Kato Mikiro, Sakihama Tomoko, Kinjo Yoshio, Itokazu David, Tokuda Yasuharu
Department of General Internal Medicine, Mito Kyodo General Hospital, University of Tsukuba, Tsukuba, Japan.
International University of Health and Welfare Graduate School, Tokyo, Japan.
Korean J Fam Med. 2022 Jan;43(1):37-41. doi: 10.4082/kjfm.20.0260. Epub 2022 Jan 20.
Effect of meteorological factors such as air temperature, humidity, and sunlight exposure on transmission dynamics of novel coronavirus disease 2019 (COVID-19) remains controversial. We investigated the association of these factors on COVID-19 incidence in Japan.
We analyzed data on reverse transcription polymerase chain reaction confirmed COVID-19 cases for each prefecture (total=47) in Japan and incidence rate was defined as the number of all reported cumulative cases from January 15 to March 17, 2020. Independent variables of each prefecture included three climatic variables (mean values of air temperature, relative humidity, and sunlight exposure), population elderly ratio, and the number of inbound travelers from China during February 2020. Multivariable-adjusted Poisson regression model was constructed to estimate COVID-19 incidence rate ratio (IRR) of independent variables.
There was a total of 702 cases during the study period in Japan (population=125, 900,000). Mean±standard deviation values of meteorological variables were 7.12°C±2.91°C for air temperature, 67.49%±7.63% for relative humidity, and 46.77±12.55% for sunlight exposure. Poisson regression model adjusted for climate variables showed significant association between the incidence and three climatic variables: IRR for air temperature 0.854 (95% confidence interval [CI], 0.804-0.907; P<0.0001), relative humidity 0.904 (95% CI, 0.864-0.945; P<0.0001), and sunlight exposure 0.973 (95% CI, 0.951-0.997; P=0.026).
Higher values of air temperature, relative humidity and sunlight exposure were associated with lower incidence of COVID-19. Public health interventions against COVID-19 epidemic in a country should be developed by considering these meteorological factors.
气温、湿度和日照等气象因素对2019年新型冠状病毒病（COVID-19）传播动态的影响仍存在争议。我们调查了这些因素与日本COVID-19发病率之间的关联。
我们分析了日本各都道府县（共47个）经逆转录聚合酶链反应确诊的COVID-19病例数据，发病率定义为2020年1月15日至3月17日所有报告的累计病例数。每个都道府县的自变量包括三个气候变量（气温、相对湿度和日照的平均值）、老年人口比例以及2020年2月期间来自中国的入境旅客数量。构建多变量调整的泊松回归模型以估计自变量的COVID-19发病率比（IRR）。
研究期间日本共有702例病例（人口为1.259亿）。气象变量的平均值±标准差分别为：气温7.12°C±2.91°C，相对湿度67.49%±7.63%，日照46.77±12.55%。经气候变量调整的泊松回归模型显示发病率与三个气候变量之间存在显著关联：气温的IRR为0.854（95%置信区间[CI]，0.804 - 0.907；P<0.0001），相对湿度为0.904（95%CI，0.864 - 0.945；P<0.0001），日照为0.973（95%CI，0.951 - 0.997；P = 0.026）。
气温、相对湿度和日照值越高，与COVID-19的发病率越低相关。在一个国家应对COVID-19疫情的公共卫生干预措施应考虑这些气象因素来制定。
