Integrating Public Health Data and Epidemiological Models in Business Decision-Making Post COVID-19

Objective: Propose the integration of public health data and epidemiological models into decision-making processes for health-related businesses in the Panamanian economy during future pandemics. Theoretical Framework: The analysis of the relationship between public health and the economy, through econometric models, basic reproduction number, effective reproduction number, and their interaction in health crisis contexts, provides a foundation for understanding the use of epidemiological data in strategic crisis management. Method: The methodology involves a quantitative approach using time series and predictive models applied to secondary data from the Ministry of Health of Panama on COVID-19 cases between march-april 2020. Results and Discussion: A strong relationship was found between hospitalized cases in regular wards and ICUs, consistent with findings from Kucharski et al. (2020) and Petrucci et al. (2020). This suggests that an increase in direct infections translates to higher demand for hospital services, enabling the anticipation of risks and strategic planning for staff and supplies. Research Implications: The implementation of models that account for trends, seasonality, cycles, and irregularities, complemented by the analysis of relationships between variables, facilitates the development of predictive models that incorporate epidemiological indicators and their effects on any economic sector, particularly health-related ones. Originality/Value: This study proposes a comprehensive framework that combines public health data with econometric models, offering an innovative tool for business decision-making during health crises.