Effects of Meteorological Factors on the Daily Domestic New CASES of Coronavirus Disease (COVID-19) in Asian Countries: A MULTI-Country Generalized Additive Modeling Analysis
Author(s)
Chin Y1, He Z1, Yu S1, Huang J2, Zhang CJP3, Ming WK4
1Jinan University, Guangzhou, 44, China, 2Imperial College London, Longdon, UK, 3LKS Faculty of Medicine,School of Public Health, The University of Hong Kong, Hongkong, China, 4Jinan University, Guangzhou, China
OBJECTIVES Since the first case of novel coronavirus-caused pneumonia was identified in December 2019, the number of new cases has been increasingly reported across China and the world. Therefore, this study investigated the associations of meteorological factors with the daily new cases of coronavirus disease (COVID-19) in nine Asian cities. METHODS Pearson correlation and generalized additive modeling were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity). RESULTS The Pearson correlation showed that daily new confirmed cases of COVID-19 were found to correlated with the average temperature and relative humidity. Moreover, generalized additive modeling analysis showed that generally, the number of daily new cases was positively associated with both average temperature and relative humidity. However, the results were inconsistent across cities and lagged time, which suggested an greater odds that the meteorological factors were unlikely to greatly influence the COVID-19 epidemic. CONCLUSIONS The associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and time. Large-scale public health measures are still required before vaccine is available.
Conference/Value in Health Info
2020-09, ISPOR Asia Pacific 2020, Seoul, South Korea
Value in Health Regional, Volume 22S (September 2020)
Code
PIN34
Topic
Epidemiology & Public Health
Topic Subcategory
Public Health
Disease
Infectious Disease (non-vaccine)