Ambulance route planning method based on patient status

Abstract

The application discloses an ambulance route planning method based on patient state, and relates to the technical field of route planning. The method comprises the following steps: acquiring vital sign data of a target patient and a departure position of the target patient; determining whether the target patient is infected with a virus according to the vital sign data; if the target patient is infected with the virus, acquiring human flow density data and path environment data between the departure position and a target position of an ambulance; and planning a route of the ambulance according to the human flow density data and the path environment data. The application can avoid the areas with concentrated human flow and the areas where the virus is easy to spread, so as to avoid the transmission path and the infection receptor, thereby reducing the infection of bacteria in the first-aid route.

Description

Technical Field

[0001] This invention relates to the technical field of route planning, and more particularly to a method for ambulance route planning based on patient condition. Background Technology

[0002] Against the backdrop of frequent public health emergencies and increasingly severe demands for infectious disease prevention and control, ambulances, as the core carriers for transporting infected patients, have their route planning's scientific accuracy and safety directly impacting patient treatment outcomes and public health security. Traditional ambulance route planning methods have long focused on optimizing traffic efficiency, largely based on classic path planning algorithms (such as Dijkstra's algorithm and A* algorithm), using the shortest travel time or minimum mileage as the objective function, and generating optimal routes through static map data (such as road topology and traffic light distribution).

[0003] In the pre-hospital emergency care system, transporting patients with infectious diseases is one of the most challenging tasks. During transport, patients may spread viruses through aerosols, droplets, or contact. Inappropriate route selection could lead to the spread of the virus to susceptible populations, exacerbating public health risks. The core objective of emergency care is that time is of the essence, neglecting the potential for pathogen transmission during transport.

[0004] Therefore, how to reduce the risk of infection along emergency routes has become a pressing technical problem. Summary of the Invention

[0005] The technical problem solved by this invention is to reduce the risk of infection in emergency rescue routes.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an ambulance route planning method based on patient status, comprising:

[0007] Obtain the target patient's vital signs data and the target patient's starting location;

[0008] Determine whether the target patient is infected with the virus based on vital signs data;

[0009] If the target patient is infected with the virus, obtain the crowd density data and route environment data between the departure location and the target location of the ambulance;

[0010] The ambulance route is planned based on pedestrian density data and route environment data.

[0011] Preferably, ambulance routes are planned based on pedestrian density data and route environment data, including:

[0012] Determine the initial transfer route of the ambulance based on the departure and destination locations;

[0013] Based on the acquired pedestrian density data and path environment data, predict the time series data of pedestrian density and path environment in the initial transfer path;

[0014] The risk of virus exposure along the initial transfer route was determined based on the time series data of the initial transfer route, the population density, and the environmental time series data along the route.

[0015] The initial transport route was adjusted based on the risk of virus exposure.

[0016] Preferably, determining the initial transfer route of the ambulance based on the departure location and the destination location includes:

[0017] Obtain information on the viral transmission characteristics, pathological status, and exposure history of the target patients;

[0018] Determine the treatment priority for the target patient based on their pathological condition;

[0019] The risk of virus transmission in target patients is determined based on their viral transmission characteristics and exposure history.

[0020] A composite priority is generated based on the target patient's virus transmission risk and treatment priority.

[0021] Construct a path feature library from the starting point to the target point;

[0022] Extract air circulation data, population exposure data, and physical isolation features along each path from the path feature database;

[0023] Each path is clustered into gradient pools with different transmission blocking capabilities based on air circulation data, population exposure data, and physical isolation characteristics;

[0024] Based on the composite priority of the target patient and the transmission blocking capability of the route, a stratified matching process is performed to assign an initial transport route to the target patient.

[0025] Preferably, air circulation data, population exposure data, and physical isolation features along each path in the path feature database are extracted, including:

[0026] The ventilation rate of the path is determined by the ratio of the road width to the height of the buildings on both sides;

[0027] The air circulation data of the path is determined based on wind force data and the ventilation rate of the path;

[0028] Population exposure data for a route are determined based on the number of susceptible locations along the route.

[0029] The physical isolation characteristics of a route are determined based on the completeness of the ambulance lanes and temporary isolation facilities included in the route.

[0030] Preferably, based on the target patient's composite priority and the transmission blocking capability of the pathway, a stratified matching process is performed to assign an initial transport pathway to the target patient, including:

[0031] If the target patient's composite priority is high transmission activity, then a path pool with high transmission blocking capability is matched for the target patient, the transmission blocking fit score between the target patient and each path in the path pool with high transmission blocking capability is determined, and the initial transfer path is determined based on the fit score.

[0032] If the target patient's composite priority is medium or low transmission activity, then the estimated travel time of the path in the path pool with medium transmission blocking capability is used to determine the initial transfer path.

[0033] Preferably, after planning the ambulance route based on pedestrian density data and route environment data, the method further includes:

[0034] Collect data on virus concentration inside the ambulance and the status of its ventilation system;

[0035] Obtain real-time population density changes and isolation facility status along the current travel route;

[0036] The transmission risk index is determined based on the virus concentration inside the vehicle, the status of the ventilation system, real-time changes in population density, and the status of isolation facilities.

[0037] The planned routes were adjusted based on the transmission risk index.

[0038] Preferably, the planned route is adjusted based on the transmission risk index, including:

[0039] If the transmission risk index exceeds the preset safety threshold, an alternative path segment will be discovered in the gradient pool of the current path, and the ambulance will be switched to the alternative path.

[0040] Preferably, after obtaining the real-time population density changes and isolation facility status of the current travel route, the method further includes:

[0041] Real-time monitoring of sudden crowd gatherings in areas traversed by the route is achieved through roadside cameras and mobile phone signaling data.

[0042] Based on the data of sudden crowd gatherings, we can extrapolate the peak population density and the corresponding increase in virus exposure risk during a future preset period while traveling along the current path.

[0043] If the increased risk of virus exposure exceeds a preset tolerance threshold, the ambulance will be switched to an alternative route.

[0044] Preferably, the initial transport route is adjusted based on the risk of virus exposure, including:

[0045] Define dual-objective constraints, where the first objective constraint is that the risk of virus exposure is less than or equal to a preset exposure threshold, and the second objective constraint is that the total transfer time is less than the golden time for the treatment of the target patient.

