Modeling the risk of aquatic species invasion spread through boater movements and river connections.

Aquatic invasive species (AIS) are one of the greatest threats to the functioning of aquatic ecosystems worldwide. Once an invasive species has been introduced to a new region, many governments develop management strategies to reduce further spread. Nevertheless, managing AIS in a new region is challenging because of the vast areas that need protection and limited resources. Spatial heterogeneity in invasion risk is driven by environmental suitability and propagule pressure, which can be used to prioritize locations for surveillance and intervention activities. To better understand invasion risk across aquatic landscapes, we developed a simulation model to estimate the likelihood of a waterbody becoming invaded with an AIS. The model included waterbodies connected via a multilayer network that included boater movements and hydrological connections. In a case study of Minnesota, we used zebra mussels (Dreissena polymorpha) and starry stonewort (Nitellopsis obtusa) as model species. We simulated the impacts of management scenarios developed by stakeholders and created a decision-support tool available through an online application provided as part of the AIS Explorer dashboard. Our baseline model revealed that 89% of new zebra mussel invasions and 84% of new starry stonewort invasions occurred through boater movements, establishing it as a primary pathway of spread and offering insights beyond risk estimates generated by traditional environmental suitability models alone. Our results highlight the critical role of interventions applied to boater movements to reduce AIS dispersal.

Modelo del riesgo de la invasión de especies acuáticas dispersadas por movimiento de botes y conexiones entre ríos Resumen Las especies acuáticas invasoras (EAI) son una de las principales amenazas para el funcionamiento de los ecosistemas acuáticos a nivel mundial. Una vez que una especie invasora ha sido introducida a una nueva región, muchos gobiernos desarrollan estrategias de manejo para disminuir la dispersión. Sin embargo, el manejo de las especies acuáticas invasoras en una nueva región se complica debido a las amplias áreas que necesitan protección y los recursos limitados. La heterogeneidad espacial de un riesgo de invasión es causada por la idoneidad ambiental y la presión de propágulo, que puede usarse para priorizar la ubicación de las actividades de vigilancia e intervención. Desarrollamos una simulación para estimar la probabilidad de que un cuerpo de agua sea invadido por EAI para tener un mejor entendimiento del riesgo de invasión en los paisajes acuáticos. El modelo incluyó cuencas conectadas a través de una red multicapa que incluía movimiento de botes y conexiones hidrológicas. Usamos como especies modelo a Dreissena polymorpha y a Nitellopsis obtusa en un estudio de caso en Minnesota. Simulamos el impacto de los escenarios de manejo desarrollado por los actores y creamos una herramienta de decisiones por medio de una aplicación en línea proporcionada como parte del tablero del Explorer de EAI. Nuestro modelo de línea base reveló que el 89% de las invasiones nuevas de D. polymorpha y el 84% de las de N. obtusa ocurrieron debido al movimiento de los botes, lo que lo estableció como una vía primaria de dispersión y nos proporcionó información más allá de las estimaciones de riesgo generadas por los modelos tradicionales de idoneidad ambiental. Nuestros resultados resaltan el papel crítico de las intervenciones aplicadas al movimiento de los botes para reducir la dispersión de especies acuáticas invasoras.

A review of the diet of the common vampire bat (Desmodus rotundus) in the context of anthropogenic change.

The common vampire bat (Desmodus rotundus) maintains a diverse, sanguivorous diet, utilizing a broad range of prey taxa. As anthropogenic change alters the distribution of this species, shifts in predator-prey interactions are expected. Understanding prey richness and patterns of prey selection is, thus, increasingly informative from ecological, epidemiological, and economic perspectives. We reviewed D. rotundus diet and assessed the geographical, taxonomical, and behavioral features to find 63 vertebrate species within 21 orders and 45 families constitute prey, including suitable host species in regions of invasion outside D. rotundus' range. Rodentia contained the largest number of species utilized by D. rotundus, though cattle were the most commonly reported prey source, likely linked to the high availability of livestock and visibility of bite wounds compared to wildlife. Additionally, there was tendency to predate upon species with diurnal activity and social behavior, potentially facilitating convenient and nocturnal predation. Our review highlights the dietary heterogeneity of D. rotundus across its distribution. We define D. rotundus as a generalist predator, or parasite, depending on the ecological definition of its symbiont roles in an ecosystem (i.e., lethal vs. non-lethal blood consumption). In view of the eminent role of D. rotundus in rabies virus transmission and its range expansion, an understanding of its ecology would benefit public health, wildlife management, and agriculture. Supplementary Information: The online version contains supplementary material available at 10.1007/s42991-023-00358-3.

