Examining the differences in format and characteristics of zoonotic virus surveillance data on state agency websites

Background: Zoonotic viruses are infectious organisms transmittable between animals and humans. Agencies of public health, agriculture, and wildlife conduct surveillance of zoonotic viruses and often report data on their websites. However, the format and characteristics of these data are not known. Objective: To describe and compare the format and characteristics of statistics of zoonotic viruses on state public health, agriculture, and wildlife agency websites. Methods: For each state, we considered the websites of that state's public health, agriculture, and wildlife agency. For each website, we noted the presence of any statistics for zoonotic viruses from 2000-2012. We analyzed the data using numerous categories including type of statistic, temporal and geographic level of detail, and format. We prioritized our analysis within each category based on assumptions of individuals' preferences for extracting and analyzing data from websites. Thus, if two types of data (such as city and state-level) were present for a given virus in a given year, we counted the one with higher priority (city). External links from agency sites to other websites were not considered. Results: From 2000-2012, state health departments had the most extensive virus data, followed by agriculture, and then wildlife. We focused on the seven viruses that were common across the three agencies. These included rabies, West Nile virus, eastern equine encephalitis, St. Louis encephalitis, western equine encephalitis, influenza, and dengue fever. Simple numerical totals were most often used to report the data (89% for public health, 81% for agriculture, and 82% for wildlife), and proportions were not different (chi-square P=.15). Public health data were most often presented yearly (66%), while agriculture and wildlife agencies often described cases as they occurred (Fisher's Exact test P<.001). Regarding format, public health agencies had more downloadable PDF files (68%), while agriculture (61%) and wildlife agencies (46%) presented data directly in the text of the HTML webpage (Fisher's Exact test P<.001). Demographics and other information including age, gender, and host were limited. Finally, a Fisher's Exact test showed no association between geography data and agency type (P=.08). However, it was noted that agriculture department data was often at the county level (63%), while public health was mixed between county (38%) and state (35%). Conclusions: This study focused on the format and characteristics of statistics of zoonotic viruses on websites of state public health, wildlife, and agriculture agencies in the context of population health surveillance. Data on zoonotic viruses varied across agencies presenting challenges for researchers needing to integrate animal and human data from different websites.