Nowcasting and forecasting the 2022 U.S. mpox outbreak: Support for public health decision making and lessons learned

• DOI: 10.1016/j.epidem.2024.100755
• Publication Date: 2024-03-02T03:58:48Z
• Authors: Kelly Charniga; Zachary J. Madewell; Nina B. Masters; Jason Asher; Yoshinori Nakazawa; Ian H. Spicknall
• Keywords: Nowcasting

In June of 2022, the U.S. Centers for Disease Control and Prevention (CDC) Mpox Response wanted timely answers to important epidemiological questions which can now be answered more effectively through infectious disease modeling. Infectious models have shown valuable tools decision making during outbreaks; however, model complexity often makes communicating results limitations makers difficult. We performed nowcasting forecasting 2022 mpox outbreak in United States using R package EpiNow2. generated nowcasts/forecasts at national level, by Census region, jurisdictions reporting greatest number cases. Modeling were shared situational awareness within CDC publicly on website. retrospectively evaluated forecast predictions four key phases (early, exponential growth, peak, decline) three metrics, weighted interval score, mean absolute error, prediction coverage. compared performance EpiNow2 with a naïve Bayesian generalized linear (GLM). The had less probabilistic error than GLM every phase except early phase. share our experiences an existing tool nowcasting/forecasting highlight areas improvement development future tools. also reflect lessons learned regarding data quality issues adapting modeling different audiences.