Forecast COVID-19 cases and fatalities to help understand what drives transmission rate in Tamil Nadu – India

Abstract

A newly emerged human Covid-19 virus from Wuhan, China caused by SARS-Cov2 having 96.1% similar genomic sequence as that of a bat has resulted in global pandemic and adversely affected the healthcare sector in terms of management, manpower, planning. The findings can be used to help the healthcare sector with better pandemic management and identify the root causes and the factors affecting the transmission rate of covid-19 cases. The study focuses on: i) Forecasting covid-19 cases, ii) to study relationship of temperature, density, lockdown, and seasonal factor on the covid-19 transmission rate, iii) how forecasting will help in terms of managerial aspects. The method used to forecast covid-19 cases was data visualization of secondary data accessed and gathered from Kaggle by using Tableau as a tool. It was done by establishing multiple connections; comparing temperature, density, lockdown and seasonal factor individually with covid-19 cases and its effect on the viral transmission rate. Density is found to be independent of transmission rate, which is affected by temperature, seasonal factor & lockdown. The rate was less at higher temperatures and under a complete lockdown imposed on the State. Healthcare workers will have a better hold in the management henceforth with creative patient consideration approaches like customized medical coverage, clinical choice supportive networks and better resource planning with the forecasted data of Covid-19 cases.

Imprint

Reeya Chaurasia, Prakash Kalke. FORECAST COVID-19 CASES AND FATALITIES TO HELP UNDERSTAND WHAT DRIVES TRANSMISSION RATE IN TAMIL NADU – INDIA. Cardiometry; Issue 25; December 2022; p.481-492; DOI: 10.18137/cardiometry.2022.25.481492; Available from: https://www.cardiometry.net/issues/no25-december-2022/forecast-covid-19-cases