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Factors determining different death rates because of the COVID-19 outbreak among countries.

ABSTRACT: Background: During the coronavirus disease 2019 (COVID-19) pandemic, all European countries were hit, but mortality rates were heterogenous. The aim of the current paper was to identify factors responsible for this heterogeneity.

Methods: Data concerning 40 countries were gathered, concerning demographics, vulnerability factors and characteristics of the national response. These variables were tested against the rate of deaths per million in each country. The statistical analysis included Person correlation coefficient and Forward Stepwise Linear Regression Analysis (FSLRA).

Results: The FSLRA results suggested that 'days since first national death for the implementation of ban of all public events' was the only variable significantly contributing to the final model, explaining 44% of observed variability.

Discussion: The current study suggests that the crucial factor for the different death rates because of COVID-19 outbreak was the fast implementation of public events ban. This does not necessarily mean that the other measures were useless, especially since most countries implemented all of them as a 'package'. However, it does imply that this is a possibility and focused research is needed to clarify it, and is in accord with a model of spreading where only a few superspreaders infect large numbers through prolonged exposure.

SUBMITTER: Fountoulakis KN

PROVIDER: S-EPMC7454744 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Factors determining different death rates because of the COVID-19 outbreak among countries.

Fountoulakis Konstantinos N KN Fountoulakis Nikolaos K NK Koupidis Sotirios A SA Prezerakos Panagiotis E PE

Journal of public health (Oxford, England) 20201101 4

<h4>Background</h4>During the coronavirus disease 2019 (COVID-19) pandemic, all European countries were hit, but mortality rates were heterogenous. The aim of the current paper was to identify factors responsible for this heterogeneity.<h4>Methods</h4>Data concerning 40 countries were gathered, concerning demographics, vulnerability factors and characteristics of the national response. These variables were tested against the rate of deaths per million in each country. The statistical analysis in ...[more]

PMID: 32728758

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Project description:BackgroundDisease control involves multiple actions overtime to halt the spread of COVID-19. The role of a country's governance in slowing the spread of COVID-19 has not yet been well investigated.ObjectiveThis study aims to investigate the association between governance and the trend of COVID-19 incidence in countries with the highest prevalence. We hypothesized that countries with better governance are more likely to mitigate the spread of COVID-19 than countries with worse governance.MethodsWe analyzed 62 most prevalent countries with at least 10,000 accumulative confirmed cases from January 22 to June 15, 2020. Countries were further grouped into three different levels of governance (25 better governance, 24 fair governance, and 13 worse governance), identified outbreak and mitigation periods using the joinpoint regression model, and compared the number of days and average daily percent change in incidence in two periods by governance level using the one-way analysis of variance.FindingsThe average outbreak period in the 62 countries lasted 84.0 days. Sixty percent of countries (N = 37) had experienced outbreak periods, followed by a mitigation period. In contrast, the rest forty percent of countries (N = 25) still had a rising trend. In the outbreak period, better governance countries had a more rapid increase but a shorter outbreak period (71.2 days) than countries with fair (93.5 days) and worse (90.8 days) governance. Most countries with better governance (84.0%) revealed a declining trend in COVID-19 incidence, while such a trend was less than half of fair and worse governance countries (38.5%-41.7%).ConclusionsCountries with better governance are more resilient during the COVID-19 crisis. While the mitigation of COVID-19 is observed in most better governance countries, the incidence of COVID-19 is still surging in most fair and worse governance countries, and the possibility of a recurring epidemic of COVID-19 in countries cannot be ignored.

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Project description:The analysis of systematically collected data for coronavirus disease 2019 (COVID-19) infectivity and death rates has revealed, in many countries around the world, a typical oscillatory pattern with a 7-day (circaseptan) period. Additionally, in some countries, 3.5-day (hemicircaseptan) and 14-day periodicities have also been observed. Interestingly, the 7-day infectivity and death rate oscillations are almost in phase, showing local maxima on Thursdays/Fridays and local minima on Sundays/Mondays. These observations are in stark contrast to a known pattern correlating the death rate with the reduced medical staff in hospitals on the weekends. While we cannot exclude the possibility that a significant portion of the observed oscillations is associated with the reporting of the individual cases, other reasons might contribute at least partly to these data. One possible hypothesis addressing these observations is that they reflect gradually increasing stress with the progressing week, which can trigger the higher death rates on Thursdays/Fridays. Moreover, assuming the weekends provide the likely time for new infections, the maximum number of new cases might fall, again, on Thursdays/Fridays. These observations deserve further study to provide a better understanding of COVID-19 dynamics.IMPORTANCE The infectivity and death rates for COVID-19 have been observed in many countries around the world as well as in the collective data of the whole world. These oscillations show distinct circaseptan periodicity, which could be associated with numerous biological reasons as well as with improper reporting of the data collected. Since very different results are observed in different countries and even continents, such as Sweden (very significant oscillations) or India (almost no oscillations), these data provide a very important message about different conditions under which the disease is spread or is reported, which, in turn, could serve as guidance tools in future epidemics. It is necessary that follow-up studies track the observed differences and fully reliably address their origins.

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Factors determining different death rates because of the COVID-19 outbreak among countries.

Publications

Factors determining different death rates because of the COVID-19 outbreak among countries.

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