease cases at the time points corresponding to each epidemic wave node, a histogram of new cases per unit time is generated. Based on the cumulative number of cases per unit time curve and the histogram of new cases per unit time of the infectious disease epidemic wave, a trend chart of the infectious disease epidemic wave is constructed.

[0007] According to the present invention, a method for monitoring and early warning of infectious disease outbreak waves by fusing multi-source data is provided. The step of determining the target infectious disease outbreak wave information type index corresponding to the monitored area in the current time period based on real-time data of infectious disease cases in the monitored area and the infectious disease outbreak wave trend map includes: The real-time data of infectious disease cases are matched with the infectious disease epidemic trend map to determine the stage information corresponding to the infectious disease monitoring area in the infectious disease epidemic trend map. The stage information includes the initial stage of the increase in the number of infectious disease cases, the early stage of monitoring and early warning, the stage of rising cases, the middle and late stage of monitoring and early warning, the stage of growth plateau, and the stage of declining cases. Based on the aforementioned stage information, target infectious disease epidemic wave multi-source data information type indicators are determined from the multi-source data information type indicators of infectious disease epidemic waves. These multi-source data information type indicators include infectious disease ecology and environmental health observation indicators, epidemiological monitoring and risk factor analysis indicators, case infection monitoring and investigation and management indicators, case environmental pathogen and genomic monitoring indicators, pathogen variability and dominance detection indicators, and whole-process monitoring and effective response system evaluation indicators. The data information type indicators have inherent contradictions in terms of lead time and predictive deterministic value. The infectious disease ecology and environmental health observation indicators include infectious disease early warning information, abnormal health events, clustered cases, suspected environmental pollution sources, population immunity, and natural and social factors; The epidemiological surveillance and risk factor analysis indicators include information on the spread and changes of the epidemic, the distribution and scope of cases, information on exposed populations, information on sensitive populations, information on suspected pathogen sources, and transmission risks; The monitoring, investigation, and management indicators for infected cases include case tracking and management rate, morbidity rate, hospitalization rate, severe case rate, case fatality rate, mortality rate, infection rate, and transmission rate. The environmental pathogen and genomic monitoring indicators for the cases include pathogen identification, pathogen infectivity, pathogen pathogenicity, pathogen virulence, pathogen phenotype, pathogen molecular typing, and genome sequencing. The pathogen variability and dominance detection indicators include pathogen genetic diversity, pathogen genetic variability, pathogen genotype, pathogen dominant genotype adaptability, pathogen dominant genotype stability, and pathogen dominant genotype predictability. The evaluation indicators for the comprehensive monitoring and effective response system include epidemic wave performance, effective monitoring information, phased measurement, subject-specific measurement, effective early warning information, early warning information at key nodes, prevention and control effect, and prevention and control benefits.

[0008] According to the present invention, a method for monitoring and early warning of infectious disease outbreak waves by fusing multi-source data is provided. The method involves effectively monitoring the infectious disease outbreak wave in the monitored area based on the multi-source data information type indicators, monitoring and control effectiveness indicators, and effective monitoring targets of the target infectious disease outbreak wave, thereby obtaining key effective monitoring data, including: Based on the indicators of multi-source data information with full correlation, the monitoring objectives of epidemic changes and impact scope, the monitoring objectives of epidemic mechanisms and response strategies, and the research objectives of routine pathogen monitoring, the effective monitoring objectives are constructed. The epidemic wave performance, pathogen characteristics, natural and social factors, and transmission mechanism in the multi-source data information type indicators of the target infectious disease epidemic wave are used as primary indicators, and the monitoring and prevention effectiveness indicators are used as secondary indicators. The correlation between the multi-source data information type indicators of the target infectious disease epidemic wave and the prevention and control effectiveness indicators is established. Based on the correlation between the multi-source data information type indicators of the target infectious disease epidemic wave and the monitoring and prevention effectiveness indicators, the effective monitoring target is effectively monitored to obtain the key data of effective monitoring. The effective monitoring process consists of four cyclical components. The first cyclical component is used to monitor the population, location, and time of the infectious disease outbreak; the second cyclical component is used to monitor changes in cases, infected persons, pathogens, and risk factors; the third cyclical component is used to determine the epidemic wave monitoring and early warning, case and infected person follow-up, risk factors, and intervention targets; and the fourth cyclical component is used to conduct prevention and control interventions and evaluate the prevention and control effects.

[0009] According to the present invention, a method for monitoring and early warning of infectious disease outbreak waves by fusing multi-source data includes determining the target outbreak wave inflection point corresponding to the infectious disease monitoring area based on the effective monitoring key data and the infectious disease outbreak wave trend map, comprising: Obtain the target stage information of the epidemic wave in the infectious disease monitoring area during the current time period, as shown in the infectious disease epidemic wave trend graph. Based on the effective monitoring key data and the target stage information, stage measurement and subject measurement are performed to determine the turning point of the target epidemic wave corresponding to the infectious disease monitoring area. The stage measurement is based on the analysis of the epidemic characteristics and development trend of the epidemic wave at different stages; the subject measurement is based on multiple disciplines to analyze the characteristics of infectious diseases in different disciplinary dimensions.

[0010] According to the present invention, a method for monitoring and early warning of infectious disease outbreaks by fusing multi-source data is provided, wherein the step of implementing key prevention and control strategies for infectious diseases in the monitored area based on the key prevention period information corresponding to the turning point of the target outbreak wave includes: If the target epidemic wave turning point is the turning point of the number of cases, construct the first critical prevention period information. The first critical prevention period information includes infectious disease initiation information, abnormal health events, cluster cases, severe syndrome cases, case distribution and scope, transmission chain and transmission route, exposed population and scope of impact, suspected pathogen source and transmission risk, pathogen certainty and infectivity, pathogen phenotype or genotype, risk assessment, prevention and control strategies and measures, early warning of outbreak or epidemic start, and emergency plan information. If the turning point of the target epidemic wave is the inflection point of the number of cases, information on the second critical prevention period is constructed. The information on the second critical prevention period includes the manifestation and mechanism of the epidemic wave, the distribution and scope of cases, the mode of outbreak or epidemic transmission, key populations and high-risk populations, morbidity, mortality, infection rate, hospitalization rate, severe case rate, case fatality rate, pathogen source, infectivity, pathogenicity and virulence, pathogen variability, diversity, stability, drug resistance, dominance, adaptability and predictability; risk assessment, epidemic intensity warning, highest alert conditions, regional health cooperation, and prevention and control strategies and measures. If the turning point of the target epidemic wave is the turning point of the decline in the number of cases, information on the third critical prevention period is constructed. The information on the third critical prevention period includes the manifestation and mechanism of the epidemic wave, the intensity and degree of harm of the epidemic, the severity of the disease, the variability, diversity, stability, drug resistance, dominance, adaptability and predictability of pathogens, the transmission dynamics of environmental pathogens, population immunity, risk factors, risk assessment, mitigation conditions, prevention and control strategies and measures, and the risk of terminating the response. Based on the infectious disease epidemic wave trend map, the time points before the turning point of the epidemic wave corresponding to the first critical prevention period information, the second critical prevention period information, and the third critical prevention period information are determined as critical nodes, and early warning information corresponding to the critical nodes is constructed. Based on the early warning information and key prevention and control conditions corresponding to the key nodes, corresponding key control strategies and measures for the infectious disease are constructed, and the key control strategies and measures for the infectious disease are implemented in the infectious disease monitoring areas. The key prevention and control conditions include the highest alert condition, mitigation condition, control effectiveness condition, and termination response condition.

[0011] This invention also provides an infectious disease outbreak monitoring and early warning system that integrates multi-source data, comprising: The infectious disease epidemic wave trend map construction module is used to determine epidemic wave nodes or epidemic wave turning points based on historical data of infectious disease cases in the region during historical periods, and to measure the stage of the epidemic wave according to the epidemic wave nodes or epidemic wave turning points, and dynamically construct an infectious disease epidemic wave trend map. The indicator construction module is used to determine the target infectious disease epidemic wave multi-source data information type indicator corresponding to the infectious disease monitoring area in the current period based on the real-time data of infectious disease cases in the current period and the infectious disease epidemic wave trend map. The monitoring module is used to effectively monitor the infectious disease epidemic wave in the target infectious disease monitoring area based on the multi-source data information type indicators, monitoring and prevention effectiveness indicators, and effective monitoring targets of the target infectious disease epidemic wave, and to obtain key data for effective monitoring. The early warning and control module is used to determine the target epidemic wave turning point corresponding to the infectious disease monitoring area based on the effective monitoring key data and the infectious disease epidemic wave trend map, and to implement key prevention and control strategies and measures for infectious diseases in the infectious disease monitoring area based on the target epidemic wave turning point.

[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the infectious disease epidemic wave monitoring and early warning method as described above, which integrates multi-source data.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the infectious disease epidemic wave monitoring and early warning method as described above, which integrates multi-source data.

[0014] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the infectious disease epidemic wave monitoring and early warning method as described above, which integrates multi-source data.

[0015] The present invention provides a method, system, and equipment for monitoring and early warning of infectious disease outbreaks by integrating multi-source data. It constructs a concept and technical model diagram of the outbreak wave using historical case data from the monitored area, determining the outbreak wave's change nodes, inflection points, and natural history stages such as initiation, rise, mitigation, and decline. Next, combining real-time data with the concept and technical model diagram, it clarifies the multi-source data information type indicators for the target outbreak wave in the current period. Based on these indicators, control effectiveness indicators, and effective monitoring targets, it conducts effective monitoring to obtain key data on the natural history of the outbreak wave, including epidemiological causes, pathogenic causes, transmission patterns, alert conditions, and mitigation conditions. Finally, based on this key data and the concept and technical model diagram, it implements key control strategies and measures in the monitored area, thereby more effectively assessing the epidemic situation and consequences, determining the natural history and mechanism of the outbreak wave, and implementing control strategies and measures. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the infectious disease outbreak monitoring and early warning method that integrates multi-source data provided by this invention; Figure 2The present invention provides an infectious disease epidemic wave curve and its conceptual model diagram that integrates multi-source data; Figure 3 This invention provides a conceptual and technical model diagram of a typhoid epidemic wave in a certain region. Figure 4 A schematic diagram of the overall methodological framework for the systematic and collaborative technology of infectious disease epidemic monitoring and early warning system provided by this invention; Figure 5 A schematic diagram of the methodological route for the systematic and collaborative technology of infectious disease epidemic wave monitoring and early warning system provided by the present invention; Figure 6 A schematic diagram of the four cyclical components and their monitoring cycle for effective monitoring of infectious disease outbreak waves provided by this invention; Figure 7 This is a schematic diagram of the infectious disease epidemic monitoring and early warning system that integrates multi-source data provided by the present invention. Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] Existing infectious disease outbreak monitoring and early warning technologies are mainly implemented through some infectious disease monitoring and early warning systems and the classic SEIR (Susceptible-Exposed-Infectious-Recovered) infectious disease mathematical model. Currently, infectious disease monitoring and early warning systems emphasize outbreak reporting and early warnings before or during outbreaks, primarily detecting abnormal information about infectious disease occurrences, risk factors, clustered cases, severe syndrome cases, abnormal health events, and outbreak precursors and conditions.

[0020] The classic SEIR infectious disease mathematical model can be summarized as the dynamic curves of sub-populations: susceptible (S), exposed (E), infected (I), ill (P), recovered (R), and dead (D). Except for the ill, recovered, and dead sub-population curves, which can be divided into rising, plateau, and declining phases, the susceptible, asymptomatic infected, and exposed sub-populations have great uncertainty. Moreover, this model is highly dependent on the management of the source of infection, pathogen characteristics, information on various types of cases, gold standard parameters for epidemic trends and distribution, and dominant transmission patterns. Therefore, it can only be used as an auxiliary means of predicting and warning infectious diseases and as a tool for prevention, control, intervention, and evaluation.