[0046] If the initial path only satisfies the first objective constraint but not the second objective constraint, then the suboptimal path is selected from the path pool with high propagation blocking capability based on the time required for transshipment.

[0047] If the initial path only meets the second objective constraint but not the first objective constraint, then a forced switch to a path pool with high propagation blocking capability will be made to adjust the initial transfer path.

[0048] Preferably, after planning the ambulance route based on pedestrian density data and route environment data, the method further includes:

[0049] Real-time collection of vital signs data of target patients during transport, including body temperature, heart rate, blood oxygen saturation, and level of consciousness;

[0050] The real-time vital signs data are compared with the vital signs data before the initial transfer to determine whether the target patient's condition has deteriorated.

[0051] If a target patient's condition worsens, the composite priority of the target patient will be updated based on the severity of the worsening.

[0052] Based on the updated composite priority, the propagation blocking adaptation score of the current transit path is re-determined;

[0053] The transport routes were adjusted based on the redefined transmission blocking fit score.

[0054] The beneficial effects of this invention are as follows: Based on vital sign data, it is determined whether the target patient is infected with a virus. If the target patient is infected with a virus, the population density data and path environment data between the departure location and the target location of the ambulance are obtained. Based on the population density data and path environment data, the route of the ambulance is planned to avoid areas with concentrated population and areas where the virus is easily spread. By avoiding transmission paths and infection receptors, the infection of pathogens in the emergency route is reduced. Attached Figure Description

[0055] Figure 1 A basic flowchart illustrating an ambulance route planning method based on patient status, provided in an embodiment of the present invention;

[0056] Figure 2 Provided for embodiments of the present invention Figure 1 A basic flowchart of the sub-steps in S140;

[0057] Figure 3 Provided for embodiments of the present invention Figure 2 A basic flowchart of the sub-step S141 in the middle;

[0058] Figure 4 Provided for embodiments of the present invention Figure 3 A basic flowchart of the sub-steps in S260. Detailed Implementation

[0059] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0060] Patients with infectious diseases (especially those in the acute phase) are mobile sources of the virus. Their physiological activities continuously release viral particles into the environment. These viruses can directly adhere to the interior surfaces of ambulances or remain suspended in the air, forming initial contamination. As a mobile transport unit for patients with infectious diseases, ambulances are prone to becoming mobile sources of virus spread during transport.

[0061] However, some ambulances use an internal recirculation mode for their air conditioning systems. Virus particles can easily circulate repeatedly inside the vehicle through the air conditioning ducts, and may even be blown back into the vehicle from the vents. If an ambulance passes through densely populated areas such as schools and shopping malls during flu season, even with the windows closed, the air conditioning recirculation may release virus-containing aerosols (especially in poorly ventilated underground passages) into the external environment, making the ambulance a mobile source of virus spread.

[0062] Based on this, in Example 1, refer to Figure 1 As an embodiment of the present invention, an ambulance route planning method based on patient status is provided, comprising:

[0063] S110, acquire the target patient's vital signs data and the target patient's starting location;

[0064] S120 determines whether a target patient is infected with a virus based on vital signs data;

[0065] S130, If the target patient is infected with the virus, obtain the crowd density data and path environment data between the departure location and the target location of the ambulance;

[0066] S140 plans ambulance routes based on pedestrian density data and route environment data.

[0067] Vital signs data refer to basic monitoring indicators that reflect a patient's physiological state, such as heart rate, blood pressure, blood oxygen saturation, body temperature, and respiratory rate. They are key inputs for assessing the urgency and potential risks to a patient's health.

[0068] In this context, viral infection specifically refers to the identification of whether a patient is infected with an infectious virus, such as influenza, by triggering an alert based on vital signs data, such as a body temperature exceeding 38 degrees Celsius accompanied by cough symptoms, through a pre-set medical model or rule base. This determination directly impacts the complexity of subsequent route planning. To simplify this determination, detection devices can be used directly. For example, Chinese patent publication number "CN111656191B" discloses a method and device for differentiating between viral and bacterial infections to quickly identify whether a target patient is infected with a virus.

[0069] Pedestrian density data refers to the real-time or near-real-time level of pedestrian gathering in a road network. It can be collected through technologies such as surveillance cameras, mobile phone signaling, or heat maps and is used to assess the risk of cross-infection during transportation.

[0070] The path environment data focuses on factors related to the spread of the virus, including road ventilation conditions, the length of time people stay in surrounding places (such as shopping malls and bus stops), the density of recent virus infection cases in the road section or area, and whether there are poorly ventilated enclosed spaces (such as underground passages and narrow alleys). This information is directly related to the probability of the virus spreading in the air and is a key basis for avoiding the risk of virus spread.

[0071] First, the system acquires the target patient's vital signs (e.g., body temperature 38.9 degrees Celsius, respiratory rate 28 breaths per minute) and departure location (e.g., the entrance of an old residential area) through multi-source data interfaces to complete basic information collection. Then, based on preset virus infection judgment rules (e.g., body temperature exceeding 38.5 degrees Celsius accompanied by respiratory symptoms), the system determines that the patient belongs to a high-risk group for virus infection. If the judgment is valid, the system simultaneously retrieves two types of data from the departure point to the target hospital (e.g., a designated infectious disease hospital): one is pedestrian density data, such as the current pedestrian density of 7,000 people per square kilometer in an old commercial street, indicating high-frequency interpersonal contact; the other is route environment data, such as the main road of the old commercial street being a poorly ventilated pedestrian street with dense surrounding shops and long dwell times, and three recent cases of virus infection in the area, while the alternative auxiliary road has good ventilation, is surrounded by an open riverside promenade, has fewer people, and no recent cases reported. Finally, the planning module integrates these two risks, avoiding both cross-infection caused by concentrated crowds and closed or high-case areas where the virus can easily spread, generating the optimal route.

