A Country Pandemic Risk Exposure Measurement Model

Simon Grima; Murat Kizilkaya; Ramona Rupeika-Apoga; Inna Romānova; Rebecca Dalli Gonzi; Mihajlo Jakovljevic

doi:10.2147/RMHP.S270553

A Country Pandemic Risk Exposure Measurement Model

Risk Manag Healthc Policy. 2020 Oct 9:13:2067-2077. doi: 10.2147/RMHP.S270553. eCollection 2020.

Authors

Simon Grima¹, Murat Kizilkaya², Ramona Rupeika-Apoga³, Inna Romānova³, Rebecca Dalli Gonzi⁴, Mihajlo Jakovljevic^{5

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Affiliations

¹ Department of Insurance, Faculty of Economics, Management and Accountancy, University of Malta, Msida, Malta.
² Department of Economics, Faculty of Economics and Administrative Sciences, Ardahan University, Ardahan, Turkey.
³ Department of Business, Management and Economics, University of Latvia, Riga, Latvia.
⁴ Department of Construction & Property Management, University of Malta, MSD, Msida, 2080, Malta.
⁵ Institute of Comparative Economic Studies ICES, Faculty of Economics, Hosei University, Tokyo, Japan.
⁶ Department of Global Health Economics and Policy, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia.
⁷ Department of Public Health and Healthcare Named After N.A. Semashko, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia.

Abstract

Purpose: The purpose of this study is to develop a Pandemic Risk Exposure Measurement (PREM) model to determine the factors that affect a country's prospective vulnerability to a pandemic risk exposure also considering the current COVID-19 pandemic.

Methods: To develop the model, drew up an inventory of possible factor variables that might expose a country's vulnerability to a pandemic such as COVID-19. This model was based on the analysis of existing literature and consultations with some experts and associations. To support the inventory of selected possible factor variables, we have conducted a survey with participants sampled from people working in a risk management environment carrying out a risk management function. The data were subjected to statistical analysis, specifically exploratory factor analysis and Cronbach Alpha to determine and group these factor variables and determine their reliability, respectively. This enabled the development of the PREM model. To eliminate possible bias, hierarchical regression analysis was carried out to examine the effect of the "Level of Experienced Hazard of the Participant (LEH)" considering also the "Level of Expertise and Knowledge about Risk and Risk Management (LEK)".

Results: Exploratory factor analysis loaded best on four factors from 19 variables: Demographic Features, Country's Activity Features, Economic Exposure and Societal Vulnerability (i.e. the PREM Model). This model explains 65.5% of the variance in the level of experienced hazard (LEH). Additionally, we determined that LEK explains only about 2% of the variance in LEH.

Conclusion: The developed PREM model shows that monitoring of Demographic Features, Country's Activity Features, Economic Exposure and Societal Vulnerability can help a country to identify the possible impact of pandemic risk exposure and develop policies, strategies, regulations, etc., to help a country strengthen its capacity to meet the economic, social and in turn healthcare demands due to pandemic hazards such as COVID-19.

Keywords: COVID-19; exposure; hazard; pandemic risk; risk measurement model.