Abstract
BACKGROUND: The reproduction number (R(0)) is vital in epidemiology to estimate the number of infected people and trace close contacts. R(0) values vary depending on social activity and type of gathering events that induce infection transmissibility and its pathophysiology dependence. OBJECTIVES: In this study, we estimated the probable outbreak size of COVID-19 clusters mathematically using a simple model that can predict the number of COVID-19 cases as a function of time. METHODS: We proposed a mathematical model to estimate the R(0) of COVID-19 in an outbreak occurring in both local and international clusters in light of published data. Different types of clusters (religious, wedding, and industrial activity) were selected based on reported events in different countries between February and April 2020. RESULTS: The highest R(0) values were found in wedding party events (5), followed by religious gathering events (2.5), while the lowest value was found in the industrial cluster (2). In return, this will enable us to assess the trend of coronavirus spread by comparing the model results and observed patterns. CONCLUSIONS: This study provides predictive COVID-19 transmission patterns in different cluster types based on different R(0) values. This model offers a contact-tracing task with the predicted number of cases, to decision-makers; this would help them in epidemiological investigations by knowing when to stop.