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Abstract：
Given the significant impact of mosquito-borne flaviviruses (MBFVs) on both human and animal health, predicting their dynamics and understanding their transmission cycle is of the utmost importance. Usually, predictions about the distribution of priority pathogens, such as Dengue, Yellow fever, West Nile Virus and St. Louis encephalitis, relate abiotic elements to simple biotic components, such as a single causal agent. Furthermore, focusing on single pathogens neglects the possibility of interactions and the existence of common elements in the transmission cycles of multiple pathogens. A necessary, but not sufficient, condition that a mosquito be a vector of a MBFV is that it co-occurs with hosts of the pathogen. We therefore use a recently developed modeling framework, based on co-occurrence data, to infer potential biotic interactions between those mosquito and mammal species which have previously been identified as vectors or confirmed positives of at least one of the considered MBFVs. We thus create models for predicting the relative importance of mosquito species as potential vectors for each pathogen, and also for all pathogens together, using the known vectors to validate the models. We infer that various mosquito species are likely to be significant vectors, even though they have not currently been identified as such, and are likely to harbor multiple pathogens, again validating the predictions with known results. Besides the above \"niche-based\" viewpoint we also consider an assemblage-based analysis, wherein we use a community-identification algorithm to identify those mosquito and/or mammal species that form assemblages by dint of their significant degree of co-occurrence. The most cohesive assemblage includes important primary vectors, such as A. aegypti, A. albopictus, C. quinquefasciatus, C. pipiens and mammals with abundant populations that are well-adapted to human environments, such as the white-tailed deer (Odocoileus virginianus), peccary (Tayassu pecari), opossum (Didelphis marsupialis) and bats (Artibeus lituratus and Sturnira lilium). Our results suggest that this assemblage has an important role in the transmission dynamics of this viral group viewed as a complex multi-pathogen-vector-host system. By including biotic risk factors our approach also modifies the geographical risk profiles of the spatial distribution of MBFVs in Mexico relative to a consideration of only abiotic niche variables.
摘要：
鉴于蚊媒黄病毒（MBFV）对人类和动物健康的重大影响，预测它们的动态和理解它们的传播周期是至关重要的。通常,关于优先病原体分布的预测，比如登革热,黄热病,西尼罗河病毒和圣路易斯脑炎，将非生物元素与简单的生物成分联系起来，比如单一的因果代理。此外，关注单一病原体忽略了多种病原体传播周期中相互作用的可能性和共同元素的存在。一个必要的,但还不够,蚊子是MBFV的媒介的条件是它与病原体的宿主共同发生。因此，我们使用最近开发的建模框架，基于共现数据，推断那些蚊子和哺乳动物物种之间的潜在生物相互作用，这些物种先前已被鉴定为载体或已确认至少一种所考虑的MBFV的阳性。因此，我们创建了模型来预测蚊子作为每种病原体的潜在载体的相对重要性，以及所有病原体，使用已知向量来验证模型。我们推断各种蚊子可能是重要的媒介，尽管它们目前还没有被识别出来，并可能携带多种病原体，再次用已知结果验证预测。除了上述“基于利基”的观点，我们还考虑了基于组合的分析，其中我们使用社区识别算法来识别那些蚊子和/或哺乳动物物种，这些物种通过它们的显著程度的共同发生来形成集合。最具凝聚力的组合包括重要的初级载体，比如埃及伊蚊，A.白纹,C.quinquefasciatus,C.pipiens和具有丰富种群的哺乳动物，非常适合人类环境，例如白尾鹿（Odocoileusvirginianus），野猪（Tayassupecari），负鼠（Didelphismarsupialis）和蝙蝠（Artibeuslituratus和Sturiralilium）。我们的结果表明，这种组合在该病毒组的传播动力学中具有重要作用，该病毒组被视为复杂的多病原体载体宿主系统。通过包括生物风险因素，我们的方法还相对于仅考虑非生物生态位变量，修改了墨西哥MBFV空间分布的地理风险概况。