[0072] For example, an emergency center received a 70-year-old patient with pneumonia, a temperature of 39.1 degrees Celsius, and an oxygen saturation of 91%. The patient originated from the Xingfuli residential area in the old city and was heading to an infectious disease hospital 2.5 kilometers away. At this time, pedestrian density data showed that Minsheng Road, the only route from the residential area to the hospital, was a concentrated area of ​​morning markets with a pedestrian density as high as 9,000 people per square kilometer, and there were multiple vegetable stalls along the roadside, leading to prolonged periods of crowd gathering. Environmental data also showed that a section of Minsheng Road was an underpass with extremely poor ventilation, and there had been four recent cases of viral infection in the neighborhood where the underpass was located. The alternative route, Binjiang Road, although 0.8 kilometers longer than Minsheng Road, was an open riverside walkway with good ventilation, almost no crowds in the surrounding area, and no recent cases. The system ultimately recommended the Binjiang Road route. Although the distance was slightly increased, by avoiding high-traffic areas and enclosed spaces where the virus could easily spread, the risk of virus transmission during the ambulance journey was reduced by approximately 65%, while the probability of infection exposure for both medical staff and the patient was also significantly reduced. If the patient is a heart patient without signs of infection, the system will skip the virus-related risk assessment and directly select the fastest route based on routine traffic efficiency data to ensure the timeliness of emergency treatment. By combining the patient's infection status with the risk of virus transmission in the environment, the route planning shifts from simply pursuing speed to balancing safety and efficiency. This is especially suitable for emergency transport scenarios during infectious disease outbreaks, as it cuts off the possibility of bacterial infection at key links in the transmission chain through proactive risk avoidance.

[0073] Reference Figure 2 Preferably, S140 includes sub-steps S141 to S144:

[0074] S141, determine the initial transfer route of the ambulance based on the departure location and the destination location;

[0075] S142, based on the acquired pedestrian density data and path environment data, predict the pedestrian density time series data and path environment time series data in the initial transfer path;

[0076] S143, Determine the virus exposure risk of the initial transfer route based on the initial transfer route, time series data of population density, and time series data of the route environment;

[0077] S144, Adjust the initial transport route based on the risk of virus exposure.

[0078] The above sub-steps focus on avoiding virus exposure during a viral infection state through path planning.

[0079] The initial transfer path is a conventional route generated based on the starting and destination locations. It is usually calculated by navigation algorithms such as Dijkstra's or A* algorithms to find the shortest or fastest path from the starting point to the destination.

[0080] Pedestrian density time series data reflects the changes in crowd density at different points in time along various sections of an initial path. This can be analyzed using time series data from mobile phone signaling and surveillance videos to determine the dynamic increase in pedestrian density on a particular section during the morning rush hour (8:00-9:00 AM) from 4,500 to 7,800 people per square kilometer. Since the resident population of a given area is relatively fixed, the pattern of pedestrian flow data changes is also relatively fixed; therefore, predictions can be made by combining historical data.

[0081] The path environment time series data refers to the fluctuations of environmental factors at each section of the path over time, including ventilation conditions such as changes in the ventilation coefficient between closed pedestrian streets and open auxiliary roads, temporary closures such as time-limited road closures during construction, and the duration of crowd gatherings in surrounding areas such as the intervals between bus stops. These data are directly related to the virus's ability to spread at different times. The patterns of change in pedestrian flow data are relatively fixed, and building data is also relatively fixed. Therefore, the path environment time series data is also relatively fixed and can be used to make predictions by combining historical data.

[0082] Virus exposure risk is a comprehensive assessment value that combines the initial route, the timing of pedestrian flow, and the timing of environmental factors. It is calculated using a weighted model, such as multiplying pedestrian density by the airborne transmission rate of the virus and adding a correction for the environmental ventilation coefficient, to finally obtain the probability of virus contact at a certain time and location on a certain road segment. This is a quantitative basis for judging whether a route is safe.

[0083] First, a conventional initial route is obtained based on the origin and destination, such as the Jiefang Road route from Heping Community to the Infectious Disease Hospital. Then, time-dimensional data is overlaid on each segment of this route, such as the pedestrian flow growth curve during the morning rush hour on Jiefang Road and the ventilation coefficient of the enclosed environment. Then, the overall virus exposure risk of the initial route is calculated. For example, after weighted averaging the risk values ​​of each segment, if the result exceeds the preset high-risk threshold, an adjustment is triggered. Finally, a route with lower exposure risk is generated by replacing high-risk segments or the order of segments.

[0084] Specifically, if a patient testing positive for Virus X has a body temperature of 39.2 degrees Celsius and blood oxygen 90, and travels from Heping Community in the old city to a designated infectious disease hospital, the initial route generated in S141 is Jiefang Road, a distance of 4 kilometers, with an estimated travel time of 15 minutes. In S142, the time-series data of Jiefang Road is calculated. During the morning rush hour from 8:00 to 9:00, the pedestrian density on Jiefang Road increases from 4,500 people per square kilometer to 7,800 people per square kilometer. This section of road is a closed pedestrian street with a ventilation coefficient of 0.3. The worse the ventilation, the easier it is for the virus to accumulate. In S143, the virus exposure risk of the initial route is assessed. After weighted calculation based on pedestrian density and ventilation coefficient, the risk value reaches 8.5, exceeding the preset threshold of 6.0. Then, in S144, the route is immediately adjusted to Zhongshan Road, which has a pedestrian density of only 3,200 people at the same time. It is an open auxiliary road with a ventilation coefficient of 0.7, and the risk value drops to 3.6. After the adjustment, the probability of virus exposure during the patient's transfer is reduced by 58%, while the travel time only increases by three minutes.

[0085] This process does not only avoid high-traffic areas, but also captures risk changes during the travel period through time-series data. For example, the traffic flow on Jiefang Road will decrease after 9:00, but the patient's journey covers the peak period, so it must be replaced in advance to cut off the spread of infectious diseases during ambulance transportation. During the epidemic of infectious diseases, it can effectively reduce the risk of bacterial infection during the emergency process. If the patient is an uninfected trauma patient, the system will skip this part of the risk calculation and directly use the initial path to ensure the timeliness of emergency treatment.

