Optimising forest benefits whilst minimising impacts of emerging zoonotic diseases: co-developing an interdisciplinary tool for forests in India

中低收入国家的大量贫困人口依靠健康的生态系统维持生计和粮食安全。在印度，大约有3亿人依赖森林为生，这些森林由于人类定居、农业扩张和过度放牧而严重退化。当他们从退化的森林中获得食物、燃料、饲料和其他产品时，这些人就有可能接触到在野生动物中自然传播的有害病原体。森林退化可以改变不同野生动物和节肢动物媒介群落之间的生态平衡，但这些生态变化与景观中人们的优先事项和行为相互作用，以确定暴露发生的时间和地点。在疟疾和利什曼病等LMICs中，人畜共患疾病(在动物和人之间传播的疾病)病例的激增与砍伐森林、重新造林或特定的森林活动有关。关于生态学和社会学在支撑这些变化中的作用的知识差距阻碍了智能疾病控制战略的发展，这些战略使人们能够从森林中受益，但将接触疾病的机会降至最低。这种战略需要来自动物健康、人类健康和林业部门的政策制定者和森林使用者的合作，从国家和国际决策者到村庄社区，所有这些都与疾病系统相互作用。通过将这些利益攸关方与公共和动物健康、生态学、流行病学和社会科学专家聚集在一个网络中，该项目旨在开发一个新的跨学科框架和决策支持工具，以减少人畜共患病对小岛屿发展中国家依靠森林为生的人的健康、福利和生计的影响。它将最初针对Kyasanur森林疾病(KFD)开发，KFD是印度森林种群的一种致命出血性疾病，在扁虱、啮齿动物和灵长类动物之间自然循环。支持该工具的研究将包括：1.绘制每个部门的关键利益攸关方、他们的知识、对决策支持工具的需求以及它们如何受到疾病系统的影响或对疾病系统的影响。深入实地观察：(I)不同森林群体，如传统的狩猎采集部落和农民，对疾病风险的优先事项、行为和认知是如何变化的；(Ii)野生动物寄主和壁虱媒介的数量和种类以及随之而来的KFD危险是如何沿着森林景观梯度从封闭到零散到疏林变化的。将人类KFD病例中的历史地理模式与模型中的环境模式相匹配，以理清印度受影响地区的社会、气候和森林景观驱动因素。结合这一知识的地理决策支持工具将绘制出疾病风险在不同森林地貌、不同活动和不同森林用户群体之间的变化情况，以及在疾病管理、可获得性和获得保健和药物方面的其他限制。该项目将通过提高森林使用者，特别是收获非木材林产品的部落群体和放牧牲畜的农民对疾病风险的认识，减少KFD对健康、福利和生计的影响。这些群体将进一步受益于以下方面的具体指导：(1)关键的森林位置和栖息地、季节和活动，以及(2)为什么以及如何获得药物和其他保护措施。决策支持工具将帮助疾病管理人员更好地针对风险最大的森林社区开展疫苗接种和风险沟通工作，并将为森林土地利用规划提供信息。与各部门的利益攸关方共同开发人畜共患疾病研究和决策支持工具的项目平台和方法，考虑到他们的需要以及潜在的生态和社会进程，将在科学、政策和从业人员方面建立应对新出现的全球威胁的重大能力。

Vast numbers of poor people in Low and Middle Income Countries (LMICs) depend on healthy ecosystems for their livelihoods and food security. In India, around 300 million people depend on forests that are badly degraded by human settlement, agricultural expansion, and over-grazing. When they access food, fuel, fodder and other products from degraded forests, these people risk exposure to harmful pathogens that circulate naturally in wildlife. The ecological balance between diverse wildlife and arthropod vector communities can be altered by forest degradation, but these ecological changes interact with the priorities and behaviour of people in the landscape to determine when and where exposure occurs. Upsurges in human cases of zoonotic diseases (diseases that circulate between animals and humans) in LMICs, like malaria and Leishmaniases, have been linked to deforestation, reforestation or particular forest activities. Knowledge gaps on the role of ecology and sociology in underpinning these changes prevents development of intelligent disease control strategies that allow people to benefit from forests but minimise exposure to disease. Such strategies require cooperation of policy-makers and forest users from across the animal health, human health and forestry sectors, from national and international decision-makers down to village communities, that all interact with the disease system.By bringing such stakeholders together in a network, along with experts in public and animal health, ecology, epidemiology and social science, this project aims to develop a new inter-disciplinary framework and decision-support tool to reduce health, welfare and livelihood impacts of zoonotic diseases on people that depend on forests in LMICs. It will be developed initially for Kyasanur Forest Disease (KFD), a fatal haemorrhagic disease of forest populations in India that cycles naturally amongst ticks, rodents and primates. The research underpinning the tool will include:1. Mapping of key stakeholders in each sector, their knowledge, needs for decision-support tools and how they are impacted by or impact upon the disease system.2. Intensive field observation of (i) how the priorities, behaviour and perceptions of disease risk of different forest groups, like traditional hunter-gatherer tribes and farmers, change; (ii) how the numbers and species of wildlife hosts and tick vectors, and the consequent hazard of KFD changes along forest landscape gradients from closed through fragmented to open forest.3. Matching of historical geographical patterns in human cases of KFD with environmental patterns within models to disentangle social, climate and forest landscape drivers across the affected region in India. A geographical decision support tool, integrating this knowledge, will map how disease risk varies across forest landscapes, from which activities and by which forest user groups, with other constraints on disease management, availability and access to health care and medicines. The project will reduce impacts of KFD on health, welfare and livelihoods by increasing awareness of disease risk in forest users, especially tribal groups that harvest non-timber forest products and farmers that graze livestock. These groups will further benefit from specific guidance on (i) the key forest locations and habitats, seasons and activities, and (ii) why and how to access medicine and other protective measures. The decision-support tool will help disease managers to better target vaccination and risk communication efforts towards the forest communities that are most at risk and will inform planning of land use in forests. The project platform and approach of co-developing research and decision support tools on zoonotic diseases with stakeholders across sectors, accounting for their needs and underlying ecological and social processes, will build significant capacity in science, policy and practitioners to respond to emerging global threats.