Climate change and risk of leishmaniasis in north america: predictions from ecological niche models of vector and reservoir species.
ABSTRACT: BACKGROUND: Climate change is increasingly being implicated in species' range shifts throughout the world, including those of important vector and reservoir species for infectious diseases. In North America (México, United States, and Canada), leishmaniasis is a vector-borne disease that is autochthonous in México and Texas and has begun to expand its range northward. Further expansion to the north may be facilitated by climate change as more habitat becomes suitable for vector and reservoir species for leishmaniasis. METHODS AND FINDINGS: The analysis began with the construction of ecological niche models using a maximum entropy algorithm for the distribution of two sand fly vector species (Lutzomyia anthophora and L. diabolica), three confirmed rodent reservoir species (Neotoma albigula, N. floridana, and N. micropus), and one potential rodent reservoir species (N. mexicana) for leishmaniasis in northern México and the United States. As input, these models used species' occurrence records with topographic and climatic parameters as explanatory variables. Models were tested for their ability to predict correctly both a specified fraction of occurrence points set aside for this purpose and occurrence points from an independently derived data set. These models were refined to obtain predicted species' geographical distributions under increasingly strict assumptions about the ability of a species to disperse to suitable habitat and to persist in it, as modulated by its ecological suitability. Models successful at predictions were fitted to the extreme A2 and relatively conservative B2 projected climate scenarios for 2020, 2050, and 2080 using publicly available interpolated climate data from the Third Intergovernmental Panel on Climate Change Assessment Report. Further analyses included estimation of the projected human population that could potentially be exposed to leishmaniasis in 2020, 2050, and 2080 under the A2 and B2 scenarios. All confirmed vector and reservoir species will see an expansion of their potential range towards the north. Thus, leishmaniasis has the potential to expand northwards from México and the southern United States. In the eastern United States its spread is predicted to be limited by the range of L. diabolica; further west, L. anthophora may play the same role. In the east it may even reach the southern boundary of Canada. The risk of spread is greater for the A2 scenario than for the B2 scenario. Even in the latter case, with restrictive (contiguous) models for dispersal of vector and reservoir species, and limiting vector and reservoir species occupancy to only the top 10% of their potential suitable habitat, the expected number of human individuals exposed to leishmaniasis by 2080 will at least double its present value. CONCLUSIONS: These models predict that climate change will exacerbate the ecological risk of human exposure to leishmaniasis in areas outside its present range in the United States and, possibly, in parts of southern Canada. This prediction suggests the adoption of measures such as surveillance for leishmaniasis north of Texas as disease cases spread northwards. Potential vector and reservoir control strategies-besides direct intervention in disease cases-should also be further investigated.
Project description:Leishmaniasis is recognized as an endemic human disease in Africa, the Middle East, Asia, and South America. Yet despite case reports of endemic human leishmaniasis in the United States, and well-documented occurrences of disease in various animal vectors and reservoirs, the endemicity of leishmaniasis in North America has not yet been established. Moreover, leishmaniasis is not a federally reportable disease in the United States. Clinical awareness of endemic disease therefore remains low, with North American physicians considering leishmaniasis a tropical disease.To assess the endemicity of human leishmaniasis in the United States.This cross-sectional multicenter observational study reviewed cases of human leishmaniasis occurring in the United States from 2007 through 2017. Previously diagnosed, deidentified cases of leishmaniasis were reported by the institutions of the authors and acknowledged contributors, as well as the Texas Department of State Health Services. Cases of leishmaniasis were identified by searching by disease name (leishmaniasis) or International Classification of Diseases, 9th and 10th Revisions diagnosis codes in the respective laboratory information systems.Via examination of deidentified demographics, cases of leishmaniasis were classified as one of the following: (1) documentation of no history of travel outside of the United States within 10 years; (2) positive history of travel outside of the United States within 10 years; or (3) unknown or no documentation of travel history.Cases of leishmaniasis were considered endemic if identified in patients with documentation of no travel history outside of the United States within 10 years.Of the 69 novel cases of human cutaneous leishmaniasis identified in this study, 41 (59%) were endemic; the median age at diagnosis was 61 years (range, 3-89 years), and 28 (68%) of the endemic cases occurred in female patients. Twenty-two (32%) cases had documentation of Leishmania speciation performed by polymerase chain reaction, and in 100% of these cases the infectious organism was identified as Leishmania mexicana.Human cutaneous leishmaniasis is endemic in the United States, and, at least regionally, is acquired endemically more frequently than it is via travel. Our data argue in favor of making leishmaniasis a federally reportable disease and may have substantial implications on North American public health initiatives, with climate models predicting the number of citizens exposed to leishmaniasis will double by 2080.