[0086] Reference Figure 3 Preferably, S141 includes sub-steps S210~S280:

[0087] S210, obtain information on the virus transmission characteristics, pathological status and exposure history of the target patient;

[0088] S220, determine the treatment priority of the target patient based on the pathological status of the target patient;

[0089] S230, determine the virus transmission risk of the target patient based on the virus transmission characteristics and exposure history information of the target patient;

[0090] S240 generates a composite priority based on the target patient's risk of virus transmission and treatment priority.

[0091] S250, construct a path feature library from the starting position to the target position;

[0092] S260, extract air circulation data, population exposure data and physical isolation features along each path in the path feature library;

[0093] S270, based on air circulation data, population exposure data and physical isolation characteristics, clusters each path into gradient pools with different transmission blocking capabilities;

[0094] S280 performs stratified matching based on the target patient's composite priority and the transmission blocking capability of the route, and assigns an initial transport route to the target patient.

[0095] Virus transmission characteristics refer to the basic attributes of the virus carried by the patient, including transmission routes (such as droplet transmission and aerosol transmission), transmission intensity (basic reproduction number R0 value), and incubation period. This information determines the spread pattern of the virus in the transportation environment and can be determined by detecting the virus through on-board equipment.

[0096] Pathological status encompasses the severity of the patient's current illness, such as whether respiratory failure or shock has occurred, directly affecting the urgency of treatment; exposure history information refers to the sources of infection or high-risk areas the patient was exposed to before the onset of illness, used to assess the activity level of the virus they carry; treatment priority is the emergency level determined based on the pathological status, for example, patients with respiratory failure have a higher priority than patients with only fever symptoms, determining the urgency of transport; composite priority is a comprehensive weight value that integrates the risk of virus transmission with treatment priority, taking into account both the patient's own infection threat and the timeliness requirements of emergency treatment.

[0097] The route feature database is the foundational database for all possible routes from the origin to the target hospital, storing static features such as geographic information and environmental parameters for each route. Air circulation data refers to quantitative indicators of ventilation conditions at each section of the route, such as road width, density of surrounding buildings, and the presence of natural wind tunnels, which affect the speed of virus spread in the air. Population exposure data represents the real-time or historical probability of contact between people at each section of the route, such as the density of pedestrian traffic in commercial areas and the number of people stopping at bus stops. Physical isolation features refer to whether the route has the physical conditions to block virus transmission, such as whether there are green belts separating the route, whether it is a closed tunnel or an open walkway, etc.

[0098] The transmission blocking capability gradient pool is a set of levels that classify paths according to their ability to block virus transmission from high to low based on three types of data: air circulation, population exposure, and physical isolation. For example, a path with high blocking capability may be a well-ventilated, sparsely populated riverside walkway with green barriers, while a path with low blocking capability may be a closed, densely populated old town street.

[0099] Stratified matching selects the most suitable path from the corresponding transmission blocking capability gradient pool based on the patient's composite priority, ensuring that high-priority patients receive timely treatment while minimizing the risk of virus exposure.

[0100] First, the patient's viral transmission characteristics are collected, such as aerosol transmission tendency, pathological condition, such as blood oxygen saturation of 80 accompanied by shortness of breath, and exposure history, such as recent travel to high-risk areas, to determine their viral transmission risk, such as high transmission risk and treatment priority, such as Level 1 emergency. Then, the high risk and high urgency are weighted to calculate a comprehensive value to generate a composite priority.

[0101] Simultaneously, a feature library covering all possible transmission routes was constructed. Data on air circulation (e.g., a road segment 10 meters wide with no tall buildings nearby, resulting in high ventilation), population exposure (e.g., 2000 people per hour during morning rush hour), and physical isolation (e.g., green belts separating the roadside) were extracted for each route. This data was then integrated and divided into three gradient pools representing high, medium, and low transmission blocking capabilities. Finally, based on the patient's composite priority, a route was selected from the matching gradient pools. For example, for patients with extremely high composite priority, routes with good ventilation, low pedestrian traffic, and physical isolation were prioritized from the high-transmission-blocking-capability gradient pool, ensuring timely treatment while minimizing the possibility of virus transmission.

[0102] Specifically, an infected patient exhibits a virus primarily transmitted via aerosols, has a high R0 value, and shows an oxygen saturation of 85 with a respiratory rate of 30 breaths per minute, placing them in the highest priority treatment category. Their exposure history indicates they visited an epidemic community three days prior to symptom onset, resulting in the highest composite priority. The system's path feature database contains three candidate paths: Path 1 is a main street in the old city, with poor air circulation (dense high-rise buildings on both sides), high population exposure (5,000 people per hour during morning rush hour), and no physical barriers, belonging to the low-interception-capacity gradient pool; Path 2 is an auxiliary road of an urban expressway, with good ventilation (open and unobstructed roads), moderate population exposure (1,500 people per hour), and a central green belt for isolation, belonging to the medium-interception-capacity gradient pool; Path 3 is a riverside scenic road, with excellent ventilation (natural riverside breeze), low population exposure (only 300 people per hour), and barriers and water features on both sides, belonging to the high-interception-capacity gradient pool. Because the patient has the highest composite priority, the system selects Path 3 from the high-interception-capacity gradient pool as the initial transfer path. Although Route 3 is slightly longer, its high ventilation, low population flow, and strong physical isolation characteristics can maximally block aerosol transmission. Meanwhile, its primary priority ensures the dispatch system prioritizes vehicle dispatch, balancing safety and timeliness. If the patient is a common infected individual with a lower priority for treatment, the system may select Route 2 from the blocking capacity gradient pool to improve transport efficiency under controllable risk. This approach aims to establish a balance between virus transmission risk and treatment timeliness through a two-way matching of individual patient characteristics and inherent route attributes.

[0103] Reference Figure 4 Preferably, S260 includes sub-steps S261 to S264:

[0104] S261, determine the ventilation rate of the path based on the ratio of the road width to the height of the buildings on both sides;

[0105] S262, determine the air circulation data of the path based on wind force data and the ventilation rate of the path;

[0106] S263, Determine population exposure data for a route based on the number of susceptible locations along the route;

[0107] S264, determine the physical isolation characteristics of the route based on the completeness of the ambulance lanes and temporary isolation facilities included in the route.