[0021] Currently, relying solely on infectious disease surveillance and early warning systems and classic SEIR infectious disease mathematical models is insufficient for a comprehensive, in-depth, and scientifically accurate understanding of the initiation, rise, mitigation, decline, and termination of epidemic waves, or their baseline natural history and mechanisms. It also fails to effectively enhance the core capabilities of full-process monitoring, effective monitoring, phased measurement, disciplinary measurement, effective early warning, key node early warning, key prevention, and key control of epidemic waves. Furthermore, it is unsuitable for systematic and collaborative monitoring, measurement, early warning, prevention, control, and evaluation of epidemic waves.

[0022] Previously, there were no universally standardized methods or technologies for monitoring and early warning of infectious disease outbreaks. Existing methods and technologies generally suffer from four major problems: 1. Lack of conceptual definitions for infectious disease outbreaks, outbreak change nodes and inflection points, early detection, early monitoring, effective monitoring, effective early warning, critical node early warning, critical prevention, critical control, as well as the measurement of outbreak stage, epidemiological etiology, and virological etiology; 2. Lack of systematic and collaborative methods or technologies for detecting, monitoring, early warning, responding to, preventing, controlling, and assessing infectious disease outbreaks; 3. Lack of a systematic and collaborative technical framework and roadmap for full-process monitoring, effective monitoring, stage measurement, disciplinary measurement, effective early warning, critical node early warning, critical prevention, and critical control of infectious disease outbreaks; 4. This leads to disordered, superficial, and inefficient monitoring and early warning of infectious disease outbreaks, and the ambiguity of their conclusions.

[0023] In the monitoring and early warning process during the early stages of some infectious disease outbreaks, infectious disease outbreaks are usually characterized by suddenness and severity. When faced with difficulties and challenges such as uncertainty in the trend of the epidemic, variability of pathogens, and difficulty in interpreting the epidemic, it is extremely difficult to judge the trend and consequences of the epidemic, formulate prevention and control strategies and measures, and mitigate the harm and impact by relying solely on existing technologies or means, regarding the replacement of epidemic waves and the evolution of pathogens, the recurrence of epidemic waves and changes in pathogen transmission dynamics, and the high infectivity and immune escape.

[0024] Infectious diseases pose a perpetual threat to human health and life. The risk of outbreaks, epidemics, and pandemics of emerging infectious diseases will continue to increase due to global climate change, population movement, and pathogen mutations. Emerging and re-emerging infectious diseases and "Disease X" are characterized by high frequency of epidemic waves, high intensity of epidemics, severe harm to health and life, wide range of impact, and great significance for prevention and control. At the same time, we will also encounter multiple epidemic waves caused by many known and unknown pathogens, which requires bearing high costs in mitigating and responding to multiple infectious disease epidemic wave crises, and will also face enormous difficulties and challenges in monitoring, early warning, prevention, and control of multiple infectious disease epidemic waves.

[0025] The occurrence of infectious disease outbreaks or the spread of their pathogens conform to the triangular model of "host, pathogen, and environment" and the chain model of "storage host, exit portal, mode of transmission, entry portal, susceptible host, and pathogen." The occurrence and formation of an outbreak includes three links: source of infection, transmission route, and susceptible population, and is influenced by natural and social factors. Transmission routes may be through air, water, food, contact, biological, blood, sexual, and soil transmission. This involves innovative theoretical technologies that differentiate and integrate multiple disciplines such as epidemiology, infectious disease geology, pathogenic biology, infectious disease ecology, and environmental health. To identify and address a range of issues and shortcomings in existing technologies, such as the uncertainty of some infectious disease outbreak trends, pathogen variability, difficulty in interpreting outbreaks, and ambiguity in monitoring and early warning results and conclusions, it is necessary to determine the mechanisms, principles, epidemiological causes, etiological causes, transmission patterns, key nodes, key prevention measures, key control measures, outbreak stages, and response strategies in the natural history of infectious disease outbreaks. Only then can we break down and eliminate the normal distribution of the histogram of new cases per unit time, the concave and convex trends of the cumulative case count curve, the nodes and processes of case number changes, the stages of monitoring and early warning, and the stages of key prevention and control in the natural history of outbreak waves. This will help us to avoid the formation of outbreak waves or suppress outbreak peaks and shorten the peak period, thereby minimizing the harm of infectious diseases to human health, life, and socio-economic development.

[0026] To address the problems existing in the prior art, the main improvement of this invention is to establish a method and technology for monitoring and early warning of infectious disease outbreaks that integrates multiple data sources and is suitable for all acute infectious diseases, especially emerging and re-emerging infectious diseases and "Disease X". It is an original, groundbreaking, systematic, and collaborative technical system that recognizes the onset, rise, easing, decline, and end of infectious disease outbreaks or their baseline natural history, and improves the ability and benefits of full-process monitoring, effective monitoring, phased measurement, disciplinary measurement, effective early warning, key node early warning, key prevention, and key control of outbreaks.

[0027] Figure 1 This is a flowchart illustrating the infectious disease epidemic wave monitoring and early warning method that integrates multi-source data provided by the present invention, as shown below. Figure 1 As shown, this invention provides a method for monitoring and early warning of infectious disease outbreaks by fusing multi-source data, including: Step 101: Based on historical data of infectious disease cases in the infectious disease monitoring area during historical periods, determine the epidemic wave nodes or epidemic wave turning points, and measure the epidemic wave stages according to the epidemic wave nodes or epidemic wave turning points, and dynamically construct an infectious disease epidemic wave trend map. Step 102: Based on the real-time data of infectious disease cases in the infectious disease monitoring area during the current period and the infectious disease epidemic wave trend map, determine the target infectious disease epidemic wave multi-source data information type index corresponding to the infectious disease monitoring area during the current period; Step 103: Based on the multi-source data information type indicators, monitoring and control effectiveness indicators, and effective monitoring targets of the target infectious disease epidemic wave, conduct effective monitoring of the infectious disease epidemic wave in the infectious disease monitoring area to obtain key data for effective monitoring; Step 104: Based on the effective monitoring key data and the infectious disease epidemic wave trend map, determine the target epidemic wave turning point corresponding to the infectious disease monitoring area, and implement key prevention and control strategies and measures for infectious diseases in the infectious disease monitoring area based on the target epidemic wave turning point.

[0028] In this invention, relevant concepts and definitions for monitoring and early warning of infectious disease outbreaks have been added and improved: An infectious disease outbreak wave refers to an epidemic fluctuation process and its mechanism characterized by an increasing or decreasing rate of case numbers, formed through outbreaks of infectious diseases originating from the same source, non-originating sources, continuous transmission, and mixed outbreak patterns. It is typically influenced by factors such as pathogen characteristics, population immunity levels, intervention measures, environmental conditions, social behavior, medical resources, policies and regulations, and information dissemination. A typical visual representation is a histogram of new cases per unit time (the trend curve of case number changes is also called the epidemic curve) showing a normal distribution with three thresholds and four phases (initial phase, rising phase, plateau phase, and declining phase), or a cumulative case count per unit time curve showing a bounded function with the convex and concave characteristics of a Logistic or Gompertz curve, with three thresholds and four phases (initial phase, early phase, late phase, and stable phase). Regarding the occurrence and control outcomes of an infectious disease outbreak wave, the minimum and maximum extreme values ​​of the number of infected individuals in the epidemiologically associated region are zero and the regional population, respectively. It should be noted that, in this invention, "epidemic wave" is a general or unified name for similar concepts such as outbreak peak, epidemic peak, outbreak wave, epidemic wave, and pandemic wave.

[0029] Epidemic wave nodes and inflection points: These refer to the points or turning points in the trend of the epidemic wave, which are characterized by three aspects: causation, trend, regularity, and boundedness. Figure 2 The present invention provides an infectious disease epidemic wave curve and its conceptual model diagram that integrates multi-source data. Figure 3 The diagram illustrating the concept and technical model of a typhoid epidemic wave in a certain region provided by this invention can be used as a reference. Figure 2 and Figure 3 As shown, Figure 2 In the epidemic curve and its conceptual model diagram, the coordinates of the midpoint between points a, c, and d, the midpoint near the end of the epidemic curve, or the midpoint between points t1, t2, and t3, and the coordinates of the three changing points or turning points near the end of the epidemic curve are as follows: Figure 3The coordinates of cases 39, 217, and 51 in the histogram, or the three points of change or turning points in March, September, and December 2001. Figure 3 The case counts of 120, 1093, and 1474 on the curve, or the coordinates of the three turning points or inflection points in March, September, and December 2001, can all be called turning points of the epidemic wave. These represent the beginning, inflection point, and end point of the rise and fall of the number of newly infected cases per unit time, or the beginning of subsequent baseline fluctuations. Among these, the case count inflection point is a key node, turning point, or inflection point in the trend of case count changes in the epidemic wave, referring to the peak of the histogram / epidemic curve showing a normal distribution trend, such as... Figure 3 The inflection point coordinates of the number of cases in the histogram (September 2001, 217 cases), or the dividing point of the concave-convex trend in the curve, such as... Figure 3 The inflection point coordinates of the number of cases in the curve (September 2001, 1093 cases) are the dividing point between the process of the rate of increase in the number of infected cases from small to large and the process of the rate of increase from large to small.

[0030] Epidemic wave staging measurement: As long as the epidemic wave histogram shows a normal distribution trend and the curve shows a concave-convex trend, a composite chart including the epidemic wave histogram, curve, and its staging measurement of detection, monitoring, early warning, response, prevention, and control can be drawn, or a diagram of the epidemic wave monitoring and early warning concept and technical model can be drawn (for reference). Figure 3 Based on this composite diagram, three key nodes of the epidemic wave are presented ( Figure 3 The curve graph shows 120, 1093, and 1474 cases and their coordinates in March, September, and December 2001. Combined with data on the consistency of etiological differentiation results and the unity of etiological fusion conclusions from epidemiology, infectious disease, pathogenic biology, infectious disease ecology, and environmental health, early detection, early monitoring, effective monitoring, effective early warning, key node early warning, key prevention, and key control are used to measure the stages.

[0031] The discipline measurement of epidemiological etiology and etiology (hereinafter referred to as discipline measurement) refers to the systematic and collaborative comprehensive analysis of infectious disease epidemic wave case data, epidemiological etiology, etiological etiology, and mechanism principles through discipline measurement such as describing epidemiological etiology hypotheses, analyzing and verifying epidemiological etiology, pathogen phenotypic and genotypic detection and genome sequencing, and infectious disease ecology and environmental health etiology analysis. Epidemiological etiology refers to the sum of sources of infection, transmission routes, susceptible populations, and natural and social factors that lead to an increase in the number of cases or incidence rate. Etiological etiology refers to the sum of pathogens that cause infectious diseases and their phenotypes and genotypes.

[0032] Detection: Strengthen the mechanisms for infectious disease monitoring, medical-prevention collaboration, medical-prevention integration, joint prevention and control, and their corresponding legal, digital, intelligent, and smart systems to promptly detect the conditions and signs of infectious disease outbreaks, severe syndrome cases, and abnormal health events before an outbreak occurs or at the beginning of an outbreak.

[0033] Monitoring: Collecting, verifying, and analyzing relevant data and information on the occurrence, development, and influencing factors of infectious diseases in the population; identifying abnormal information such as outbreak or epidemic conditions, increased case numbers, clustered cases, and severe syndrome cases as early as possible; dynamically analyzing changes in case distribution over time, space, and among populations, and their underlying mechanisms; and using the results to guide infectious disease early warning and control. Main uses: Case detection and management; identifying outbreaks or epidemics; monitoring changes in pathogens and risk factors; understanding distribution characteristics and trends; evaluating intervention measures.

[0034] Early warning: Collect and analyze relevant data and information on infectious disease outbreaks, study the risk of outbreaks or epidemics, assess the development trend and severity of the epidemic, and issue timely warnings or alerts before or in the early stages of an infectious disease outbreak and at key points in the change of the epidemic situation, so that relevant departments, institutions and target groups affected by the event can respond in a timely manner to prevent or reduce the harm of the event.

[0035] Prediction: Based on past and current data on infectious diseases and their influencing factors, the risk, level, and trend of future occurrence and development of infectious diseases are estimated. Prediction based on the technical solution of this invention is considered effective.

