SIRD Model for Analyzing Coronavirus (COVID-19) Pandemic
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This Demonstration presents a simple susceptible\[Hyphen]infectious\[Hyphen]recovered-deceased (SIRD) model for analyzing pandemic dynamics, in the wake of the second wave of the coronavirus (COVID-19) pandemic. A control parameter 
in the range 
is introduced into the model to measure the overall effectiveness of the current control policies of social distancing, mask usage and personal hygiene. Higher values of 
indicate increased effectiveness. You can vary each model parameter to see the effect on the dynamics of the disease.
Contributed by: Wusu Ashiribo Senapon and Olabanjo Olusola Aanu (January 2021)
(Department of Mathematics and Department of Computer Science, Lagos State University, Lagos, Nigeria)
Open content licensed under CC BY-NC-SA
Snapshots
Details
This Demonstration implements the SIRD model for COVID-19 given by the coupled system of ordinary differential equations:
,
,
,
,
where
= susceptible fraction of the population,
= infected fraction of the population,
= fraction of population that has recovered,
= fraction of population that has died of the infection,
= overall effectiveness of control measures (social distancing, mask usage, personal hygiene),
= infection rate,
= recovery rate,
= mortality rate.
References
[1] Worldometer. "COVID-19 Coronavirus Pandemic." (Dec 19, 2020) www.worldometers.info/coronavirus.
[2] L. Peng, W. Yang, D. Zhang, C. Zhuge and L. Hong, "Epidemic Analysis of COVID-19 in China by Dynamical Modeling," medRxiv, 2020. doi:10.1101/2020.02.16.20023465.
[3] B. M. Ndiaye, L. Tendeng and D. Seck, "Analysis of the COVID-19 Pandemic by SIR Model and Machine Learning Technics for Forecasting." arxiv.org/abs/2004.01574v1.
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