Optimizing public health measures to control the spread of COVID-19

Abstract

There has been a lot of discussion on Corona virus pandemic (COVID-19). Number of studies has been conducted to explore its structure and infection. Moreover, many articles assessed its impact on various dimension of world economy and demography (like on particular age group or population cluster). There are number of studies has been conducted to explore the medical, biological, social, cultural and economic aspects of COVID-19 virus. Whole world scenario got changed with the emergence of this virus. New COVID-19 are being reported on daily basis in all over the world. As per the WHO report, approximately 18 million confirmed cases found all over the world and 681 thousand death cases have been reported in at least 188 countries and territories. This project tries to analyse the time series trend pattern of COVID-19 in the top 10 affected countries. Furthermore, the project assesses the adopted health measure to mitigate the effects of COVID-19. This project will also consider another economic and demographic parameter to study the impact of COVID- 19 on the growth and development of the country. Unlike other studies, this project is dealing with hospital preparedness for handling COVID- 19 and demographic factors simultaneously. Moreover, the project will develop a model to optimize the health facilities to mitigate the COVID-19 effects. Econometrics tools are used to analyse the data framed in numerical form whereas literature review will be used to support the findings and represent the arguments for the study conclusion. 69 countries and 84 days data are pooled to run the Regression model with fixed affect. Project (this study) revealed that preparedness in terms of bed facilities per thousand patients and testing units are found the key factors to get the optimum results for minimizing the COVID-19 cases. Further the Stringency Index should be maintained at its highest level to protect the vulnerable countries to avoid COVID-19 infection.