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

Author(s)

Viayna E1, Candel FJ2, Callejo-Velasco D3, Ramos R4, San-Roman J5, Barreiro P6, Carretero MDM7, Kolipinski A8, Canora J9, Zapatero A9, Runken MC10
1Grifols, Sant Cugat del Valles, Spain, 2Hospital Clínico San Carlos, Madrid, Spain, 3IQVIA, Madrid, Spain, 4University of Barcelona, Barcelona, Spain, 5Universidad Rey Juan Carlos, Madrid, Spain, 6Hospital La Paz, Madrid, Spain, 7Public Health Laboratory of Madrid, Madrid, Spain, 8IQVIA, Warsaw, Poland, 9Public Health Council, Madrid, Spain, 10Grifols SSNA, Research Triangle Park, NC, USA

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.

Conference/Value in Health Info

2021-11, ISPOR Europe 2021, Copenhagen, Denmark

Value in Health, Volume 24, Issue 12, S2 (December 2021)

Code

POSB174

Topic

Epidemiology & Public Health

Topic Subcategory

Public Health

Disease

Infectious Disease (non-vaccine)

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