COVID-19 infection in Hokkaido, Japan might depend on the viscosity of atmospheric air
Autor: | Kyoya Sakashita, Katsuya Komatsu, Yukinori Akiyama, Nobuhiro Mikuni, Takeshi Mikami, Yusuke Kimura, Masayasu Arihara |
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Rok vydání: | 2021 |
Předmět: |
Atmospheric air
Cancer Research Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) media_common.quotation_subject Viral transmission Transdermal Patch Biology Piperazines 03 medical and health sciences Double-Blind Method Japan Piperidines Virology Humans 030304 developmental biology media_common 0303 health sciences SARS-CoV-2 Viscosity 030306 microbiology Incidence (epidemiology) COVID-19 Infectious Diseases Air temperature Schizophrenia Reproduction Negative correlation Demography |
Zdroj: | Virus Research |
ISSN: | 0168-1702 |
DOI: | 10.1016/j.virusres.2020.198259 |
Popis: | Background The large number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has plunged the world into fear in recent times. In Japan, 18,769 novel coronavirus disease 2019 (COVID-19) cases have been reported as of June 30, 2020. This study aimed to assess whether cluster infection prevention is possible by evaluating the association between viral transmission and meteorological factors. Methods This study included 1263 people who were successively diagnosed with COVID-19 in Hokkaido, Japan between January 24, 2020 and June 30, 2020. After obtaining the values from the Japanese Meteorological Agency, the average scores of air temperature and humidity were calculated and compared with COVID-19 reproduction numbers, and the association between COVID-19 incidence or reproduction number and meteorological factors was assessed. Results The COVID-19 reproduction number in Hokkaido had three peaks that came several days before the surge in COVID-19 cases. The peaks are indicative of cluster infections. There was a strong negative correlation between the kinematic viscosity of atmospheric air and the reproduction number. Discussion and Conclusion Analysis of the reproduction number is important for predicting or suppressing COVID-19 infection clusters. The authors found a strong association between meteorological factors, such as kinematic viscosity of atmospheric air and the incidence of COVID-19 infection. Meteorological forecasts could provide foreknowledge about COVID-19 infection clusters in the future. |
Databáze: | OpenAIRE |
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