[0108] The ratio of road width to the height of buildings on both sides is the physical basis for measuring road ventilation capacity. The ventilation rate is an air flow index calculated based on this ratio. For example, wide roads paired with low buildings allow for more thorough air exchange, resulting in a higher ventilation rate and a shorter time for viruses to remain in the air.

[0109] Air circulation data is the result of further correction based on ventilation rate and real-time wind data (such as wind speed and wind direction), which can more accurately reflect the actual air flow status of the current road section. For example, on roads with the same ventilation rate, the virus will spread faster when the wind is downwind, but may be blown away when the wind is upwind.

[0110] Population exposure data is determined by counting the number of susceptible locations along the path. Susceptible locations refer to areas where people are densely populated and spend a long time, such as supermarkets, bus stops, and farmers' markets. These places have frequent contact between people and a higher risk of virus transmission. The more susceptible locations there are, the greater the risk of population exposure along the path.

[0111] Physical isolation features focus on the availability of dedicated ambulance lanes and the adequacy of temporary isolation facilities along the route. For example, whether there are separate lanes to reduce traffic sharing with other vehicles, or whether there are physical barriers (such as guardrails or green belts) to reduce the possibility of contact between people. The more complete these facilities are, the lower the risk of virus transmission through contact or droplets.

[0112] First, the basic ventilation capacity is calculated using road geometry parameters, then corrected to reflect actual airflow conditions using meteorological data. Simultaneously, the number of susceptible locations along the route is tallied to assess the exposure risk from contact with people. Finally, the level of isolation facilities along the route itself is examined. These three aspects combine to create a comprehensive picture of the virus transmission risk along the route. These four dimensions, addressing airflow, virus spread dynamics, opportunities for contact with people, and physical protective capabilities, respectively, collectively form the underlying assessment basis for virus exposure risk. By quantifying multi-dimensional environmental characteristics, this provides more refined underlying support for virus exposure risk assessment.

[0113] Specifically, an emergency center needs to transfer a positive patient from the community to a designated hospital. The system needs to evaluate two candidate routes. Route 1 is a main urban road, 30 meters wide, with buildings on both sides 20 meters high, and a ventilation rate of 1.5. Real-time wind data shows a southerly wind of level 3, and the air circulation data is corrected to 1.2. The route passes through 5 susceptible locations (supermarkets, bus stops, etc.), and the population exposure data is marked as high. The route includes one dedicated ambulance lane but lacks temporary isolation facilities, and the physical isolation characteristic score is moderate. Route 2 is a secondary urban road, 20 meters wide, with buildings on both sides 15 meters high, and a ventilation rate of 1.3. Wind data shows a northerly wind of level 2, and the air circulation data is corrected to 1.1. The route only passes through 2 susceptible locations, and the population exposure data is marked as low. The route has a dedicated ambulance lane and is equipped with temporary isolation barriers, and the physical isolation characteristic score is high. After comprehensive calculation, the virus exposure risk value of Route 1 is 8.2, and that of Route 2 is 4.5. The system ultimately recommends Route 2. Although Route 2 is slightly longer, it effectively reduces the risk of virus transmission during transport due to lower ventilation barriers, less contact between people, and more effective physical isolation. If the patient is an asymptomatic carrier, the system simplifies this assessment, relying primarily on traditional traffic efficiency data for route selection to ensure timely emergency care.

[0114] By breaking down the environmental factors affecting virus spread into quantifiable technical indicators through four dimensions—road physical characteristics, airflow conditions, probability of population exposure, and physical isolation capabilities—this provides a more comprehensive risk basis for subsequent route adjustments, and can significantly improve the safety of ambulance route planning, especially in infectious disease prevention and control scenarios.

[0115] Preferably, S280 includes sub-steps S281~S282:

[0116] S281, If ​​the composite priority of the target patient is high transmission activity, then match the target patient with a path pool with high transmission blocking capability, determine the transmission blocking adaptation score of the target patient and each path in the path pool with high transmission blocking capability, and determine the initial transfer path based on the adaptation score.

[0117] S282, if the target patient's composite priority is medium or low transmission activity, then in the path pool with medium transmission blocking capability, the estimated travel time of the path is used to determine the initial transfer path.

[0118] The composite priority is a comprehensive assessment of the potential transmission risk of a target patient, taking into account multiple dimensions such as vital signs (e.g., high fever, blood oxygen levels), virus type, and disease stage (e.g., higher infectivity during acute exacerbations), classifying patients into three levels of high, medium, and low transmission activity. Transmission blocking capability refers to the characteristics of the pathway itself in inhibiting virus spread, such as road ventilation conditions (open streets are more conducive to airflow and virus dilution than closed tunnels), surrounding environment (avoiding crowded places like shopping malls reduces contact opportunities), and road width (wide roads reduce the probability of close contact between pedestrians). The transmission blocking fit score is a quantitative assessment of the degree of match between the target patient and a particular pathway in terms of transmission blocking requirements. It is calculated by weighting the patient's transmission activity level with pathway blocking capability indicators (e.g., ventilation coefficient, population density threshold). A higher score indicates a better inhibitory effect of the pathway on the patient's transmission risk.

[0119] For patients with a composite priority of high transmissibility, the system first retrieves a pool of routes with high transmission blocking capabilities. These routes typically include well-ventilated urban expressways and parallel auxiliary roads away from commercial areas, which are highly effective in blocking virus spread. The system then calculates the transmission blocking fit score between the patient and each route in the pool. For example, a patient who tests positive for Omega-1 has high transmissibility; a riverside expressway in the pool has a high fit score of 9.2 due to its high ventilation and lack of densely populated areas, while another side road passing through several densely populated communities has a fit score of only 6.5. The system ultimately selects the riverside expressway with the highest score as the initial transfer route. For patients with a composite priority of medium or low transmissibility, considering their lower risk of virus spread, the system then retrieves a pool of routes with medium transmission blocking capabilities, focusing on travel efficiency—for example, for an influenza virus infected person with medium transmissibility, the system calculates the estimated travel time for each route in this pool and selects the route with the shortest travel time to ensure timely emergency treatment.

