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.

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.

Impacts of prescription drug monitoring program policy changes and county opioid safety coalitions on prescribing and overdose outcomes in California, 2015-2018.

In 2015, California received funding to implement the Prescription Drug Overdose Prevention Initiative, a 4-year program to reduce deaths involving prescription opioids by 1) leveraging improvements to California's prescription drug monitoring program (PDMP) (i.e., mandatory PDMP registration for prescribers and pharmacists), and 2) supporting county opioid safety coalitions.