Development of Decision Support System for Effective COVID-19 Management

TL;DR

This paper presents a versatile decision support system for COVID-19 case prediction, resource allocation, and lockdown management, adaptable to various regions and implementable via a MATLAB GUI for local authorities.

Contribution

It introduces a data-driven, region-independent DSS for COVID-19 management, integrating prediction, resource allocation, and lockdown decisions.

Findings

The DSS accurately predicts active cases across regions.

It effectively allocates resources based on demand and availability.

The MATLAB GUI facilitates practical implementation by authorities.

Abstract

This paper discusses a Decision Support System (DSS) for cases prediction, allocation of resources, and lockdown management for managing COVID-19 at different levels of a government authority. Algorithms incorporated in the DSS are based on a data-driven modeling approach and independent of physical parameters of the region, and hence the proposed DSS is applicable to any area. Based on predicted active cases, the demand of lower-level units and total availability, allocation, and lockdown decision is made. A MATLAB-based GUI is developed based on the proposed DSS and could be implemented by the local authority.