Assessing the accuracy of California county level COVID-19 hospitalization forecasts to inform public policy decision making.

Background: The COVID-19 pandemic has highlighted the role of infectious disease forecasting in informing public policy. However, significant barriers remain for effectively linking infectious disease forecasts to public health decision making, including a lack of model validation. Forecasting model performance and accuracy should be evaluated retrospectively to understand under which conditions models were reliable and could be improved in the future.

Visual policy narrative messaging improves COVID-19 vaccine uptake.

In the face of vaccine hesitancy, public health officials are seeking more effective risk communication approaches to increase vaccination rates. We test the influence of visual policy narratives on COVID-19 vaccination behavior through a panel survey experiment conducted in early 2021 ( = 3,900) and then 8 weeks later ( = 2,268). We examine the effects of three visual policy narrative messages that test the narrative mechanism of character selection (, , and ) and a nonnarrative control on COVID-19 vaccine behavior.

Policy learning and change during crisis: COVID-19 policy responses across six states.

Whereas policy change is often characterized as a gradual and incremental process, effective crisis response necessitates that organizations adapt to evolving problems in near real time. Nowhere is this dynamic more evident than in the case of COVID-19, which forced subnational governments to constantly adjust and recalibrate public health and disease mitigation measures in the face of changing patterns of viral transmission and the emergence of new information. This study assesses (a) the extent to which subnational policies changed over the course of the pandemic; (b) whether these changes are emblematic of policy learning; and (c) the drivers of these changes, namely changing political and public health conditions.

COVIDNearTerm: A simple method to forecast COVID-19 hospitalizations.

Introduction: COVID-19 has caused tremendous death and suffering since it first emerged in 2019. Soon after its emergence, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy.

Methods: Here we present a method called COVIDNearTerm to "forecast" hospitalizations in the short term, two to four weeks from the time of prediction.