Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the world's largest public health concern in 2021. This study evaluated the associations of the prevalence of airway symptoms among the tested individuals and data regarding the natural environmental factors with the weekly number of newly diagnosed COVID-19 patients in Sendai City (Nt). For the derivatives of the screening test results, data from individuals with a contact history who underwent nasopharyngeal swab reverse transcription-polymerase chain reaction (RT-PCR) testing between July 2020 and April 2021 (6,156 participants, including 550 test-positive patients) were used. The value of Nt correlated with the weekly RT-PCR test-positive rate after close contact, prevalence of cough symptoms in test-positive individuals or in test-negative individuals, lower air temperature, lower air humidity, and higher wind speed. The weekly test-positive rate correlated with lower air humidity and higher wind speed. In cross-correlation analyses, natural environmental factors correlated with the regional epidemic status on a scale of months, whereas the airway symptoms among non-COVID-19 population affected on a scale of weeks. When applying an autoregression model to the serial data of Nt, large-scale movements of people were suggested to be another factor to influence the local epidemics on a scale of days. In conclusion, the prevalence of cough symptoms in the local population, lower air humidity or higher wind speed, and large-scale movements of people in the locality would jointly influence the local epidemic status of COVID-19.
Keywords: atmospheric humidity; coronavirus disease 2019 (COVID-19); cough symptoms; local epidemics; time-series analysis.