Impact of Weather Parameters and Population Density on the COVID-19 Transmission: Evidence from 81 Provinces of Turkey

Abstract

Weather factors are effective to transmission of various diseases. Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and kinds of influenza can be given as example these diseases. The novel corona virus which is called COVID-19 is the most dangerous problem all around the world in these days. Early studies have revealed that COVID-19 cases are affected by environmental factors. Therefore, the purpose of this paper is to examine the relationship between the number of novel coronavirus cases and several weather parameters in 81 provinces of Turkey. Mean incubation period of COVID-19 is in question. Thus, this paper also aims to provide better understanding of the exact incubation period in Turkey by employing four different timeframe which are on the day (lag 0), 3 days ago (lag 3), 7 days ago (lag 7) and 14 days ago (lag 14). We have considered population density as a control variable. The dataset cover COVID-19 cases, population density, average temperature, humidity, pressure, dew point, wind speed, and sunshine duration for 81 provinces of Turkey. We find that population density has a positive correlation with COVID-19 cases. We also find that in lag 3, all parameters except for sunshine duration are negatively correlated with COVID-19 cases and significant. However, only 3 parameters, temperature, air pressure and dew point are negatively correlated with COVID-19 cases and significant for lag 0, lag 7 and lag 14. In addition, temperature, air pressure and dew point parameters are negative and significant in all timeframes.