ArticleMathematical biosciences2021
Optimal control of the SIR model in the presence of transmission and treatment uncertainty.
Article in Mathematical biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Optimal vaccination in a SIRS epidemic model.Economic theory · 2022Article
- From pandemic to a new normal: Strategies to optimise governmental interventions in Indonesia based on an SVEIQHR-type mathematical model.Infectious Disease Modelling · 2022Article
- Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil.Physica D. Nonlinear phenomena · 2022Article
- Optimal control of the SIR model with constrained policy, with an application to COVID-19.Mathematical biosciences · 2022Article
- Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States.The European physical journal. Special topics · 2022Article
- Trends in COVID-19 prevalence and mortality: A year in review.Physica D. Nonlinear phenomena · 2021Article
- The second and third waves in India: when will the pandemic be culminated?European physical journal plus · 2021Article
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Abstract
The COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes, or submodels, of the stochastic SIR model, where the population consists of three groups: susceptible, infected and recovered and dead. In the first regime the proportion of infected is very low, and the proportion of susceptible is very close to 100the proportion of infected is moderate, but not negligible. We show that the first regime corresponds almost exactly to a well-known problem in finance, the problem of portfolio and consumption decisions under mean-reverting returns (Wachter, JFQA 2002), for which the optimal control has an analytical solution. We develop a perturbative solution for the second problem. To our knowledge, this paper represents one of the first attempts to develop analytical/perturbative solutions, as opposed to numerical solutions to stochastic SIR models.
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