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1. Trends and Opportunities in Tick-Borne Disease Geography

   https://doi.org/10.1093/jme/tjab086  

   Lippi, Catherine A; Ryan, Sadie J; White, Alexis L; Gaff, Holly D; Carlson, Colin J (May 2021, Journal of Medical Entomology)

   Rich, Stephen (Ed.)

   Abstract Tick-borne diseases are a growing problem in many parts of the world, and their surveillance and control touch on challenging issues in medical entomology, agricultural health, veterinary medicine, and biosecurity. Spatial approaches can be used to synthesize the data generated by integrative One Health surveillance systems, and help stakeholders, managers, and medical geographers understand the current and future distribution of risk. Here, we performed a systematic review of over 8,000 studies and identified a total of 303 scientific publications that map tick-borne diseases using data on vectors, pathogens, and hosts (including wildlife, livestock, and human cases). We find that the field is growing rapidly, with the major Ixodes-borne diseases (Lyme disease and tick-borne encephalitis in particular) giving way to monitoring efforts that encompass a broader range of threats. We find a tremendous diversity of methods used to map tick-borne disease, but also find major gaps: data on the enzootic cycle of tick-borne pathogens is severely underutilized, and mapping efforts are mostly limited to Europe and North America. We suggest that future work can readily apply available methods to track the distributions of tick-borne diseases in Africa and Asia, following a One Health approach that combines medical and veterinary surveillance for maximum impact. 

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2. Estimating the distribution of Oryzomys palustris , a potential key host in expanding rickettsial tick‐borne disease risk

   https://doi.org/10.1002/ecs2.4445  

   Lippi, Catherine_A; Canfield, Samuel; Espada, Christina; Gaff, Holly_D; Ryan, Sadie_J (March 2023, Ecosphere)

   Abstract Increasingly, geographic approaches to assessing the risk of tick‐borne diseases are being used to inform public health decision‐making and surveillance efforts. The distributions of key tick species of medical importance are often modeled as a function of environmental factors, using niche modeling approaches to capture habitat suitability. However, this is often disconnected from the potential distribution of key host species, which may play an important role in the actual transmission cycle and risk potential in expanding tick‐borne disease risk. Using species distribution modeling, we explore the potential geographic range ofOryzomys palustris, the marsh rice rat, which has been implicated as a potential reservoir host ofRickettsia parkeri, a pathogen transmitted by the Gulf Coast tick (Amblyomma maculatum) in the southeastern United States. Due to recent taxonomic reclassification ofO. palustrissubspecies, we reclassified geolocated collections records into the newer clade definitions. We modeled the distribution of the two updated clades in the region, establishing for the first time, range maps and distributions of these two clades. The predicted distribution of both clades indicates a largely Gulf and southeastern coastal distribution. Estimated suitable habitat forO. palustrisextends into the southern portion of the Mid‐Atlantic region, with a discontinuous, limited area of suitability in coastal California. Broader distribution predictions suggest potential incursions along the Mississippi River. We found considerable overlap of predictedO. palustrisranges with the distribution ofA. maculatum, indicating the potential need for extended surveillance efforts in those overlapping areas and attention to the role of hosts in transmission cycles. 

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3. Linking Lyme disease ecology and epidemiology: reservoir host identity, not richness, determines tick infection and human disease in California

   https://doi.org/10.1088/1748-9326/ac9ece  

   MacDonald, Andrew J; McComb, Sofie; Sambado, Samantha (November 2022, Environmental Research Letters)

   Abstract Understanding the community ecology of vector-borne and zoonotic diseases, and how it may shift transmission risk as it responds to environmental change, has become a central focus in disease ecology. Yet, it has been challenging to link the ecology of disease with reported human incidence. Here, we bridge the gap between local-scale community ecology and large-scale disease epidemiology, drawing from a priori knowledge of tick-pathogen-host ecology to model spatially-explicit Lyme disease (LD) risk, and human Lyme disease incidence (LDI) in California. We first use a species distribution modeling approach to model disease risk with variables capturing climate, vegetation, and ecology of key reservoir host species, and host species richness. We then use our modeled disease risk to predict human disease incidence at the zip code level across California. Our results suggest the ecology of key reservoir hosts—particularly dusky-footed woodrats—is central to disease risk posed by ticks, but that host community richness is not strongly associated with tick infection. Predicted disease risk, which is most strongly influenced by the ecology of dusky-footed woodrats, in turn is a strong predictor of human LDI. This relationship holds in the Wildland-Urban Interface, but not in open access public lands, and is stronger in northern California than in the state as a whole. This suggests peridomestic exposure to infected ticks may be more important to LD epidemiology in California than recreational exposure, and underlines the importance of the community ecology of LD in determining human transmission risk throughout this LD endemic region of far western North America. More targeted tick and pathogen surveillance, coupled with studies of human and tick behavior could improve understanding of key risk factors and inform public health interventions. Moreover, longitudinal surveillance data could further improve forecasts of disease risk in response to global environmental change. 