[0036] Early detection: Monitoring and early warning in the early stages of an infectious disease outbreak, before it occurs or during its initial phase, or indicated by histograms or curves of the epidemic wave. Figure 2 Point a or point t1, Figure 3 Before March 2001 (the horizontal axis point), we should detect and discover abnormal information such as the conditions for the occurrence of an epidemic, the initial events of an outbreak, risk factors, clustered cases, the first case, and index cases as early as possible, make preliminary predictions of the corresponding risks, and take appropriate measures to avoid the occurrence of an epidemic or reduce the degree of harm.

[0037] Early surveillance: Monitoring is conducted before an infectious disease outbreak occurs or when the outbreak is indicated by histograms or curves. Figure 2 Point a or point t1, Figure 3 Before March 2001 (the horizontal axis point), complete the monitoring and investigation of cases and infected persons as soon as possible, and analyze the cases and pathogens, the onset and process, and the source and spread of pathogens.

[0038] Effective monitoring: During the monitoring period indicated by the infectious disease epidemic wave histogram and curve chart (e.g.) Figure 3Before December 2001 (the horizontal axis point), complete the detection, monitoring, investigation, measurement and assessment of the epidemic wave as soon as possible, comprehensively and accurately understand the epidemic wave conditions, risk factors, transmission routes, pathogen phenotypes and genotypes, determine the epidemic wave cases and pathogens, the onset and process, the source and transmission of pathogens, pathogen mutation and adaptability, and propose scientific, precise and efficient prevention and control strategies and measures.

[0039] Effective early warning: The entire early warning period is indicated by the epidemic wave histogram and curve chart (e.g., Figure 3 Before the abscissa point of December 2001, based on the systematic and collaborative results and conclusions of epidemic wave detection, monitoring, response, and assessment data and information, as well as their phased and disciplinary measurements, as early as possible... Figure 3 Before the inflection point in the number of cases in September 2001, timely and accurate early warnings and scientific decisions were made, and appropriate response measures such as tiered and zoned response activation, social action, and public communication were taken as early as possible to avoid the occurrence of an epidemic or reduce its harm.

[0040] Key Node Early Warning: In the composite graphs of the normal distribution trend of infectious disease epidemic waves, such as histograms and concave-convex trend curves, one, two, or three of the three key nodes—causality, trend, regularity, and boundedness—are presented. Continuous tracking of the dynamic changes in the number of infected cases, affected populations or scope, pathogen phenotype or genotype, transmission vector or environment, etc., is conducted. Combined with the consistency of etiological differentiation results and the unification of etiological fusion conclusions in the epidemiology, infectious disease, pathogenic biology, infectious disease ecology, and environmental health data before and after each key node, early warnings are issued for each key node, and corresponding prevention and control decisions are formulated. Scientific, precise, and timely response measures are taken as early as possible in the subsequent period of each key node to avoid the continuation of the epidemic and the increase in the number of cases in the subsequent period of each key node, to suppress the peak of the entire epidemic wave and shorten the peak period, and to reduce the degree of harm of the phased and whole-process epidemic wave.

[0041] Key prevention: refers to the period of early detection, early monitoring, and early warning as indicated by the histogram and curve chart of infectious disease outbreaks (e.g., Figure 2 Point a or point t1, Figure 3 Before March 2001 (the period before the horizontal axis point), that is, during the critical period when various infectious disease monitoring and early warning systems attach importance to epidemic reporting and early warning or early warning of outbreaks, it is necessary to discover, diagnose, treat and manage infected cases in epidemic areas as early as possible, control the source of risk points and risk factors, strive to have no or few secondary cases and infected persons in the epidemiologically related population (the minimum extreme value is zero), the epidemic intensity is sporadic or clustered, the related population is not large, the affected area is limited, and the number of cases increases slowly during this period.

[0042] Key control: refers to the period of rapid increase in the number of cases indicated by the histogram or curve chart of an infectious disease outbreak (e.g., Figure 3The period from March to December 2001 (on the horizontal axis) is a critical time to reduce the harm of phased and continuous epidemic waves. It is crucial to identify the dynamic changes in cases and infected persons, affected populations and regions, pathogen phenotypes and genotypes, transmission patterns and sources of pollution as early as possible, and to take tiered and zoned administrative, technical and social response strategies and measures as early as possible to avoid the continuation of the epidemic and the surge in the number of cases, and to suppress the peak and shorten the peak period as much as possible. The epidemic intensity is an outbreak, epidemic or pandemic (the maximum number of infected persons is the population of the epidemiologically associated area). Secondary cases and transmission chains increase, the associated population increases, and the affected area expands. During this period, the number of cases increases rapidly.

[0043] This invention focuses on historical infectious disease case data from a monitored region. This data records the past occurrence of infectious diseases in the region. By analyzing this data, an infectious disease epidemic trend map is dynamically constructed, identifying key time points (such as the start of an epidemic's rise, peak, and decline) and inflection points (points where the epidemic trend undergoes significant changes). Then, based on these points and inflection points, the epidemic wave is segmented and measured, for example, divided into rising, peak, and declining phases. Finally, an infectious disease epidemic trend map or conceptual / technical model diagram (such as a monitoring and early warning concept and technical model diagram) is constructed, visually presenting the epidemic's changing trend over time.

[0044] Furthermore, real-time data on infectious disease cases in the monitored area during the current period are obtained. This data reflects the latest developments in the epidemic. Combining the infectious disease epidemic trend map obtained in step 101, the position and characteristics of the current epidemic in the trend map are analyzed to determine the target infectious disease epidemic wave information type indicators corresponding to the region during the current period, such as the current epidemic's spread speed, scope, and affected population.

[0045] Next, based on the target infectious disease outbreak wave information type indicators determined in step 102, and considering both effective monitoring objectives (such as the accuracy and timeliness of monitoring) and control benefit indicators (such as the cost-effectiveness ratio of control measures), effective monitoring of infectious disease outbreak waves is implemented. During the monitoring process, various monitoring methods and technologies are used to collect various types of data related to the outbreak. After screening and analysis, key data for effective monitoring are obtained, which will provide important basis for subsequent decision-making.

[0046] Finally, using the effective key monitoring data obtained in step 103, and combining it again with the infectious disease epidemic trend map, the target epidemic wave turning point corresponding to the monitored area is further precisely determined. Once the target epidemic wave turning point is identified, key infectious disease control strategies and measures can be formulated and implemented for the monitored area based on this point, such as strengthening personnel management and adjusting the allocation of medical resources, to effectively control the development of the epidemic.

[0047] Figure 4 This is a diagram illustrating the overall methodological framework of the infectious disease outbreak monitoring and early warning system and collaborative technology provided by this invention. Figure 5 A schematic diagram illustrating the systematic and collaborative technology for infectious disease outbreak monitoring and early warning systems provided by this invention can be referenced. Figure 4 and Figure 5 As shown, this paper comprehensively presents the innovative, groundbreaking, systematic, and collaborative methodological and technical framework and roadmap for monitoring and early warning of acute infectious diseases, emerging and re-emerging infectious diseases, and "Disease X" epidemic waves. It is not only a technical flowchart of the invention's methods for full-process monitoring, early detection, early monitoring, effective monitoring, staged measurement, disciplinary measurement, effective early warning, key node early warning, key prevention, and key control of infectious disease epidemic waves, but also a theoretical and technical guideline for the interdisciplinary integration and innovation of epidemic wave monitoring and early warning involving epidemiology, infectious disease geology, pathogenic biology, infectious disease ecology, and environmental health. Furthermore, it provides a diagram showing the natural history of the epidemic wave's initiation, rise, mitigation, decline, and termination, or baseline, as well as the overall and integrated connections between monitoring, early warning, response, and assessment. This has significant guiding significance for understanding the natural history and mechanistic principles of epidemic waves, epidemiological etiology, pathogenic etiology, key nodes, completing risk assessment and trend analysis, determining key prevention and control strategies, evaluating the effectiveness of monitoring, early warning, and control, and solving a series of problems related to epidemic wave trends, pathogens, mechanisms, and monitoring and early warning results and conclusions. It also plays a crucial guiding role in avoiding or reducing the harm of infectious disease epidemic waves to health, life, and economic development.

[0048] The infectious disease outbreak monitoring and early warning method provided by this invention integrates multi-source data. It constructs an outbreak wave concept and technical model diagram using historical case data from the monitored area, determining the outbreak wave's change nodes, inflection points, and natural history stages such as initiation, rise, mitigation, and decline. Next, combining real-time data with the concept and technical model diagram, it clarifies the multi-source data information type indicators for the target outbreak wave in the current period. Based on these indicators, control effectiveness indicators, and effective monitoring targets, it conducts effective monitoring to obtain key data on the outbreak wave's natural history, including epidemiological etiology, pathogenic etiology, transmission patterns, alert conditions, and mitigation conditions. Finally, based on this key data and the concept and technical model diagram, it implements key control strategies and measures in the monitored area, thereby more effectively assessing the epidemic situation and consequences, determining the outbreak wave's natural history and mechanisms, and implementing control strategies and measures.

[0049] Based on the above embodiments, the step of determining epidemic wave nodes or epidemic wave turning points based on historical infectious disease case data of the infectious disease surveillance area over a historical period, and dynamically constructing an infectious disease epidemic wave trend map based on the epidemic wave nodes or epidemic wave turning points, includes: Based on the historical data of infectious disease cases in the monitored area during the historical period, the characteristics of the growth rate of cases and the trend of infectious disease epidemic fluctuations are obtained; Based on a preset unit time, the epidemic wave nodes corresponding to each time point in the historical period of the infectious disease monitoring area are constructed, and based on the fluctuation characteristics of the increase in the number of cases and the fluctuation process of the trend of the infectious disease epidemic, the epidemic wave turning point is determined from multiple epidemic wave nodes, wherein the epidemic wave turning point includes at least the turning point of the increase in the number of cases, the inflection point of the number of cases, and the turning point of the number of cases. Based on the historical number of infectious disease cases at the time points corresponding to the turning points of the epidemic wave, a cumulative case count curve of the infectious disease epidemic wave per unit time is generated; based on the historical number of new infectious disease cases at the time points corresponding to each epidemic wave node, a histogram of new cases per unit time is generated. Based on the cumulative number of cases per unit time curve and the histogram of new cases per unit time of the infectious disease epidemic wave, a trend chart of the infectious disease epidemic wave is constructed.

[0050] This invention analyzes historical data on infectious disease cases in a monitored area over a specific historical period. This historical data records the number of infectious disease cases in the area at different points in time. By calculating changes in the number of cases at adjacent time points, such as daily, weekly, or monthly new cases and the case growth rate, the fluctuation characteristics of the case growth rate are obtained. For example, it observes whether the case growth rate is continuously rising, relatively stable, declining, or exhibiting cyclical fluctuations. Simultaneously, by comprehensively analyzing this data, the trend and fluctuation process of the infectious disease epidemic throughout the historical period can be identified, such as whether the epidemic began to break out at a certain time and then gradually spread, whether it was effectively controlled, or whether it experienced multiple rounds of fluctuations.

[0051] Then, according to preset time units (such as days, weeks, months, etc.), the infectious disease monitoring area is divided into multiple time points in the historical period. At each time point, based on the changes in the number of cases, corresponding epidemic wave nodes are constructed. These nodes serve as markers in the development of the epidemic, reflecting the state of the epidemic at different times.

[0052] Next, based on the previously obtained characteristics of the fluctuations in the growth rate of case numbers and the fluctuation process of infectious disease epidemic trends, turning points in the epidemic wave were selected from numerous epidemic wave nodes. These turning points are key locations where the epidemic trend undergoes significant changes, and at least include turning points in case number increases (e.g., the moment when the epidemic changes from slow growth to rapid growth), inflection points in case numbers (the moment when the growth or decline trend of case numbers reverses), and turning points in case number decreases (e.g., the moment when the epidemic changes from a slow decline to a rapid decline). These turning points are crucial for understanding the development patterns of the epidemic and predicting future trends.

[0053] Furthermore, based on the historical number of infectious disease cases at the time points corresponding to the turning points of the epidemic wave, a histogram or epidemic curve of the number of new cases per unit time is plotted with time as the horizontal axis and the number of new cases per unit time as the vertical axis. This histogram or curve can intuitively show the normal distribution, nodes, inflection points, etc. of the number of new cases per unit time in historical periods, including the beginning, peak, and trough stages of the epidemic, as well as the changes in the number of cases at each turning point.

