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10.26355/eurrev_202008_22512

http://scihub22266oqcxt.onion/10.26355/eurrev_202008_22512
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32767354!ä!32767354

suck abstract from ncbi


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pmid32767354      Eur+Rev+Med+Pharmacol+Sci 2020 ; 24 (15): 8226-8231
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  • Association between the spread of COVID-19 and weather-climatic parameters #MMPMID32767354
  • Carta MG; Scano A; Lindert J; Bonanno S; Rinaldi L; Fais S; Orru G
  • Eur Rev Med Pharmacol Sci 2020[Aug]; 24 (15): 8226-8231 PMID32767354show ga
  • OBJECTIVE: To explore whether the climate has played a role in the COVID-19 outbreak, we compared virus lethality in countries closer to the Equator with others. Lethality in European territories and in territories of some nations with a non-temperate climate was also compared. MATERIALS AND METHODS: Lethality was calculated as the rate of deaths in a determinate moment from the outbreak of the pandemic out of the total of identified positives for COVID-19 in a given area/nation, based on the COVID-John Hopkins University website. Lethality of countries located within the 5th parallels North/South on 6 April and 6 May 2020, was compared with that of all the other countries. Lethality in the European areas of The Netherlands, France and the United Kingdom was also compared to the territories of the same nations in areas with a non-temperate climate. RESULTS: A lower lethality rate of COVID-19 was found in Equatorial countries both on April 6 (OR=0.72 CI 95% 0.66-0.80) and on May 6 (OR=0.48, CI 95% 0.47-0.51), with a strengthening over time of the protective effect. A trend of higher risk in European vs. non-temperate areas was found on April 6, but a clear difference was evident one month later: France (OR=0.13, CI 95% 0.10-0.18), The Netherlands (OR=0.5, CI 95% 0.3-0.9) and the UK (OR=0.2, CI 95% 0.01-0.51). This result does not seem to be totally related to the differences in age distribution of different sites. CONCLUSIONS: The study does not seem to exclude that the lethality of COVID-19 may be climate sensitive. Future studies will have to confirm these clues, due to potential confounding factors, such as pollution, population age, and exposure to malaria.
  • |*Climate[MESH]
  • |*Seasons[MESH]
  • |*Weather[MESH]
  • |Betacoronavirus[MESH]
  • |Brunei/epidemiology[MESH]
  • |Burundi/epidemiology[MESH]
  • |COVID-19[MESH]
  • |Congo/epidemiology[MESH]
  • |Coronavirus Infections/epidemiology/*mortality[MESH]
  • |Ecuador/epidemiology[MESH]
  • |Equatorial Guinea/epidemiology[MESH]
  • |Europe[MESH]
  • |France/epidemiology[MESH]
  • |Gabon/epidemiology[MESH]
  • |Humans[MESH]
  • |Indian Ocean Islands/epidemiology[MESH]
  • |Indonesia/epidemiology[MESH]
  • |Kenya/epidemiology[MESH]
  • |Malaysia/epidemiology[MESH]
  • |Melanesia/epidemiology[MESH]
  • |Micronesia/epidemiology[MESH]
  • |Netherlands/epidemiology[MESH]
  • |Pandemics[MESH]
  • |Papua New Guinea/epidemiology[MESH]
  • |Pneumonia, Viral/epidemiology/*mortality[MESH]
  • |Rwanda/epidemiology[MESH]
  • |SARS-CoV-2[MESH]
  • |Samoa/epidemiology[MESH]
  • |Sao Tome and Principe/epidemiology[MESH]
  • |Seychelles/epidemiology[MESH]
  • |Singapore/epidemiology[MESH]
  • |Somalia/epidemiology[MESH]
  • |Timor-Leste/epidemiology[MESH]
  • |Tropical Climate[MESH]
  • |Uganda/epidemiology[MESH]


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