Ecological niche modelling for predicting the risk of cutaneous leishmaniasis in the Neotropical moist forest biome
| Autor: | Magalie Demar, Jean-François Guégan, Giovanny Herrera, Ghislaine Prévot, Alessandra Nava, Thiago Vasconcelos dos Santos, Benoit de Thoisy, Marine Ginouves, Agathe Chavy, Juan David Ramírez, Sérgio Luiz Bessa Luz |
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| Přispěvatelé: | Donnat, Martin, Laboratoires d'excellence - CEnter of the study of Biodiversity in Amazonia - - CEBA2010 - ANR-10-LABX-0025 - LABX - VALID, Laboratoire des Interactions Virus-Hôtes [Cayenne, Guyane Française], Institut Pasteur de la Guyane, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Ecosystemes Amazoniens et Pathologie Tropicale (EPat), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Guyane (UG), Fundação Oswaldo Cruz (FIOCRUZ), Réseau International des Instituts Pasteur (RIIP), Universidad del Rosario [Bogota], Instituto Evandro Chagas, Laboratoire Hospitalo-Universitaire de Parasitologie-Mycologie, Coordination Régionale de la lutte contre le Virus de L'Immunodéficience Humaine (COREVIH)-Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française]-Université des Antilles (UA), Génétique et évolution des maladies infectieuses (GEMI), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), This study was conducted within the RESERVOIRS program supported by European (ERDF/FEDER) funds and assistance from Collectivité Territoriale de la Guyane and Direction Régionale pour la Recherche et la Technologie, and the MicroBIOME project granted by Laboratoire d'Excellence CEBA 'Investissement d’Avenir' and managed by the Agence Nationale de la Recherche (CEBA, Ref. ANR-10-LABEX-25-01). AC benefits from a PhD grant from the French Guiana University. JFG is sponsored by Institut de Recherche pour le Développement, the Centre National de la Recherche Scientifique, Institut national de la recherche agronomique and Montpellier University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., ANR-10-LABX-0025,CEBA,CEnter of the study of Biodiversity in Amazonia(2010), Université des Antilles (UA)-Coordination Régionale de la lutte contre le Virus de L'Immunodéficience Humaine (COREVIH)-Centre Hospitalier Andrée Rosemon [Cayenne, Guyane Française], Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), ANR-10- LABX-25-01,CEBA,Labex CEBA ANR-10- LABX-25-01, de Thoisy, Benoit, Fundação Oswaldo Cruz / Oswaldo Cruz Foundation (FIOCRUZ) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Climate Ecological phenomena and functions Seasonal variation RC955-962 Disease transmission Ecological niche Biome Forests Disease Vectors 0302 clinical medicine [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases Arctic medicine. Tropical medicine Zoonoses Prevalence Medicine and Health Sciences Biomass Leishmaniasis Mammals French guiana Ecology cutaneous Altitude Incidence Eukaryota Terrestrial Environments French Guiana Santé publique et épidémiologie Infectious Diseases Geography Leishmaniose Cut?nea / transmiss?o Vertebrates [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases Seasons Public aspects of medicine RA1-1270 Human Research Article Neglected Tropical Diseases Leishmaniose Cut?nea Neotropics Forest Ecology Ecological Metrics 030231 tropical medicine Leishmaniasis Cutaneous Skin leishmaniasis Ecosystems 03 medical and health sciences Population Metrics Cutaneous leishmaniasis Tropical rain forest Forest ecology Parasitic Diseases medicine Human footprint Humans Animals [SDV.EE.SANT] Life Sciences [q-bio]/Ecology environment/Health Ecosystem Forest Environmental temperature Poverty Population Density [SDV.EE.SANT]Life Sciences [q-bio]/Ecology environment/Health Ecologia / tend?ncias Protozoan Infections Population Biology Ecology and Environmental Sciences Organisms Public Health Environmental and Occupational Health Biology and Life Sciences Species Diversity South America 15. Life on land Tropical Diseases medicine.disease Human impact on the environment Ecossistema Species Interactions 030104 developmental biology South america 13. Climate action [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie Anthropology Vector (epidemiology) Amniotes Population density [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie Season Species richness Geographic distribution Prediction |
| Zdroj: | Repositório Digital do Instituto Evandro Chagas (Patuá) Instituto Evandro Chagas (IEC) instacron:IEC PLoS Neglected Tropical Diseases PLoS Neglected Tropical Diseases, 2019, 13 (8), pp.e0007629. ⟨10.1371/journal.pntd.0007629⟩ PLoS Neglected Tropical Diseases, Public Library of Science, 2019, 13 (8), pp.e0007629. ⟨10.1371/journal.pntd.0007629⟩ Repositorio EdocUR-U. Rosario Universidad del Rosario instacron:Universidad del Rosario Plos Neglected Tropical Diseases 8 (13), 21 p.. (2019) PLoS Neglected Tropical Diseases, Vol 13, Iss 8, p e0007629 (2019) |
| ISSN: | 1935-2727 1935-2735 |
| Popis: | A major challenge of eco-epidemiology is to determine which factors promote the transmission of infectious diseases and to establish risk maps that can be used by public health authorities. The geographic predictions resulting from ecological niche modelling have been widely used for modelling the future dispersion of vectors based on the occurrence records and the potential prevalence of the disease. The establishment of risk maps for disease systems with complex cycles such as cutaneous leishmaniasis (CL) can be very challenging due to the many inference networks between large sets of host and vector species, with considerable heterogeneity in disease patterns in space and time. One novelty in the present study is the use of human CL cases to predict the risk of leishmaniasis occurrence in response to anthropogenic, climatic and environmental factors at two different scales, in the Neotropical moist forest biome (Amazonian basin and surrounding forest ecosystems) and in the surrounding region of French Guiana. With a consistent data set never used before and a conceptual and methodological framework for interpreting data cases, we obtained risk maps with high statistical support. The predominantly identified human CL risk areas are those where the human impact on the environment is significant, associated with less contributory climatic and ecological factors. For both models this study highlights the importance of considering the anthropogenic drivers for disease risk assessment in human, although CL is mainly linked to the sylvatic and peri-urban cycle in Meso and South America. Author summary Cutaneous leishmaniasis is a vector-borne zoonotic disease with a complex transmission cycle that includes many parasite, vector and host species. This disease continues to pose public health problems worldwide despite the measures put in place. In recent years, methodological tools commonly used in ecology, called ecological niche prediction models, have made it possible to determine the environmental and anthropogenic variables that may be favourable to the presence of the host and vector species communities involved in the cycle and therefore to the presence of certain disease agents. The use of these models, based on the presence of human cases of the disease, can overcome some of the uncertainties concerning the diversity of the vectors and the potential hosts involved in the transmission cycle. This approach of health ecology combining ecology and epidemiology could provide new insights into understanding the cycle of disease transmission and the influence of environmental factors and thus improve the prediction of disease emergence and epidemics. It can be applied to various vector-borne diseases whose transmission cycles are still poorly understood and for which studies classically carried out in epidemiology have not prevented disease progression. |
| Databáze: | OpenAIRE |
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