[0120] For example, consider this case: An 80-year-old critically ill patient with a high viral load and in the acute phase was classified as having high transmissibility. The system retrieved a pool of high-transmission-blocking routes, including three candidate routes: Route 1 is an urban expressway with a ventilation coefficient of 0.8, no large venues nearby, and a fit score of 9.1; Route 2 is a secondary urban road with a ventilation coefficient of 0.6, passing through small communities, and a fit score of 8.3; Route 3 is a partially enclosed scenic avenue with a ventilation coefficient of 0.5 and a fit score of 7.5. Route 1 was ultimately selected as the initial transfer route because it offered the best transmission-blocking effect, minimizing the risk of virus spread during transport. Another case involved a 50-year-old influenza patient with a moderate viral load, classified as having medium transmissibility. The system retrieved a pool of routes with medium transmission-blocking capabilities and calculated the travel time for three routes: Route A required 12 minutes, Route B required 15 minutes, and Route C required 18 minutes. Route A was ultimately selected to prioritize emergency response efficiency.

[0121] High-risk patients are given priority for routes with strong anti-spread measures, while medium- and low-risk patients are prioritized for timely delivery. This approach avoids low-risk patients excessively occupying high-quality route resources and creates a physical barrier for virus transmission for high-risk patients, reducing the potential threat of virus spread during the transportation process.

[0122] Preferably, after S140, the method further includes S151 to S154:

[0123] S151, collect data on virus concentration inside the ambulance and the status of its ventilation system;

[0124] S152, obtain the real-time population density changes and isolation facility status of the current travel route;

[0125] S153, the transmission risk index is determined based on the virus concentration inside the vehicle, the status of the ventilation system, real-time changes in population density, and the status of isolation facilities;

[0126] S154, adjust the planned route based on the transmission risk index.

[0127] Dynamic risk management during ambulance transport involves not only controlling virus transmission through route planning, but also adapting to the real-time environment during the journey.

[0128] Among them, the virus concentration inside the vehicle refers to the number of virus particles floating in the air inside the ambulance compartment. It is monitored in real time by biosensors deployed inside the vehicle and can directly reflect the infection risk in the vehicle environment. The higher the concentration, the greater the probability that medical staff and patients are exposed to the virus.

[0129] The status of the ventilation system refers to the operating parameters of the ambulance's air conditioning or ventilation equipment, including the fresh air volume and air exchange frequency. These parameters determine the rate of air renewal and the ability to dilute the virus inside the vehicle. The better the ventilation, the slower the virus accumulates. Real-time population density changes refer to the immediate crowd gathering situation on the road ahead or around the destination while the ambulance is traveling. For example, sudden market appearances or rush hour crowds can directly affect the risk of cross-infection during the journey. The status of isolation facilities refers to the existing protective measures along the route, such as temporary isolation zones, closed areas, or virus screening points. These measures can physically block the spread of the virus and reduce the possibility of the virus entering the vehicle from outside.

[0130] First, the system collects virus concentration and ventilation status through in-vehicle sensors to establish an infection baseline inside the vehicle. Then, it acquires real-time changes in pedestrian flow and the status of isolation facilities along the current route to capture the dynamic risks of the external environment. Next, it combines the in-vehicle virus concentration, ventilation efficiency, and real-time pedestrian density, subtracts the protection coefficient of the isolation facilities, and derives a quantitative index reflecting the transmission risk. The specific index can be weighted by coefficients, which will not be elaborated here. If the index exceeds the safety threshold, the system will immediately adjust the route, such as changing to a section of road with less pedestrian flow and more complete isolation facilities, or adjusting the vehicle speed to enhance ventilation.

[0131] Specifically, a positive patient was transferred from a community hospital in the old city area to a designated infectious disease hospital, initially via Jiefang Road. During the journey, the viral load inside the vehicle increased from 50 copies per cubic meter to 120 copies per cubic meter. Simultaneously, route data showed a sudden increase in pedestrian density on the road ahead, from 3,000 to 6,000 people per square kilometer, with no temporary isolation zones in place. The system calculated a transmission risk index of 7.2, exceeding the preset threshold of 6.0, and immediately switched to Zhongshan Road. Zhongshan Road had a real-time pedestrian flow of only 2,500 people, with temporary isolation zones along the roadside, better ventilation, and a 30% higher fresh air volume. After the adjustment, the increase in viral load inside the vehicle slowed, and the risk index dropped to 4.1. This adjustment not only avoided high-traffic, unprotected areas but also reduced virus accumulation through better ventilation, thus minimizing the risk of secondary infection.

[0132] If the patient is a trauma patient, the system will reduce the weight of virus concentration in the vehicle and focus more on passage efficiency, but will still retain the monitoring of people flow and isolation facilities to ensure basic safety.

[0133] Preferably, S154 includes sub-step S154a: if the propagation risk index exceeds a preset safety threshold, then an alternative path segment is extracted in the gradient pool to which the current path belongs, and the ambulance is switched to the alternative path.

[0134] The gradient pool is a grouping system built based on path risk attributes and spatial characteristics. It groups geographically adjacent road segments with similar environmental characteristics (such as population density, ventilation conditions, and isolation facilities) into the same category. Paths in each gradient pool share a similar baseline of virus transmission risk. For example, the gradient pool in the core area of ​​the old city generally contains road segments with high population density and poor ventilation. Alternative path segments are low-exposure road segments pre-stored in the gradient pool. These are either pre-calculated safe route segments or temporary optional paths selected based on real-time data. The risk attributes of these road segments are highly matched with the current path, but the exposure risk is lower.

[0135] When the transmission risk index exceeds a preset safety threshold, the system first locates the gradient pool to which the current path belongs, for example, the high-traffic gradient pool in the old city area. Instead of venturing out of this group to find alternatives in completely unrelated paths, it directly identifies low-risk path segments within the pool that meet the requirements. Next, it filters for even lower-risk alternative routes from the gradient pool, such as smaller roads in the old city area with less traffic and isolation facilities. Finally, it guides the ambulance to switch to this alternative route segment, rather than replanning the entire route. This design saves computation time, avoids detours, and allows for rapid response to real-time risk changes, minimizing the cost of adjustments.

