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Summary: Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health—Climate Risk framework.

BackgroundLeishmaniases are vector borne diseases caused by Leishmania spp. parasites transmitted by female sandflies (Diptera: Psychodidae) whose geographic distribution is influenced by environmental factors. Among the main tools for studying the distribution of vector species, modeling techniques are used to analyze the influence of climatic and environmental factors on the distribution of these insects and their association with human cases of the disease.Methodology/principal findingsHere, we used a multiscale ecological niche modeling approach to assess the environmental suitability of sandfly vectors of the etiological agents of Visceral (VL) and American Cutaneous Leishmaniasis (ACL) in Piauí state, northeastern Brazil, and then evaluated their relationship with human disease incidence. For this, we obtained the geographic coordinates of the vector species Lutzomyia longipalpis and Nyssomyia whitmani through literature review, online databases and unpublished records. These data were used for the development of predictive models of the distribution of both sandflies species based on climatic and environmental variables. Finally, the environmental suitability for the presence of these vectors was compared with the incidence of both the diseases at the municipality level. The final models for each sandfly species showed good predictive powers with performance metric values of 0.889 for Lu. longipalpis and 0.776 for Ny. whitmani. The areas with greater environmental suitability for the presence of these species were concentrated in the central-north region of Piauí and coincide with the location of those municipalities presenting higher incidences of VL and ACL, situated in the central-north and extreme north of the state, respectively. The south and southeast regions of Piauí state have low incidence of these diseases and presented low environmental suitability for the presence of both vectors.Conclusions/significanceWe discuss how predictive modeling can guide entomological and epidemiological surveillances and recommend an increased supervision and control activities in Teresina (capital of the state of Piaui), Altos and Pedro II, in addition to other municipalities with similar social and environmental characteristics.

ABSTRACT The municipality of Paracambi (Rio de Janeiro, Brazil) reports sporadic cases of American cutaneous leishmaniasis (ACL). Previous studies detected Nyssomyia intermedia (Diptera: Psychodidae) as the main vector in the region, but its spatial distribution and the presence of other vector species have not been evaluated. This study aims at filling this knowledge gap, by studying the ecology of sand flies, their spatiotemporal distribution, and correlation with land use/cover. Two campaigns of monthly sand fly collections using light traps and manual captures were conducted in 1992–1994 and 2001–2003. Females were dissected to detect natural Leishmania infections. The spatial distribution of sand flies was assessed using kernel density maps. Correlations with land use/cover were evaluated by extracting satellite imagery data around the capture points. A total of 17,232 sand flies from 13 species were captured. Medically important species included Ny. intermedia, Migonemyia migonei, Pintomyia fischeri and Ny. whitmani. No Leishmania-infected females were detected. Highest densities were detected in the peri-urban areas Cascata and Sabugo, and in rural areas São José and Mutirão. Ny. intermedia had statistically significant correlations with pasture and agricultural areas. Present results strengthened that Ny. intermedia and Mg. migonei are the main local ACL vectors. Correlations with land use evidence the association between ACL and anthropic environmental change.

Climate change affects human health either directly or indirectly, and related impacts are complex, non-linear, and depend on several variables. The various climate change impacts on health include a change in the spatial distribution of vector-borne diseases. In this regard, this study presents and discusses changes in the spatial distribution of climate suitability for visceral leishmaniasis, yellow fever and malaria in Brazil, in different global warming scenarios. Maximum entropy (MaxEnt) was used to construct climate suitability models in warming scenarios. Models were based in climate variables generated by the Eta-HadGEM2 ES regional model, in the baseline period 1965-2005 and RCP8.5 scenario, representing global warming levels of 1,5ºC (2011-2040), 2,0ºC (2041-2070) and 4,0ºC (2071-2099). The three diseases studied are largely influenced by climate and showed different distribution patterns within the country. In global warming scenarios, visceral leishmaniasis found more favorable climate conditions in the Southeastern and Southern regions of Brazil, while climate in the Northern and Center-West regions gradually became more favorable to yellow fever. In malaria scenarios, an increase in favorable climate conditions to its high incidence was observed in the Atlantic Forest, where currently extra-Amazonian cases occur. The scenarios presented herein represent different possible consequences for the health sector in terms of adopting (or not) different measures to mitigate climate change in Brazil, such as reducing the emission of greenhouse gases. Â

In some transmission foci of Leishmania infantum in Brazil, Lutzomyia cruzi could be considered the main vector of this pathogen. In addition, L. cruzi is a permissive vector of L. amazonensis. Its geographical distribution seems to be restricted and limited to Cerrado and Pantanal biomes, which includes some areas in Brazil and Bolivia. Considering that predicting the distribution of the species involved in transmission cycles is an effective approach for assessing human disease risk, this study aims to predict the spatial distribution of L. cruzi using a multiscale ecological niche model based in both climate and habitat variables. Ecological niche modelling was used to identify areas in South America that are environmentally suitable for this particular vector species, but its presence is not recorded. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Bioclimatic variables, altitude, and land use and cover were used as predictors in five ecological niche model algorithms: BIOCLIM, generalised linear model (logistic regression), maximum entropy, random forests, and support vector machines. The vector occurs in areas where annual mean temperature values range from 21.76°C to 26.58°C, and annual total precipitation varies from 1005 mm and 2048 mm. Urban areas were most present around capture locations. The potential distribution area of L. cruzi according to the final ecological niche model spans Brazil and Bolivia in patches of suitable habitats inside a larger climatically favourable area. The bigger portion of this suitable area is located at Brazilian States of Mato Grosso do Sul and Mato Grosso. Our findings identified environmentally suitable areas for L. cruzi in regions without its known occurrence, so further field sampling of sand flies is recommended, especially in southern Goiás State, Mato Grosso do Sul (borders with Mato Grosso, São Paulo and Minas Gerais); and in Bolivian departments Santa Cruz and El Beni.