ArticleInfectious diseases of poverty2021
Spatial-temporal pattern of cutaneous leishmaniasis in Brazil.
Article in Infectious diseases of poverty, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 21 citations in OpenAlex.
- Ethnic-Racial and Spatial Inequalities of American Cutaneous Leishmaniasis in Brazil: A Nationwide Analysis of Cumulative Notification and Mortality.Pathogens (Basel, Switzerland) · 2026Article
- Fragments of urban forest in a large Amazonian city as habitats for potential Leishmania vectors.Parasite epidemiology and control · 2026Article
- Structural Drivers of Cutaneous Leishmaniasis: Examining How the Converging Effects of Displacement, Environmental Disruption, and Political Instability Reshape Epidemiology Beyond Endemic Regions.Tropical medicine and infectious disease · 2025Review
- Unveiling Novel Arginase Inhibitors for Cutaneous Leishmaniasis Using Drug Repurposing and Virtual Screening Approaches.Journal of cellular biochemistry · 2025Article
- Co-endemicity of schistosomiasis and tegumentary leishmaniasis: Spatial co-clustering in endemic areas.Tropical medicine & international health : TM & IH · 2025Article
- Molecular Detection of Trypanosomatids in Rodents and Marsupials in the State of Amapá, Brazil.Microorganisms · 2025Article
- Spatial epidemiologic trends of cutaneous leishmaniasis in Rio de Janeiro State, Southeast Brazil, 2001-2020.Revista do Instituto de Medicina Tropical de Sao Paulo · 2025Article
- Advances in Cysteine Protease B Inhibitors for Leishmaniasis Treatment.Current drug targets · 2025Review
- Tegumentary leishmaniasis in Brazil: priority municipalities and spatiotemporal relative risks from 2001 to 2020.Pathogens and global health · 2024Article
- Spatiotemporal pattern of leprosy in southwest China from 2010 to 2020: an ecological study.BMC public health · 2024Observational
- Incidence of Human and Free-Ranging Wild Rodent Infections withPathogens (Basel, Switzerland) · 2023Article
- Temporal patterns, spatial risks, and characteristics of tegumentary leishmaniasis in Brazil in the first twenty years of the 21st Century.PLoS neglected tropical diseases · 2023Article
- High-risk spatiotemporal patterns of cutaneous leishmaniasis: a nationwide study in Iran from 2011 to 2020.Infectious diseases of poverty · 2023Article
- Phylogenetic and biogeographical traits predict unrecognized hosts of zoonotic leishmaniasis.PLoS neglected tropical diseases · 2023Article
- First report of Leishmania (Mundinia) martiniquensis in South American territory and confirmation of Leishbunyavirus infecting this parasite in a mare.Memorias do Instituto Oswaldo Cruz · 2023Article
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundCutaneous leishmaniasis (CL) is a vector-borne disease classified by the World Health Organization as one of the most neglected tropical diseases. Brazil has the highest incidence of CL in America and is one of the ten countries in the world with the highest number of cases. Understanding the spatiotemporal dynamics of CL is essential to provide guidelines for public health policies in Brazil. In the present study we used a spatial and temporal statistical approach to evaluate the dynamics of CL in Brazil.
methodsWe used data of cutaneous leishmaniasis cases provided by the Ministry of Health of Brazil from 2001 to 2017. We calculated incidence rates and used the Mann-Kendall trend test to evaluate the temporal trend of CL in each municipality. In addition, we used Kuldorff scan method to identify spatiotemporal clusters and emerging hotspots test to evaluate hotspot areas and their temporal trends.
resultsWe found a general decrease in the number of CL cases in Brazil (from 15.3 to 8.4 cases per 100 000 habitants), although 3.2% of municipalities still have an increasing tendency of CL incidence and 72.5% showed no tendency at all. The scan analysis identified a primary cluster in northern and central regions and 21 secondary clusters located mainly in south and southeast regions. The emerging hotspots analysis detected a high spatial and temporal variability of hotspots inside the main cluster area, diminishing hotspots in eastern Amazon and permanent, emerging, and new hotspots in the states of Amapá and parts of Pará, Roraima, Acre and Mato Grosso. The central coast the state of Bahia is one of the most critical areas due to the detection of a cluster of the highest rank in a secondary cluster, and because it is the only area identified as an intensifying hotspot.
conclusionsUsing a combination of statistical methods we were able to detect areas of higher incidence of CL and understand how it changed over time. We suggest that these areas, especially those identified as permanent, new, emerging and intensifying hotspots, should be targeted for future research, surveillance, and implementation of vector control measures.
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