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The Human Footprint and Climate Change Shape Current and Future Scenarios of Visceral Leishmaniasis Distribution in Doce River Basin in Brazil
Josefa Clara Lafuente Monteiro
Josefa Clara Lafuente Monteiro
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Sérvio Pontes Ribeiro
Sérvio Pontes Ribeiro
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Laboratory of Ecology of Diseases & Forests, Center for Research in Biological Sciences, Institute of Exact and Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Laboratory of Ecology of Diseases & Forests, Center for Research in Biological Sciences, Institute of Exact and Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Rafael Vieira Duarte
Rafael Vieira Duarte
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
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Andrés Lira-Noriega
Andrés Lira-Noriega
Consejo Nacional de Humanidades, Ciencias y Tecnologías; Red de Estudios Moleculares Avanzados, Instituto de Ecología, AC, Xalapa, Mexico;
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Octavio R. Rojas-Soto
Octavio R. Rojas-Soto
Red de Biología Evolutiva, Instituto de Ecología, AC, Xalapa, Mexico;
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Mariângela Carneiro
Mariângela Carneiro
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Postgraduate Program in Parasitology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil;
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Postgraduate Program in Parasitology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil;
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Alexandre Barbosa Reis
Alexandre Barbosa Reis
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Laboratory of Immunopathology, Center for Research in Biological Sciences, Institute of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
National Institute of Science and Technology in Tropical Diseases, INCT-DT, Salvador, Brazil
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Laboratory of Immunopathology, Center for Research in Biological Sciences, Institute of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
National Institute of Science and Technology in Tropical Diseases, INCT-DT, Salvador, Brazil
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Wendel Coura-Vital
wendelcoura@ufop.edu.br
Wendel Coura-Vital
Graduate Program in Biological Sciences, Center for Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil;
Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
National Institute of Science and Technology in Tropical Diseases, INCT-DT, Salvador, Brazil
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Laboratory of Epidemiology of Infectious Diseases, Department of Clinical Analysis, School of Pharmacy, Federal University of Ouro Preto, Ouro Preto, Brazil;
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ABSTRACT.
The identification of factors that influence the distribution of visceral leishmaniasis (VL) is key for future surveillance and control. This study sought to understand how environmental and climate variables can interfere with VL expansion in the Doce River basin located in Brazil. This ecological study explored the influence of anthropogenic, environmental, and climatic factors on VL expansion. Ecological niche modeling was used to assess the current situation and predict the future spread of the disease. The study used 855 human cases of VL recorded in the Doce River basin from 2001-2018 and analyzed them within the context of climatic and environmental variables. To model the current and future distributions, MaxEnt with the kuenm R package was used. To model the future projections, the global climate model of the National Centre for Meteorological Research (CNRM-CM6-1) was used as well as two Shared Socioeconomic Pathways (SSP370 and SSP585) for 2021–2040 and 2061–2080. Variables that contributed to the VL distribution were the human footprint index (62.6%), isothermality (28.1%), precipitation during the wettest month (6.4%), and temperature during the hottest month (3.8%). Future climate change scenarios showed areas suitable for the disease increasing over time (by about 7% between 2021 and 2041 and about 12% between 2061 and 2080) and the maintenance of the disease in places already considered endemic. Our results demonstrate the importance of anthropic and climatic factors in VL expansion. We hope that these results will contribute to boosting surveillance and vector control programs along the Doce River basin.
- Supplemental Materials (PDF 152.27 KB)
Author Notes
Financial support: The study was supported by the
Disclosures: As a requirement to obtain data on human cases, this study was submitted and approved by the Ethics Committee of the Federal University of Ouro Preto (CAAE: 07279419.0.0000.5150).
Current contact information: Josefa Clara Lafuente Monteiro, Sérvio Pontes Ribeiro, Rafael Vieira Duarte, Mariângela Carneiro, Alexandre Barbosa Reis, and Wendel Coura-Vital, Federal University of Ouro Preto, Ouro Preto, Brazil, E-mails: josefalafuente@hotmail.com, serviopr@gmail.com, rafael.vieira@aluno.ufop.edu.br, mariangelaufmg@gmail.com, alexreis@ufop.edu.br, and wendelcoura@ufop.edu.br. Andrés Lira-Noriega and Octavio R. Rojas-Soto, Instituto de Ecología, AC, Xalapa, Mexico, E-mails: aliranoriega@gmail.com and octavio.rojas@inecol.mx.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
Intergovernmental Panel on Climate Change, 2014. Climate Change 2014—Mitigation of Climate Change. Copenhagen, Denmark: IPCC.
-
2.
