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1. Data-driven predictions of potential Leishmania vectors in the Americas

   https://doi.org/10.1371/journal.pntd.0010749  

   Vadmal, Gowri M.; Glidden, Caroline K.; Han, Barbara A.; Carvalho, Bruno M.; Castellanos, Adrian A.; Mordecai, Erin A. (February 2023, PLOS Neglected Tropical Diseases)

   McDowell, Mary Ann (Ed.)

   The incidence of vector-borne diseases is rising as deforestation, climate change, and globalization bring humans in contact with arthropods that can transmit pathogens. In particular, incidence of American Cutaneous Leishmaniasis (ACL), a disease caused by parasites transmitted by sandflies, is increasing as previously intact habitats are cleared for agriculture and urban areas, potentially bringing people into contact with vectors and reservoir hosts. Previous evidence has identified dozens of sandfly species that have been infected with and/or transmit Leishmania parasites. However, there is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. Here, we apply machine learning models (boosted regression trees) to leverage biological and geographical traits of known sandfly vectors to predict potential vectors. Additionally, we generate trait profiles of confirmed vectors and identify important factors in transmission. Our model performed well with an average out of sample accuracy of 86%. The models predict that synanthropic sandflies living in areas with greater canopy height, less human modification, and within an optimal range of rainfall are more likely to be Leishmania vectors. We also observed that generalist sandflies that are able to inhabit many different ecoregions are more likely to transmit the parasites. Our results suggest that Psychodopygus amazonensis and Nyssomia antunesi are unidentified potential vectors, and should be the focus of sampling and research efforts. Overall, we found that our machine learning approach provides valuable information for Leishmania surveillance and management in an otherwise complex and data sparse system. 

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2. Estimating pathogen‐spillover risk using host–ectoparasite interactions

   https://doi.org/10.1002/ece3.11509  

   Brennan, Reilly_N; Paulson, Sally_L; Escobar, Luis_E (June 2024, Ecology and Evolution)

   Abstract Pathogen spillover corresponds to the transmission of a pathogen or parasite from an original host species to a novel host species, preluding disease emergence. Understanding the interacting factors that lead to pathogen transmission in a zoonotic cycle could help identify novel hosts of pathogens and the patterns that lead to disease emergence. We hypothesize that ecological and biogeographic factors drive host encounters, infection susceptibility, and cross‐species spillover transmission. Using a rodent–ectoparasite system in the Neotropics, with shared ectoparasite associations as a proxy for ecological interaction between rodent species, we assessed relationships between rodents using geographic range, phylogenetic relatedness, and ectoparasite associations to determine the roles of generalist and specialist hosts in the transmission cycle of hantavirus. A total of 50 rodent species were ranked on their centrality in a network model based on ectoparasites sharing. Geographic proximity and phylogenetic relatedness were predictors for rodents to share ectoparasite species and were associated with shorter network path distance between rodents through shared ectoparasites. The rodent–ectoparasite network model successfully predicted independent data of seven known hantavirus hosts. The model predicted five novel rodent species as potential, unrecognized hantavirus hosts in South America. Findings suggest that ectoparasite data, geographic range, and phylogenetic relatedness of wildlife species could help predict novel hosts susceptible to infection and possible transmission of zoonotic pathogens. Hantavirus is a high‐consequence zoonotic pathogen with documented animal‐to‐animal, animal‐to‐human, and human‐to‐human transmission. Predictions of new rodent hosts can guide active epidemiological surveillance in specific areas and wildlife species to mitigate hantavirus spillover transmission risk from rodents to humans. This study supports the idea that ectoparasite relationships among rodents are a proxy of host species interactions and can inform transmission cycles of diverse pathogens circulating in wildlife disease systems, including wildlife viruses with epidemic potential, such as hantavirus. 

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3. Physiology and ecology combine to determine host and vector importance for Ross River virus

   https://doi.org/10.7554/eLife.67018  

   Kain, Morgan P; Skinner, Eloise B; van den Hurk, Andrew F; McCallum, Hamish; Mordecai, Erin A (August 2021, eLife)

   Identifying the key vector and host species that drive the transmission of zoonotic pathogens is notoriously difficult but critical for disease control. We present a nested approach for quantifying the importance of host and vectors that integrates species’ physiological competence with their ecological traits. We apply this framework to a medically important arbovirus, Ross River virus (RRV), in Brisbane, Australia. We find that vertebrate hosts with high physiological competence are not the most important for community transmission; interactions between hosts and vectors largely underpin the importance of host species. For vectors, physiological competence is highly important. Our results identify primary and secondary vectors of RRV and suggest two potential transmission cycles in Brisbane: an enzootic cycle involving birds and an urban cycle involving humans. The framework accounts for uncertainty from each fitted statistical model in estimates of species’ contributions to transmission and has has direct application to other zoonotic pathogens. 

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4. Mixed-species assemblages and disease: the importance of differential vector and parasite attraction in transmission dynamics

   https://doi.org/10.1098/rstb.2022.0109  

   Trillo, Paula A.; Bernal, Ximena E.; Hall, Richard J. (June 2023, Philosophical Transactions of the Royal Society B: Biological Sciences)

   Individuals from multiple species often aggregate at resources, group to facilitate defense and foraging, or are brought together by human activity. While it is well-documented that host-seeking disease vectors and parasites show biases in their responses to cues from different hosts, the influence of mixed-species assemblages on disease dynamics has received limited attention. Here, we synthesize relevant research in host-specific vector and parasite bias. To better understand how vector and parasite biases influence infection, we provide a conceptual framework describing cue-oriented vector and parasite host-seeking behaviour as a two-stage process that encompasses attraction of these enemies to the assemblage and their choice of hosts once at the assemblage. We illustrate this framework, developing a case study of mixed-species frog assemblages, where frog-biting midges transmit trypanosomes. Finally, we present a mathematical model that investigates how host species composition and asymmetries in vector attraction modulate transmission dynamics in mixed-species assemblages. We argue that differential attraction of vectors by hosts can have important consequences for disease transmission within mixed-species assemblages, with implications for wildlife conservation and zoonotic disease. 

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5. Human footprint is associated with shifts in the assemblages of major vector-borne diseases

   https://doi.org/10.1038/s41893-023-01080-1  

   Skinner, Eloise B.; Glidden, Caroline K.; MacDonald, Andrew J.; Mordecai, Erin A. (April 2023, Nature Sustainability)

   Abstract Predicting how increasing intensity of human–environment interactions affects pathogen transmission is essential to anticipate changing disease risks and identify appropriate mitigation strategies. Vector-borne diseases (VBDs) are highly responsive to environmental changes, but such responses are notoriously difficult to isolate because pathogen transmission depends on a suite of ecological and social responses in vectors and hosts that may differ across species. Here we use the emerging tools of cumulative pressure mapping and machine learning to better understand how the occurrence of six medically important VBDs, differing in ecology from sylvatic to urban, respond to multidimensional effects of human pressure. We find that not only is human footprint—an index of human pressure, incorporating built environments, energy and transportation infrastructure, agricultural lands and human population density—an important predictor of VBD occurrence, but there are clear thresholds governing the occurrence of different VBDs. Across a spectrum of human pressure, diseases associated with lower human pressure, including malaria, cutaneous leishmaniasis and visceral leishmaniasis, give way to diseases associated with high human pressure, such as dengue, chikungunya and Zika. These heterogeneous responses of VBDs to human pressure highlight thresholds of land-use transitions that may lead to abrupt shifts in infectious disease burdens and public health needs. 

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