![]() ![]() Simulation represents a way of mapping several real-world scenarios as a model ( 22). Simulation is an effective technique to provide solutions to real-time problems because it obviates the burden of making changes to physical systems that require a lot of investment in time, cost and risks ( 21). ![]() It is important to understand the time required between exposure and complete recovery, using these interventions, to take timely responsive actions against COVID-19 ( 20). Other non-pharmaceutical interventions (NPIs) such as restrictions on public gatherings, intra-city movements, etc., may flatten the curve. Travel restrictions have reduced the rate of spread of the infection ( 18, 19). Yet, the existence of a significant proportion of asymptomatic carriers makes it a greater cause for concern as they remain unidentified and can unknowingly spread the disease to healthy people ( 15- 17). Common symptoms of COVID-19 include fever, cough and fatigue ( 9). The behaviour of COVID-19 is found to be similar to that of Severe Acute Respiratory Syndrome (SARS) epidemic family which reduces the chance of reinfection ( 12, 14). Reports estimate that the transmission rates range from 2.24 to 3.58 and WHO estimates transmission rates between 1.4 to 2.5 ( 10, 13). Higher transmission rate of the disease further increases the vulnerability. There are several underlying factors such as age, comorbidities, exposure to air pollution, amount of exposure to virus, etc., that may determine the severity of Infection and rate of recovery ( 12). In a country like India having a denser population, the situation poses a serious challenge ( 11). Globally, COVID-19 has spread across 213 nations, infecting 28,035,700 people worldwide and claiming 908,991 lives as on Sep 10, 2020, posing a global health emergency ( 8- 10). Since then, epidemic has spread across India infecting 44,94,389 people with 9,27,545 active cases, 34,90,908 recovered cases and 75,328 deaths as on ( 7). The first reported case of the novel coronavirus (COVID-19 or SARS-CoV-2) in India dates back to Januwhen it was also announced as pandemic by WHO ( 5, 6). The results could provide a platform for researchers and modelers to explore using ABM approach for COVID-19 projections with inclusion of interventions and health system preparedness. Results revealed that the peak values and slope of the curve declined as NPI became more stringent. AnyLogic platform was used for the ABM simulations. The parameters for the ABM model were defined and model run for a period of 365 days for three different non-pharmaceutical intervention (NPI) scenarios, namely no lockdown, 50% lockdown and 75% lockdown scenarios. district, as this prove to be much helpful for policymaking compared to models estimating nation-wide disease projections. The model is developed based on data pertaining to a local area, i.e. We present an ABM approach with a synthetic population from Rangareddy district, Telangana state, India, to examine the patterns and trends of the COVID-19 in terms of infected, admitted, critical cases requiring intensive care and/ or ventilator support, mortality and recovery. ABMs, provide better insights into projections compared to compartmental models ( 4). Unlike compartmental models, which consider population averages, Agent Based Models (ABM) consider individual behavior in the models for disease projections. These projections are being used for policy level decisions and public health prevention activities ( 2, 3). ![]() Several mathematical models, mostly based on compartmental modeling, are being used for projections for COVID-19 in India. It has been declared as a “Public Health Emergency of International Concern” (PHE 1C), by the World Health Organization ( 1). COVID-19 disease, caused by SARS-CoV-2 virus, has infected over four million people globally. ![]()
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