The time-dependent reproductive number, Rt, representing the average secondary infection at any specific time, is an important epidemiological metric in determining the transmission trend of infectious diseases. With the emergence of SARS-CoV-2, the virus causing the highly contagious Coronavirus disease (COVID-19), there has been an emphasis on accurately estimating the reproductive number to help public health officials assess the effectiveness of intervention policies. However, the current methods for estimating the reproductive number have failed to account for human mobility throughout a region, which greatly impacts the spread of a disease. In this study, we will introduce a method of computing from the data, incorporating human mobility. Using our method on the COVID-19 case data collected from Nepal during the first wave of pandemic (March 2020 to September 2020), we highlight the effect that human mobility has on the reproductive number of COVID-19.
