Impact of meteorological factors on the COVID-19 pandemic in Thailand
Issued Date
2022-01-01
Resource Type
eISSN
26300087
Scopus ID
2-s2.0-85148296606
Journal Title
Science, Engineering and Health Studies
Volume
16
Rights Holder(s)
SCOPUS
Bibliographic Citation
Science, Engineering and Health Studies Vol.16 (2022)
Suggested Citation
Saengchut P., Ruksakulpiwat S., Wonglertarak W., Kokaphan C., Phengarree K. Impact of meteorological factors on the COVID-19 pandemic in Thailand. Science, Engineering and Health Studies Vol.16 (2022). doi:10.14456/sehs.2022.61 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/86629
Title
Impact of meteorological factors on the COVID-19 pandemic in Thailand
Author's Affiliation
Other Contributor(s)
Abstract
Meteorological factors such as humidity, wind speed, rainfall, and temperature have been found to impact the spread of COVID-19. However, there is still a lack of studies on this aspect in Thailand. Therefore, this study aimed to determine the impact of meteorological factors on the COVID-19 pandemic in Thailand. The data regarding the number of COVID-19 patients between January to May 2021 and meteorological factors from 12 provinces in Thailand were retrieved from Thai Digital Government Development Agency and Thai Meteorological Department, respectively. The differences in meteorological factors in 12 provinces, and between meteorological factors were analyzed. Multiple regression method was used to examine the impact of meteorological factors on the number of COVID-19 patients. The number of COVID-19 patients in Thailand in the third pandemic wave was higher than in the first and second waves. The cumulative patients of the third wave since January-May 2021 in Bangkok, Chiang Mai, Samut Prakan, and Chon Buri were among the highest. The meteorological factors in each province, including relative humidity, wind speed, and temperature, were significantly different. Furthermore, a significant association between temperature and the number of COVID-19 patients was found. Finally, the multiple regression analysis showed that the temperature factor could significantly predict the number of COVID-19 patients. The result from this study may be useful for future study aimed at determining a strategy to prevent the COVID-19 pandemic cause by meteorological factors.