Salje Henrik, Lessler Justin, Maljkovic Berry Irina, Melendrez Melanie C, Endy Timothy, Kalayanarooj Siripen, A-Nuegoonpipat Atchareeya, Chanama Sumalee, Sangkijporn Somchai, Klungthong Chonticha, Thaisomboonsuk Butsaya, Nisalak Ananda, Gibbons Robert V, Iamsirithaworn Sopon, Macareo Louis R, Yoon In-Kyu, Sangarsang Areerat, Jarman Richard G, Cummings Derek A T
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.
Science. 2017 Mar 24;355(6331):1302-1306. doi: 10.1126/science.aaj9384.
A fundamental mystery for dengue and other infectious pathogens is how observed patterns of cases relate to actual chains of individual transmission events. These pathways are intimately tied to the mechanisms by which strains interact and compete across spatial scales. Phylogeographic methods have been used to characterize pathogen dispersal at global and regional scales but have yielded few insights into the local spatiotemporal structure of endemic transmission. Using geolocated genotype (800 cases) and serotype (17,291 cases) data, we show that in Bangkok, Thailand, 60% of dengue cases living <200 meters apart come from the same transmission chain, as opposed to 3% of cases separated by 1 to 5 kilometers. At distances <200 meters from a case (encompassing an average of 1300 people in Bangkok), the effective number of chains is 1.7. This number rises by a factor of 7 for each 10-fold increase in the population of the "enclosed" region. This trend is observed regardless of whether population density or area increases, though increases in density over 7000 people per square kilometer do not lead to additional chains. Within Thailand these chains quickly mix, and by the next dengue season viral lineages are no longer highly spatially structured within the country. In contrast, viral flow to neighboring countries is limited. These findings are consistent with local, density-dependent transmission and implicate densely populated communities as key sources of viral diversity, with home location the focal point of transmission. These findings have important implications for targeted vector control and active surveillance.
登革热和其他传染性病原体的一个基本谜团是，观察到的病例模式与个体传播事件的实际链条之间的关系。这些传播途径与毒株在不同空间尺度上相互作用和竞争的机制密切相关。系统发育地理学方法已被用于描述病原体在全球和区域尺度上的传播，但对于地方性传播的局部时空结构却鲜有深入见解。利用地理定位的基因型（800例）和血清型（17291例）数据，我们发现，在泰国曼谷，相距不到200米的登革热病例中有60%来自同一传播链，而相距1至5公里的病例中这一比例为3%。在距离某病例不到200米的范围内（在曼谷平均涵盖1300人），传播链的有效数量为1.7。“封闭”区域的人口每增加10倍，这个数字就会增加7倍。无论人口密度或面积增加与否，这一趋势都能观察到，不过每平方公里超过7000人的密度增加并不会导致额外的传播链。在泰国境内，这些传播链很快就会混合，到下一个登革热季节，病毒谱系在该国境内就不再具有高度的空间结构。相比之下，病毒向邻国的传播是有限的。这些发现与局部的、密度依赖性传播一致，并表明人口密集的社区是病毒多样性的关键来源，家庭住址是传播的焦点。这些发现对有针对性的病媒控制和主动监测具有重要意义。
