协作监测:使用一组最少的关键数据参数进行“同一健康”参与式监测

Collaborative Surveillance: Using a Minimum Set of Key Data Parameters for One Health Participatory Surveillance.

作者信息

Smolinski Mark, Divi Nomita, Leal Neto Onicio

机构信息

Ending Pandemics Academy, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, United States.

出版信息

JMIR Public Health Surveill. 2025 Aug 8;11:e77448. doi: 10.2196/77448.

Abstract

Early detection of a newly emerging or reemerging infectious disease is crucial to minimize the impact of such a threat on lives and livelihoods. With three of four pathogens capable of causing epidemics or pandemics arising first in animals and spreading to humans as zoonosis, a One Health approach to early detection is paramount. One Health participatory surveillance, defined as the bidirectional receiving and transmitting of data for action through direct engagement of the target population, is an effective form of collaborative surveillance to enhance global health security. Participatory surveillance systems can vary greatly when developed for a specific purpose or to meet a particular community's needs. Different geographies, languages, customs, beliefs, and practices often influence the breadth and depth of the data collected within each system. Imagine, however, if each of these varied systems could "speak" to each other, sharing their aggregated, deidentified data to create a comprehensive, real-time view of planetary health. The key is to collect the same information from users in each system, or at least a minimum set of key data parameters, to generate One Health surveillance greater than that of any individual system. To enable this vision, we propose a minimum set of key data parameters for One Health participatory surveillance that could be collected in any system through self-reporting by the public. This real-time collaborative surveillance could be the earliest indicator of a human, animal, or environmental health threat as it does not require interaction with a health care facility or provider where most disease surveillance traditionally occurs. One Health participatory surveillance that can detect major syndromes of potential emerging or reemerging pathogens through self-reporting on human, animal, or environmental health is a practical, scalable solution to identify and respond to rapidly spreading contagions.

摘要

尽早发现新出现或再度出现的传染病对于将此类威胁对生命和生计的影响降至最低至关重要。四分之三能够引发流行病或大流行的病原体最初都出现在动物身上,并作为人畜共患病传播给人类,因此采用“同一健康”方法进行早期检测至关重要。“同一健康”参与式监测被定义为通过目标人群的直接参与双向接收和传输数据以采取行动,是加强全球卫生安全的一种有效协作监测形式。当为特定目的或满足特定社区的需求而开发时,参与式监测系统可能会有很大差异。不同的地理环境、语言、习俗、信仰和做法往往会影响每个系统内所收集数据的广度和深度。然而,想象一下,如果这些各不相同的系统能够相互“交流”,共享其汇总的、经过去标识化处理的数据,以创建一个全面的、实时的地球健康视图。关键在于从每个系统的用户那里收集相同的信息,或者至少收集一组最低限度的关键数据参数,以生成比任何单个系统都更强大的“同一健康”监测。为实现这一愿景,我们提出了一组用于“同一健康”参与式监测的最低限度关键数据参数,这些参数可以通过公众自我报告在任何系统中收集。这种实时协作监测可能是人类、动物或环境卫生威胁的最早指标,因为它不需要与传统上进行大多数疾病监测的医疗机构或医疗服务提供者进行互动。通过对人类、动物或环境卫生进行自我报告来检测潜在新出现或再度出现病原体的主要症状的“同一健康”参与式监测,是识别和应对迅速传播的传染病的一种切实可行、可扩展的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e56d/12374133/d86f08e30b1f/publichealth_v11i1e77448_fig1.jpg

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