Related Experiment Video
Updated: Nov 9, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
A prognostic dynamic model applicable to infectious diseases providing easily visualized guides: a case study of
Yuxuan Zhang1,2, Chen Gong3, Dawei Li4
1Department of Pharmacology, University of Oxford, Oxford, OX1 3QT, UK.
Abstract:
A reasonable prediction of infectious diseases' transmission process under different disease control strategies is an important reference point for policy makers. Here we established a dynamic transmission model via Python and realized comprehensive regulation of disease control measures. We classified government interventions into three categories and introduced three parameters as descriptions for the key points in disease control, these being intraregional growth rate, interregional communication rate, and detection rate of infectors. Our simulation predicts the infection by COVID-19 in the UK would be out of control in 73 days without any interventions; at the same time, herd immunity acquisition will begin from the epicentre. After we introduced government interventions, a single intervention is effective in disease control but at huge expense, while combined interventions would be more efficient, among which, enhancing detection number is crucial in the control strategy for COVID-19. In addition, we calculated requirements for the most effective vaccination strategy based on infection numbers in a real situation. Our model was programmed with iterative algorithms, and visualized via cellular automata; it can be applied to similar epidemics in other regions if the basic parameters are inputted, and is able to synthetically mimic the effect of multiple factors in infectious disease control.
Related Concept Videos
Steps in Outbreak Investigation
Principles of Disease Surveillance
Causality in Epidemiology
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results...
Pareto Chart
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
Statistical Methods for Analyzing Epidemiological Data