Project description:Lyme disease is the most commonly reported vector-borne illness in the United States. Lyme disease occurrence is highly seasonal and the annual springtime onset of cases is modulated by meteorological conditions in preceding months. A meteorological-based empirical model for Lyme disease onset week in the United States is driven with downscaled simulations from five global climate models and four greenhouse gas emissions scenarios to project the impacts of 21st century climate change on the annual onset week of Lyme disease. Projections are made individually and collectively for the 12 eastern States where >90% of cases occur. The national average annual onset week of Lyme disease is projected to become 0.4-0.5 weeks earlier for 2025-2040 (p<0.05), and 0.7-1.9 weeks earlier for 2065-2080 (p<0.01), with the largest shifts for scenarios with the highest greenhouse gas emissions. The more southerly mid-Atlantic States exhibit larger shifts (1.0-3.5 weeks) compared to the Northeastern and upper Midwestern States (0.2-2.3 weeks) by 2065-2080. Winter and spring temperature increases primarily cause the earlier onset. Greater spring precipitation and changes in humidity partially counteract the temperature effects. The model does not account for the possibility that abrupt shifts in the life cycle of Ixodes scapularis, the primary vector of the Lyme disease spirochete Borrelia burgdorferi in the eastern United States, may alter the disease transmission cycle in unforeseen ways. The results suggest 21st century climate change will make environmental conditions suitable for earlier annual onset of Lyme disease cases in the United States with possible implications for the timing of public health interventions.
Project description:Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4(th) Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts.
Project description:Ecological niche models are useful tools to infer potential spatial and temporal distributions in vector species and to measure epidemiological risk for infectious diseases such as the Leishmaniases. The ecological niche of 28 North and Central American sand fly species, including those with epidemiological relevance, can be used to analyze the vector's ecology and its association with transmission risk, and plan integrated regional vector surveillance and control programs. In this study, we model the environmental requirements of the principal North and Central American phlebotomine species and analyze three niche characteristics over future climate change scenarios: i) potential change in niche breadth, ii) direction and magnitude of niche centroid shifts, iii) shifts in elevation range. Niche identity between confirmed or incriminated Leishmania vector sand flies in Mexico, and human cases were analyzed. Niche models were constructed using sand fly occurrence datapoints from Canada, USA, Mexico, Guatemala and Belize. Nine non-correlated bioclimatic and four topographic data layers were used as niche components using GARP in OpenModeller. Both B2 and A2 climate change scenarios were used with two general circulation models for each scenario (CSIRO and HadCM3), for 2020, 2050 and 2080. There was an increase in niche breadth to 2080 in both scenarios for all species with the exception of Lutzomyia vexator. The principal direction of niche centroid displacement was to the northwest (64%), while the elevation range decreased greatest for tropical, and least for broad-range species. Lutzomyia cruciata is the only epidemiologically important species with high niche identity with that of Leishmania spp. in Mexico. Continued landscape modification in future climate change will provide an increased opportunity for the geographic expansion of NCA sand flys' ENM and human exposure to vectors of Leishmaniases.
Project description:Zoonotic visceral leishmaniasis (ZVL) is a serious neglected tropical disease that is endemic in 98 countries. ZVL is primarily transmitted via a sand fly vector. In the United States, it is enzootic in some canine populations; it is transmitted from infectious mother to pup transplacentally, and vector-borne transmission is absent. This absence affords a unique opportunity to study (1) vertical transmission dynamics in dogs and (2) the importance of vertical transmission in maintaining an infectious reservoir in the presence of a vector. In this paper, we present Bayesian compartmental models and reproductive number formulations to examine (1) and (2), providing a mechanism to plan and evaluate interventions in regions where both transmission modes are present. First, we propose an individual-level susceptible, infectious, removed (SIR) model to study the effect of maternal infection status during pregnancy on pup infection progression. We provide evidence that pups born to diagnostically positive mothers during pregnancy are more likely to become diagnostically positive both earlier in life, and at some point during their lifetime, than those born to diagnostically negative mothers. Second, we propose a population-level SIR model to study the impact of a vertically maintained reservoir on propagating infection in a naive canine population through emergent vector transmission using simulation studies. We also present reproductive numbers to quantify contributions of vertically infected and vector-infected dogs to maintaining infection in the population. We show that a vertically maintained canine reservoir can propagate infection in a theoretical naive population in the presence of a vector.
