Confidence in Public Institutions is Critical in Containing the COVID-19 Pandemic

Abstract

Background There is substantial heterogeneity in COVID-19 prevalence and deaths across countries. Several potential mechanisms have already been revealed behind this phenomenon, and from policy point of view, it is key to find the most important ones to fight pandemics that are expected to occur more often in the future.Methods We employ regression and machine learning methods to identify the most critical predictors of deaths attributed to the pandemic. We control for each type of confounding factors used in the previous articles.Findings We find that confidence in public institutions is one of the most important predictors of deaths attributed to COVID-19, compared to country-level measures of individual health risks, the health system, demographics, economic and political development, and social capital. A one standard deviation increase (e.g., the actual difference between the US and Finland) in confidence is associated with 350·9 (95% CI -531·922 - -169·831, p=0·000) fewer predicted deaths per million inhabitants.Interpretation Our results suggest that effective policy implementation during pandemics requires citizens to cooperate with their governments, and willingness to cooperate relies on confidence in public institutions.Funding Hungarian National Scientific Research Program (PD128850 and FK131422).Declaration of Interest: None to declare.