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

ABSTRACT: The progress of viral diseases such as the new coronavirus (COVID-19) can be influenced not only by social isolation policies, but also by climatic factors. Understanding how these factors affect the progress of the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be essential to know the risks each country is facing because of the disease. In this study, we verified the existence of a relationship between the basic reproduction number (R0) of SARS-CoV-2 with different climate variables, while also considering the Global Health Security Index (GHS). We collected data from confirmed cases of COVID-19 along with their respective GHS notes and climate data, from December 31, 2019 to April 13, 2020, for 52 countries. The generalized additive model (GAM) was applied to explore the effect of temperature, relative humidity, solar radiation index, and GHS score on the spread rate of COVID-19. The countries that showed similarity to each other were grouped into clusters using the Kohonen self-organizing map methodology to investigate the importance of each variable in the dissemination of the disease. The temperature variable presented a linear relationship (p < 0.001) with the R0, with an explained variation of 36.2%, while the relative humidity variable did not present a significant relationship with the R0. The response curve of the solar radiation variable presented a significant nonlinear relationship (p < 0.001) with an explained variation of 32.3%. The GHS index variable, with a significant nonlinear relationship (p < 0.001), presented the largest explanatory response in the control of COVID-19, with an explained variation of 38.4%; further, it was observed that the countries with the largest GHS index scores were less influenced by climate variables.

SUBMITTER: Leichtweis BG

PROVIDER: S-EPMC7943391 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionGlobal Health Security borders on prevention, detection and response to public health threats like the novel coronavirus disease 2019 (COVID-19). Global Health Security Index (GHSI) of 2019 and 2021 revealed the world remains ill-prepared to deal with future pandemics, evident in the historic impact of COVID-19 on countries. As at 7th December 2022, COVID-19 has infected over 600 million people and claimed over six million lives, mostly in countries with higher GHSI scores.ObjectiveDetermine whether the GHSI scores of countries have a correlation with COVID-19 cases, deaths and vaccination coverage, while adjusting for country level dynamics.MethodsThis paper utilizes GHSI database of 195 countries. Data consists of 171 questions grouped into 37 indicators across six overarching categories on health security and COVID-19. Multivariate multiple regression analysis with robust standard errors was conducted to test the hypothesis that high GHSI ratings do not guarantee better COVID-19 outcomes like cases, deaths and vaccination coverage. Also, avplots STATA command was used to check outliers with potential negative effect on outcome and predictor variables.ResultsGlobal average GHSI score for all 195 countries was 38.9. United States of America recorded the highest GHSI score of 75.9 but also recorded one of the highest COVID-19 cases and deaths; Somalia recorded the worst GHSI score of 16.0 and one of the lowest COVID-19 cases and deaths. High GHSI scores did not associate positively with reduction in COVID-19 cases (Coef=157133.4, p-value=0.009, [95%CI 39728.64 274538.15]) and deaths (Coef=1405.804, p-value=0.047, [95%CI 18.1 2793.508]). However, high GHSI ratings associated with increases in persons fully vaccinated per 100 population (Coef=0.572, p-value=0.000, [95%CI.272.873]).ConclusionIt appears the world might still not be adequately prepared for the next major pandemic, if the narrative remains unchanged. Countries that recorded higher GHSI scores, counter-intuitively, recorded higher COVID-19 cases and deaths. Countries need to invest more in interventions towards attaining Universal Health Coverage (UHC) including integrated health systems and formidable primary health care to enhance preparedness and response to pandemics.

Project description:ObjectiveWe aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.DesignEcological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January-May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data.Primary outcomeCountry-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.ParticipantsThirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA.ResultsOf all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (-0.018 (95% CI -0.034 to -0.002)), were significantly associated with the natural logarithm of the mean death rate.ConclusionsInternational travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

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

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