[0054] Meanwhile, based on the historical number of new infectious disease cases at each epidemic wave node, a cumulative case count per unit time curve is generated with time as the horizontal axis and the cumulative case count per unit time as the vertical axis. This curve can clearly reflect the continuous changes, nodes, and inflection points of the cumulative case count in different time periods, helping to understand the spread speed and epidemic intensity of the epidemic at different stages.

[0055] Finally, by combining the histogram or epidemic curve of the number of new cases per unit time and the curve of the cumulative number of new cases per unit time of the infectious disease epidemic wave, a trend chart or conceptual / technical model diagram of the infectious disease epidemic wave is constructed. This composite chart can more comprehensively and accurately present the development trend and fluctuation characteristics of infectious disease epidemics over historical periods. Through the analysis of the trend chart, we can better understand the evolution characteristics, trends, and patterns of the epidemic, providing a strong basis for predicting future epidemic trends and formulating prevention and control strategies.

[0056] Based on the above embodiments, the step of determining the target infectious disease epidemic wave information type index corresponding to the infectious disease monitoring area in the current time period based on the real-time data of infectious disease cases in the infectious disease monitoring area and the infectious disease epidemic wave trend map includes: The real-time data of infectious disease cases are matched with the infectious disease epidemic trend map to determine the stage information corresponding to the infectious disease monitoring area in the infectious disease epidemic trend map. The stage information includes the initial stage of the increase in the number of infectious disease cases, the early stage of monitoring and early warning, the stage of rising cases, the middle and late stage of monitoring and early warning, the stage of growth plateau, and the stage of declining cases. Based on the aforementioned stage information, target infectious disease epidemic wave multi-source data information type indicators are determined from the multi-source data information type indicators of infectious disease epidemic waves. These multi-source data information type indicators include infectious disease ecology and environmental health observation indicators, epidemiological monitoring and risk factor analysis indicators, case infection monitoring and investigation and management indicators, case environmental pathogen and genomic monitoring indicators, pathogen variability and dominance detection indicators, and whole-process monitoring and effective response system evaluation indicators. The data information type indicators have inherent contradictions in terms of lead time and predictive deterministic value. The infectious disease ecology and environmental health observation indicators include infectious disease early warning information, abnormal health events, clustered cases, suspected environmental pollution sources, population immunity, and natural and social factors; The epidemiological surveillance and risk factor analysis indicators include information on the spread and changes of the epidemic, the distribution and scope of cases, information on exposed populations, information on sensitive populations, information on suspected pathogen sources, and transmission risks; The monitoring, investigation, and management indicators for infected cases include case tracking and management rate, morbidity rate, hospitalization rate, severe case rate, case fatality rate, mortality rate, infection rate, and transmission rate. The environmental pathogen and genomic monitoring indicators for the cases include pathogen identification, pathogen infectivity, pathogen pathogenicity, pathogen virulence, pathogen phenotype, pathogen molecular typing, and genome sequencing. The pathogen variability and dominance detection indicators include pathogen genetic diversity, pathogen genetic variability, pathogen genotype, pathogen dominant genotype adaptability, pathogen dominant genotype stability, and pathogen dominant genotype predictability. The evaluation indicators for the comprehensive monitoring and effective response system include epidemic wave performance, effective monitoring information, phased measurement, subject-specific measurement, effective early warning information, early warning information at key nodes, prevention and control effect, and prevention and control benefits.

[0057] This invention provides innovative and groundbreaking mechanisms, principles, methods, techniques, means, and tools for resolving the inherent contradiction between the lead time of data information types and the predictive deterministic value of infectious disease epidemic waves, while also demonstrating systematicity and synergy (see details for reference). Figures 2 to 5 and subsequent Figure 6 (See Table 1). The data information types and indicators for infectious disease outbreaks include: infectious disease ecology and environmental hygiene observation indicators, epidemiological monitoring and risk factor analysis indicators, case infection monitoring, investigation and management indicators, case-environmental pathogen and genomic monitoring indicators, pathogen variability and dominance detection indicators, and comprehensive monitoring and effective response system evaluation indicators. These six data information types and indicators reflect, in order, the increasing lead time required to obtain the corresponding data information types and the decreasing predictive certainty value. This inherent contradiction is that "the more lead time required to obtain complete and accurate data information types and indicators, the smaller their predictive certainty value; if insufficient lead time is spent obtaining various data information types and indicators, it usually means that it is difficult to obtain correspondingly large predictive certainty value." Resolving the inherent contradictions of the data information types and indicators for infectious disease outbreaks and obtaining the corresponding data information type and indicator results are the basic requirements and common goals of comprehensive and effective monitoring.

[0058] In this invention, real-time data on infectious disease cases acquired in the current time period in an infectious disease surveillance area are matched with a previously constructed infectious disease epidemic trend map. The infectious disease epidemic trend map presents the characteristics of different stages of epidemic development over time. By matching, the specific stage of the epidemic wave in the trend map during the current time period can be determined. This stage information covers several key periods in the development of infectious diseases, such as the initial growth stage (the period when the epidemic just begins to show signs of growth), the early monitoring and early warning stage (the period when the epidemic has just appeared and monitoring and early warning need to be strengthened), the case rise stage (the period when the number of cases begins to rise rapidly), the mid-to-late monitoring and early warning stage (the period when the focus of monitoring and early warning is adjusted after the epidemic has developed for a period of time), the growth plateau stage (the period when the increase in the number of cases tends to stabilize), and the case decline stage (the period when the number of cases begins to decrease). Clearly defining the stage information helps to carry out targeted prevention and control work.

[0059] Furthermore, based on the determined stage information, target infectious disease epidemic multi-source data information type indicators are selected from the indicators of infectious disease epidemic multi-source data information types. These indicators monitor and evaluate infectious disease epidemics from different dimensions, as follows: Indicators for observation in infectious disease ecology and environmental health include: early signs of infectious diseases (such as reports of early abnormal symptoms), abnormal health events (such as multiple people developing similar symptoms within a short period of time), clusters of cases (cases occurring in a concentrated area or group), suspected sources of environmental pollution (environmental factors that may be related to the spread of the epidemic), population immunity (the population's resistance to infectious diseases), and natural and social factors (such as the impact of climate and population density on the spread of the epidemic). These indicators help to understand the background and potential risks of an epidemic from an ecological and environmental perspective.

[0060] Epidemiological surveillance and risk factor analysis indicators include: information on the spread and changes of the epidemic (changes in the scope and speed of epidemic transmission), case distribution and scope (the distribution of cases in different regions), information on exposed populations (characteristics of people who have been in contact with cases), information on susceptible populations (characteristics of populations susceptible to infectious diseases), information on suspected pathogen sources (pathogens that may cause the epidemic), and transmission risk (the likelihood of epidemic transmission). By analyzing these indicators, we can gain a deeper understanding of the transmission patterns and potential risk factors of the epidemic.

[0061] Indicators for case surveillance, investigation, and management include: case tracking and management rate (the proportion of cases tracked and managed), incidence rate (the proportion of people who develop the disease within a certain period of time out of the total population), hospitalization rate (the proportion of people hospitalized after onset of illness), severe illness rate (the proportion of people with severe illness requiring special treatment), case fatality rate (the proportion of people who die from infectious diseases out of the total number of cases), mortality rate (the proportion of people who die from infectious diseases out of the total population), infection rate (the proportion of people infected with the pathogen out of the total population), and transmission rate (the speed at which the epidemic spreads). These indicators directly reflect the extent of the epidemic's impact on population health and its transmission efficiency.

[0062] Case-environmental pathogen and genomic surveillance indicators include: pathogen determinism (the accuracy of pathogen identification), pathogen infectivity (the pathogen's ability to spread to others), pathogen pathogenicity (the pathogen's ability to cause disease), pathogen virulence (the degree of damage a pathogen inflicts on an organism), pathogen phenotype (the external characteristics of a pathogen), pathogen molecular typing (the molecular-level classification of pathogens), and genome sequencing (the sequencing analysis of the pathogen's genome). These indicators help to gain a deeper understanding of the characteristics and transmission mechanisms of pathogens.

[0063] Indicators for detecting pathogen variability and dominance include: pathogen genetic diversity (the degree of diversity of pathogen genes), pathogen genetic variability (the frequency of changes in pathogen genes), pathogen genotype (the gene type of the pathogen), pathogen dominant genotype adaptability (the ability of the dominant genotype to adapt to different environments), pathogen dominant genotype stability (the stability of the dominant genotype during transmission), and pathogen dominant genotype predictability (the ability to predict future changes in the dominant genotype). By monitoring these indicators, we can understand the variation of pathogens and the characteristics of dominant genotypes, providing a basis for adjusting prevention and control strategies.

[0064] Evaluation indicators for a comprehensive monitoring and effective response system include: epidemic wave performance (characteristics of the epidemic at each stage), effective monitoring information (monitoring data that accurately reflects the epidemic situation), phased measurement (classifying and assessing the stages of epidemic development), disciplinary measurement (assessing the epidemic from different disciplinary perspectives), effective early warning information (information that can issue accurate early warnings), critical node early warning information (early warning information issued at key turning points in the epidemic), prevention and control effectiveness (the results achieved after the implementation of prevention and control measures), and prevention and control benefits (the cost-effectiveness ratio of prevention and control measures). These indicators are used to evaluate the operational effectiveness of the entire monitoring and response system.

[0065] In the process of acquiring the six major data information types of epidemic waves (i.e., infectious disease epidemic wave information type indicators), there is an inherent contradiction: the lead time required to obtain each indicator sequentially tends to increase, while the predictive certainty value tends to decrease. Lead time refers to the time required from the start of data collection to obtaining the indicator results. Some indicators can acquire data and produce results relatively quickly, but the predictive certainty is relatively low; while other indicators require a longer time to collect and analyze data to obtain more accurate predictive results, but by then the optimal control opportunity may have been missed. This contradiction needs to be weighed and coordinated in epidemic prevention and control work, selecting appropriate indicators and control strategies based on the actual situation. See Table 1 for details. Table 1 Lead time and predictive certainty value of six major data information types of infectious disease epidemic waves

[0066] Among them, T1, T2, T3, T4, T5, T6 and V1, V2, V3, V4, V5, V6 are semi-quantitative data information, representing the inherent contradiction between the trend of increasing lead time required to obtain the six major data information types of the epidemic wave in order and the trend of decreasing predictive certainty value.

[0067] Based on the above embodiments, the effective monitoring of infectious disease outbreaks in the target infectious disease monitoring area, based on the multi-source data information type indicators, monitoring and control effectiveness indicators, and effective monitoring targets, to obtain key effective monitoring data includes: Based on the indicators of multi-source data information with full correlation, the monitoring objectives of epidemic changes and impact scope, the monitoring objectives of epidemic mechanisms and response strategies, and the research objectives of routine pathogen monitoring, the effective monitoring objectives are constructed. The epidemic wave performance, pathogen characteristics, natural and social factors, and transmission mechanism in the multi-source data information type indicators of the target infectious disease epidemic wave are used as primary indicators, and the monitoring and prevention effectiveness indicators are used as secondary indicators. The correlation between the multi-source data information type indicators of the target infectious disease epidemic wave and the prevention and control effectiveness indicators is established. Based on the correlation between the multi-source data information type indicators of the target infectious disease epidemic wave and the monitoring and prevention effectiveness indicators, the effective monitoring target is effectively monitored to obtain the key data of effective monitoring. The effective monitoring process consists of four cyclical components. The first cyclical component is used to monitor the population, location, and time of the infectious disease outbreak; the second cyclical component is used to monitor changes in cases, infected persons, pathogens, and risk factors; the third cyclical component is used to determine the epidemic wave monitoring and early warning, case and infected person follow-up, risk factors, and intervention targets; and the fourth cyclical component is used to conduct prevention and control interventions and evaluate the prevention and control effects.

[0068] This invention provides innovative and groundbreaking, systematic and collaborative mechanisms, principles, methods, technologies, means and tools for effectively monitoring infectious disease outbreaks (details can be found in the reference). Figures 2 to 5 Table 1, and subsequent tables Figure 6 (See Table 2) Effective monitoring is a key component of the infectious disease epidemic monitoring and early warning technology system, and is the foundation and prerequisite for understanding, responding to and evaluating the effectiveness of epidemic prevention and control.

