Improved Two-Stage Epidemic Dynamics Model

Infectious diseases have always been critical factors affecting human life, health, and social stability throughout history. The recurrent epidemics of infectious diseases have caused enormous disasters for human survival and national well-being. Establishing mathematical models to describe the transmission process of infectious diseases, analyze the variation patterns of infected individuals, and predict disease outbreak timing is significant for providing a decision-making basis to prevent the spread of infectious diseases. The use of dynamic models specific to infectious diseases offers unique advantages in addressing these issues. In this paper, a two-stage infectious disease dynamics model with a latent period and asymptomatic infection is established to model the transmission of highly infectious pathogens in a population. Utilizing epidemic data from Shanghai spanning February 8, 2022, to July 1, 2022, the model is numerically simulated, and the basic reproduction number R 0 for the two stages is calculated using the next generation matrix method. Studies indicate that timely enhancements in epidemic control measures can significantly reduce the number of confirmed cases in hospitals, decrease the peak number of infections, and hasten the arrival of the epidemic’s inflection point.

Authors

Publication Details

Journal
Journal of Applied Mathematics and Physics
Published
2025-01-01
DOI
https://doi.org/10.4236/jamp.2025.135092
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved Two-Stage Epidemic Dynamics Model

Xin Yao, Shan Gao, Hua He
Journal of Applied Mathematics and Physics
COVID-19 epidemiological studies
article

Improved Two-Stage Epidemic Dynamics Model

Xin Yao, Shan Gao, Hua He
article en

Abstract

Infectious diseases have always been critical factors affecting human life, health, and social stability throughout history. The recurrent epidemics of infectious diseases have caused enormous disasters for human survival and national well-being. Establishing mathematical models to describe the transmission process of infectious diseases, analyze the variation patterns of infected individuals, and predict disease outbreak timing is significant for providing a decision-making basis to prevent the spread of infectious diseases. The use of dynamic models specific to infectious diseases offers unique advantages in addressing these issues. In this paper, a two-stage infectious disease dynamics model with a latent period and asymptomatic infection is established to model the transmission of highly infectious pathogens in a population. Utilizing epidemic data from Shanghai spanning February 8, 2022, to July 1, 2022, the model is numerically simulated, and the basic reproduction number R 0 for the two stages is calculated using the next generation matrix method. Studies indicate that timely enhancements in epidemic control measures can significantly reduce the number of confirmed cases in hospitals, decrease the peak number of infections, and hasten the arrival of the epidemic’s inflection point.

Journal of Applied Mathematics and PhysicsVol. 13(05)
Good health and well-being
Openalex Percentile: Top 88%
COVID-19 epidemiological studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.