[0136] Traditional route planning struggles to cover unforeseen scenarios, thus necessitating proactive prevention of the risk of sudden crowd gatherings during ambulance transport. Preferably, following S152, the method further includes S155-S157:

[0137] S155 uses roadside cameras and mobile phone signaling data to monitor in real time data on sudden crowd gatherings in the areas it passes through.

[0138] S156, Based on the data of sudden crowd gatherings, extrapolate the peak population density and the corresponding increase in virus exposure risk within a preset time period while traveling along the current path;

[0139] S157 If the increased risk of virus exposure exceeds a preset tolerance threshold, the ambulance will be switched to an alternative route.

[0140] Among them, the data on sudden crowd gatherings is the result of real-time integration of roadside high-definition cameras (capturing abnormal crowd concentrations within the visual range) and mobile phone signaling data (tracking sudden convergences of user movement trajectories), which can identify temporary gatherings that were not originally within the planned scope. For example, accident onlookers at intersections, temporary exhibitions in squares, or street gatherings, the occurrence of these scenarios can instantly increase the possibility of cross-infection of the virus.

[0141] The increased risk of virus exposure is based on the ambulance's current speed and the development trend of the sudden gathering, predicting the peak population density within a preset time period (e.g., the next 10 minutes), and the risk increase of this peak relative to the original planned route. Alternative routes are backup routes that the system pre-stores based on historical data and real-time traffic conditions, bypassing the sudden gathering area. These routes typically have characteristics such as stable population flow and good ventilation, keeping the risk increase within a tolerable range.

[0142] While the ambulance is en route, the system continuously scans the area via roadside cameras and mobile phone signals. If a sudden crowd gathering is detected (e.g., a large crowd suddenly appearing in a previously sparsely populated square), the system immediately uses the ambulance's location and speed to predict the peak population density in the area within the next 10 minutes. For example, a square that normally has 2,000 people per square kilometer might see a rise to 9,000 people in 10 minutes. The system then calculates the increased risk of virus exposure under these circumstances; for instance, considering the enclosed environment of the square, the risk would increase by 3.5 compared to the original planned route. If this increase exceeds a preset tolerance threshold (e.g., 2.0), the system immediately switches to a pre-calculated alternative route, such as Jianguo Road, which has stable pedestrian flow and a safety barrier. The entire process doesn't wait for the ambulance to reach the gathering point; instead, it anticipates and adjusts in advance to minimize risk.

[0143] Preferably, S144 includes S144a to S144c:

[0144] S144a defines a dual-objective constraint condition, wherein the first objective constraint condition is that the risk of virus exposure is less than or equal to a preset exposure threshold, and the second objective constraint condition is that the total transfer time is less than the golden time for the treatment of the target patient.

[0145] S144b, if the initial path only satisfies the first objective constraint but not the second objective constraint, then the suboptimal path is selected from the path pool with high propagation blocking capability based on the time required for transshipment.

[0146] S144c, if the initial path only satisfies the second objective constraint but not the first objective constraint, then a forced switch to a path pool with high propagation blocking capability is made to adjust the initial transfer path.

[0147] The dual-objective constraint consists of two conditions that the route planning must simultaneously meet: the first objective is that the risk of virus exposure does not exceed a preset safety threshold. This risk integrates factors such as population density, environmental ventilation, and isolation facilities, and is a quantitative assessment of the possibility of infection during transport. The second objective is that the total transport time cannot exceed the golden time for the target patient's treatment, which is the latest time window from the onset of illness to when the patient must receive effective treatment. This time varies greatly depending on the severity of the illness; for example, critically ill patients may need to start antiviral treatment within 6 hours, while patients with external bleeding may only need 30 minutes. The high transmission blocking capability route pool is a pre-screened set of risk routes. These routes generally have characteristics such as good ventilation, sparse population, and temporary isolation zones or screening points, which can cut off the virus transmission chain at the environmental level.

[0148] If the initial path only meets the virus risk requirement, such as choosing a remote side road, which has low risk but is a long detour and causes the total time to exceed the golden time, the system will look for a suboptimal solution in the high transmission blocking path pool. This route has the same controllable risk but the time is closer to the golden time. If the initial path only meets the time requirement, such as choosing the fastest main road, but the virus risk exceeds the standard due to large crowds and poor ventilation, the system will forcibly switch to the high transmission blocking path pool, even if the route is slightly longer, to pull the virus risk back to the safe zone.

[0149] For patients with viral infections, worsening conditions not only increase the urgency of treatment but may also increase the risk of infection due to weakened immunity, necessitating a simultaneous strengthening of protective measures along the route. Preferably, after S140, the method further includes S161-S165:

[0150] S161 collects vital signs data of the target patient in real time during transport. The vital signs data include body temperature, heart rate, blood oxygen saturation and level of consciousness.

[0151] S162 compares the real-time collected vital signs data with the vital signs data before the initial transfer to determine whether the target patient's condition has deteriorated.

[0152] S163, If the target patient's condition worsens, the composite priority of the target patient shall be updated based on the severity of the worsening.

[0153] S164, Based on the updated composite priority, redetermine the propagation blocking adaptation score of the current transit path;

[0154] S165, adjust the transit route based on the redefined transmission blocking adaptation score.

[0155] Among these, real-time vital sign data is continuously acquired through electrocardiogram monitors, portable pulse oximeters, temperature probes, and consciousness assessment tools (such as the GCS score) mounted on the ambulance, continuously measuring body temperature, heart rate, blood oxygen saturation, and consciousness status indicators, enabling immediate detection of signals of changes in the patient's condition. Deterioration assessment compares real-time data with baseline values ​​before transport; for example, a temperature increase exceeding 1°C, a sudden increase in heart rate of 20 beats / minute or more, a decrease in blood oxygen saturation of 5% or more, or a shift from alertness to drowsiness or coma are clear signals of worsening condition. Composite priority is a comprehensive assessment of the patient's current urgency, combining the severity of deterioration (mild, moderate, severe) with the patient's original baseline priority (e.g., critically ill patients originally had a higher priority than ordinary infected patients), forming a new priority hierarchy that directly reflects the urgency of the patient's treatment needs. Transmission blocking fit score is a quantitative indicator measuring the current route's ability to block virus transmission; a higher score indicates lower population density, better ventilation, and more comprehensive isolation facilities, thus reducing the risk of virus exposure.

