ABSTRACT
In times of epidemics and humanitarian crises, it is essential to translate scientific findings into digestible information for government policy makers who have a short time to make critical decisions. To predict how far and fast the disease would spread across Hungary and to support the epidemiological decision-making process, a multidisciplinary research team performed a large amount of scientific data analysis and mathematical and socioeconomic modeling of the COVID-19 epidemic in Hungary, including modeling the medical resources and capacities, the regional differences, gross domestic product loss, the impact of closing and reopening elementary schools, and the optimal nationwide screening strategy for various virus-spreading scenarios and R metrics. KETLAK prepared 2 extensive reports on the problems identified and suggested solutions, and presented these directly to the National Epidemiological Policy-Making Body. The findings provided crucial data for the government to address critical measures regarding health care capacity, decide on restriction maintenance, change the actual testing strategy, and take regional economic, social, and health differences into account. Hungary managed the first part of the COVID-19 pandemic with low mortality rate. In times of epidemics, the formation of multidisciplinary research groups is essential for policy makers. The establishment, research activity, and participation in decision-making of these groups, such as KETLAK, can serve as a model for other countries, researchers, and policy makers not only in managing the challenges of COVID-19, but in future pandemics as well.
