Working Papers

2020-23 | December 2020

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Weather, Mobility, and COVID-19: A Panel Local Projections Estimator for Understanding and Forecasting Infectious Disease Spread

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This paper derives a local projections panel data model that can be used both to identify the dynamic causal effects of disease transmission factors as well as to forecast disease spread. The empirical model is derived from the canonical SIR epidemiological model of infectious disease spread. Using high-frequency panel data for U.S. counties through early December, I first use this model to estimate the impulse response functions (IRFs) of COVID-19 infections to shocks to individual mobility and weather. This analysis reveals several important results. First, holding mobility fixed, temperature reduces COVID-19 infections up to 30 days ahead. Second, holding weather fixed, mobility increases infections up to at least 70 days ahead, with peak effects around 30 to 40 days ahead. The IRFs are positive and significant across a variety of mobility measures, including visits to establishments of different economic sectors. Third, the deleterious effects of mobility on COVID-19 spread are greater when the local effective reproduction number is above one - evidence supportive of public health policies aiming to reduce mobility specifically in places experiencing high transmission rates while relaxing restrictions elsewhere. In the latter part of the paper, I use the estimated empirical model to provide out-of-sample forecasts of COVID-19 infections at the county level throughout the United States, which utilize data on current and lagged values of infections, mobility, and weather. The model's 30-day ahead out-of-sample forecasts based on data through early November correlate strongly with actual new infections between early November and early December.

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Article Citation

Wilson, Daniel J. 2020. "Weather, Mobility, and COVID-19: A Panel Local Projections Estimator for Understanding and Forecasting Infectious Disease Spread," Federal Reserve Bank of San Francisco Working Paper 2020-23. Available at https://doi.org/10.24148/wp2020-23