[0069] In this invention, effective monitoring of infectious disease outbreak waves involves the above six data information types and indicators, as well as their effective monitoring methods and objectives. That is, the process of detecting, monitoring, investigating, measuring and warning of outbreak waves is completed by describing epidemiological etiological hypotheses, analyzing and verifying epidemiological etiological causes, pathogen detection and genome sequencing, and analyzing the etiological causes of infectious diseases and environmental health.

[0070] In this invention, the key data for effective monitoring is obtained based on four cyclical components in the effective monitoring process: including: systematic monitoring of the population, location and time of infectious disease occurrence, i.e., the first cyclical component; detection of changes in cases, infected persons, pathogens and risk factors, i.e., the second cyclical component; monitoring and early warning of epidemic waves, follow-up of cases and infected persons, determination of risk factors and intervention targets, i.e., the third cyclical component; and prevention and control intervention and effect evaluation, i.e., the fourth cyclical component. Figure 6 The schematic diagram of the four cyclical components and their monitoring cycle for effective monitoring of infectious disease outbreak waves provided by this invention can be referred to. Figure 6 As shown, the effective monitoring process is through Figure 6 The monitoring cycle of the four major cyclical components in the middle obtains six major data information types and primary and secondary indicators such as epidemic wave performance, pathogen characteristics, natural and social factors, transmission mechanism and prevention and control effectiveness (see Table 1 and Table 2 for reference).

[0071] In this invention, effective monitoring targets include: understanding the full-process correlation information of epidemic wave case distribution and ecological environment, source of infection and source of pollution, epidemic point and risk area, transmission route and population protection, pathogen survival environment and human contact with pathogen, transmission dynamics and population immunity (i.e., full-process correlation information target); understanding the conditions for the occurrence of epidemic waves, pathogen characteristics, source of infection, source of pollution, risk factors, epidemiological etiology, etiological etiology, transmission route, transmission mode, and sensitive population and scope of impact (i.e., epidemic change and scope of impact monitoring target); determining the "host, pathogen, environment" triangular model and the "storage host, exit portal, transmission mode, entry portal, susceptible host, pathogen" chain model of the principle of epidemic wave occurrence or pathogen transmission mechanism, and response strategies and measures such as risk prevention, timely detection of epidemics, prevention and control of secondary outbreaks, avoidance of outbreaks, reduction of intensity, and reduction of harm (i.e., epidemic mechanism and response strategy monitoring target); continuing to implement routine monitoring and prevention, and continuing to study pathogen phenotypes and genotypes and their variability and adaptability (i.e., routine monitoring pathogen research target).

[0072] In this invention, the goal of the whole-process correlation multi-source data information objective is to comprehensively grasp various correlation information in the entire process of an infectious disease epidemic from its occurrence, development to its end, including the connection between different stages of the epidemic and the interaction between the epidemic and other related factors (such as medical resources, social activities, etc.), so as to be able to grasp the dynamic changes of the epidemic as a whole.

[0073] The monitoring objectives for epidemic changes and impact range focus on monitoring the core elements of infectious disease epidemic waves, such as the number of cases, transmission routes, and susceptible populations, while also paying attention to the scope of impact of the epidemic, including geographical scope (such as which regions are affected) and population scope (such as which age groups and occupational groups are affected), so as to accurately assess the severity and spread of the epidemic.

[0074] The monitoring objectives of epidemic wave mechanisms and response strategies require in-depth research into the occurrence mechanisms of infectious disease epidemic waves, including the transmission methods, infectivity, pathogenicity, virulence, and variability of pathogens. At the same time, it is necessary to monitor the implementation and effectiveness of response strategies adopted in response to the epidemic, so as to adjust and optimize prevention and control measures in a timely manner.

[0075] The goal of routine pathogen monitoring research emphasizes continuous research on pathogens during routine monitoring work to understand their variability, drug resistance, immune evasion, etc., and to provide a scientific basis for epidemic prevention and control.

[0076] This invention integrates the above four objectives to construct a comprehensive and systematic set of effective monitoring targets, providing a clear direction for subsequent monitoring work.

[0077] Furthermore, the epidemic wave performance, pathogen characteristics, natural and social factors, and transmission mechanisms from the multi-source data information types of the target infectious disease epidemic wave are used as primary indicators. These primary indicators reflect the key characteristics of the infectious disease epidemic from different perspectives, specifically: The performance of the epidemic wave reflects the development trend of the epidemic at different stages, such as growth, peak, and decline.

[0078] Pathogen characteristics: including the type of pathogen, infectivity, pathogenicity, virulence and variability, are important factors affecting the spread and control of an epidemic.

[0079] Natural and social factors: These include climate, geographical environment, population density, and social activities, all of which can influence the spread and diffusion of an epidemic.

[0080] Transmission mechanism: describes how pathogens spread in the population, including transmission routes, transmission patterns, and transmission speed.

[0081] Furthermore, by using monitoring and prevention effectiveness indicators as secondary indicators and establishing correlations between primary and secondary indicators, the mutual influence and mechanism of action among different indicators can be clarified. Establishing such correlations helps to more comprehensively assess the development trend and prevention and control effectiveness of infectious disease outbreaks. The specific correlations between primary and secondary indicators are shown in Table 2. Table 2. Primary and Secondary Indicators Relationship between Infectious Disease Outbreak Waves, Pathogens, Influencing Factors, and Transmission Mechanisms

[0082] It should be noted that as long as there is a systematic and synergistic relationship between the primary indicators such as the manifestation of the infectious disease epidemic wave and the characteristics of the pathogen in each case, the number of secondary indicators differentiated from each primary indicator depends on the degree of certainty of the mechanism trend supporting the epidemic wave and its dominant transmission mode or the effectiveness of prevention and control.

[0083] In this invention, effective monitoring of targets is achieved based on the correlation between multi-source data information type indicators of target infectious disease outbreaks and monitoring and control effectiveness indicators. The effective monitoring process consists of four cyclical components that cooperate to form a complete monitoring system: The first cyclical component is responsible for monitoring the population, location, and time of infectious disease outbreaks. By collecting and analyzing relevant data, it understands which populations the epidemic is spreading in, which regions it is occurring in, and when it is occurring, thereby determining the scope and temporal trend of the epidemic's spread.

[0084] The second cyclical component involves monitoring changes in cases, infected individuals, pathogens, and risk factors. This includes real-time tracking of the number of cases and infected individuals, changes in their condition, monitoring pathogen mutations and transmission, and identifying potential risk factors that could lead to the spread of the epidemic, such as environmental contamination and population movement.

[0085] The third cyclical component: Based on the monitoring results of the first two components, it determines the epidemic wave monitoring and early warning, case and infected person follow-up, risk factors, and intervention targets. When abnormal changes in the epidemic are detected, an early warning is issued in a timely manner; cases and infected persons are followed up to understand their recovery status and transmission risk; corresponding intervention targets are formulated for risk factors, and measures are taken to reduce the risk of epidemic transmission.

[0086] The fourth cyclical component involves implementing prevention and control interventions and evaluating their effectiveness. Based on the established intervention goals, corresponding prevention and control measures are implemented, such as isolation and treatment, vaccination, and environmental disinfection. Simultaneously, the effectiveness of the prevention and control measures is evaluated by comparing epidemic data before and after implementation, assessing the effectiveness of the measures, and adjusting the prevention and control strategy based on the evaluation results.

[0087] Through the coordinated operation of these four cyclical components, monitoring data is continuously collected, analyzed, and fed back, ultimately yielding effective key monitoring data. This key data can provide a scientific basis for epidemic prevention and control decisions, helping relevant departments to adjust prevention and control measures in a timely manner and improve the effectiveness of prevention and control.

[0088] Based on the above embodiments, determining the target epidemic wave turning point corresponding to the infectious disease monitoring area according to the effective monitoring key data and the infectious disease epidemic wave trend map includes: Obtain the target stage information of the epidemic wave in the infectious disease monitoring area during the current time period, as shown in the infectious disease epidemic wave trend graph. Based on the effective monitoring key data and the target stage information, stage measurement and subject measurement are performed to determine the turning point of the target epidemic wave corresponding to the infectious disease monitoring area. The stage measurement is based on the analysis of the epidemic characteristics and development trend of the epidemic wave at different stages; the subject measurement is based on multiple disciplines to analyze the characteristics of infectious diseases in different disciplinary dimensions.

[0089] In this invention, the staging and subject-based measurement methods are specifically embodied in: as long as the infectious disease epidemic wave histogram / epidemic curve shows a normal distribution trend at the three boundary points, or the curve graph shows the concave-convex trend characteristics of a Logistic or Gompertz curve at the three boundary points of a bounded function (such as... Figure 3 The histogram shows cases 39, 217, and 51, or cases from March, September, and December of 2001. Figure 3If the histogram shows 120, 1093, and 1474 cases (or March, September, and December of 2001), then from the origin 0 on the histogram coordinate system to the right, it will experience four stages: a delayed and gradual increase in the rate of increase in the number of cases (initial stage), an increase from small to large (rising stage), a stabilization (plateau stage), and a decrease from large to small (declining stage). Similarly, if the histogram is used in conjunction with other methods... Figure 4 Phased, Curve Figure 4 The composite model diagram of the stages and monitoring and early warning, effective response, key prevention, and key control stages integrates the six major data information types of infectious disease epidemic waves and their four major cyclical components, as well as the primary and secondary indicators of epidemic wave performance, pathogen characteristics, natural and social factors, transmission mechanism determinism, and prevention and control effects. This allows for the phased or full-process measurement and disciplinary measurement of epidemic waves. The corresponding composite model diagrams and tables are collectively referred to as epidemic wave staged response measurement charts.

[0090] In this invention, the specific objectives of phased measurement and discipline measurement are: to understand the onset, rise, mitigation, decline and end of an epidemic wave or its baseline natural history and key nodes and stages of the epidemic; to determine the onset and process of the epidemic wave, the source and spread of the pathogen, the epidemiological etiology and the etiological etiology, the pathogen variation and adaptation, the epidemic intensity and control targets; to evaluate the phased or full-process performance of the epidemic wave, the level of monitoring and early warning and the effectiveness of prevention and control; and to continue to study the pathogen phenotype and genotype and their variation and adaptation.

[0091] In this invention, real-time data of the epidemic wave collected in the infectious disease monitoring area during the current period is matched and compared with a pre-constructed infectious disease epidemic wave trend map, concept, technical model map, or composite model map. The infectious disease epidemic wave trend map is drawn after analyzing historical epidemic data; it shows the characteristics and trends of the epidemic at different stages of its development over time, such as the initial growth stage, rapid development stage, stable stage, and decline stage. Through this matching, the specific stage of the epidemic wave in the infectious disease epidemic wave trend map during the current period can be accurately determined; this stage information is the target stage information. Clearly defining the target stage information is crucial for subsequent epidemic prevention and control decisions and measures, as it helps relevant departments understand the current development trend and mechanism of the epidemic, thereby enabling them to take targeted response strategies.

[0092] In this invention, the staging measurement is mainly based on the analysis of the epidemic characteristics and development trends exhibited at different stages of the epidemic wave. Different stages of the epidemic have their own unique characteristics. For example, in the initial growth stage of the epidemic, the number of cases may begin to increase slowly, and the spread is relatively small; while in the rapid development stage, the number of cases will rise rapidly, the spread will accelerate, and multiple transmission chains may emerge. By analyzing the effective monitoring key data of the epidemic wave in the current period (such as the number of cases, the speed of transmission, and the scope of transmission), combined with information from the target stage, it is determined whether the current epidemic wave conforms to the characteristics and development trend of a certain stage. For example, if the current number of cases continues to grow rapidly, and the spread continues to expand, which is consistent with the characteristics of the rapid development stage in the epidemic wave trend chart, then the staging measurement can further confirm that the current stage is rapid development, and based on this, analyze the potential risks and problems in this stage, such as whether medical resources are sufficient and whether prevention and control measures can effectively curb the spread of the epidemic.

