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Assessing the impact of non‐pharmaceutical (NPI) interventions and the role of mutations on the SARS‐CoV‐2 Virus spread in India using a discrete renewal process

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Assessing the impact of non‐pharmaceutical (NPI) interventions and the role of mutations on the SARS‐CoV‐2 Virus spread in India using a discrete renewal process
 
Identifier https://doi.org/10.7910/DVN/WNFQBS
 
Creator Ghosh, Prithwish
Banerjee, Meghna
Chakraborty, Arindom
 
Publisher Harvard Dataverse
 
Description In recent years, the world has not suffered so much compared to the devastation caused by Covid 19. The present study aims to investigate the impact of various comprehensive and stringent
interventions (as advised by the government of India) implemented to decelerate the spread of
the SARS-CoV-2 virus. Studying the effects of different mutations found in India is equally important. We consider a stochastic model based on a discrete renewal process that
includes various controlling measures to systematically evaluate their effects on the disease
transmission dynamics through three inter-linked components. A Bayesian model has been considered for the
infection cycle to observe deaths with upper and lower bounds of the total population infected
(attack rates), case detection probabilities, and the reproduction number over time. The MCMC
technique was adopted to analyze the data. This model is related to the widely used
susceptible-infected-recovered (SIR) model, except the renewal is not expressed in differential
form. In this study, we treat interventions as covariates in modeling the average
reproduction number. Here, the time-varying reproduction number ($R_t$) has been assumed to be a
piece-wise constant function that starts from a baseline prior, and mutations are used as covariates alongwith the NPIs.
 
Subject Mathematical Sciences
Medicine, Health and Life Sciences
 
Date 2024-03-06
 
Contributor Ghosh, Prithwish