Murray Kris A, Preston Nicholas, Allen Toph, Zambrana-Torrelio Carlos, Hosseini Parviez R, Daszak Peter
Grantham Institute-Climate Change and the Environment, Faculty of Natural Sciences, Imperial College London, London SW7 2AZ, United Kingdom; School of Public Health, Faculty of Medicine, Imperial College London, London W2 1PG, United Kingdom;
Children's Hospital Informatics Program, Boston Children's Hospital, Boston, MA 02215;
Proc Natl Acad Sci U S A. 2015 Oct 13;112(41):12746-51. doi: 10.1073/pnas.1507442112. Epub 2015 Sep 28.
The distributions of most infectious agents causing disease in humans are poorly resolved or unknown. However, poorly known and unknown agents contribute to the global burden of disease and will underlie many future disease risks. Existing patterns of infectious disease co-occurrence could thus play a critical role in resolving or anticipating current and future disease threats. We analyzed the global occurrence patterns of 187 human infectious diseases across 225 countries and seven epidemiological classes (human-specific, zoonotic, vector-borne, non-vector-borne, bacterial, viral, and parasitic) to show that human infectious diseases exhibit distinct spatial grouping patterns at a global scale. We demonstrate, using outbreaks of Ebola virus as a test case, that this spatial structuring provides an untapped source of prior information that could be used to tighten the focus of a range of health-related research and management activities at early stages or in data-poor settings, including disease surveillance, outbreak responses, or optimizing pathogen discovery. In examining the correlates of these spatial patterns, among a range of geographic, epidemiological, environmental, and social factors, mammalian biodiversity was the strongest predictor of infectious disease co-occurrence overall and for six of the seven disease classes examined, giving rise to a striking congruence between global pathogeographic and "Wallacean" zoogeographic patterns. This clear biogeographic signal suggests that infectious disease assemblages remain fundamentally constrained in their distributions by ecological barriers to dispersal or establishment, despite the homogenizing forces of globalization. Pathogeography thus provides an overarching context in which other factors promoting infectious disease emergence and spread are set.
大多数导致人类疾病的传染病原体的分布情况尚未得到充分解析或仍不为人知。然而，鲜为人知和未知的病原体导致了全球疾病负担，并且将成为未来许多疾病风险的根源。因此，现有的传染病共发模式可能在解析或预测当前及未来的疾病威胁方面发挥关键作用。我们分析了187种人类传染病在225个国家的全球发生模式，以及七种流行病学类别（人类特异性、人畜共患、媒介传播、非媒介传播、细菌、病毒和寄生虫），结果表明人类传染病在全球范围内呈现出明显的空间分组模式。我们以埃博拉病毒疫情为例进行论证，表明这种空间结构提供了一个尚未开发的先验信息来源，可用于在早期阶段或数据匮乏的环境中，收紧一系列与健康相关的研究和管理活动的重点，包括疾病监测、疫情应对或优化病原体发现。在研究这些空间模式的相关因素时，在一系列地理、流行病学、环境和社会因素中，哺乳动物生物多样性是总体传染病共发以及所研究的七个疾病类别中的六个类别的最强预测指标，这使得全球病原地理模式与“华莱士式”动物地理模式之间出现了惊人的一致性。这种清晰的生物地理信号表明，尽管存在全球化的同质化力量，但传染病组合在其分布上仍然从根本上受到扩散或定殖的生态障碍的限制。因此，病原地理学提供了一个总体背景，在这个背景下，其他促进传染病出现和传播的因素得以确立。