Project description:<h4>Abstract' background</h4>For >100 years cattle production in the southern United States has been threatened by cattle fever. It is caused by an invasive parasite-vector complex that includes the protozoan hemoparasites Babesia bovis and B. bigemina, which are transmitted among domestic cattle via Rhipicephalus tick vectors of the subgenus Boophilus. In 1906 an eradication effort was started and by 1943 Boophilus ticks had been confined to a narrow tick eradication quarantine area (TEQA) along the Texas-Mexico border. However, a dramatic increase in tick infestations in areas outside the TEQA over the last decade suggests these tick vectors may be poised to re-invade the southern United States. We investigated historical and potential future distributions of climatic habitats of cattle fever ticks to assess the potential for a range expansion.<h4>Methods</h4>We built robust spatial predictions of habitat suitability for the vector species Rhipicephalus (Boophilus) microplus and R. (B.) annulatus across the southern United States for three time periods: 1906, present day (2012), and 2050. We used analysis of molecular variance (AMOVA) to identify persistent tick occurrences and analysis of bias in the climate proximate to these occurrences to identify key environmental parameters associated with the ecology of both species. We then used ecological niche modeling algorithms GARP and Maxent to construct models that related known occurrences of ticks in the TEQA during 2001-2011 with geospatial data layers that summarized important climate parameters at all three time periods.<h4>Results</h4>We identified persistent tick infestations and specific climate parameters that appear to be drivers of ecological niches of the two tick species. Spatial models projected onto climate data representative of climate in 1906 reproduced historical pre-eradication tick distributions. Present-day predictions, although constrained to areas near the TEQA, extrapolated well onto climate projections for 2050.<h4>Conclusions</h4>Our models indicate the potential for range expansion of climate suitable for survival of R. microplus and R. annulatus in the southern United States by mid-century, which increases the risk of reintroduction of these ticks and cattle tick fever into major cattle producing areas.
Project description:<h4>Background</h4>Chagas disease, caused by Trypanosoma cruzi, remains a serious public health concern in many areas of Latin America, including México. It is also endemic in Texas with an autochthonous canine cycle, abundant vectors (Triatoma species) in many counties, and established domestic and peridomestic cycles which make competent reservoirs available throughout the state. Yet, Chagas disease is not reportable in Texas, blood donor screening is not mandatory, and the serological profiles of human and canine populations remain unknown. The purpose of this analysis was to provide a formal risk assessment, including risk maps, which recommends the removal of these lacunae.<h4>Methods and findings</h4>The spatial relative risk of the establishment of autochthonous Chagas disease cycles in Texas was assessed using a five-stage analysis. 1. Ecological risk for Chagas disease was established at a fine spatial resolution using a maximum entropy algorithm that takes as input occurrence points of vectors and environmental layers. The analysis was restricted to triatomine vector species for which new data were generated through field collection and through collation of post-1960 museum records in both México and the United States with sufficiently low georeferenced error to be admissible given the spatial resolution of the analysis (1 arc-minute). The new data extended the distribution of vector species to 10 new Texas counties. The models predicted that Triatoma gerstaeckeri has a large region of contiguous suitable habitat in the southern United States and México, T. lecticularia has a diffuse suitable habitat distribution along both coasts of the same region, and T. sanguisuga has a disjoint suitable habitat distribution along the coasts of the United States. The ecological risk is highest in south Texas. 2. Incidence-based relative risk was computed at the county level using the Bayesian Besag-York-Mollié model and post-1960 T. cruzi incidence data. This risk is concentrated in south Texas. 3. The ecological and incidence-based risks were analyzed together in a multi-criteria dominance analysis of all counties and those counties in which there were as yet no reports of parasite incidence. Both analyses picked out counties in south Texas as those at highest risk. 4. As an alternative to the multi-criteria analysis, the ecological and incidence-based risks were compounded in a multiplicative composite risk model. Counties in south Texas emerged as those with the highest risk. 5. Risk as the relative expected exposure rate was computed using a multiplicative model for the composite risk and a scaled population county map for Texas. Counties with highest risk were those in south Texas and a few counties with high human populations in north, east, and central Texas showing that, though Chagas disease risk is concentrated in south Texas, it is not restricted to it.<h4>Conclusions</h4>For all of Texas, Chagas disease should be designated as reportable, as it is in Arizona and Massachusetts. At least for south Texas, lower than N, blood donor screening should be mandatory, and the serological profiles of human and canine populations should be established. It is also recommended that a joint initiative be undertaken by the United States and México to combat Chagas disease in the trans-border region. The methodology developed for this analysis can be easily exported to other geographical and disease contexts in which risk assessment is of potential value.
