A Time-Series Analysis on the Covid-19 Mortality, PM2.5 Levels, and Weather Variables in Denpasar City, Indonesia

Abstract

The objective of this study is to explore the relationship between Covid-19 mortality cases and environmental variables, namely PM2.5 concentration and weather variables, in Denpasar City, Indonesia. Regression models were used. The response variable was the monthly Covid-19 mortality from March 2020 to December 2021 and the predictor variables were the mean concentration of PM2.5, temperature, wind speed, rainfall and duration of sunshine. All data analyzed were provided by the Indonesian Government. Simple linear regression (SLR) and dynamic regression with ARIMA error models were used. Further, of the 22 monthly data, the first 19 months data were used to train the models and the remaining data were used as the test data. It is found that both wind speed and the interaction between PM2.5 concentration and wind speed have statistically significant relationships with Covid-19 mortality. The estimates of SLR and ARIMA (0,1,1) with interaction models show that on average, in case of 0.5 m/s wind speed, an increase of 1 \U0001d707g/m3 in the monthly mean of daily PM2.5 concentrations associates with 17.4 and 16.3 increase in the monthly Covid-19 mortality case, respectively. Although this study is observational, its findings suggest the importance of controlling PM2.5 concentration.