Correlation Between COVID-19 Infection Rate and Atmospheric Environmental Factors in Seoul Metropolitan City, South Korea

Abstract

The purpose of this study is to statistically analyze whether the change in the COVID-19 virus infection rate is affected by atmospheric environmental factors in Seoul metropolitan city of South Korea. The research period of this study is from January 1, 2020 to March 31, 2021. The correlation relationship between the COVID-19 virus infection rate and atmospheric environmental factors such as PM10, PM2.5, temperature, and humidity was analyzed by multiple regression analysis. In the correlation between PM10 and PM2.5 and the COVID-19 virus infection rate, correlation coefficient between PM10 and infection rate was r=0.114(p=0.019), showing a positive correlation. The correlation coefficient between PM2.5 and infection rate was r=0.147(p=0.002), which indicates a higher positive correlation than PM10. In the correlation between thermal factors and infection rate, the correlation coefficients between temperature and infection rate and between relative humidity and infection rate were r= -0.527(p=0.000) and r= -0.91(p=0.060), respectively. Unlike PM10 and PM2.5, temperature and relative humidity showed a negative correlation with the infection rate. Except for relative humidity, PM10, PM2.5 and temperature had statistically significant correlations with the infection rate (p<0.05). Based on the results obtained from this study, it is recommended to avoid outdoor activities as much as possible in weather with high PM10 and PM2.5 and low temperature and humidity.

Air Pollution and Meteorological Parameters in SARS-CoV-2 Virus Spread and Transition

“…Since NO and NO 2 are emitted from the exhaust and oxidized to other nitrogen oxides (NOx) by solar radiation and free radicals, these contaminants are expected to be associated with the infectivity of SARS-CoV-2 (due to people mobility). In one Study, SO2 was positively correlated with SARS-CoV-2 cases [12] but this contradicts the results reported in another study, however, they studied COVID deaths instead of SARS-CoV-2 cases [12,38]. NO 2 , SO 2 , and CO are common products of burned fuels, and as they rise together and are correlated positively to infection cases, they could be used to predict SARS-CoV-2 spread [11,39].…”

“…Because CO could be taken as a marker of people's mobility (because of the use of cars), this pollutant could indicate that people kept interacting and getting infected regardless of the lockdown politics of the Government. NO, NO 2 and NOx show also positive correlations [12,38]. Since NO and NO 2 are emitted from the exhaust and oxidized to other nitrogen oxides (NOx) by solar radiation and free radicals, these contaminants are expected to be associated with the infectivity of SARS-CoV-2 (due to people mobility).…”

A Study on the Preliminary Plan for Environmental Health in Seoul, Korea

“…Under this vision, the national plan is composed of four strategies, twelve main tasks, and fifty subtasks. For the community level, in 2013, the “Seoul City Environmental Health Policy Roadmap (SCEHPR)” [ 23 ] was established to investigate the adverse effects of hazardous environmental factors on human health and the environment, reduce the effects, prevent environmental diseases, and compensate those afflicted by environmental hazards. The Roadmap was composed of 4 strategies, 16 main tasks, and 45 subtasks.…”

The Influence of Meteorological Factors on the Effect of SARS-CoV-2 Transmission and Its Delayed Effect

“…In addition, the delayed effects of the effects of meteorological factors have rarely been discussed in depth in relevant studies. The study by Choi and Kim et al established a 2-day delay, but did not elaborate [3]. The study by Ma et al established a delay interval of 1 to 5 days, but the interval was clearly too small [1].…”

“…Nottmeyer et al used data from 455 cities in 20 countries, a negative correlation was analysed between temperature and absolute humidity and the effect of new coronavirus transmission [2]. Examining data from Seoul from 1 January 2020 to 31 March 2021, Choi and Kim found that temperature and relative humidity were negatively correlated with the rate of new coronavirus infections [3]. In addition, a research team have conducted animal model tests using guinea pigs as hosts for the new coronavirus, showing that both cold and dry conditions are conducive to the spread of the new coronavirus [4].…”