Ending Pandemics, San Francisco, CA, United States.
JMIR Public Health Surveill. 2022 Aug 5;8(8):e38551. doi: 10.2196/38551.
Participatory surveillance systems augment traditional surveillance systems through bidirectional community engagement. The digital platform evolution has enabled the expansion of participatory surveillance systems, globally, for the detection of health events impacting people, animals, plants, and the environment, in other words, across the entire One Health spectrum.
The aim of this landscape was to identify and provide descriptive information regarding system focus, geography, users, technology, information shared, and perceived impact of ongoing participatory surveillance systems across the One Health spectrum.
This landscape began with a systematic literature review to identify potential ongoing participatory surveillance systems. A survey was sent to collect standardized data from the contacts of systems identified in the literature review and through direct outreach to stakeholders, experts, and professional organizations. Descriptive analyses of survey and literature review results were conducted across the programs.
The landscape identified 60 ongoing single-sector and multisector participatory surveillance systems spanning five continents. Of these, 29 (48%) include data on human health, 26 (43%) include data on environmental health, and 24 (40%) include data on animal health. In total, 16 (27%) systems are multisectoral; of these, 9 (56%) collect animal and environmental health data; 3 (19%) collect human, animal, and environmental health data; 2 (13%) collect human and environmental health data; and 2 (13%) collect human and animal health data. Out of 60 systems, 31 (52%) are designed to cover a national scale, compared to those with a subnational (n=19, 32%) or multinational (n=10, 17%) focus. All systems use some form of digital technology. Email communication or websites (n=40, 67%) and smartphones (n=29, 48%) are the most common technologies used, with some using both. Systems have capabilities to download geolocation data (n=31, 52%), photographs (n=29, 48%), and videos (n=6, 10%), and can incorporate lab data or sample collection (n=15, 25%). In sharing information back with users, most use visualization, such as maps (n=43, 72%); training and educational materials (n=37, 62%); newsletters, blogs, and emails (n=34, 57%); and disease prevention information (n=32, 53%). Out of the 46 systems responding to the survey regarding perceived impacts of their systems, 36 (78%) noted "improved community knowledge and understanding" and 31 (67%) noted "earlier detection."
The landscape demonstrated the breadth of applicability of participatory surveillance around the world to collect data from community members and trained volunteers in order to inform the detection of events, from invasive plant pests to weekly influenza symptoms. Acknowledging the importance of bidirectionality of information, these systems simultaneously share findings back with the users. Such directly engaged community detection systems capture events early and provide opportunities to stop outbreaks quickly.
参与式监测系统通过双向社区参与来增强传统监测系统。数字平台的发展使参与式监测系统在全球范围内得以扩展,用于检测影响人类、动物、植物和环境的健康事件,换句话说,涵盖整个“同一健康”领域。
本研究旨在识别和提供正在进行的“同一健康”领域参与式监测系统的系统重点、地理位置、用户、技术、共享信息和感知影响方面的描述性信息。
本研究从系统的文献综述开始,以确定潜在的正在进行的参与式监测系统。通过向文献综述中确定的系统的联系人以及通过直接联系利益相关者、专家和专业组织发送调查,以收集标准化数据。对调查和文献综述结果进行了跨项目的描述性分析。
该研究确定了 60 个正在进行的单部门和多部门参与式监测系统,分布在五个大陆。其中,29 个(48%)包括人类健康数据,26 个(43%)包括环境健康数据,24 个(40%)包括动物健康数据。总共有 16 个(27%)系统是多部门的;其中,9 个(56%)收集动物和环境健康数据;3 个(19%)收集人类、动物和环境健康数据;2 个(13%)收集人类和环境健康数据;2 个(13%)收集人类和动物健康数据。在 60 个系统中,有 31 个(52%)旨在覆盖国家范围,而侧重于国家以下(n=19,32%)或跨国(n=10,17%)的系统较少。所有系统都使用某种形式的数字技术。电子邮件通信或网站(n=40,67%)和智能手机(n=29,48%)是最常用的技术,其中一些系统同时使用这两种技术。系统具有下载地理位置数据(n=31,52%)、照片(n=29,48%)和视频(n=6,10%)的功能,并可以合并实验室数据或样本采集(n=15,25%)。在将信息反馈给用户方面,大多数系统使用可视化,如地图(n=43,72%);培训和教育材料(n=37,62%);新闻通讯、博客和电子邮件(n=34,57%);和疾病预防信息(n=32,53%)。在回应调查的 46 个系统中,有 36 个(78%)表示“提高了社区的知识和理解”,31 个(67%)表示“更早地发现”。
该研究展示了参与式监测系统在全球范围内的广泛适用性,可从社区成员和经过培训的志愿者那里收集数据,以检测从入侵植物害虫到每周流感症状等事件。承认信息双向性的重要性,这些系统同时将发现结果反馈给用户。这种直接参与社区检测系统可以及早发现事件,并提供快速阻止疫情爆发的机会。