METHODS: We used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed.
RESULTS: The results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = -0.230; p < 0.05, r = 0.211; p < 0.05 and r = -0.418; p < 0.01, respectively.
CONCLUSIONS: We recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread.