Effectiveness of preventive measures against COVID-19: A systematic review of In Silico modeling studies in indian context

Abstract

In the absence of any approved treatment or vaccine against novel Severe Acute Respiratory Syndrome Coronavirus -2 (SARS-CoV-2) infection, Non-Pharmaceutical Interventions (NPIs) are the cornerstone to prevent the disease, especially in a populous country like India. To understand the effectiveness of NPIs reported in the contemporary literatures describing prediction models for prevention of the ongoing pandemic of SARS-CoV-2 specifically in Indian population. Original research articles in English obtained through keyword search in PubMed, WHO Global Database for COVID19, and pre-print servers were included in the review. Thematic synthesis of extracted data from articles were done. Twenty-four articles were found eligible for the review - four published articles and twenty pre-print articles. Compartmental model was found to be the most commonly used mathematical model; along with exponential, time varying, neural network and cluster kinetic models. Social distancing, specifically lockdown, was the most commonly modelled intervention strategy. Additionally, contact tracing using smartphone application, international travel restriction, increasing hospital/ICU beds, changes in testing strategy were also dealt with. Social distancing along with increasing testing seemed to be effective in delaying the peak of the epidemic and reducing the peak prevalence. Although there is mathematical rationality behind implementation of social distancing measures including lockdown, this study also emphasised the importance of other associated measures like increasing tests and increasing the number of hospital and ICU beds. The later components are particularly important during the social mixing period to be observed after lifting of lockdown.