Examining the differences in format and characteristics of zoonotic virus surveillance data on state agency websites.
Examining the differences in format and characteristics of zoonotic virus surveillance data on state agency websites.
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DOI：
10.2196/jmir.2487
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发表时间：
2013-04-26
影响因子：
7.4
通讯作者：
Halden RU
中科院分区：
文献类型：
--
作者：
Scotch M;Baarson B;Beard R;Lauder R;Varman A;Halden RU
人畜共患病毒是可在动物和人之间传播的传染性生物。公共卫生、农业和野生动物机构对人畜共患病毒进行监测，并经常在其网站上报告数据。然而，这些数据的格式和特征尚不清楚。描述和比较国家公共卫生、农业和野生动物机构网站上人畜共患病毒统计的格式和特征。对于每个州，我们都考虑了该州公共卫生、农业和野生动物机构的网站。对于每个网站，我们都注意到存在2000-2012年人畜共患病毒的统计数据。我们使用多种类别分析数据，包括统计类型、时间和地理详细程度以及格式。我们根据个人对从网站提取和分析数据的偏好的假设，在每个类别中对我们的分析进行优先排序。因此，如果给定年份的特定病毒存在两种类型的数据（例如城市和州级），我们将计算优先级较高的数据（城市）。不考虑从代理网站到其他网站的外部链接。从2000年到2012年，州卫生部门拥有最广泛的病毒数据，其次是农业，然后是野生动物。我们关注的是这三家机构中常见的七种病毒。这些疾病包括狂犬病、西尼罗河病毒、东部马脑炎、圣路易斯脑炎、西部马脑炎、流感和登革热。简单的数字总数最常用于报告数据（公共卫生为89%，农业为81%，野生动物为82%），比例没有差异（卡方P=.15）。公共卫生数据最常每年提交一次（66%），而农业和野生动物机构经常如实描述病例（Fisher’s Exact检验P<.001）。在格式方面，公共卫生机构有更多可下载的PDF文件（68%），而农业（61%）和野生动物机构（46%）直接在HTML网页的文本中提供数据（Fisher’s Exact检验P<.001）。人口统计和其他信息，包括年龄、性别和东道主，是有限的。最后，Fisher精确检验显示地理数据与代理类型之间没有关联（P=.08）。然而，有人指出，农业部的数据往往是县一级的（63%），而公共卫生部门的数据则是县（38%）和州（35%）的混合数据。本研究的重点是在人口健康监测背景下，国家公共卫生、野生动物和农业机构网站上人畜共患病毒的统计格式和特征。各机构关于人畜共患病毒的数据各不相同，这给需要整合来自不同网站的动物和人类数据的研究人员带来了挑战。
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. To describe and compare the format and characteristics of statistics of zoonotic viruses on state public health, agriculture, and wildlife agency websites. 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. 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%). 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.
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