Investigating the effect of health measures and social restrictions on the COVID-19 epidemic based on the SIQR mathematical model

Background & Aims: COVID-19 pandemic is a serious concern of the World Health Organization and is considered the most important global health challenge. This study aimed to study the effect of health measures and social restrictions on the COVID-19 epidemic based on the susceptible-infectious-quarantine-recovered (SIQR) mathematical model. Materials & Methods: Using the SIQR model, we assessed the effect of health measures and social restrictions on the COVID-19 epidemic by considering different values for the reproductive rate parameter and constant values for the recovery rate and quarantined rate (or disease detection rate). Results: The results indicated that with increasing the level of social restrictions and health measures equivalent to 20, 40, 60, and 80%, the reproductive rate of the COVID-19 reduced from 2.5 to 2, 1.5, 1, and 0.5, respectively. Also, with increasing the levels of social restrictions and health measures, a smaller percentage of people in the community became infected. Considering the level of social restrictions equal to 20, 40, 60, and 80% during the COVID-19 epidemic, about 60, 50, 35, and 10% of the individuals were infected with COVID-19, respectively. Conclusion: The study of the impact of health measures and social restrictions on the COVID-19 epidemic will provide appropriate information on how the disease spreads and also help researchers select the proper level of these measures and restrictions to prevent further spread of COVID-19 disease.