Collaborative Research: Socio-economic and environmental drivers of emerging infectious diseases

新出现的传染病(如艾滋病、SARS、埃博拉)在全球范围内威胁着人类健康，但这些毁灭性疾病涌现到人类人口中的过程尚不清楚。人口、社会经济和人为的土地利用变化导致了森林砍伐、城市化、农村人口变化、贸易和旅行全球化、气候变化和生物多样性丧失的全球格局。尽管从未量化，但这些变化及其结果被假设与这些疾病的出现有关。在这项提案中，我们概述了一个多学科研究计划，以首次分析环境以及人类和社会动态在疾病出现中所起的作用，并开发一个预测模型，该模型将确定未来疾病出现的“热点”。我们将首先分析全球范围内疾病出现的时空格局。例如，我们问，在过去几十年里，出现在人类人口中的传染病数量是否有所增加？世界上某一特定地区发生的突发事件是否比其他地区更多？其次，我们是否会量化新发传染病的人口、社会经济、环境和生态驱动因素？例如，全球人口密度、贫困、港口通达性、农业、宿主生物多样性、降水和温度的变化对疾病出现的可能性有什么作用？第三，我们将使用量化的驱动因素建立一个模型，预测未来传染病可能在哪里出现，从而更好地了解全球人类健康面临的风险。该项目将总部设在哥伦比亚大学的两个国际公认的组织联系起来：保护医学联合会(CCM)和国际地球科学信息网络中心(CIESIN)，前者研究新出现的传染病的生态学，后者专门测试人口、社会经济和环境变化方面的全球趋势和模式。

Emerging infectious diseases (e.g. AIDS, SARS, Ebola) threaten human health on a global scale but the processes underlying these devastating disease emergences into human populations are not well understood. Demographic, socio-economic and anthropogenic land use change have led to a global pattern of deforestation, urbanization, rural population change, globalization of trade and travel, climate change and biodiversity loss. Although never quantified, these changes and their outcomes have been hypothesized to be linked to these disease emergences. In this proposal, we outline a multidisciplinary program of research to analyze for the first time the role that the environment and human and social dynamics play in disease emergence and to develop a predictive model that will identify 'hotspots' for future disease emergence. We will firstly analyze the spatial and temporal pattern of disease emergence on a global scale. For example, we ask whether the number of infectious diseases emerging into human populations has increased over the last few decades? Have more emergences occurred in one particular area of the world than others? Secondly, will we quantify the demographic, socio-economic, environmental and ecological drivers of emerging infectious disease? For example, what roles do changes in global human population density, poverty, accessibility to ports, agriculture, host biodiversity, precipitation and temperature have on the likelihood of a disease emerging? Thirdly, we will use the quantified drivers to build a model to predict where future emergences of infectious diseases might occur, leading to a better understanding of the risks to global human health. This project links two internationally-recognized groups based at Columbia University: the Consortium for Conservation Medicine (CCM), which studies the ecology of emerging infectious diseases, and the Center for International Earth Science Information Network (CIESIN), which specializes in testing global trends and patterns in demography, socio-economic and environmental changes.