Statistical deconvolution for inference of infection time series (preprint)

Accurate measurement of daily infection incidence is crucial to epidemic response. However, delays in symptom onset, testing, and reporting obscure the dynamics of transmission, necessitating methods to remove the effects of stochastic delays from observed data. Existing estimators can be sensitive to model misspecification and censored observations; many analysts have instead used methods that exhibit strong bias or do not account for delays. We develop an estimator with a regularization scheme to cope with these sources of noise, which we term the Robust Incidence Deconvolution Estimator (RIDE). We validate RIDE on synthetic data, comparing accuracy and stability to existing approaches. We then use RIDE to study COVID-19 records in the United States, and find evidence that infection estimates from reported cases can be more informative than estimates from mortality data. To implement these methods, we release incidental, a ready-to-use R implementation of our estimator that can aid ongoing efforts to monitor the COVID-19 pandemic.

Mobility trends provide a leading indicator of changes in SARS-CoV-2 transmission (preprint)

Determining the impact of non-pharmaceutical interventions on transmission of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is paramount for the design and deployment of effective public health policies. Incorporating Apple Maps mobility data into an epidemiological model of daily deaths and hospitalizations allowed us to estimate an explicit relationship between human mobility and transmission in the United States. We find that reduced mobility explains a large decrease in the effective reproductive number attained by April 1st and further identify state-to-state variation in the inferred transmission-mobility relationship. These findings indicate that simply relaxing stay-at-home orders can rapidly lead to outbreaks exceeding the scale of transmission that has occurred to date. Our findings provide quantitative guidance on the impact policies must achieve against transmission to safely relax social distancing measures.