[0093] In this invention, the disciplinary metric is based on multiple disciplines, conducting in-depth analysis of the characteristics of infectious diseases across different disciplinary dimensions. Infectious disease prevention and control involves multiple disciplines, such as medicine, epidemiology, environmental science, and sociology. From a medical perspective, it is necessary to analyze the characteristics of pathogens, pathogenic mechanisms, and transmission routes; from an epidemiological perspective, it is necessary to study the distribution patterns of cases and transmission dynamics; from an environmental science perspective, it is necessary to examine the impact of environmental factors (such as climate and sanitation conditions) on the spread of the epidemic; from a sociological perspective, it is necessary to analyze the relationship between population behavior, social activities, and the spread of the epidemic. By conducting a comprehensive multidisciplinary analysis of key monitoring data, a more complete understanding of the epidemiological characteristics of infectious diseases and their pathogen transmission mechanisms can be achieved.

[0094] After completing the staging and disciplinary metrics, the analysis results of both are combined to determine the target epidemic wave inflection point for the infectious disease surveillance area. Epidemic wave inflection points are critical moments in the development of an epidemic, such as the inflection point of rising case numbers (the moment when case numbers change from slow to rapid growth), the inflection point of case numbers (the boundary between a small to large rate of increase and a large to small rate of increase in case numbers), and the inflection point of declining case numbers (the moment when the epidemic changes from rapid growth to decline). Staging metrics allow us to understand the development trend of the epidemic at different stages and determine whether it is approaching an inflection point and is in the corresponding stage. Disciplinary metrics allow us to analyze factors influencing epidemic inflection points from multiple disciplinary perspectives, such as changes in epidemic intensity, changes in transmission dynamics, pathogen mutations, and the effectiveness of control measures. For example, if staging metrics show that the current epidemic wave is in a stage where the rate of case growth is gradually slowing down, while disciplinary metrics find that control measures (such as transmission route intervention and vaccination) have begun to take effect, then we can comprehensively judge that we may be approaching an inflection point in case numbers, thus allowing us to prepare in advance, such as clarifying control strategies, strengthening the allocation of medical resources, and improving the effectiveness of control measures.

[0095] Based on the above embodiments, the implementation of key prevention and control strategies for infectious diseases in the infectious disease monitoring area based on the key prevention period information corresponding to the turning point of the target epidemic wave includes: If the target epidemic wave turning point is the turning point of the number of cases, construct the first critical prevention period information. The first critical prevention period information includes infectious disease initiation information, abnormal health events, cluster cases, severe syndrome cases, case distribution and scope, transmission chain and transmission route, exposed population and scope of impact, suspected pathogen source and transmission risk, pathogen certainty and infectivity, pathogen phenotype or genotype, risk assessment, prevention and control strategies and measures, early warning of outbreak or epidemic start, and emergency plan information. If the turning point of the target epidemic wave is the inflection point of the number of cases, information on the second critical prevention period is constructed. The information on the second critical prevention period includes the manifestation and mechanism of the epidemic wave, the distribution and scope of cases, the mode of outbreak or epidemic transmission, key populations and high-risk populations, morbidity, mortality, infection rate, hospitalization rate, severe case rate, case fatality rate, pathogen source, infectivity, pathogenicity and virulence, pathogen variability, diversity, stability, drug resistance, dominance, adaptability and predictability; risk assessment, epidemic intensity warning, highest alert conditions, regional health cooperation, and prevention and control strategies and measures. If the turning point of the target epidemic wave is the turning point of the decline in the number of cases, information on the third critical prevention period is constructed. The information on the third critical prevention period includes the manifestation and mechanism of the epidemic wave, the intensity and degree of harm of the epidemic, the severity of the disease, the variability, diversity, stability, drug resistance, dominance, adaptability and predictability of pathogens, the transmission dynamics of environmental pathogens, population immunity, risk factors, risk assessment, mitigation conditions, prevention and control strategies and measures, and the risk of terminating the response. Based on the infectious disease epidemic wave trend map, the time points before the turning point of the epidemic wave corresponding to the first critical prevention period information, the second critical prevention period information, and the third critical prevention period information are determined as critical nodes, and early warning information corresponding to the critical nodes is constructed. Based on the early warning information and key prevention and control conditions corresponding to the key nodes, corresponding key control strategies and measures for the infectious disease are constructed, and the key control strategies and measures for the infectious disease are implemented in the infectious disease monitoring areas. The key prevention and control conditions include the highest alert condition, mitigation condition, control effectiveness condition, and termination response condition.

[0096] This invention integrates and synthesizes the relevant theoretical concepts, definitions, technical framework, technical routes, full-process monitoring, effective monitoring, phased measurement and disciplinary measurement results, conclusions and objectives of infectious disease epidemic wave monitoring and early warning technology (see reference). Figures 2 to 6 By using Tables 1 to 2, and subsequently Tables 3 and 4, effective early warning of epidemic waves and key nodes can be achieved, specifically as follows: Based on the powerful data collection and analysis capabilities of relevant monitoring and early warning systems and global Internet infectious disease epidemic intelligence systems, combined with the technical solution of this invention, the epidemic wave monitoring and early warning of case distribution, effective monitoring, etiology research, real-time analysis, risk assessment, trend judgment, effective early warning, key node early warning and effective response can be carried out in a timely manner to detect the threat of epidemic waves, formulate early warning decisions and initiate full-process and phased responses. Based on the technical solution of this invention, the natural history of infectious disease epidemic waves and their etiological, trend, regular, and bounded change points or nodes are analyzed in the normal distribution trend histogram or concave-convex trend curve of the epidemic wave. Figure 3 One, two, or three key nodes should obtain effective monitoring and early warning data as early as possible in the corresponding stages, and issue corresponding node alarms or warning signals as early as possible at each key node. As long as there are systematic and synergistic relationships among the primary indicators of the epidemic wave performance, pathogen characteristics, natural and social factors, and transmission mechanisms in the cases under study, the natural history of the epidemic wave will present stages of the highest alert condition, mitigation condition, control effectiveness, and termination of response condition. Among these, effective early warning of the epidemic wave already includes early warning of key nodes, and early warning scenarios or situations also include clustered outbreaks, the onset of outbreaks or epidemics, epidemic intensity, the highest alert condition, disease severity warning, and single case warning.

[0097] In this invention, targeted key control strategies and measures for infectious diseases are implemented in the monitored areas based on the critical prevention and control period information corresponding to the turning points of the target epidemic wave. The critical prevention and control period information differs for different turning points of the epidemic wave, and the corresponding prevention and control strategies and measures also vary.

[0098] When the turning point of the target epidemic wave is the turning point of the increase in the number of cases, information for the first critical prevention period should be constructed. This stage is the critical period when the epidemic begins to spread rapidly, and it is necessary to comprehensively collect and analyze various types of information. Information on infectious disease incipients, abnormal health events, cluster cases, and severe syndrome cases can help to detect abnormal situations in the epidemic early; the distribution and scope of cases, transmission chains and routes, exposed populations and affected populations can clarify the scope of the epidemic's spread and the potential populations affected; information such as suspected pathogen sources and transmission risks, pathogen certainty and infectivity, pathogen phenotype or genotype is crucial for understanding the characteristics and transmission mechanisms of pathogens; risk assessment can quantify the degree of risk of the epidemic; prevention and control strategies and measures, early warning of the outbreak or epidemic, and emergency plan information provide specific action guidelines for responding to the epidemic.

[0099] If the turning point of the target epidemic wave is the inflection point of the number of cases, information for the second critical prevention period should be constructed. At this time, the development of the epidemic enters a critical turning point, and it is necessary to pay attention to the manifestation and mechanism of the epidemic wave in order to deeply understand the development pattern of the epidemic; the distribution and scope of cases, and the mode of outbreak or epidemic transmission help to grasp the dynamics of the epidemic's spread; key populations and high-risk groups are the key targets for prevention and control; indicators such as morbidity, mortality, infection rate, hospitalization rate, severe illness rate, and case fatality rate can reflect the degree of harm of the epidemic to the health of the population; information such as the source of the pathogen, infectivity, pathogenicity and virulence, pathogen variability, diversity, stability, drug resistance, dominance, adaptability, and predictability are of great significance for assessing the threat of the pathogen and formulating prevention and control strategies; information such as risk assessment, epidemic intensity warning, maximum alert conditions, regional health cooperation, and prevention and control strategies and measures can help to adjust prevention and control measures in a timely manner to ensure that the epidemic is effectively controlled.

[0100] When the turning point of the target epidemic wave is the turning point of declining case numbers, information for the third critical prevention period is constructed. During this stage, the epidemic tends to ease or gradually come under control, but it is still necessary to monitor the epidemic wave's manifestations and mechanisms, its intensity and severity, and disease severity to prevent a resurgence. Information on pathogen variability, diversity, stability, drug resistance, dominance, adaptability, and predictability helps assess the long-term threat of the pathogen. Information on environmental pathogen transmission dynamics, population immunity, and risk factors is crucial for understanding the transmission environment and influencing factors of the epidemic. Information on risk assessment, mitigation conditions, control strategies and measures, and the risk of terminating the response provides a basis for gradually lifting control measures.

[0101] Furthermore, based on the infectious disease epidemic trend map, the turning points of the epidemic wave corresponding to the first, second, and third critical prevention periods are identified. These points are critical moments in epidemic prevention and control, requiring early warning information to be issued in advance. For example, before the turning point of rising case numbers, by analyzing the information from the first critical prevention period, if a trend of accelerated spread of the epidemic is found, a timely warning can be issued to remind relevant departments to take measures to strengthen prevention and control. The warning information can include information such as the severity of the epidemic, the scope of transmission, and the possible impact, so that relevant departments and the public can prepare accordingly.

[0102] In this invention, based on the early warning information and key prevention and control conditions corresponding to key nodes, corresponding key infectious disease prevention and control strategies and measures are constructed. Key prevention and control conditions include maximum alert conditions, mitigation conditions, prevention and control effectiveness conditions, and termination of response conditions, wherein: Highest alert level: When a specific infectious disease outbreak reaches the highest alert level, it means that the epidemic situation is very serious and the strictest prevention and control measures need to be taken for the corresponding infectious disease.

[0103] Mitigation conditions: When the epidemic of a specific infectious disease shows signs of mitigation and the mitigation conditions are met, the corresponding infectious disease prevention and control measures can be appropriately adjusted.

[0104] Conditions for the effectiveness of prevention and control: When formulating prevention and control strategies, it is necessary to consider the conditions for the effectiveness of prevention and control objectives to ensure that the cost of prevention and control measures is commensurate with their effectiveness.

[0105] Termination of response conditions: When the epidemic is effectively controlled and the termination of response conditions are met, prevention and control measures can be gradually lifted and normal production and life order can be restored.

[0106] For specific early warning alarms or alert signals, please refer to Table 3: Table 3 Effective Early Warning Data and Key Node Early Warning Alarms or Warning Signals

[0107] It should be noted that the key nodes 1, 2, and 3 of the histogram represent: Figure 3 The histogram shows three coordinate points representing March, September, and December 2001, and cases 39, 217, and 51; the key nodes 1, 2, and 3 on the curve graph represent... Figure 3 The graph shows three coordinate points: March, September, and December 2001, and cases numbering 120, 1093, and 1474. Effective early warning refers to acquiring data as early as possible in the corresponding stages before each critical node. Critical node early warning refers to timely alarms or warning signals issued at each critical node.

[0108] Key prevention and control conditions are shown in Table 4: Table 4 Key Prevention and Control Conditions

[0109] It should be noted that, in this invention, as long as there is a systematic and synergistic relationship between the epidemic wave performance, pathogen characteristics, natural and social factors, and primary indicators of the transmission mechanism of the case under study, the natural history of each epidemic wave will present the stages of highest alert conditions, mitigation conditions, control effectiveness, and termination of response conditions.

