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Computational Ecology and Software, 2020, 10(3): 94-104
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Article

A generalized discrete dynamic model for human epidemics

WenJun Zhang1, ZeLiang Chen2, Yi Lu3, ZhongMin Guo4, YanHong Qi5, GuoLing Wang2, JiaHai Lu2
1School of Life Sciences, Sun Yat-sen University, Guangzhou, P. R. China
2School of Public Health, Sun Yat-sen University, Guangzhou, P. R. China
3Department of Health Law, Policy and Management, School of Public Health, Boston University, U.S.A
4Animal Experiment Center, Sun Yat-sen University, Guangzhou, P. R. China
5Sun Yat-sen University Libraries, Sun Yat-sen University, Guangzhou, P. R. China

Received 4 March 2020;Accepted 8 March 2020;Published 1 September 2020
IAEES

Abstract
A discrete dynamic model for human epidemics was developed in present study. The model included major parameters as transmission strength and its dynamic changes, mean incubation period, hospitalization time (i.e., the time from illness to hospitalization), non-hospitalization (i.e., outside hospitals) daily mortality, non-hospitalization daily recovery rate, and hospitalization proportion (proportion of cases for hospitalization), etc. Sensitivity analysis of the model indicated the total cumulative cases significantly increased with the increase of initial transmission strength and hospitalization time. The total cumulative cases significantly decreased with the increase of transmission strength's dynamic decline and hospitalization proportion, and decreased with the increase of non-hospitalization daily mortality and non-hospitalization daily recovery rate. The total cumulative cases significantly increased with the decrease of mean incubation period. Sensitivity analysis demonstrated that dynamic change of transmission strength is one of the most important and controllable factors. In addition, reducing the delay for hospitalization (i.e., hospitalization time) is much effective in weakening disease epidemic. Enhancing immunity to recover from the disease is of importance for increasing non-hospitalization recovery rate.

Keywords discrete dynamic model;difference and differential equations;human epidemics;hospitalization time;hospitalization proportion;incubation period;transmission strength;COVID-19.



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