POSB174 Clinical and Economic Impact of Non-Pharmacological Interventions on the COVID-19 Pandemic: A Predictive Model Based on the Spanish Case

ABSTRACT

Objectives: With over 172 million cases and 3.7 million deaths worldwide, the COVID-19 pandemic has overwhelmed health systems forcing governments to implement non-pharmacological interventions (NPI) to control the spread of the disease. Spain was one of the first and most severely impacted countries by the COVID-19 pandemic. The models developed herein aim to assess the clinical and economic consequences of such NPI, based on the Spanish case. Methods: Two separate models were developed to assess the epidemiological and economic impacts of different NPI (i.e. social restrictions and testing) on the COVID-19 pandemic. First, a dynamic, modified, Susceptible-Exposed-Infectious-Removed (SEIR) model was developed. Then, the output from the SEIR model was used in the second model to estimate direct healthcare costs and Gross Domestic Product (GDP) changes using a regression model which correlated different NPI and GDP changes observed across 42 countries. Overall, 13 scenarios combining different NPIs based on social restrictions and testing rates were simulated through both models. Results: Based on the results from the SEIR simulation both increased social restrictions (Composite COVID-19 Stringency Index≥73) and increased testing rates (positivity≤1%) would manage to control the COVID-19 spread. However, notable differences are observed in terms of direct healthcare costs and GDP impact. Policies entailing increased testing rates translated into higher healthcare costs and lower GDP decline (vs. same quarter from previous year), whereas increased social restrictions are correlated with greater GDP declines, with differences of up to 4.4% points among scenarios. Increased test sensitivity also leads to higher reductions on cases, hospitalizations and deaths. Conclusions: Increased testing appears to be able to control the COVID-19 pandemic while minimizing the GDP impact. These models may provide evidence for decision makers during future pandemics and in countries where vaccination rates are still low helping to better balance health and socioeconomic concerns.