[0156] First, the patient's vital signs are continuously tracked through the vehicle-mounted equipment. Once a worsening trend is detected compared to the initial state, the patient's composite priority is immediately updated. For example, a patient who was originally of moderate priority becomes severely prioritized after their condition worsens. Then, the transmission blocking adaptation score of the current route is recalculated based on the new priority. Severe patients need a route with a higher score and are safer. If the current route score does not meet the standard, the system will adjust to a path with a higher transmission blocking adaptation score.

[0157] This application embodiment determines whether the target patient is infected with a virus based on vital sign data. If the target patient is infected with a virus, it obtains the crowd density data and path environment data between the departure location and the target location of the ambulance. Based on the crowd density data and path environment data, it plans the ambulance route to avoid areas with concentrated crowds and areas where the virus is easily spread, thereby avoiding transmission paths and infection receptors and reducing the risk of infection in the emergency route.

[0158] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0159] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for ambulance route planning based on patient status, characterized in that, include: Obtain the target patient's vital signs data and the target patient's starting location; Determine whether the target patient is infected with a virus based on the vital signs data; If the target patient is infected with a virus, then obtain the crowd density data and path environment data between the departure location and the target location of the ambulance; The ambulance route is planned based on the pedestrian density data and the path environment data; wherein, The step of planning the ambulance route based on the pedestrian density data and the path environment data includes: The initial transfer route of the ambulance is determined based on the departure location and the destination location; Based on the acquired pedestrian density data and path environment data, predict the pedestrian density time series data and the path environment time series data in the initial transfer path; The virus exposure risk of the initial transfer route is determined based on the initial transfer route, the time series data of the population density, and the time series data of the route environment. The initial transport route is adjusted based on the stated virus exposure risk; wherein... Determining the initial transfer route of the ambulance based on the departure location and the destination location includes: To obtain information on the viral transmission characteristics, pathological status, and exposure history of the target patients; The treatment priority of the target patient is determined based on the pathological condition of the target patient; The viral transmission risk of the target patient is determined based on the viral transmission characteristics of the target patient and the exposure history information; A composite priority is generated based on the virus transmission risk of the target patient and the treatment priority. Construct a path feature library between the starting position and the target position; Extract air circulation data, population exposure data, and physical isolation features along each path from the path feature library; Each path is clustered into gradient pools with different propagation blocking capabilities based on the air circulation data, the population exposure data, and the physical isolation characteristics. Based on the composite priority of the target patient and the transmission blocking capability of the route, a hierarchical matching is performed to assign an initial transfer route to the target patient; The adjustment of the initial transport route based on the virus exposure risk includes: Define dual-objective constraints, wherein the first objective constraint is that the risk of virus exposure is less than or equal to a preset exposure threshold, and the second objective constraint is that the total transfer time is less than the golden time for the treatment of the target patient. If the initial transfer path only satisfies the first objective constraint but not the second objective constraint, then the suboptimal path is selected from the path pool with high propagation blocking capability based on the transfer time required. If the initial transit path satisfies only the second objective constraint but not the first objective constraint, then a forced switch to a path pool with high propagation blocking capability is initiated, and the initial transit path is adjusted; wherein, The extraction of air circulation data, population exposure data, and physical isolation features along each path in the path feature database includes: The ventilation rate of the path is determined by the ratio of the road width to the height of the buildings on both sides; The air circulation data of the path is determined based on wind force data and the ventilation rate of the path; Population exposure data for a route are determined based on the number of susceptible locations along the route. The physical isolation characteristics of a route are determined based on the completeness of the ambulance lanes and temporary isolation facilities included in the route.

2. The method as described in claim 1, characterized in that, The step of performing stratified matching based on the target patient's composite priority and the transmission blocking capability of the pathway to assign an initial transport pathway to the target patient includes: If the composite priority of the target patient is high transmission activity, then a path pool with high transmission blocking capability is matched for the target patient, the transmission blocking adaptation score of the target patient and each path in the path pool with high transmission blocking capability is determined, and the initial transfer path is determined based on the adaptation score. If the target patient's composite priority is medium or low transmission activity, then in the path pool with medium transmission blocking capability, the estimated travel time of the path is used to determine the initial transfer path.

3. The method as described in claim 2, characterized in that, After planning the ambulance route based on the pedestrian density data and the path environment data, the method further includes: The virus concentration inside the ambulance and the status of its ventilation system were collected. Obtain real-time population density changes and isolation facility status along the current travel route; The transmission risk index is determined based on the virus concentration inside the vehicle, the status of the ventilation system, the real-time population density changes, and the status of the isolation facilities. The planned routes are adjusted based on the aforementioned transmission risk index.

4. The method as described in claim 3, characterized in that, The adjustment of the planned route based on the transmission risk index includes: If the transmission risk index exceeds a preset safety threshold, an alternative path segment is discovered in the gradient pool to which the current path belongs, and the ambulance is switched to the alternative path.

5. The method as described in claim 4, characterized in that, After obtaining the real-time population density changes and isolation facility status of the current travel route, the method further includes: Real-time monitoring of sudden crowd gatherings in areas traversed by the route is achieved through roadside cameras and mobile phone signaling data. Based on the data on sudden crowd gatherings, the peak population density and the corresponding increase in virus exposure risk are extrapolated within a preset time period while traveling along the current path. If the increase in the risk of virus exposure exceeds a preset tolerance threshold, the ambulance will be switched to the alternative route.

6. The method as described in claim 5, characterized in that, After planning the ambulance route based on the pedestrian density data and the path environment data, the method further includes: Real-time collection of vital signs data of the target patient during transport, including body temperature, heart rate, blood oxygen saturation, and level of consciousness; The real-time vital signs data are compared with the vital signs data before the initial transfer to determine whether the target patient's condition has deteriorated. If the target patient's condition worsens, the composite priority of the target patient will be updated based on the severity of the worsening. Based on the updated composite priority, the propagation blocking adaptation score of the current transit path is re-determined; The transport routes were adjusted based on the redefined transmission blocking fit score.

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