Integrating participatory approaches and traditional models to strengthen One Health responses to zoonotic diseases in India's changing environments

在动物和人类之间传播的人畜共患病原体，如利什曼病病毒、尼帕病毒和基孔肯雅病毒，造成了全球60%的新发传染病事件，对热带资源贫乏地区的人们造成了不成比例的影响。除了损害人类和动物健康外，人畜共患疾病还对生计和经济有害，例如，阻止小农通过增加牲畜产量摆脱贫困。随着环境和社会的迅速变化，人畜共患疾病的影响正在全球范围内增加和转移。由于我们对这些病原体如何在野生动物、牲畜（以及可能的昆虫和蜱虫媒介）和人类之间传播，以及人们在使用景观时如何暴露于这些病原体缺乏了解，因此很难理解这些变化的影响，也很难在许多地方制定有效的疾病控制策略。有效管理和了解人畜共患病需要来自动物卫生、人类健康、农业和环境部门的政策制定者和管理者的合作，从国家和国际决策者到地区管理者，他们都与疾病系统相互作用，正如全球"一个健康“倡议所倡导的那样，该倡议认识到“人类健康的相互关联性，野生动物和家畜健康与环境”。监测、决策和政策需要更好地跨部门整合，导致信息学支持管理决策的研究，如地图和预测，必须参考当地疾病管理人员和决策者的知识、优先事项和需求。此外，在政策框架和监测系统中需要更好地反映影响贫困社区的被忽视的地方病病原体。该项目将印度作为地方病和新出现的人畜共患病和小农户畜牧业社区的全球关键热点，并将公共和动物卫生、生态学、流行病学和社会科学方面的专家与利益攸关方网络聚集在一起，旨在减少健康、通过更好地了解监测、知识、研究和跨部门模式之间的联系以及改进支持干预措施的现有信息系统，减少人畜共患疾病对福利和生计的影响。支持这些改进的研究将包括：（1）查明每个部门的主要利益攸关方、其优先事项和对决策支持工具的需求（2）查明监测数据、知识和技能的存在情况，并查明可以跨部门利用这些数据、知识和技能，以更好地了解和管理人畜共患病（3）了解可能导致疾病影响增加的各种潜在社会生态驱动因素（4）参照模型内的环境数据解释疾病影响的地理模式，以便为个案研究疾病和环境理清诱发疾病的社会、气候和景观因素，（5）建设研究能力，数据分析和跨部门合作，以支持印度未来的“一个健康”方法。支持工具将帮助疾病管理人员更好地针对风险最大的社区开展疫苗接种和宣传工作，农业和环境部门的管理人员了解疾病对这些社区的影响如何与环境变化的其他负面影响同时发生。与各部门利益攸关方共同开发关于人畜共患病的研究和决策支持工具的项目平台和方法，考虑到他们的需求和基本的生态和社会进程，将在科学、政策和从业人员方面建立重要的能力，以应对这些新出现的和地方性的全球威胁。

Zoonotic pathogens, that circulate between animals and humans, like the Leishmaniases, and Nipah and Chikungunya viruses, cause 60% of emerging infectious disease events worldwide and disproportionately affect people in tropical, resource-poor areas. Aside from impairing human and animal health, zoonotic diseases are detrimental to livelihoods and economies, for example, preventing small-holder farmers being lifted out of poverty by increasing livestock production. The impacts of zoonotic diseases are increasing and shifting globally, as the environment and societies undergo rapid change. Our lack of knowledge on how these pathogens circulate between wildlife, livestock (as well as possible insect and tick vectors) and people, and how people are exposed as they use the landscape makes it difficult to understand these changes in terms of impact, and to develop effective disease control strategies in many local settings. Effective management and understanding of zoonotic diseases requires cooperation of policy-makers and managers from across the animal health, human health, agriculture and environment sectors, from national and international decision-makers down to district managers that all interact with the disease system, as advocated by the global One Health initiative, that recognises the "interconnectedness of human health, wildlife and domestic animal health and the environment". Surveillance, decisions and policy need to be better integrated across sectors, and research that leads to informatics to support management decisions, like maps and forecasts must be informed by the knowledge, priorities and needs of local disease managers and policy makers. More-over, neglected endemic pathogens that affect poor communities need to be better represented in policy frameworks and surveillance systems.Focussing in India as a key global hotspot for endemic and emerging zoonotic diseases and small-holder livestock communities, and bringing together a network of stakeholders with experts in public and animal health, ecology, epidemiology and social science, this project aims to reduce health, welfare and livelihood impacts of zoonotic diseases by better understanding links between surveillance, knowledge, research and models across sectors and improving current information systems that support intervention. The research underpinning these improvements will include:(1) Mapping of key stakeholders in each sector, their priorities and needs for decision-support tools (2) Identifying where surveillance data, knowledge and skills exist and could be leveraged across sectors to better understand and manage zoonotic diseases(3) Understanding the full range of potential socio-ecological drivers that might cause disease impacts to increase (4) Interpreting geographical patterns in disease impacts in relation to environmental data within models to disentangle social, climate and landscape factors precipitating disease for case-study diseases and settings and, in turn, predicting outcomes of intervention(5) Building capacity in research, data analysis and cross-sectoral collaboration to underpin future One Health approaches in India.Improved decision-support tools will help disease managers to better target vaccination and communication efforts towards the communities that are most at risk and help managers in agriculture and environmental sectors to understand how, for these communities, disease impacts may coincide with other negative impacts of environmental change. 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 these emerging and endemic global threats.