The data portal allows researchers to download time series from a public domain. However, in the present form and due to substantial data compression, the available data and visualizations provided are limited in scope preventing the characterization of inter-annual trends and seasonality characteristics and comparisons across locations, diseases, and time 14, 15, 17, 22, 23, 24. The visualizations aim to aid users in identifying trends of nine laboratory-confirmed foodborne diseases in select counties from ten US states and nationally. The FoodNet Fast platform contains rich demographic data, including age group, gender, and ethnic group, valuable for a broad spectrum of analyses. The CDC Foodborne Disease Active Surveillance Network (FoodNet) provides preprocessed population-based foodborne-disease surveillance records and visualizations via FoodNet Fast, a publicly available data portal 20, 21. More specifically, these visualizations fail to provide detailed examination of how long-term trends change over time, how seasonality estimates vary by year or across locations, or how peak timing and amplitude estimates could change over time.
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Visualizations using these annual trends or broad assessments of seasonality fail to utilize the full complexity of surveillance data and in some cases may be misleading. However, current surveillance systems, including foodborne disease surveillance in the United States, often compress time series records to simplistic annual trends 9, 10, 11, 12, 13 and describe seasonality by the month(s) with the highest cases per year or the first month of outbreak onset 14, 15, 16, 17, 18, 19. These visualizations, and the methodologies used to generate them, must be standardized to enable comparability across time periods, locations, at-risk populations, and pathogens. As the quantity and diversity of data available for processing, synthesizing, and communicating increases, new visual analytics, including complex multi-panel plots, must be considered to monitor trends, investigate seasonality, and support public health planning 8. The pandemic of 2019 novel coronavirus disease (COVID-19) serves as a vivid demonstration of how limited access to publicly available high-quality data can stymy research. Publicly available downloads increase the flexibility for analyses and enables adaptive research due to frequent and timely reporting. The World Health Organization’s (WHO) FluNet, for example, provides time-referenced data on worldwide influenza 7. Web-based platforms provide access to more accurate, timely, and frequent surveillance data. Decade-long efforts to sustain surveillance systems improve early outbreak detection, infection containment, and mobilization of health resources 1, 2, 3, 4 and create adaptive, near-time forecasts for disease outbreaks 5, 6. The resulting compilation, or analecta, of 436 visualizations of records and codes are openly available online.ĭisease surveillance systems worldwide face increasing pressure to maintain and distribute data in usable formats with clearly communicated visualizations to promote actionable policy and programming responses 1. We offer suggestions on how current FoodNet Fast data organization and visual analytics can be improved to facilitate data interpretation, decision-making, and communication of features related to trend and seasonality. The Centers for Disease Control and Prevention’s (CDC) FoodNet Fast provides population-based foodborne-disease surveillance records and visualizations for select counties across the US.
Yet, detecting potential disease outbreaks and supporting public health interventions requires detailed spatiotemporal comparisons to characterize spatiotemporal patterns of illness across diseases and locations. Analyses and visuals are typically limited to reporting the annual time series and the month with the highest number of cases per year. Annual reports and interactive portals provide access to surveillance data and visualizations depicting temporal trends and seasonal patterns of diseases. Disease surveillance systems worldwide face increasing pressure to maintain and distribute data in usable formats supplemented with effective visualizations to enable actionable policy and programming responses.