MAMMALNET – Citizen Science Data Collection from a One Health Perspective

Graham C. Smith, David Roy, P. Stephens, J. Casaer, Patrick C. M. H. F. Jansen, J. A. Blanco-Aguiar
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Abstract

The ambition of One Health (OH) is to focus on people, animals and the ecosystem equally (Tripartite and UNEP support OHHLEP’s definition of “One Health” (who.int)). This requires adequate data on wildlife. MAMMALNET is a European consortium set up to collect wildlife occurrence data, with the specific aim of improving our understanding and prediction of disease spread. MAMMALMET encourages citizens and professionals to report mammal sightings on an ad hoc basis (iMammalia app) or through surveys using remote camera traps (MammalWeb or Agouti). This combines data from different sources, increases our understanding of mammal distribution and aids in monitoring the spread of invasive species. MAMMALNET participants can see their records and maintain a list of species sightings. These data are vital to our understanding of the ecosystem and how this may change over time, providing background data for monitoring species. These data complement and contribute to reinforcing wildlife health reports, such as recording dead wild boar in outbreak areas of African Swine Fever. Such records are followed up for disease sampling to monitor the spread of disease. The data can also be used to predict the distribution and abundance of wild species, provide the denominator data for disease reports and predict the potential for disease spread and control. MAMMALNET is committed to open science since OH requires not only an interdisciplinary approach but practical collaboration and sharing of standardized data. These outputs can help predict the potential spread and control of zoonotic diseases, such as rabies, with benefits for human health. © The Authors 2023
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从一个健康角度收集公民科学数据
“同一个健康”的目标是平等地关注人、动物和生态系统(三方和环境规划署支持“同一个健康”的定义(世卫组织.int))。这需要充分的野生动物数据。MAMMALNET是一个欧洲联盟,旨在收集野生动物发生的数据,其具体目标是提高我们对疾病传播的理解和预测。MAMMALMET鼓励市民和专业人士在临时基础上报告哺乳动物的目击情况(iMammalia应用程序)或通过使用远程相机陷阱(MammalWeb或Agouti)进行调查。这结合了来自不同来源的数据,增加了我们对哺乳动物分布的了解,并有助于监测入侵物种的传播。MAMMALNET的参与者可以看到他们的记录,并保留一份物种目击清单。这些数据对我们了解生态系统及其如何随时间变化至关重要,为监测物种提供了背景数据。这些数据补充并有助于加强野生动物健康报告,例如在非洲猪瘟暴发地区记录死野猪。对这些记录进行跟踪,以便进行疾病抽样,以监测疾病的传播。这些数据还可用于预测野生物种的分布和丰度,为疾病报告提供分母数据,并预测疾病传播和控制的潜力。MAMMALNET致力于开放科学,因为OH不仅需要跨学科的方法,还需要实际的合作和标准化数据的共享。这些产出有助于预测狂犬病等人畜共患疾病的潜在传播和控制,有利于人类健康。©作者2023
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