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4. Global mosquito observations dashboard (GMOD): creating a user-friendly web interface fueled by citizen science to monitor invasive and vector mosquitoes

   https://doi.org/10.1186/s12942-023-00350-7  

   Uelmen, Jr., Johnny A.; Clark, Andrew; Palmer, John; Kohler, Jared; Van Dyke, Landon C.; Low, Russanne; Mapes, Connor D.; Carney, Ryan M. (October 2023, International Journal of Health Geographics)

   Abstract BackgroundMosquitoes and the diseases they transmit pose a significant public health threat worldwide, causing more fatalities than any other animal. To effectively combat this issue, there is a need for increased public awareness and mosquito control. However, traditional surveillance programs are time-consuming, expensive, and lack scalability. Fortunately, the widespread availability of mobile devices with high-resolution cameras presents a unique opportunity for mosquito surveillance. In response to this, the Global Mosquito Observations Dashboard (GMOD) was developed as a free, public platform to improve the detection and monitoring of invasive and vector mosquitoes through citizen science participation worldwide. MethodsGMOD is an interactive web interface that collects and displays mosquito observation and habitat data supplied by four datastreams with data generated by citizen scientists worldwide. By providing information on the locations and times of observations, the platform enables the visualization of mosquito population trends and ranges. It also serves as an educational resource, encouraging collaboration and data sharing. The data acquired and displayed on GMOD is freely available in multiple formats and can be accessed from any device with an internet connection. ResultsSince its launch less than a year ago, GMOD has already proven its value. It has successfully integrated and processed large volumes of real-time data (~ 300,000 observations), offering valuable and actionable insights into mosquito species prevalence, abundance, and potential distributions, as well as engaging citizens in community-based surveillance programs. ConclusionsGMOD is a cloud-based platform that provides open access to mosquito vector data obtained from citizen science programs. Its user-friendly interface and data filters make it valuable for researchers, mosquito control personnel, and other stakeholders. With its expanding data resources and the potential for machine learning integration, GMOD is poised to support public health initiatives aimed at reducing the spread of mosquito-borne diseases in a cost-effective manner, particularly in regions where traditional surveillance methods are limited. GMOD is continually evolving, with ongoing development of powerful artificial intelligence algorithms to identify mosquito species and other features from submitted data. The future of citizen science holds great promise, and GMOD stands as an exciting initiative in this field. 

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5. The roles of habitat isolation, landscape connectivity and host community in tick-borne pathogen ecology

   https://doi.org/10.1098/rsos.240837  

   Shaw, Grace; Lilly, Marie; Mai, Vincent; Clark, Jacoby; Summers, Shannon; Slater, Kimetha; Karpathy, Sandor; Nakano, Angie; Crews, Arielle; Lawrence, Alexandra; et al (November 2024, Royal Society Open Science)

   Habitat loss and forest fragmentation are often linked to increased pathogen transmission, but the extent to which habitat isolation and landscape connectivity affect disease dynamics through movement of disease vectors and reservoir hosts has not been well examined. Tick-borne diseases are the most prevalent vector-borne diseases in the United States and on the West Coast,Ixodes pacificusis one of the most epidemiologically important vectors. We investigated the impacts of habitat fragmentation on pathogens transmitted byI. pacificusand sought to disentangle the effects of wildlife communities and landscape metrics predictive of pathogen diversity, prevalence and distribution. We collected pathogen data for four co-occurring bacteria transmitted byI. pacificusand measured wildlife parameters. We also used spatial data and cost-distance analysis integrating expert opinions to assess landscape metrics of habitat fragmentation. We found that landscape metrics were significant predictors of tick density and pathogen prevalence. However, wildlife variables were essential when predicting the prevalence and distribution of pathogens reliant on wildlife reservoir hosts for maintenance. We found that landscape structure was an informative predictor of tick-borne pathogen richness in an urban matrix. Our work highlights the implications of large-scale land management on human disease risk. 

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