Prediction method for small-spatial-scale infectious disease space-time propagation mode

Abstract

The invention discloses a prediction method for a small-spatial-scale infectious disease space-time propagation mode. The method comprises the steps: fusing a constructed SEIR model with an estimated resident trip OD matrix, forming a small-spatial-scale infectious disease epidemic situation propagation SEIR model which is based on population flow and is fused with non-drug intervention measures, and employing different intervention measures to deal with an infectious disease epidemic situation scene; multi-source data such as mobile phone communication signaling are collected and arranged, a space-time transmission mode of infectious diseases is iteratively simulated, intervention prevention and control measures are refined into indexes and parameters to be brought into an SEIR model, and the development trend of epidemic situations and the accumulated number of cases under different scenes are simulated; therefore, the small-space-scale diffusion path, epidemic curve and space-time propagation network of the infectious diseases in the city can be explored; meanwhile, multi-source driving factors and public health intervention measures are considered, and the prediction result is more reliable; more accurate study and judgment are provided for the development situation of early epidemic situations, and the practicability is higher.

Description

technical field [0001] The invention relates to the field of methods for predicting epidemic situation of infectious diseases, in particular to a method for predicting spatio-temporal propagation patterns of small spatial scale infectious diseases. Background technique [0002] One of the important methods for the study of infectious diseases is the mathematical model of infectious diseases and its dynamic analysis. According to the characteristics of population growth, the occurrence of diseases and the laws of transmission within the population, a mathematical model that can reflect the dynamic characteristics of infectious diseases is established, and through the analysis of Qualitative, quantitative analysis and numerical simulation of model dynamics can reveal its epidemic law, predict its change and development trend, and seek the optimal strategy for its prevention and control, which can play an auxiliary role in the research, judgment and decision-making of the epidem...

AI Technical Summary

Problems solved by technology

[0003] Although some scholars have recently used the classical infectious disease dynamics compartment model (Susceptible-Exposed-Infectious-Recovered, SEIR) to construct a population flow network dynamics model to simulate the spatio-temporal development trend of the epidemic and evaluate the effect of prevention and control measures from a mathematical perspective. Most of these studies are based on large spatial scales such as cities and provinces, while studies on small spatial scales such as 1*1 km are still lacking, which is obviously not conducive to the early stage of infectious disease epidemic situation research and judgment and precise zone prevention and control

[0004] In addition, most of the existing studies failed to consider multiple factors at the same time in modeling, such as environment, meteorology, pathogenic surveillance, population flow, and intervention measures, etc., and the model settings also need to be improved

Images