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Background Infectious disease forecasting aims to predict characteristics of both seasonal epidemics and future pandemics. Accurate and timely infectious disease forecasts could aid public health responses by informing key preparation and mitigation efforts. Main body For forecasts to be fully integrated into public health decision-making, federal, state, and local officials must understand how forecasts were made, how to interpret forecasts, and how well the forecasts have performed in the past. Since the 2013–14 influenza season, the Influenza Division at the Centers for Disease Control and Prevention (CDC) has hosted collaborative challenges to forecast the timing, intensity, and short-term trajectory of influenza-like illness in the United States. Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provides an overview of infectious disease forecasting; applications of forecasting to public health; and current work to develop best practices for forecast methodology, applications, and communication. Conclusions These efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.

This article describes a CDI outbreak in a long-term care (LTC) facility that used molecular typing techniques and whole-genome sequencing to identify widespread dissemination of the clonal strain in the environment which was successfully removed after terminal cleaning. This study was conducted in a long-term care facility in Texas. A recently hospitalized LTC patient was diagnosed with CDI followed shortly thereafter by 7 subsequent CDI cases. A stool specimen was obtained from each patient for culturing and typing. An environmental point-prevalence study of the facility was conducted before and after terminal cleaning of the facility to assess environmental contamination. Cultured isolates were typed using ribotyping, multilocus variant analysis, and whole-genome sequencing. Stool samples were available for 5 of 8 patients; of these specimens, 4 grew toxigenic C. difficile ribotype 027. Of 50 environmental swab samples collected throughout the facility prior to the facility-wide terminal cleaning, 19 (38%) grew toxigenic C. difficile (most commonly ribotype 027, 79%). The terminal cleaning was effective at reducing C. difficile spores in the environment and at eradicating the ribotype 027 strain (P<.001). Using multilocus variance analysis and whole-genome sequencing, clinical and environmental strains were highly related and, in some cases, were identical. Using molecular typing techniques, we demonstrated reduced environmental contamination with toxigenic C. difficile and the eradication of a ribotype 027 clone. These techniques may help direct infection control efforts and decrease the burden of CDI in the healthcare system.