Transmission risk of Oropouche fever across the Americas.

BACKGROUND: Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. METHODS: To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. RESULTS: Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. CONCLUSIONS: Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.

Climate change and infectious disease: a review of evidence and research trends.

BACKGROUND: Climate change presents an imminent threat to almost all biological systems across the globe. In recent years there have been a series of studies showing how changes in climate can impact infectious disease transmission. Many of these publications focus on simulations based on in silico data, shadowing empirical research based on field and laboratory data. A synthesis work of empirical climate change and infectious disease research is still lacking. METHODS: We conducted a systemic review of research from 2015 to 2020 period on climate change and infectious diseases to identify major trends and current gaps of research. Literature was sourced from Web of Science and PubMed literary repositories using a key word search, and was reviewed using a delineated inclusion criteria by a team of reviewers. RESULTS: Our review revealed that both taxonomic and geographic biases are present in climate and infectious disease research, specifically with regard to types of disease transmission and localities studied. Empirical investigations on vector-borne diseases associated with mosquitoes comprised the majority of research on the climate change and infectious disease literature. Furthermore, demographic trends in the institutions and individuals published revealed research bias towards research conducted across temperate, high-income countries. We also identified key trends in funding sources for most resent literature and a discrepancy in the gender identities of publishing authors which may reflect current systemic inequities in the scientific field. CONCLUSIONS: Future research lines on climate change and infectious diseases should considered diseases of direct transmission (non-vector-borne) and more research effort in the tropics. Inclusion of local research in low- and middle-income countries was generally neglected. Research on climate change and infectious disease has failed to be socially inclusive, geographically balanced, and broad in terms of the disease systems studied, limiting our capacities to better understand the actual effects of climate change on health.

Neglected tropical diseases risk correlates with poverty and early ecosystem destruction.

BACKGROUND: Neglected tropical diseases affect the most vulnerable populations and cause chronic and debilitating disorders. Socioeconomic vulnerability is a well-known and important determinant of neglected tropical diseases. For example, poverty and sanitation could influence parasite transmission. Nevertheless, the quantitative impact of socioeconomic conditions on disease transmission risk remains poorly explored. METHODS: This study investigated the role of socioeconomic variables in the predictive capacity of risk models of neglected tropical zoonoses using a decade of epidemiological data (2007-2018) from Brazil. Vector-borne diseases investigated in this study included dengue, malaria, Chagas disease, leishmaniasis, and Brazilian spotted fever, while directly-transmitted zoonotic diseases included schistosomiasis, leptospirosis, and hantaviruses. Environmental and socioeconomic predictors were combined with infectious disease data to build environmental and socioenvironmental sets of ecological niche models and their performances were compared. RESULTS: Socioeconomic variables were found to be as important as environmental variables in influencing the estimated likelihood of disease transmission across large spatial scales. The combination of socioeconomic and environmental variables improved overall model accuracy (or predictive power) by 10% on average (P < 0.01), reaching a maximum of 18% in the case of dengue fever. Gross domestic product was the most important socioeconomic variable (37% relative variable importance, all individual models exhibited P < 0.00), showing a decreasing relationship with disease indicating poverty as a major factor for disease transmission. Loss of natural vegetation cover between 2008 and 2018 was the most important environmental variable (42% relative variable importance, P < 0.05) among environmental models, exhibiting a decreasing relationship with disease probability, showing that these diseases are especially prevalent in areas where natural ecosystem destruction is on its initial stages and lower when ecosystem destruction is on more advanced stages. CONCLUSIONS: Destruction of natural ecosystems coupled with low income explain macro-scale neglected tropical and zoonotic disease probability in Brazil. Addition of socioeconomic variables improves transmission risk forecasts on tandem with environmental variables. Our results highlight that to efficiently address neglected tropical diseases, public health strategies must target both reduction of poverty and cessation of destruction of natural forests and savannas.

Revealing the complexity of vampire bat rabies "spillover transmission".

