Geeshath Panditharatne . Hasitha Erandi . Naleen Ganegoda . Paduma Eranga

Department of Mathematics, University of Colombo, Email: geeshath96@gmail.com, Department of Mathematics, University of Colombo, Email: hasitha.erandi@yahoo.com, Department of Mathematics, University of Sri Jayewardenepura, SriLanka, Email: naleen@sjp.ac.lk, Department of Mathematics, University of Colombo, Email: paduma@maths.cmb.ac.lk

Received in final form on January 22, 2022

Abstract
Epidemiological models have been of immense use in modelling the spread of infectious diseases and these models have been used to understand the dynamics of infectious diseases and to make predictions on how the disease will behave into the future. In this study, we develop an age-structured extended versions of the classical compartmental model to better under- stand the age specific spread of COVID-19 disease in San Francisco city. We fit actual data into the model to find age specific parameters of the spread of the virus using mathematical methods and the behaviour of each infected age group is predicted using the estimated parameters. A sensitivity analysis has been performed to understand the most critical parameters. Furthermore, a parametrized version of the model has been used to determine the change of parameter values due to the effect of the control strategies imposed. It was observed that the age groups 20-40 and 40-60 had a greater impact on the spread of the virus in San Francisco city. The spread of the virus could be drastically reduced if age specific control measures are implemented on the above age groups. The implementation of the mandatory face masks policy resulted in reducing the effective exposure(contact) rate by 50% whereas the relaxation of the stay at home policy almost neutralized the reduction of the parameters.

Keywords
Compartmental models, Sensitivity analysis, COVID-19 and Age-structure.

Cite This Article
Geeshath Panditharatne . Hasitha Erandi . Naleen Ganegoda . Paduma Eranga, Age Structured Simulation Model for the Spread of COVID-19, J.Innovation Sciences and Sustainable Technologies, 2(2)(2022), 67-74. https://doie.org/10.0608/JISST.2022925885

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