Baker RE et al., 2022. Infectious disease in an era of global change. Nat Rev Microbiol 20: 193–205.
-
3.
WHO, 2023. Global Report on Neglected Tropical Diseases 2023. Geneva, Switzerland: World Health Organization.
-
4.
Pan American Health Organization, 2022. Leishmanioses: Informe epidemiológico das Américas. Nº 11 (Dezembro de 2022). Washington, DC: PAHO.
-
5.
Desjeux P, 2004. Leishmaniasis: Current situation and new perspectives. Comp Immunol Microbiol Infect Dis 27: 305–318.
-
6.
Salomon OD, 2021. Lutzomyia longipalpis, gone with the wind and other variables. Neotrop Entomol 50: 161–171.
-
7.
Oryan A, Akbari M, 2016. Worldwide risk factors in leishmaniasis. Asian Pac J Trop Med 9: 925–932.
-
8.
Magalhães P, Mayrink W, Da Costa C, Mn M, Dias M, Sm B, 1980. Calazar na zona do Rio Doce—Minas Gerais. Resultados de medidas profilaticas. Revista Instituto Medicina Tropical São Paulo 22: 197–202.
-
9.
ESRI, 2011. ArcGIS Desktop: Version 10.3. Redlands, CA: Environmental Systems Research Institute.
-
10.
Aiello‐Lammens ME, Boria RA, Radosavljevic A, Vilela B, Anderson RP, 2015. spThin: An R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38: 541–545.
-
11.
Cobos ME, Peterson AT, Barve N, Osorio-Olvera L, 2019. Kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ 7: e6281.
-
12.
Booth TH, 2022. Checking bioclimatic variables that combine temperature and precipitation data before their use in species distribution models. Austral Ecology 47: 1506–1514.
-
13.
Escobar LE, Lira-Noriega A, Medina-Vogel G, Townsend Peterson A, 2014. Potential for spread of the white-nose fungus (Pseudogymnoascus destructans) in the Americas: Use of MaxEnt and NicheA to assure strict model transference. Geospat Health 9: 221–229.
-
14.
Phillips SJ, Dudík M, 2008. Modeling of species distributions with MaxEnt: New extensions and a comprehensive evaluation. Ecography 31: 161–175.
-
15.
Dalapicolla J, 2016. Tutorial de Modelos de Distribuição de Espécies: Guia Prático Usando o MaxEnt e o ArcGIS 10. Vitória, Brazil: Laboratório de Mastozoologia e Biogeografia, Universidade Federal do Espírito Santo.
-
16.
Liu C, Berry PM, Dawson TP, Pearson RG, 2005. Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28: 385–393.
-
17.
Fick SE, Hijmans RJ, 2017. WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas.Int J Climatol 37: 4302–4315.
-
18.
Zappa G, Shepherd TG, 2017. Storylines of atmospheric circulation change for European regional climate impact assessment.J Climate 30: 6561–6577.
-
19.
Osorio‐Olvera L, Lira‐Noriega A, Soberón J, Peterson AT, Falconi M, Contreras‐Díaz RG, Martínez‐Meyer E, Barve V, Barve N, 2020. ntbox: An R package with graphical user interface for modelling and evaluating multidimensional ecological niches. Methods Ecol Evol 11: 1199–1206.
-
20.
Owens HL et al., 2013. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. Ecol Model 263: 10–18.
-
21.
Fernandes GW et al., 2016. Deep into the mud: Ecological and socio-economic impacts of the dam breach in Mariana, Brazil. Natureza Conservação 14: 35–45.
-
22.
WHO, 2023. The Global Health Observatory Data. Leishmaniasis. Available at: https://www.who.int/data/gho/data/themes/topics/gho-ntd-leishmaniasis. Accessed January 5, 2024.
-
23.
WHO, 2021. Global Leishmaniasis Surveillance: 2021, Assessing the Impact of the COVID-19 Pandemic. Geneva, Switzerland: World Health Organization.
-
24.
Afonso MM, Duarte R, Miranda JC, Caranha L, Rangel EF, 2012. Studies on the feeding habits of Lutzomyia (Lutzomyia) longipalpis (Lutz & Neiva, 1912) (Diptera: Psychodidae: Phlebotominae) populations from endemic areas of American visceral leishmaniasis in northeastern Brazil. J Trop Med 2012: 858657.
-
25.
Lainson R, Dye C, Shaw JJ, Macdonald DW, Courtenay O, Souza AA, Silveira FT, 1990. Amazonian visceral leishmaniasis—Distribution of the vector Lutzomyia longipalpis (Lutz & Neiva) in relation to the fox Cerdocyon thous (linn.) and the efficiency of this reservoir host as a source of infection. Mem Inst Oswaldo Cruz 85: 135–137.