BACKGROUND: The term virus 'spillover' embodies a highly complex phenomenon and is often used to refer to viral transmission from a primary reservoir host to a new, naïve yet susceptible and permissive host species. Spillover transmission can result in a virus becoming pathogenic, causing disease and death to the new host if successful infection and transmission takes place. MAIN TEXT: The scientific literature across diverse disciplines has used the terms virus spillover, spillover transmission, cross-species transmission, and host shift almost indistinctly to imply the complex process of establishment of a virus from an original host (source/donor) to a naïve host (recipient), which have close or distant taxonomic or evolutionary ties. Spillover transmission may result in unsuccessful onward transmission, if the virus dies off before propagation. Alternatively, successful viral establishment in the new host can occur if subsequent secondary transmission among individuals of the same novel species and among other sympatric susceptible species occurred. As such, virus spillover transmission is a common yet highly complex phenomenon that encompasses multiple subtle stages that can be deconstructed to be studied separately to better understand the drivers of disease emergence. Rabies virus (RABV) is a well-documented viral pathogen which still inflicts heavy impact on humans, companion animals, wildlife, and livestock throughout Latin America due substantial spatial temporal and ecological-natural and expansional-overlap with several virus reservoir hosts. Thereby, the rabies disease system represents a robust avenue through which the drivers and uncertainties surrounding spillover transmission can be unravel at its different subtle stages to better understand how they may be affected by coarse, medium, and fine scale variables. CONCLUSIONS: The continued study of viral spillover transmission necessitates the elucidation of its complexities to better assess the cross-scale impacts of ecological forces linked to the propensity of spillover success. Improving capacities to reconstruct and predict spillover transmission would prevent public health impacts on those most at risk populations across the globe.

Reconstructing landscapes of ungulate parturition and predation using vegetation phenology.

Enhanced vegetation index (EVI) data can be used to identify and define the space in which ungulates practice parturition and encounter predation. This study explores the use of EVI data to identify landscapes linked to ungulate parturition and predation events across space, time, and environmental conditions. As a case study, we used the moose population (Alces alces) of northern Minnesota in the USA. Using remotely sensed EVI data rasters and global positioning system collar data, we quantified how vegetation phenology and moose movement shaped the births and predation of 52 moose calves from 2013 to 2020 on or adjacent to the Grand Portage Indian Reservation. The known sources of predation were American black bears (Ursus americanus, n = 22) and gray wolves (Canis lupus, n = 28). Satellite-derived data summarizing seasonal landscape features at the local level revealed that landscape heterogeneity use by moose can help to quantitatively identify landscapes of parturition and predation in space and time across large areas. Vegetation phenology proved to be differentiable between adult moose ranges, sites of cow parturition, and sites of calf predation. Landscape characteristics of each moose group were consistent and tractable based on environment, suggesting that sites of parturition and predation of moose are predictable in space and time. It is possible that moose selected specific landscapes for parturition despite risk of increased predation of their calves, which could be an example of an "ecological trap." This analytical framework can be employed to identify areas for future ungulate research on the impacts of landscape on parturition and predation dynamics.

Tracking the impacts of climate change on human health via indicators: lessons from the Lancet Countdown.

BACKGROUND: In the past decades, climate change has been impacting human lives and health via extreme weather and climate events and alterations in labour capacity, food security, and the prevalence and geographical distribution of infectious diseases across the globe. Climate change and health indicators (CCHIs) are workable tools designed to capture the complex set of interdependent interactions through which climate change is affecting human health. Since 2015, a novel sub-set of CCHIs, focusing on climate change impacts, exposures, and vulnerability indicators (CCIEVIs) has been developed, refined, and integrated by Working Group 1 of the "Lancet Countdown: Tracking Progress on Health and Climate Change", an international collaboration across disciplines that include climate, geography, epidemiology, occupation health, and economics. DISCUSSION: This research in practice article is a reflective narrative documenting how we have developed CCIEVIs as a discrete set of quantifiable indicators that are updated annually to provide the most recent picture of climate change's impacts on human health. In our experience, the main challenge was to define globally relevant indicators that also have local relevance and as such can support decision making across multiple spatial scales. We found a hazard, exposure, and vulnerability framework to be effective in this regard. We here describe how we used such a framework to define CCIEVIs based on both data availability and the indicators' relevance to climate change and human health. We also report on how CCIEVIs have been improved and added to, detailing the underlying data and methods, and in doing so provide the defining quality criteria for Lancet Countdown CCIEVIs. CONCLUSIONS: Our experience shows that CCIEVIs can effectively contribute to a world-wide monitoring system that aims to track, communicate, and harness evidence on climate-induced health impacts towards effective intervention strategies. An ongoing challenge is how to improve CCIEVIs so that the description of the linkages between climate change and human health can become more and more comprehensive.

A database of common vampire bat reports.

