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Distribution of COVID-19 cases and deaths in Europe during the first 12 peak weeks of outbreak.
Zach, Hana; Hanová, Martina; Letkovicová, Mária.
  • Zach H; Department of Statistics and Operations Research, Faculty of Economics and Management, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic.
  • Hanová M; Department of Statistics and Operations Research, Faculty of Economics and Management, Slovak University of Agriculture in Nitra, Nitra, Slovak Republic.
  • Letkovicová M; Environment a.s., Centre for Biostatistics and Environment, Nitra, Slovak Republic.
Cent Eur J Public Health ; 29(1): 9-13, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1173110
ABSTRACT

OBJECTIVE:

The aim of the study was to identify similar WHO European countries in COVID-19 incidence and mortality rate during the first 12 peak weeks of pandemic outbreak to find out whether exact coherent parts of Europe were more affected than others, and to set relationship between age and higher COVID-19 mortality rate.

METHODS:

COVID-19 cases and deaths from 28 February to 21 May 2020 of 37 WHO European countries were aggregated into 12 consecutive weeks. The fuzzy C-means clustering was performed to identify similar countries in COVID-19 incidence and mortality rate. Pearson product-moment correlation coefficient and log-log linear regression analyses were performed to set up relation between COVID-19 mortality rate and age. Mann-Whitney (Wilcoxon) test was used to explore differences between countries possessing higher mortality rate and age.

RESULTS:

Based on the highest value of the coefficient of overall separation five clusters of similar countries were identified for incidence rate, mortality rate and in total. Analysis according to weeks offered trends where progress of COVID-19 incidence and mortality rate was visible. Pearson coefficient (0.69) suggested moderately strong connection between mortality rate and age, Mann-Whitney (Wilcoxon) test proved statistically significant differences between countries experiencing higher mortality rate and age vs. countries having both indicators lower (p < 0.001). Log-log linear regression analysis defined every increase in life expectancy at birth in total by 1% meant growth in mortality rate by 22% (p < 0.001).

CONCLUSION:

Spain, Belgium and Ireland, closely followed by Sweden and Great Britain were identified as the worst countries in terms of incidence and mortality rate in the monitored period. Luxembourg, Belarus and Moldova accompanied the group of the worst countries in terms of incidence rate and Italy, France and the Netherland in terms of mortality rate. Correlation analysis and the Mann-Whitney (Wilcoxon) test proved statistically significant positive relationship between mortality rate and age. Log-log linear regression analysis proved that higher age accelerated the growth of mortality rate.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Europa Language: English Journal: Cent Eur J Public Health Journal subject: Epidemiology / Public Health Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Country/Region as subject: Europa Language: English Journal: Cent Eur J Public Health Journal subject: Epidemiology / Public Health Year: 2021 Document Type: Article