-
26.
Alexander B, de Carvalho RL, McCallum H, Pereira MH, 2002. Role of the domestic chicken (Gallus gallus) in the epidemiology of urban visceral leishmaniasis in Brazil. Emerg Infect Dis 8: 1480–1485.
-
27.
Karesh WB et al., 2012. Ecology of zoonoses: Natural and unnatural histories. Lancet 380: 1936–1945.
-
28.
Keesing F, Ostfeld RS, 2021. Impacts of biodiversity and biodiversity loss on zoonotic diseases. Proc Natl Acad Sci USA 118: e2023540118.
-
29.
Singh N, Tang Y, Zhang Z, Zheng C, 2020. COVID-19 waste management: Effective and successful measures in Wuhan, China. Resour Conserv Recycl 163: 105071.
-
30.
Codeço CT et al., 2021. Epidemiology, biodiversity, and technological trajectories in the Brazilian Amazon: From malaria to COVID-19. Front Public Health 9: 647754.
-
31.
Venter O et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat Commun 7: 12558.
-
32.
Hora AM, Dias CA, Guedes GR, Vieira da Costa AS, Júnior MJF, 2021. Da exploração econômica da bacia hidrográfica do Rio Doce ao atual processo de degradação de seus recursos naturais. Território, Mobilidade Populacional e Ambiente 201–234.
-
33.
Hassell JM, Begon M, Ward MJ, Fèvre EM, 2017. Urbanization and disease emergence: Dynamics at the wildlife–livestock–human interface. Trends Ecol Evol 32: 55–67.
-
34.
Oliveira AM, Lopez RVM, Dibo MR, Rodas LAC, Guirado MM, Chiaravalloti-Neto F, 2018. Dispersion of Lutzomyia longipalpis and expansion of visceral leishmaniasis in Sao Paulo state, Brazil: Identification of associated factors through survival analysis. Parasit Vectors 11: 503.
-
35.
Chavy A et al., 2019. Ecological niche modelling for predicting the risk of cutaneous leishmaniasis in the neotropical moist forest biome. PLoS Negl Trop Dis 13: e0007629.
-
36.
de Thoisy B, Silva NIO, Sacchetto L, de Souza Trindade G, Drumond BP, 2020. Spatial epidemiology of yellow fever: Identification of determinants of the 2016–2018 epidemics and at-risk areas in Brazil. PLoS Negl Trop Dis 14: e0008691.
-
37.
Ximenes MdFFdM, Castellón EG, de Souza MDF, Menezes AAL, Queiroz JW, Macedo E Silva VP, Jerônimo SMB, 2006. Effect of abiotic factors on seasonal population dynamics of Lutzomyia longipalpis (Diptera: Psychodidae) in northeastern Brazil. J Med Entomol 43: 990–995.
-
38.
Galati EAB, Nunes VLB, Rego FdA Jr., Oshiro ET, Rodrigues Chang M, 1997. Estudo de flebotomíneos (Diptera: Psychodidae) em foco de leishmaniose visceral no Estado de Mato Grosso do Sul, Brasil.Rev Saúde Pública 31: 378–390.
-
39.
da Silva Fonseca E, Rodgers MdSM, Casagrande B, Rodrigues NB, Guimarães RB, 2019. Influência de variáveis climáticas e ambientais na distribuição potencial do Lutzomyia longipalpis (Psychodidae: Phlebotominae) no estado de São Paulo, Brasil.Hygeia 15: 11–22.
-
40.
Duarte RV, Monteiro JCL, Cruz TC, Ribeiro LM, Franco Morais MH, Carneiro M, Reis AB, Ribeiro SP, Coura-Vital W, 2022. Influence of climatic variables on the number of cases of visceral leishmaniasis in an endemic urban area. Journal of Global Health Economics and Policy 2: 1–7.
-
41.
Marins de Aguiar G, Medeiros WM, 2003. Distribuição regional e habitats das espécies de flebotomíneos do Brasil. Flebotomíneos Brasil 207–255.
-
42.
Andrade-Filho JD, Scholte RGC, Amaral ALG, Shimabukuro PHF, Carvalho OS, Caldeira RL, 2017. Occurrence and probability maps of Lutzomyia longipalpis and Lutzomyia cruzi (Diptera: Psychodidae: Phlebotominae) in Brazil. J Med Entomol 54: 1430–1434.
-
43.
Deane LM, Deane MP, 1963. Visceral leishmaniasis in Brazil: Geographical distribution and transmission. Revista Instituto Medicina Tropical São Paulo 5: 198–212.
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