The common vampire bat (Desmodus rotundus) is a sanguivorous (i.e., blood-eating) bat species distributed in the Americas from northern Mexico southwards to central Chile and Argentina. Desmodus rotundus is one of only three mammal species known to feed exclusively on blood, mainly from domestic mammals, although large wildlife and occasionally humans can also serve as a food source. Blood feeding makes D. rotundus an effective transmissor of pathogens to its prey. Consequently, this species is a common target of culling efforts by various individuals and organizations. Nevertheless, little is known about the historical distribution of D. rotundus. Detailed occurrence data are critical for the accurate assessment of past and current distributions of D. rotundus as part of ecological, biogeographical, and epidemiological research. This article presents a dataset of D. rotundus historical occurrence reports, including >39,000 locality reports across the Americas to facilitate the development of spatiotemporal studies of the species. Data are available at https://doi.org/10.6084/m9.figshare.15025296 .

Sarcoptic mange: An emerging panzootic in wildlife.

Sarcoptic mange, a skin infestation caused by the mite Sarcoptes scabiei, is an emerging disease for some species of wildlife, potentially jeopardizing their welfare and conservation. Sarcoptes scabiei has a near-global distribution facilitated by its forms of transmission and use of a large diversity of host species (many of those with broad geographic distribution). In this review, we synthesize the current knowledge concerning the geographic and host taxonomic distribution of mange in wildlife, the epidemiological connections between species, and the potential threat of sarcoptic mange for wildlife conservation. Recent sarcoptic mange outbreaks in wildlife appear to demonstrate ongoing geographic spread, increase in the number of hosts and increased virulence. Sarcoptic mange has been reported in at least 12 orders, 39 families and 148 species of domestic and wild mammals, making it one of the most generalist ectoparasites of mammals. Taxonomically, the orders with most species found infested so far include Perissodactyla (67% species from the entire order), Artiodactyla (47%), and Diprotodontia (67% from this order). This suggests that new species from these mammal orders are likely to suffer cross-species transmission and be reported positive to sarcoptic mange as surveillance improves. We propose a new agenda for the study of sarcoptic mange in wildlife, including the study of the global phylogeography of S. scabiei, linkages between ecological host traits and sarcoptic mange susceptibility, immunology of individuals and species, development of control strategies in wildlife outbreaks and the effects of global environmental change in the sarcoptic mange system. The ongoing transmission globally and sustained spread among areas and wildlife species make sarcoptic mange an emerging panzootic in wildlife. A better understanding of sarcoptic mange could illuminate the aspects of ecological and evolutionary drivers in cross-species transmission for many emerging diseases.

Spatial compartmentalization: A nonlethal predator mechanism to reduce parasite transmission between prey species.

Predators can modulate disease transmission within prey populations by influencing prey demography and behavior. Predator-prey dynamics can involve multiple species in heterogeneous landscapes; however, studies of predation on disease transmission rarely consider the role of landscapes or the transmission among diverse prey species (i.e., spillover). We used high-resolution habitat and movement data to model spillover risk of the brainworm parasite (Parelaphostrongylus tenuis) between two prey species [white-tailed deer (Odocoileus virginianus) and moose (Alces alces)], accounting for predator [gray wolf (Canis lupus)] presence and landscape configuration. Results revealed that spring migratory movements of cervid hosts increased parasite spillover risk from deer to moose, an effect tempered by changes in elevation, land cover, and wolf presence. Wolves induced host-species segregation, a nonlethal mechanism that modulated disease emergence by reducing spatiotemporal overlap between infected and susceptible prey, showing that wildlife disease dynamics may change with landscape disturbance and the loss of large carnivores.

A database of global coastal conditions.

Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth's surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.

A Landscape Epidemiological Approach for Predicting Chronic Wasting Disease: A Case Study in Virginia, US.

Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases. Chronic wasting disease (CWD), a fatal prion disease of the deer family Cervidae, currently affects white-tailed deer (Odocoileus virginianus) populations in the Mid-Atlantic United States (US) and challenges wildlife veterinarians and disease ecologists from its unclear mechanisms and associations within landscapes, particularly in early phases of an outbreak when CWD detections are sparse. We aimed to provide guidance for wildlife disease management by identifying the extent to which CWD-positive cases can be reliably predicted from landscape conditions. Using the CWD outbreak in Virginia, US from 2009 to early 2020 as a case study system, we used diverse algorithms (e.g., principal components analysis, support vector machines, kernel density estimation) and data partitioning methods to quantify remotely sensed landscape conditions associated with CWD cases. We used various model evaluation tools (e.g., AUC ratios, cumulative binomial testing, Jaccard similarity) to assess predictions of disease transmission risk using independent CWD data. We further examined model variation in the context of uncertainty. We provided significant support that vegetation phenology data representing landscape conditions can predict and map CWD transmission risk. Model predictions improved when incorporating inferred home ranges instead of raw hunter-reported coordinates. Different data availability scenarios identified variation among models. By showing that CWD could be predicted and mapped, our project adds to the available tools for understanding the landscape ecology of CWD transmission risk in free-ranging populations and natural conditions. Our modeling framework and use of widely available landscape data foster replicability for other wildlife diseases and study areas.