[0110] For the critical prevention period of infectious disease outbreaks (such as...) Figure 3 Before the horizontal axis point of March 2001, that is, before the relevant infectious disease monitoring and early warning system emphasized epidemic reporting and the occurrence of outbreaks or early warnings, based on the alarm system signals of the relevant monitoring and early warning system and the monitoring and early warning results and conclusions of the technical solution of this invention, key prevention strategies and measures to solve regional health problems during this period (such as...) Figures 2 to 6 (See Tables 1 to 4), and do the following five things as early as possible: 1. To detect, diagnose, treat, and manage cases of infectious disease infection in epidemic areas as early as possible, and to identify early warning signs and abnormal health events; 2. Complete epidemiological investigations, clinical characteristic analyses, three-dimensional distribution description analyses, and infectious disease ecology and field hygiene surveys of the initial and index cases, cluster cases, and severe syndrome cases as early as possible; 3. Propose hypotheses about the causes or clues of the epidemic wave as early as possible, including the exposure time of cases, pathogenic factors, transmission routes, sources of infection, risk factors, affected populations and scope; 4. Conduct epidemiological studies and multi-pathogen detection of pathogenic factors as early as possible based on hypotheses to verify the transmission routes and pathogenic factors hypotheses; 5. Implement comprehensive interventions as early as possible, including managing the source of infection, blocking transmission routes, and protecting susceptible populations, and issue early warnings of the onset of an epidemic wave to prevent transmission and spread and reduce the impact and intensity of the disease.

[0111] Ideal goal: Epidemiologically linked populations have few or no secondary cases and infections (minimum extreme value is zero), and do not exhibit the characteristics, trends, or patterns of the natural history of the epidemic wave, such as a normal distribution of the histogram of new cases per unit time, a concave-convex trend of the curve of cumulative cases per unit time, nodes and processes of case number changes, monitoring and early warning stages, key prevention and control stages, etc.

[0112] During periods of rapid increase in case numbers, as indicated by histograms and curves of infectious disease outbreaks (e.g., ... Figure 3 The period from March to December 2001 (on the horizontal axis), that is, the critical period for reducing the harm of phased and continuous epidemic waves, is based on the technical solution of this invention for effective monitoring, phased measurement, disciplinary measurement, effective early warning, and key node early warning, and key control strategies and measures to solve the epidemic wave problem during this period (such as...). Figures 2 to 6 (See Tables 1 to 4), and do the following five things as early as possible: 1. Identify as early as possible the highest alert conditions, including infected cases and their risks, affected populations and regions, pathogen diversity and variability, the adaptability and predictability of dominant genotypes, epidemic wave mechanisms and principles, transmission patterns and routes, epidemic intensity and degree of harm, pathogen transmission dynamics and population immunity; 2. Implement tiered and zoned administrative, technical, and social response strategies as early as possible, along with non-pharmaceutical interventions, treatment of various types of cases, and drug and vaccine research and development measures, and issue early warnings regarding epidemic intensity and the highest alert level. 3. Implement comprehensive interventions as early as possible, including source management, transmission route blocking, and protection of susceptible populations; implement prevention measures for exposed, key, and high-risk groups; and strengthen actions for affected populations and social organizations. 4. To prevent the epidemic from continuing and the number of cases from surging as early as possible, to suppress the peak and shorten the peak period, and to achieve the conditions for mitigation; 5. Determine the diversity, variability, dominance, immune evasion, drug resistance, adaptability and predictability of pathogens, population immunity and the dynamics of environmental pathogen transmission, and the risk of terminating the epidemic wave response as early as possible.

[0113] Ideal goal: To break and eliminate the normal distribution of the histogram of new cases per unit time, the concave and convex trends of the curve of cumulative cases per unit time, the nodes and processes of case number changes, the monitoring and early warning stages, and the key prevention and control stages of the epidemic wave's natural historical trend or pattern, with the incidence rate, morbidity rate, severe case rate, mortality rate, and socio-economic harm at the lowest or acceptable level. To achieve the best level of prevention and control effectiveness in a comprehensive comparison of the epidemic wave performance of the same infectious disease in multiple spatiotemporal populations globally, considering pathogen characteristics, natural and social factors, and prevention and control efficiency indicators.

[0114] From November 2000 to February 2002, the number of newly reported typhoid and paratyphoid cases in a certain region each month was 12, 13, 22, 34, 39, 93, 125, 155, 186, 197, 217, 207, 123, 51, 35, and 24, respectively. In 2001, the incidence rate in this region reached 355 per 100,000, and the incidence rate in key towns was as high as 800 per 100,000, presenting public health problems such as high incidence rate, high epidemic intensity, obvious dominant bacterial type, existence of environmental pollution, heavy disease burden, and significant socioeconomic impact. Since 2020, the incidence rate of typhoid and paratyphoid in this region has been ≤2.5 per 100,000 and has continued to decline, reaching the level of a low incidence area globally.

[0115] From November 2000 to February 2025, this invention, employing its innovative, groundbreaking, systematic, and collaborative technical solutions, defined the concept of infectious disease epidemic wave monitoring and early warning, established a technical framework and methodology, and developed comprehensive monitoring, effective monitoring, phased measurement, disciplinary measurement, effective early warning, key node early warning, key prevention, and key control techniques for epidemic waves. This enabled the systematic and collaborative detection, monitoring, measurement, early warning, prevention, control, and evaluation of typhoid and paratyphoid epidemic waves in the region. Nearly 100% of the information was gained regarding the full-process correlation between epidemic wave case distribution and environmental pollution, transmission routes and population protection, polluted environment and human contact with pathogens, and transmission dynamics and population immunity. Nearly 100% of the information was also gained regarding the conditions for epidemic wave occurrence and its natural history (initiation, rise, mitigation, and decline), as well as pathogen characteristics, sources of infection, sources of pollution, risk factors, epidemiological etiology, etiological etiology, transmission routes, and transmission patterns. The study identified sensitive populations and the scope of impact; innovatively formulated the definition and characteristics of high-prevalence areas and their assessment technical models, as well as the technical routes, models, and strategies for monitoring, investigation, control, and elimination of high-prevalence areas. It applied pathogen molecular typing and genome sequencing technologies to source tracing research, which is of great significance for improving the early detection capability of epidemic waves, identifying the causes of diseases in high-prevalence areas, reducing morbidity and disease burden, solving public health problems in the region, and preventing spillover transmission and spread. The study also established a "host, pathogen, environment" triangular model and a "storage host, exit portal, transmission mode, entry portal, susceptible host, pathogen" chain model based on the principles of epidemic wave occurrence or pathogen transmission mechanisms, and developed prevention and control strategies and measures such as risk prevention, outbreak avoidance, intensity reduction, and harm reduction. Furthermore, it identified mechanisms and objectives for proactively integrating with major public health service projects to promote the control and elimination of high-prevalence areas, and evaluated the phased or continuous performance of epidemic waves, the level of monitoring and early warning, and the effectiveness of prevention and control.

[0116] This invention embodies five major technological advantages: 1. Enhancing the core capabilities of comprehensive monitoring, effective monitoring, phased measurement, disciplinary measurement, effective early warning, key node early warning, key prevention, and key control of infectious disease outbreaks; 2. Understanding the conditions for outbreak occurrence, sources of infection, sources of pollution, risk factors, epidemiological causes, etiological causes, transmission patterns, and affected populations and their scope; 3. Understanding the natural history of outbreak initiation, rise, mitigation, decline, and termination, or baseline, as well as the key nodes and monitoring and early warning stages of outbreak mechanisms; 4. Determining the "host, pathogen, environment" triangular model and the "storage host, exit portal, transmission mode, entry portal, susceptible host, pathogen" chain model and their response strategies for outbreak occurrence or pathogen transmission mechanisms; 5. Evaluating the effectiveness and benefits of outbreak manifestations, pathogen characteristics, comprehensive monitoring, effective monitoring, phased measurement, disciplinary measurement, transmission mechanisms, effective early warning, key node early warning, key prevention and key control capabilities, and the control effects of preventing further spread or maintaining a controllable low incidence level.

[0117] The technical solution of this invention is of great significance for preventing and responding to the risks and threats of infectious disease outbreaks, judging and predicting the trend and consequences of outbreaks, formulating and implementing prevention and control strategies and measures, obtaining and evaluating the benefits of monitoring, early warning and prevention and control, and avoiding and mitigating harm and impact. It provides reference and basis for the establishment of general standard methods or technologies for monitoring and early warning of infectious disease outbreaks, as well as for the monitoring, measurement, early warning, prevention, control and evaluation of infectious disease outbreaks.

[0118] The following describes the infectious disease epidemic wave monitoring and early warning system that integrates multi-source data provided by the present invention. The infectious disease epidemic wave monitoring and early warning system that integrates multi-source data described below can be referred to in correspondence with the infectious disease epidemic wave monitoring and early warning method that integrates multi-source data described above.

[0119] Figure 7 This is a schematic diagram of the infectious disease epidemic wave monitoring and early warning system that integrates multi-source data provided by the present invention, as shown below. Figure 7As shown, this invention provides an infectious disease epidemic wave monitoring and early warning system that integrates multi-source data, including an infectious disease epidemic wave trend map construction module 701, an indicator construction module 702, a monitoring module 703, and an early warning control module 704. The infectious disease epidemic wave trend map construction module 701 is used to dynamically construct an infectious disease epidemic wave trend map based on historical infectious disease case data of the monitored area over a historical period, determine epidemic wave nodes or epidemic wave turning points, and perform epidemic wave staging measurement based on the epidemic wave nodes or epidemic wave turning points to dynamically construct the infectious disease epidemic wave trend map. The indicator construction module 702 is used to construct the infectious disease epidemic wave trend map based on real-time infectious disease case data of the monitored area in the current period. Based on the infectious disease epidemic wave trend map, the monitoring module 703 determines the target infectious disease epidemic wave multi-source data information type indicators corresponding to the infectious disease monitoring area in the current time period; the monitoring module 703 is used to effectively monitor the infectious disease epidemic wave in the infectious disease monitoring area based on the target infectious disease epidemic wave multi-source data information type indicators, monitoring and prevention benefit indicators, and effective monitoring targets, and obtain effective monitoring key data; the early warning and control module 704 is used to determine the target epidemic wave turning point corresponding to the infectious disease monitoring area based on the effective monitoring key data and the infectious disease epidemic wave trend map, and to implement key infectious disease prevention and control strategies and measures in the infectious disease monitoring area based on the target epidemic wave turning point.

[0120] The infectious disease outbreak monitoring and early warning system provided by this invention integrates multi-source data. It constructs an outbreak wave concept and technical model diagram using historical case data from the monitored area, determining the outbreak wave's change nodes, inflection points, and natural history stages such as initiation, rise, mitigation, and decline. Next, combining real-time data with the concept and technical model diagram, it clarifies the multi-source data information type indicators for the target outbreak wave in the current period. Based on these indicators, control effectiveness indicators, and effective monitoring targets, it conducts effective monitoring to obtain key data on the outbreak wave's natural history, including epidemiological etiology, pathogenic etiology, transmission patterns, alert conditions, and mitigation conditions. Finally, based on this key data and the concept and technical model diagram, it implements key control strategies and measures in the monitored area, thereby more effectively assessing the epidemic situation and consequences, determining the outbreak wave's natural history and mechanisms, and implementing control strategies and measures.

[0121] The system provided in this embodiment of the invention is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0122] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 8As shown, the electronic device may include: a processor 801, a communications interface 802, a memory 803, and a communication bus 804, wherein the processor 801, the communications interface 802, and the memory 803 communicate with each other through the communication bus 804. The processor 801 can call logic instructions in the memory 803 to execute a method for monitoring and early warning of infectious disease outbreaks by fusing multi-source data. This method includes: dynamically constructing an infectious disease outbreak trend map based on historical infectious disease case data of the monitored area over a historical period; determining outbreak nodes or outbreak turning points; performing outbreak stage measurement based on the outbreak nodes or outbreak turning points; determining the target infectious disease outbreak multi-source data information type index corresponding to the monitored area in the current period based on real-time infectious disease case data and the infectious disease outbreak trend map; effectively monitoring the infectious disease outbreak in the monitored area based on the target infectious disease outbreak multi-source data information type index, monitoring and control effectiveness index, and effective monitoring targets; and determining the target outbreak turning point corresponding to the monitored area based on the effective monitoring key data and the infectious disease outbreak trend map, and implementing key infectious disease prevention and control strategies and measures for the monitored area based on the target outbreak turning point.

