Abstract: Methods for reviewing epidemiological signals are necessary to building and maintaining data-driven public health capabilities. We have developed a novel approach for assessing the plausibility of infectious disease forecasts and surveillance data. The PLANES (PLausibility ANalysis of Epidemiological Signals) methodology is designed to be multi-dimensional and flexible, yielding an overall score based... MORE

Abstract: The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles... MORE

Abstract: Near-term disease forecasting and scenario projection efforts rely on the availability of data to train and evaluate model performance. In most cases, more extensive epidemiological time series data can lead to better modeling results and improved public health insights. Here we describe a procedure to augment an epidemiological time... MORE

Abstract: Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS),... MORE

Abstract: Operational infectious disease modeling efforts are important to public health response before, during, and after outbreak events. Recent collaborative initiatives have demonstrated the success of hubs, which openly solicit modeling output from contributors. Automation techniques can help improve timeliness of submissions to hubs. Furthermore, we suggest that containerization approaches... MORE