Infection risk varies within urbanized landscapes: the case of coyotes and heartworm.

BACKGROUND: Urbanization can have profound effects on ecological interactions. For host-pathogen interactions, differences have been detected between urban and non-urban landscapes. However, host-pathogen interactions may also differ within highly heterogeneous, urbanized landscapes. METHODS: We investigated differences in infection risk (i.e., probability of infection) within urbanized landscapes using the coyote (Canis latrans) and mosquito-borne nematode, Dirofilaria immitis (the causative agent for canine heartworm), as a case study. We focused on a coyote population in Chicago for which extensive behavioral and heartworm infection data has been collected between 2001 and 2016. Our objectives were to: (i) determine how onset and duration of the heartworm transmission season varied over the 16-year period and across the urban-suburban gradient; and (ii) investigate how heartworm infection risk in coyotes varied over the years, across the urban-suburban gradient, by coyote characteristics (e.g., age, sex, resident status), and coyote use of the urbanized landscape (e.g., use of urban areas, mosquito habitats). RESULTS: While onset of the heartworm transmission season differed neither by year nor across the urban-suburban gradient, it was longer closer to the core of Chicago. Of the 315 coyotes sampled, 31.1% were infected with D. immitis. Older coyotes and coyotes sampled in later years (i.e., 2012-2016) were more likely to have heartworm. While coyote location in the urban-suburban gradient was not a significant predictor of infection, the proportion of urban land in coyote home ranges was. Importantly, the size and direction of this association varied by age class. For adults and pups, infection risk declined with urbanization, whereas for subadults it increased. Further, models had a higher predictive power when focusing on resident coyotes (and excluding transient coyotes). The proportion of mosquito habitat in coyote home ranges was not a significant predictor of infection. CONCLUSIONS: Our findings suggest that urbanization may affect host exposure to vectors of D. immitis, that risk of infection can vary within urbanized landscapes, and that urbanization-wildlife infection associations may only be detected for animals with certain characteristics (e.g., age class and resident status).

Use of partial N-gene sequences as a tool to monitor progress on rabies control and elimination efforts in Ethiopia.

Ethiopia is one of the African countries most affected by rabies. A coarse catalog of rabies viruses (RABV) was created as a benchmark to assess the impact of control and elimination activities. We evaluated a 726 bp amplicon at the end of the N-gene to infer viral lineages in circulation using maximum likelihood and Bayesian methods for phylogenetic reconstruction. We sequenced 228 brain samples from wild and domestic animals collected in five Ethiopian regions during 2010-2017. Results identified co-circulating RABV lineages that are causing recurrent spillover infections into wildlife and domestic animals. We found no evidence of importation of RABVs from other African countries or vaccine-induced cases in the area studied. A divergent RABV lineage might be involved in an independent rabies cycle in jackals. This investigation provides a feasible approach to assess rabies control and elimination efforts in resource-limited countries.

A Cross Sectional Sampling Reveals Novel Coronaviruses in Bat Populations of Georgia.

Mammal-associated coronaviruses have a long evolutionary history across global bat populations, which makes them prone to be the most likely ancestral origins of coronavirus-associated epidemics and pandemics globally. Limited coronavirus research has occurred at the junction of Europe and Asia, thereby investigations in Georgia are critical to complete the coronavirus diversity map in the region. We conducted a cross-sectional coronavirus survey in bat populations at eight locations of Georgia, from July to October of 2014. We tested 188 anal swab samples, remains of previous pathogen discovery studies, for the presence of coronaviruses using end-point pan-coronavirus RT-PCR assays. Samples positive for a 440 bp amplicon were Sanger sequenced to infer coronavirus subgenus or species through phylogenetic reconstructions. Overall, we found a 24.5% positive rate, with 10.1% for Alphacoronavirus and 14.4% for Betacoronavirus. Albeit R. euryale, R. ferrumequinum, M. blythii and M. emarginatus were found infected with both CoV genera, we could not rule out CoV co-infection due to limitation of the sequencing method used and sample availability. Based on phylogenetic inferences and genetic distances at nucleotide and amino acid levels, we found one putative new subgenus and three new species of Alphacoronavirus, and two new species of Betacoronavirus.

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises.

TRANSLATIONS: For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.