• Francisco Javier Candel, Elisabet Viayna, Daniel Callejo, Raul Ramos, Jesús San-Roman-Montero, Pablo Barreiro, María Del Mar Carretero, Adam Kolipiński, Jesus Canora, Antonio Zapatero, and Michael Chris Runken.
• Clinical Microbiology and Infectious Diseases, Hospital Clínico San Carlos, IdISSC and IML Health Institutes, Council of Public Health, Prof Martín Lagos, s/n, 28040 Madrid, Spain.
• Viruses Basel. 2021 May 15; 13 (5).

AbstractThe global COVID-19 spread has forced countries to implement non-pharmacological interventions (NPI) (i.e., mobility restrictions and testing campaigns) to preserve health systems. Spain is one of the most severely impacted countries, both clinically and economically. In an effort to support policy decision-making, we aimed to assess the impacts of different NPI on COVID-19 epidemiology, healthcare costs and Gross Domestic Product (GDP). A modified Susceptible-Exposed-Infectious-Removed epidemiological model was created to simulate the pandemic evolution. Its output was used to populate an economic model to quantify healthcare costs and GDP variation through a regression model which correlates NPI and GDP change from 42 countries. Thirteen scenarios combining different NPI were consecutively simulated in the epidemiological and economic models. Both increased testing and stringency could reduce cases, hospitalizations and deaths. While policies based on increased testing rates lead to higher healthcare costs, increased stringency is correlated with greater GDP declines, with differences of up to 4.4% points. Increased test sensitivity may lead to a reduction of cases, hospitalizations and deaths and to the implementation of pooling techniques that can increase throughput testing capacity. Alternative strategies to control COVID-19 spread entail differing economic outcomes. Decision-makers may utilize this tool to identify the most suitable strategy considering epidemiological and economic outcomes.

27 keywords...

hide…