Behzad Heibati1,2,3, Wenge Wang4, Niilo R I Ryti1,2,3, Francesca Dominici5, Alan Ducatman6, Zhijie Zhang4, Jouni J K Jaakkola1,2,3,7. 1. Faculty of Medicine, Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland. 2. Faculty of Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland. 3. Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland. 4. Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China. 5. Department of Biostatistics, T. H. Chan School of Public Health, Harvard University, Boston, MA, United States. 6. West Virginia University School of Public Health, Morgantown, WV, United States. 7. Finnish Meteorological Institute, Helsinki, Finland.
Abstract
Background: The current coronavirus disease 2019 (COVID-19) is spreading globally at an accelerated rate. There is some previous evidence that weather may influence the incidence of COVID-19 infection. We assessed the role of meteorological factors including temperature (T) and relative humidity (RH) considering the concentrations of two air pollutants, inhalable coarse particles (PM10) and nitrogen dioxide (NO2) in the incidence of COVID-19 infections in Finland, located in arctic-subarctic climatic zone. Methods: We retrieved daily counts of COVID-19 in Finland from Jan 1 to May 31, 2020, nationwide and separately for all 21 hospital districts across the country. The meteorological and air quality data were from the monitoring stations nearest to the central district hospital. A quasi-Poisson generalized additional model (GAM) was fitted to estimate the associations between district-specific meteorological factors and the daily counts of COVID-19 during the study period. Sensitivity analyses were conducted to test the robustness of the results. Results: The incidence rate of COVID-19 gradually increased until a peak around April 6 and then decreased. There were no associations between daily temperature and incidence rate of COVID-19. Daily average RH was negatively associated with daily incidence rate of COVID-19 in two hospital districts located inland. No such association was found nationwide. Conclusions: Weather conditions, such as air temperature and relative humidity, were not related to the COVID-19 incidence during the first wave in the arctic and subarctic winter and spring. The inference is based on a relatively small number of cases and a restricted time period.
Background: The current coronavirus disease 2019 (COVID-19) is spreading globally at an accelerated rate. There is some previous evidence that weather may influence the incidence of COVID-19infection. We assessed the role of meteorological factors including temperature (T) and relative humidity (RH) considering the concentrations of two air pollutants, inhalable coarse particles (PM10) and nitrogen dioxide (NO2) in the incidence of COVID-19infections in Finland, located in arctic-subarctic climatic zone. Methods: We retrieved daily counts of COVID-19 in Finland from Jan 1 to May 31, 2020, nationwide and separately for all 21 hospital districts across the country. The meteorological and air quality data were from the monitoring stations nearest to the central district hospital. A quasi-Poisson generalized additional model (GAM) was fitted to estimate the associations between district-specific meteorological factors and the daily counts of COVID-19 during the study period. Sensitivity analyses were conducted to test the robustness of the results. Results: The incidence rate of COVID-19 gradually increased until a peak around April 6 and then decreased. There were no associations between daily temperature and incidence rate of COVID-19. Daily average RH was negatively associated with daily incidence rate of COVID-19 in two hospital districts located inland. No such association was found nationwide. Conclusions: Weather conditions, such as air temperature and relative humidity, were not related to the COVID-19 incidence during the first wave in the arctic and subarctic winter and spring. The inference is based on a relatively small number of cases and a restricted time period.
Authors: Malay Pramanik; Parmeshwar Udmale; Praffulit Bisht; Koushik Chowdhury; Sylvia Szabo; Indrajit Pal Journal: Int J Environ Health Res Date: 2020-07-16 Impact factor: 3.411
Authors: Mohammad M Sajadi; Parham Habibzadeh; Augustin Vintzileos; Shervin Shokouhi; Fernando Miralles-Wilhelm; Anthony Amoroso Journal: JAMA Netw Open Date: 2020-06-01
Authors: Yu Wu; Wenzhan Jing; Jue Liu; Qiuyue Ma; Jie Yuan; Yaping Wang; Min Du; Min Liu Journal: Sci Total Environ Date: 2020-04-28 Impact factor: 7.963