# What drives the effectiveness of social distancing in combating COVID-19 across U.S. states?

## TL;DR

The paper explores how information affects voluntary social distancing during the pandemic, showing that informed states had better outcomes.

## Contribution

A new theory of information-based voluntary social distancing is proposed and integrated into a predictive framework.

## Key findings

- Lockdown effectiveness varied widely across U.S. states during the early pandemic.
- Voluntary social distancing was higher in more informed states.
- Improved information could have significantly reduced fatalities.

## Abstract

We propose a new theory of information-based voluntary social distancing in which people’s responses to disease prevalence depend on the credibility of reported cases and fatalities and vary locally. We embed this theory into a new pandemic prediction and policy analysis framework that blends compartmental epidemiological/economic models with Machine Learning. We find that lockdown effectiveness varies widely across US States during the early phases of the COVID-19 pandemic. We find that voluntary social distancing is higher in more informed states, and increasing information could have substantially changed social distancing and fatalities.