Alternative Global Health Security Indexes for Risk Analysis of COVID-19

Abstract

Given the volume of research and discussion on the health, medical, economic, financial, political, and travel advisory aspects of the SARS-CoV-2 virus that causes the COVID-19 disease, it is essential to enquire if an outbreak of the epidemic might have been anticipated, given the well-documented history of SARS and MERS, among other infectious diseases. If various issues directly related to health security risks could have been predicted accurately, public health and medical contingency plans might have been prepared and activated in advance of an epidemic such as COVID-19. This paper evaluates an important source of health security, the Global Health Security Index (2019), which provided data before the discovery of COVID-19 in December 2019. Therefore, it is possible to evaluate how countries might have been prepared for a global epidemic, or pandemic, and acted accordingly in an effective and timely manner. The GHS index numerical scores are calculated as the arithmetic (AM), geometric (GM), and harmonic (HM) means of six categories, where AM uses equal weights for each category. The GHS Index scores are regressed on the numerical score rankings of the six categories to check if the use of equal weights of 0.167 in the calculation of the GHS Index using AM is justified, with GM and HM providing a check of the robustness of the arithmetic mean. The highest weights are determined to be around 0.244-0.246, while the lowest weights are around 0.186-0.187 for AM. The ordinal GHS Index is regressed on the ordinal rankings of the six categories to check for the optimal weights in the calculation of the ordinal Global Health Security (GHS) Index, where the highest weight is 0.368, while the lowest is 0.142, so the estimated results are wider apart than for the numerical score rankings. Overall, Rapid Response and Detection and Reporting have the largest impacts on the GHS Index score, whereas Risk Environment and Prevention have the smallest effects. The quantitative and qualitative results are different when GM and HM are used.Among the 140 questions, the GHS Index "prioritizes not only countries' capacities, but also the existence of functional, tested, proven capabilities for stopping outbreaks at the source" (https: //www.ghsindex.org/about/#About-the-Index-Project-Team).The questions are organized across the following six categories:Notes: * denotes significance at 1%; 195 observations; PR = Prevention, DR = Detection and Reporting, RR = Rapid Response, HS = Health System, CO = Compliance, RE = Risk Environment, AO = Average, Overall. GM is the geometric mean GHS score, and HM is the harmonic mean GHS score.Notes: * denotes significance at 1%; 195 observations; PR = Prevention, DR = Detection and Reporting, RR = Rapid Response, HS = Health System, CO = Compliance, RE = Risk Environment, AO = Average, Overall. GM is the geometric mean GHS score, and HM is the harmonic mean GHS score.

How the global health security index and environment factor influence the spread of COVID-19: A country level analysis

“…The indicators and sub-indicators used for developing the scores can be found online on the GHS Index website [ 19 ]. It is known that the way in which this index is calculated can enter as a bias in these analyzes, however according to [ 5 ] the GHS index uses the arithmetic mean of the data for the six categories under analysis, so the weights are distributed equally among them. When analyzing each of these categories separately and using different types of statistics, it is possible to conclude that the items where the rapid response to a pandemic and risk detection is foreseen, factors evaluated in this article, have the least impacts for both statistical tests.…”

Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis

“…Recent studies focused on the impact of coronavirus on various measures such as exchange rate [ 26 ], financial volatility [ 27 , 28 ], stock returns [ 29 , 30 , 31 , 32 , 33 , 34 ], corporate bonds [ 35 ] or Eurobonds [ 36 ], oil price [ 37 ], or economic policy uncertainty [ 38 ], alongside employing various methods towards assessing the diffusion of the virus [ 39 , 40 ] or assessing the source of health security [ 41 , 42 ]. We contribute to this growing literature by exploring the associations in stock markets throughout COVID-19 pandemic outbreak.…”

Predicting the Impact of COVID-19 on Australian Universities

“…Modelling released by the Australian Government Department of Health (2020b) highlights that the government enforced shutdowns of economic activity and the implementation of strict social distancing measures have to this point been effective in suppressing community transmission of COVID-19. Consequently, there currently exists a trade-off between health-related risks, which have largely been prioritised, and economic risk which has greatly increased (Hedegaard and Hodrick 2016;Chang and McAleer 2020;White 2020). This creates higher risk exposure for all Australian industries, including education and more specifically the university sector, with economic growth contracting as a result of government enforced lockdowns (Wen et al 2020;OECD 2020).…”