Risk Management and Healthcare Policy (Oct 2020)
A Country Pandemic Risk Exposure Measurement Model
Abstract
Simon Grima,1 Murat Kizilkaya,2 Ramona Rupeika-Apoga,3 Inna Romānova,3 Rebecca Dalli Gonzi,4 Mihajlo Jakovljevic5– 7 1Department of Insurance, Faculty of Economics, Management and Accountancy, University of Malta, Msida, Malta; 2Department of Economics, Faculty of Economics and Administrative Sciences, Ardahan University, Ardahan, Turkey; 3Department of Business, Management and Economics, University of Latvia, Riga, Latvia; 4Department of Construction & Property Management, University of Malta, MSD, Msida, 2080, Malta; 5Institute of Comparative Economic Studies ICES, Faculty of Economics, Hosei University, Tokyo, Japan; 6Department of Global Health Economics and Policy, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia; 7Department of Public Health and Healthcare Named After N.A. Semashko, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RussiaCorrespondence: Simon GrimaUniversity of Malta, Msida MSD 2080, MaltaTel +356 79 651 410Email [email protected]: 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, pandemic risk, risk measurement model, hazard, exposure
