A comparison of five epidemiological models for transmission of SARS-CoV-2 in India.

ABSTRACT:

Background

Many popular disease transmission models have helped nations respond to the COVID-19 pandemic by informing decisions about pandemic planning, resource allocation, implementation of social distancing measures, lockdowns, and other non-pharmaceutical interventions. We study how five epidemiological models forecast and assess the course of the pandemic in India: a baseline curve-fitting model, an extended SIR (eSIR) model, two extended SEIR (SAPHIRE and SEIR-fansy) models, and a semi-mechanistic Bayesian hierarchical model (ICM).

Methods

Using COVID-19 case-recovery-death count data reported in India from March 15 to October 15 to train the models, we generate predictions from each of the five models from October 16 to December 31. To compare prediction accuracy with

SUBMITTER: Purkayastha S 

PROVIDER: S-EPMC8181542 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature