ABSTRACT
Since its discovery in the Hubei province of China, the global spread of the novel coronavirus SARS-CoV-2 has resulted in millions of COVID-19 cases and hundreds of thousands of deaths. The spread throughout Asia, Europe, and the Americas has presented one of the greatest infectious disease threats in recent history and has tested the capacity of global health infrastructures. Since no effective vaccine is available, isolation techniques to prevent infection such as home quarantine and social distancing while in public have remained the cornerstone of public health interventions. While government and health officials were charged with implementing stay-at-home strategies, many of which had little guidance as to the consequences of how quickly to begin them. Moreover, as the local epidemic curves have been flattened, the same officials must wrestle with when to ease or cease such restrictions as to not impose economic turmoil. To evaluate the effects of quarantine strategies during the initial epidemic, an agent based modeling framework was created to take into account local spread based on geographic and population data with a corresponding interactive desktop and web-based application. Using the state of Massachusetts in the United States of America, we have illustrated the consequences of implementing quarantines at different time points after the initial seeding of the state with COVID-19 cases. Furthermore, we suggest that this application can be adapted to other states, small countries, or regions within a country to provide decision makers with critical information necessary to best protect human health. Author summaryIn this work we presented a local agent-based geographic model for the epidemic spread of COVID-19 with and without quarantine measures. The model is implemented as an interactive Microsoft Windows application, as a web tool online (summaries only), and the source code is freely available at GitHub. In this article, the model is presented for the state of Massachusetts (United States), but can be easily adopted to other administrative districts, areas and territories where the demographics and population characteristics of the reported cases are known. After calibration, the model predicts the morbidity and mortality of the epidemic as it spreads with different quarantine parameters, which lead to reduction of social contact probabilities between individuals. The model outputs for different quarantine start dates and durations are then summarized and compared to actual disease incidence. These summaries demonstrate the effectiveness of the early quarantine measures on the reduction of the number of new infections and deaths. The model framework can also be adopted for use in future decision making process for government and health officials as plans to cease or ease quarantines continue to evolve using the interactive application.