Project description:Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.
Project description:The enormous global burden of vector-borne diseases disproportionately affects poor people in tropical, developing countries. Changes in vector-borne disease impacts are often linked to human modification of ecosystems as well as climate change. For tropical ecosystems, the health impacts of future environmental and developmental policy depend on how vector-borne disease risks trade off against other ecosystem services across heterogeneous landscapes. By linking future socio-economic and climate change pathways to dynamic land use models, this study is amongst the first to analyse and project impacts of both land use and climate change on continental-scale patterns in vector-borne diseases. Models were developed for cutaneous and visceral leishmaniasis in the Americas-ecologically complex sand fly borne infections linked to tropical forests and diverse wild and domestic mammal hosts. Both diseases were hypothesised to increase with available interface habitat between forest and agricultural or domestic habitats and with mammal biodiversity. However, landscape edge metrics were not important as predictors of leishmaniasis. Models including mammal richness were similar in accuracy and predicted disease extent to models containing only climate and land use predictors. Overall, climatic factors explained 80% and land use factors only 20% of the variance in past disease patterns. Both diseases, but especially cutaneous leishmaniasis, were associated with low seasonality in temperature and precipitation. Since such seasonality increases under future climate change, particularly under strong climate forcing, both diseases were predicted to contract in geographical extent to 2050, with cutaneous leishmaniasis contracting by between 35% and 50%. Whilst visceral leishmaniasis contracted slightly more under strong than weak management for carbon, biodiversity and ecosystem services, future cutaneous leishmaniasis extent was relatively insensitive to future alternative socio-economic pathways. Models parameterised at narrower geographical scales may be more sensitive to land use pattern and project more substantial changes in disease extent under future alternative socio-economic pathways.
Project description:Chagas disease kills approximately 45 thousand people annually and affects 10 million people in Latin America and the southern United States. The parasite that causes the disease, Trypanosoma cruzi, can be transmitted by insects of the family Reduviidae, subfamily Triatominae. Any study that attempts to evaluate risk for Chagas disease must focus on the ecology and biogeography of these vectors. Expected distributional shifts of vector species due to climate change are likely to alter spatial patterns of risk of Chagas disease, presumably through northward expansion of high risk areas in North America.We forecast the future (2050) distributions in North America of Triatoma gerstaeckeri and T. sanguisuga, two of the most common triatomine species and important vectors of Trypanosoma cruzi in the southern United States. Our aim was to analyze how climate change might affect the future shift of Chagas disease in North America using a maximum entropy algorithm to predict changes in suitable habitat based on vector occurrence points and predictive environmental variables. Projections based on three different general circulation models (CCCMA, CSIRO, and HADCM3) and two IPCC scenarios (A2 and B2) were analyzed. Twenty models were developed for each case and evaluated via cross-validation. The final model averages result from all twenty of these models. All models had AUC >0.90, which indicates that the models are robust. Our results predict a potential northern shift in the distribution of T. gerstaeckeri and a northern and southern distributional shift of T. sanguisuga from its current range due to climate change.The results of this study provide baseline information for monitoring the northward shift of potential risk from Chagas disease in the face of climate change.