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1. Phylogenetic and biogeographical traits predict unrecognized hosts of zoonotic leishmaniasis

   https://doi.org/10.1371/journal.pntd.0010879  

   Glidden, Caroline K.; Murran, Aisling Roya; Silva, Rafaella Albuquerque; Castellanos, Adrian A.; Han, Barbara A.; Mordecai, Erin A. (May 2023, PLOS Neglected Tropical Diseases)

   Ramos, Alberto Novaes (Ed.)

   The spatio-temporal distribution of leishmaniasis, a parasitic vector-borne zoonotic disease, is significantly impacted by land-use change and climate warming in the Americas. However, predicting and containing outbreaks is challenging as the zoonotic Leishmania system is highly complex: leishmaniasis (visceral, cutaneous and muco-cutaneous) in humans is caused by up to 14 different Leishmania species, and the parasite is transmitted by dozens of sandfly species and is known to infect almost twice as many wildlife species. Despite the already broad known host range, new hosts are discovered almost annually and Leishmania transmission to humans occurs in absence of a known host. As such, the full range of Leishmania hosts is undetermined, inhibiting the use of ecological interventions to limit pathogen spread and the ability to accurately predict the impact of global change on disease risk. Here, we employed a machine learning approach to generate trait profiles of known zoonotic Leishmania wildlife hosts (mammals that are naturally exposed and susceptible to infection) and used trait-profiles of known hosts to identify potentially unrecognized hosts. We found that biogeography, phylogenetic distance, and study effort best predicted Leishmania host status. Traits associated with global change, such as agricultural land-cover, urban land-cover, and climate, were among the top predictors of host status. Most notably, our analysis suggested that zoonotic Leishmania hosts are significantly undersampled, as our model predicted just as many unrecognized hosts as unknown hosts. Overall, our analysis facilitates targeted surveillance strategies and improved understanding of the impact of environmental change on local transmission cycles. 

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2. Effects of predation risk on parasite–host interactions and wildlife diseases

   https://doi.org/10.1002/ecy.4315  

   Thieltges, David W; Johnson, Pieter_T J; van_Leeuwen, Anieke; Koprivnikar, Janet (June 2024, Ecology)

   Abstract Landscapes of fear can determine the dynamics of entire ecosystems. In response to perceived predation risk, prey can show physiological, behavioral, or morphological trait changes to avoid predation. This in turn can indirectly affect other species by modifying species interactions (e.g., altered feeding), with knock‐on effects, such as trophic cascades, on the wider ecosystem. While such indirect effects stemming from the fear of predation have received extensive attention for herbivore–plant and predator–prey interactions, much less is known about how they alter parasite–host interactions and wildlife diseases. In this synthesis, we present a conceptual framework for how predation risk—as perceived by organisms that serve as hosts—can affect parasite–host interactions, with implications for infectious disease dynamics. By basing our approach on recent conceptual advances with respect to predation risk effects, we aim to expand this general framework to include parasite–host interactions and diseases. We further identify pathways through which parasite–host interactions can be affected, for example, through altered parasite avoidance behavior or tolerance of hosts to infections, and discuss the wider relevance of predation risk for parasite and host populations, including heuristic projections to population‐level dynamics. Finally, we highlight the current unknowns, specifically the quantitative links from individual‐level processes to population dynamics and community structure, and emphasize approaches to address these knowledge gaps. 

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3. Interventions can shift the thermal optimum for parasitic disease transmission

   https://doi.org/10.1073/pnas.2017537118  

   Nguyen, Karena H.; Boersch-Supan, Philipp H.; Hartman, Rachel B.; Mendiola, Sandra Y.; Harwood, Valerie J.; Civitello, David J.; Rohr, Jason R. (March 2021, Proceedings of the National Academy of Sciences)

   null (Ed.)

   Temperature constrains the transmission of many pathogens. Interventions that target temperature-sensitive life stages, such as vector control measures that kill intermediate hosts, could shift the thermal optimum of transmission, thereby altering seasonal disease dynamics and rendering interventions less effective at certain times of the year and with global climate change. To test these hypotheses, we integrated an epidemiological model of schistosomiasis with empirically determined temperature-dependent traits of the human parasite Schistosoma mansoni and its intermediate snail host ( Biomphalaria spp.). We show that transmission risk peaks at 21.7 °C ( T opt ), and simulated interventions targeting snails and free-living parasite larvae increased T opt by up to 1.3 °C because intervention-related mortality overrode thermal constraints on transmission. This T opt shift suggests that snail control is more effective at lower temperatures, and global climate change will increase schistosomiasis risk in regions that move closer to T opt . Considering regional transmission phenologies and timing of interventions when local conditions approach T opt will maximize human health outcomes. 

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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. 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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