[0123] Furthermore, the logical instructions in the aforementioned memory 803 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0124] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the infectious disease epidemic wave monitoring and early warning method merging multi-source data provided by the above methods, the method comprising: dynamically constructing an infectious disease epidemic wave trend map based on historical infectious disease case data of an infectious disease monitoring area over a historical period, determining epidemic wave nodes or epidemic wave turning points, and performing epidemic wave staging measurement according to the epidemic wave nodes or the epidemic wave turning points, dynamically constructing an infectious disease epidemic wave trend map; and according to the infectious disease... Based on real-time data of infectious disease cases in the monitored area during the current period and the infectious disease epidemic wave trend map, the target infectious disease epidemic wave multi-source data information type indicators corresponding to the monitored area during the current period are determined. Based on the target infectious disease epidemic wave multi-source data information type indicators, monitoring and control effectiveness indicators, and effective monitoring targets, effective monitoring of the infectious disease epidemic wave is carried out in the monitored area to obtain key effective monitoring data. According to the key effective monitoring data and the infectious disease epidemic wave trend map, the target epidemic wave turning point corresponding to the monitored area is determined, and based on the target epidemic wave turning point, key infectious disease prevention and control strategies and measures are implemented in the monitored area.

[0125] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the infectious disease epidemic wave monitoring and early warning method provided in the above embodiments, which integrates multi-source data. The method includes: dynamically constructing an infectious disease epidemic wave trend map based on historical data of infectious disease cases in an infectious disease monitoring area over a historical period; determining epidemic wave nodes or epidemic wave turning points; performing epidemic wave staging measurement based on the epidemic wave nodes or epidemic wave turning points; dynamically constructing an infectious disease epidemic wave trend map; determining the target infectious disease epidemic wave multi-source data information type index corresponding to the infectious disease monitoring area in the current period based on the real-time data of infectious disease cases in the infectious disease monitoring area and the infectious disease epidemic wave trend map; effectively monitoring the infectious disease epidemic wave in the infectious disease monitoring area based on the target infectious disease epidemic wave multi-source data information type index, monitoring and control effectiveness index, and effective monitoring target, and obtaining effective monitoring key data; determining the target epidemic wave turning point corresponding to the infectious disease monitoring area based on the effective monitoring key data and the infectious disease epidemic wave trend map, and implementing key prevention and control strategies and measures for infectious diseases in the infectious disease monitoring area based on the target epidemic wave turning point.

[0126] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring and early warning of infectious disease epidemic wave by fusing multi-source data, characterized in that, The method comprises the following steps: Based on the infectious disease case history data of the infectious disease monitoring area in the historical period, the epidemic wave node or the epidemic wave turning point is determined, and the epidemic wave staging measurement is carried out according to the epidemic wave node or the epidemic wave turning point, and the infectious disease epidemic wave trend chart is dynamically constructed; According to the infectious disease case real-time data of the infectious disease monitoring area in the current period and the infectious disease epidemic wave trend chart, the target infectious disease epidemic wave multi-source data information type index corresponding to the current period of the infectious disease monitoring area is determined; Based on the target infectious disease epidemic wave multi-source data information type index, the monitoring and prevention benefit index and the effective monitoring target, the infectious disease epidemic wave effective monitoring of the infectious disease monitoring area is carried out, and the effective monitoring key data is obtained; According to the effective monitoring key data and the infectious disease epidemic wave trend chart, the target epidemic wave turning point corresponding to the infectious disease monitoring area is determined, and the infectious disease key prevention and control strategy measure is executed for the infectious disease monitoring area based on the target epidemic wave turning point. 2.The method of claim 1, wherein, The method comprises the following steps: According to the infectious disease case history data of the infectious disease monitoring area in the historical period, the case number growth fluctuation characteristic and the infectious disease epidemic trend fluctuation process are obtained; According to the preset unit time, the epidemic wave node corresponding to each time point of the infectious disease monitoring area in the historical period is constructed, and the epidemic wave turning point is determined from a plurality of epidemic wave nodes based on the case number growth fluctuation characteristic and the infectious disease epidemic trend fluctuation process, wherein the epidemic wave turning point at least includes a case number rising turning point, a case number inflection point and a case number falling turning point; Based on the infectious disease case history number of the time point corresponding to the epidemic wave turning point, an infectious disease epidemic wave unit time cumulative case number curve chart is generated; based on the infectious disease case history new number of the time point corresponding to each epidemic wave node, a unit time new case number histogram is generated; According to the infectious disease epidemic wave unit time cumulative case number curve chart and the unit time new case number histogram, the infectious disease epidemic wave trend chart is constructed. 3.The method of claim 2, wherein, The method comprises the following steps: The infectious disease case real-time data is matched with the infectious disease epidemic wave trend chart to determine the stage information corresponding to the infectious disease monitoring area in the infectious disease epidemic wave trend chart, wherein the stage information includes the case number growth starting period stage of the infectious disease, the early monitoring and early warning stage, the case number rising period stage, the middle and late monitoring and early warning stage, the growth platform period stage and the case number falling period stage; According to the stage information, determine a target infectious disease epidemic wave multi-source data information type index from the infectious disease epidemic wave multi-source data information type index, the infectious disease epidemic wave multi-source data information type index including an infectious disease ecology and environmental health observation index, an epidemiology monitoring and risk factor analysis index, a case infection monitoring and investigation and management index, a case environmental pathogen and genomics monitoring index, a pathogen variability and dominance detection index, and a whole-process monitoring and effective response system evaluation index, a data information type index lead time and a prediction certainty value inherent contradiction; The infectious disease ecology and environmental health observation index includes infectious disease early information, abnormal health events, clustered cases, suspected environmental pollution sources, population immunity, and natural and social factors. The epidemiology monitoring and risk factor analysis index includes epidemic wave change information, case distribution and range, exposed population information, sensitive population information, suspected pathogen source information, and transmission risk. The case infection monitoring and investigation and management index includes case tracking management rate, incidence rate, hospitalization rate, severe rate, case fatality rate, mortality rate, infection rate, and transmission speed. The case environmental pathogen and genomics monitoring index includes pathogen certainty, pathogen infectivity, pathogen pathogenicity, pathogen virulence, pathogen phenotype, pathogen molecular typing, and genome sequencing. The pathogen variability and dominance detection index includes pathogen genetic diversity, pathogen genetic variability, pathogen genetic genotype, pathogen dominant genotype adaptability, pathogen dominant genotype stability, and pathogen dominant genotype predictability. The whole-process monitoring and effective response system evaluation index includes epidemic wave performance, effective monitoring information, staging measurement, discipline measurement, effective early warning information, key node early warning information, prevention and control effect, and prevention and control benefit.

4. The method according to claim 3, wherein, Based on the target infectious disease epidemic wave multi-source data information type index, monitoring and prevention and control benefit index, and effective monitoring target, the infectious disease monitoring area is subjected to infectious disease epidemic wave effective monitoring, and effective monitoring key data is obtained, including: According to the whole-process correlation multi-source data information index, epidemic change and influence range monitoring target, epidemic mechanism and response strategy monitoring target, and normalized monitoring pathogen research target, the effective monitoring target is constructed. The epidemic wave performance, pathogen characteristics, natural and social factors, and transmission mechanism in the target infectious disease epidemic wave multi-source data information type index are taken as first-level indexes, the monitoring and prevention and control benefit index is taken as a second-level index, and the correlation between the target infectious disease epidemic wave multi-source data information type index and the prevention and control benefit index is established. The effective monitoring key data is obtained by performing effective monitoring on the effective monitoring target based on the correlation between the target infectious disease epidemic wave multi-source data information type index and the monitoring and prevention benefit index. The effective monitoring process is composed of four cyclic components. The first cyclic component is used to monitor the infectious disease occurrence population, location and time. The second cyclic component is used to monitor the case, infected person, pathogen and risk factor change. The third cyclic component is used to determine the epidemic wave monitoring and early warning, case and infected person follow-up, risk factor and intervention target. The fourth cyclic component is used to perform prevention and control intervention and prevention and control effect evaluation.

5. The method according to claim 3 or 4, wherein, The target epidemic wave turning point of the infectious disease monitoring area is determined according to the effective monitoring key data and the infectious disease epidemic wave trend chart, including: Obtaining the target stage information of the infectious disease epidemic wave of the infectious disease monitoring area in the current period in the infectious disease epidemic wave trend chart; According to the effective monitoring key data and the target stage information, the staging measurement and the discipline measurement are performed to determine the target epidemic wave turning point corresponding to the infectious disease monitoring area. The staging measurement is based on the analysis of the epidemic characteristics and development trend of the epidemic wave in different stages. The discipline measurement is based on the analysis of the characteristics of the infectious disease in different discipline dimensions.

6. The method of claim 5, wherein the method further comprises: The key prevention and control strategy measures of the infectious disease are performed on the infectious disease monitoring area based on the key prevention period information corresponding to the target epidemic wave turning point, including: If the target epidemic wave turning point is the turning point of the number of cases, the first key prevention period information is constructed. The first key prevention period information includes infectious disease head information, abnormal health events, aggregation cases, severe syndrome cases, case distribution and range, transmission chain and transmission route, exposed population and scope, suspected pathogen source and transmission risk, pathogen certainty and infectivity, pathogen phenotype or genotype, risk assessment, prevention and control strategy and measures, outbreak or epidemic start early warning, and emergency plan information; If the target epidemic wave turning point is the inflection point of the number of cases, the second key prevention period information is constructed. The second key prevention period information includes epidemic wave performance and mechanism principle, case distribution and range, outbreak or epidemic transmission mode, key population and high-risk population, incidence rate, mortality rate, infection rate, hospitalization rate, severe rate, case fatality rate, pathogen source, infectivity, pathogenicity and virulence, pathogen variability, diversity, stability, drug resistance, dominance, adaptability and predictability, risk assessment, epidemic intensity early warning, highest alert condition, regional health cooperation, and prevention and control strategy and measures; If the target epidemic wave turning point is the turning point of the number of cases, a third key prevention period information is constructed, including epidemic wave performance and mechanism principle, epidemic intensity and harm degree, disease severity, pathogen variability, diversity, stability, drug resistance, dominance, adaptability and predictability, environmental pathogen transmission dynamics, population immunity, risk factors, risk assessment, mitigation conditions, prevention and control strategies and measures, and termination response risk; Based on the infectious disease epidemic wave trend chart, the first key prevention period information, the second key prevention period information and the third key prevention period information are determined respectively corresponding to the time point before the turning point of the epidemic wave, and the warning information corresponding to the key node is constructed; Based on the warning information and key prevention control conditions corresponding to the key node, the corresponding infectious disease key control strategy measures are constructed, and the infectious disease key control strategy measures are executed in the infectious disease monitoring area, wherein the key prevention control conditions include the highest alert condition, the mitigation condition, the prevention and control benefit condition and the termination response condition.

7. An infectious disease epidemic wave monitoring and early warning system that fuses multi-source data, characterized in that, It comprises: An infectious disease epidemic wave trend chart construction module is configured to determine epidemic wave nodes or epidemic wave turning points based on infectious disease case historical data of an infectious disease monitoring area in a historical period, and dynamically construct an infectious disease epidemic wave trend chart according to the epidemic wave nodes or the epidemic wave turning points. An index construction module is configured to determine a target infectious disease epidemic wave multi-source data information type index corresponding to the infectious disease monitoring area in a current period according to infectious disease case real-time data of the infectious disease monitoring area in the current period and the infectious disease epidemic wave trend chart. A monitoring module is configured to perform infectious disease epidemic wave effective monitoring on the infectious disease monitoring area based on the target infectious disease epidemic wave multi-source data information type index, a monitoring and prevention and control benefit index and an effective monitoring target, and obtain effective monitoring key data. A warning control module is configured to determine a target epidemic wave turning point corresponding to the infectious disease monitoring area according to the effective monitoring key data and the infectious disease epidemic wave trend chart, and execute infectious disease key prevention and control strategy measures on the infectious disease monitoring area based on the target epidemic wave turning point.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the computer program to realize the fusion multi-source data infectious disease epidemic wave monitoring and early warning method of any one of claims 1 to 6. The processor executes the computer program to realize the fusion multi-source data infectious disease epidemic wave monitoring and early warning method of any one of claims 1 to 6.

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