Abstract
Reinfection and multiple viral strains are among the latest challenges in the current COVID-19 pandemic. In contrast, epidemic models often consider a single strain and perennial immunity. To bridge this gap, we present a new epidemic model that simultaneously considers multiple viral strains and reinfection due to waning immunity. The model is general, applies to any viral disease and includes an optimal control formulation to seek a trade-off between the societal and economic costs of mitigation. We validate the model, with and without mitigation, in the light of the COVID-19 epidemic in England and in the state of Amazonas, Brazil. The model can derive optimal mitigation strategies for any number of viral strains, whilst also evaluating the effect of distinct mitigation costs on the infection levels. The results show that relaxations in the mitigation measures cause a rapid increase in the number of cases, and therefore demand more restrictive measures in the future.
Highlights
Known as COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2) is believed to have appeared at the end of 2019 in Wuhan, China [1]
This paper proposed a novel modelling framework based on the classical SEIR model that considers multiple viral strains, reinfections, and optimal control
Whilst general and applicable to any viral epidemic, the framework was validated in light of the current COVID-19 pandemic, which has challenged healthcare systems around the globe
Summary
Known as COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2) is believed to have appeared at the end of 2019 in Wuhan, China [1]. It is worth emphasising that, the COVID-19 pandemic is certainly a motivation, we propose a general framework for a realistic modelling of the spread of viral diseases As such, it includes the possibility of reinfection due to waning immunity, as well as multiple viral strains and optimal control. Another important characteristic of the model is that it considers a single viral strain.
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