Droplets during human speech are found to remain suspended in the air for minutes, while studies suggest that the SARS-CoV-2 virus is infectious in experimentally produced aerosols for more than one hour. However, the absence of a large-scale association between regional outbreaks and weather-influenced virus-laden speech-generated aerosol characteristics such as settling time and viral viability makes it challenging for policy making on appropriate infection control measures. Here we investigate the correlation between the time series of daily infections and of settling times of virus-containing particles produced by speaking. Characteristic droplet settling times determined by the Stokes–Cunningham equation as influenced by daily weather conditions were estimated based on local meteorological data. Daily infection data were calibrated from local reported cases based on established infection timeframes. Linear regression, vector autoregression, simple recurrent neural network, and long short-term memory models predict transmission rates within one-sigma intervals using the settling times and viral viability over 5 days before the day of prediction. Corroborating with previous health science studies, from the perspective of meteorology-modulated transmission, our results strengthen that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2. Furthermore, historical weather data can improve the prediction accuracy of infection spreading rates.