Why do regions differ in vulnerability to СOVID-19? Spatial nonlinear modeling of social and economic patterns

Olha Kuzmenko,Sergej Vojtovič,Tetyana Vasylieva,Olena Chygryn,Vytautas Snieška

doi:10.14254/2071-789x.2020/13-4/20

Abstract

Certain groups of determinants (economic, environmental, social, healthcare) with the highest vulnerability identify the reasons for regional differentiation in morbidity and mortality from COVID-19. This defines the necessity to find appropriate combinations of factors characterizing the vulnerability of a region. The methodology and tools to explain the regional specifics of population vulnerability to COVID-19 are investigated through a systematic consideration of many public health factors, environmental, social and economic specific nature of regions. The aim of the article is to study the reasons for regional differentiation of population vulnerability (morbidity and mortality rates) from COVID-19. The authors investigate a nonlinear spatial model in which the stepwise algorithm of individual factor variables is added/removed from the model specifications step by step by the Aitken method depending on their correlation with morbidity and mortality from COVID-19 in the region. The Farrar-Glober method is used to eliminate the multicollinearity of factors, the Spearman test is used to detect the heteroskedastic effect, and the Darbin-Watson test is used to check the presence of autocorrelation between the residues. As a result, the specification of the model with the highest adequacy in terms of p-value and t-statistics is formed. Relevant socioecological-economic vulnerability indices of regions to mortality and morbidity from COVID-19 are identified. The obtained results allow making adjustments in the state and regional programs concerning the mobilization of economic and healthcare systems.

Highlights

At the beginning of October 2020, the number of reported deaths in the world caused by COVID-19 exceeded 1 million
It is evident that the morbidity and mortality level among the patients with COVID-19 depends on many factors, including employment and unemployment rates; migration movement; birth and death rates; income; the number of first registered cases by 19 classes of diseases; the number of laboratory tests performed on COVID-19, the number of contracts for medical care for population under various programs, the readiness of medical institutions to receive patients; environmental pollution; economic indices of regional development
The definition of the most important economic, environmental, social, and public health factors, which have accumulated over the years and eventually formed the so-called "retrospective portrait of the vulnerability of population from different regions to COVID-19", is especially relevant today

Summary

19. This defines the necessity to find appropriate

ORCID 0000-0001-8575-5725 combinations of factors characterizing the vulnerability of a region. The methodology and tools to explain the Tetyana Vasylieva regional specifics of population vulnerability to COVID-. ● ORCID 0000-0003-0635-7978 of population vulnerability (morbidity and mortality rates) from COVID-19. The authors investigate a Sergej Vojtovič nonlinear spatial model in which the stepwise algorithm. Alexander Dubcek University of of individual factor variables is added/removed from the Trencin, Trencin, Slovakia model specifications step by step by the Aitken method. ORCID 0000-0002-4007-3728 with the highest adequacy in terms of p-value and tstatistics is formed. Kaunas University of Technology, from COVID-19 are identified. JEL Classification: С21, С51, C 31, C12, I15, I18, R58, R11 Keywords: COVID-19, vulnerability, modelling, public health

Introduction

Literature review

Methodological approach

Conducting research and results

Conclusion