Mathematical Models for COVID-19 Pandemic: A Comparative Analysis

Abstract

COVID-19 pandemic represents an unprecedented global health crisis in the last 100 years. Its economic, social and health impact continues to grow and is likely to end up as one of the worst global disasters since the 1918 pandemic and the World Wars. Mathematical models have played an important role in the ongoing crisis; they have been used to inform public policies and have been instrumental in many of the social distancing measures that were instituted worldwide. In this article, we review some of the important mathematical models used to support the ongoing planning and response efforts. These models differ in their use, their mathematical form and their scope.

Artificial neural networks for short-term forecasting of cases, deaths, and hospital beds occupancy in the COVID-19 pandemic at the Brazilian Amazon

“…This is due to the massive and parallel processing of neurons and the tolerance to noise [ 23 ]. In addition, this technique captures small distortions in the observed data and transfers them for projections differently from mechanistic models [ 24 ]. Another advantage is that this type of approach also makes it possible to use several predictor variables simultaneously, such as demographic data and incidence curves, which helps in capturing the dynamics of virus transmission in the cities over time [ 25 , 26 ].…”

Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model

“…A variant known as ‘structured metapopulation models’ can represent differences in contact patterns by dividing the compartments to reflect sub-populations. For example, sub-populations can be based on age (to reflect the different risk levels and behavior as the age increases) and/or location (to model the spread of a contagion via commuter flows) [2].…”

Health Heatmap of India: An Open Data Platform

“…The recent widespread use of these modeling efforts in the context of the raging pandemic of COVID-19 are well known and are also described in several articles in this issue of the journal. The article by Adiga et al, 23 in this issue presents a modern overview of the use of mathematical models in the context of a pandemic like COVID-19. The quality and predictive power of the models built will largely depend on the quality of data repositories that we build and maintain for current and future disease burdens of the country.…”