Global and Temporal COVID-19 Risk Evaluation.

Mudassar Arsalan,Fady Alnajjar,Nazar Zaki,Omar Mubin,Belal Alsinglawi

doi:10.3389/fpubh.2020.00440

Mudassar Arsalan, Fady Alnajjar + Show 3 more

Open Access

https://doi.org/10.3389/fpubh.2020.00440

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Abstract

The COVID-19 pandemic has caused unprecedented crisis across the world, with many countries struggling with the pandemic. In order to understand how each country is impacted by the virus and assess the risk on a global scale we present a regression based analysis using two pre-existing indexes, namely the Inform and Infectious Disease Vulnerability Index, in conjunction with the number of elderly living in the population. Further we introduce a temporal layer in our modeling by incorporating the stringency level employed by each country over a period of 6 time intervals. Our results show that the indexes and level of stringency are not ideally suited for explaining variation in COVID-19 risk, however the ratio of elderly in the population is a stand out indicator in terms of its predictive power for mortality risk. In conclusion, we discuss how such modeling approaches can assist public health policy.

Highlights

At the end of 2019, a new respiratory tract infection emerged in Wuhan, China
Our results show that due to the inherent differences primarily related to transmission between COVID-19 and other pandemics of the past, future effort is to be dedicated to design customized indexes once the impact of COVID-19 is understood
The level of stringency that a country had imposed was unable to explain the variation across countries when it came to COVID-19 risk

Summary

Introduction

At the end of 2019, a new respiratory tract infection emerged in Wuhan, China. Termed COVID-19, the virus has spread all over the globe, with the World Health Organization (WHO) designating it a pandemic. Amongst the large volume of work on the impact of COVID-19, a stream of research attempts to decipher the various baseline or constituent factors that could put a nation at risk to COVID-19 [4]. These include the study of socio-demographic or economic factors as well as natural elements, such as climate or temperature [5]. We have seen the usage of standardized risk indexes developed by large organizations These indexes are an aggregate of many indicators and factors [8]. Computing the risk of COVID-19 is largely complicated [10]—leading to some efforts to deduce a customized index [11]

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