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.

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal ‘gold standard’ method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Leishmaniases are neglected diseases transmitted by sand flies. They disproportionately affect vulnerable groups globally. Understanding the relationship between climate and disease transmission allows the development of relevant decision-support tools for public health policy and surveillance. The aim of this modelling study was to develop an indicator that tracks climatic suitability for Leishmania infantum transmission in Europe at the subnational level. Historical records of sand fly vectors, human leishmaniasis, bioclimatic indicators, and environmental variables were integrated in a machine learning framework (XGBoost) to predict suitability in two past periods (2001–2010 and 2011–2020). We further assessed if predictions were associated with human and animal disease data from selected countries (France, Greece, Italy, Portugal, and Spain). An increase in the number of climatically suitable regions for leishmaniasis was detected, especially in southern and eastern countries, coupled with a northward expansion towards central Europe. The final model had excellent predictive ability (AUC = 0.970 [0.947–0.993]), and the suitability predictions were positively associated with human leishmaniasis incidence and canine seroprevalence for Leishmania. This study demonstrates how key epidemiological data can be combined with open-source climatic and environmental information to develop an indicator that effectively tracks spatiotemporal changes in climatic suitability and disease risk. The positive association between the model predictions and human disease incidence demonstrates that this indicator could help target leishmaniasis surveillance to transmission hotspots. European Union Horizon Europe Research and Innovation Programme (European Climate-Health Cluster), United Kingdom Research and Innovation.

Although leishmaniases are regarded as serious public health issues in the State of Tocantins, as consequence of the impact of environmental changes, small advances in taxonomic and ecological studies of Phlebotominae fauna are taking place in this state. The present study aimed to improve the knowledge about the sand flies, as well as about the aspects of the bioecology of leishmaniases vectors from Porto Nacional, a city that was directly impacted by the construction of Luís Eduardo Magalhães Hydroelectric Plant (HEP – Lajeado). Sand flies were collected monthly using CDC light traps and Shannon traps for a period of 40 consecutive months, at different monitoring stations, where 7162 specimens were collected and 48 species were detected. Among the species found, 22 are first records in the state and seven are considered important vectors of leishmaniases. Lutzomyia longipalpis, the vector of American Visceral Leishmaniasis (AVL) showed higher frequency in urban compared to rural areas, and Nyssomyia whitmani, the vector of American Cutaneous Leishmaniasis (ACL), predominated in rural areas. The frequency and habits of sand fly vectors are discussed considering environmental characteristics and climatic factors. The construction of dams requires a great amount of labor, therefore attracting people from elsewhere. Increased migration, without adequate structure, leads to bad living conditions in new and unplanned settlements. It also leads to deforestation associated with environmental impacts, which can facilitate the spread of leishmaniases. This study discusses the importance of Lu. longipalpis and Ny. whitmani on the transmission cycles of leishmaniases in Porto Nacional and the record of Bi. flaviscutellata in periurban area of the city.

The south coast of Rio de Janeiro State, in Brazil, is endemic for cutaneous and visceral leishmaniases and is frequently visited by tourists from different parts of the world. Since the complex epidemiology of leishmaniases demands local studies, the goal of this study was to investigate the phlebotomine sand fly fauna and leishmaniases transmission in Ilha Grande, an ecotourism area of Angra dos Reis municipality.