Evidence map›Paper›PMID 41501696›Full record

ArticleBMC infectious diseases2026

Serum geoepidemiology of leprosy biomarkers in a city-wide COVID-19 survey in Brazil.

Filipe Rocha Lima, Mateus Mendonça Ramos Simões, Bruno Vitiritti, Cláudia Maria Lincoln Silva, Natália Aparecida de Paula, Vanderson Mayron Granemann Antunes, Josafá Gonçalves Barreto, Fernando Bellissimo-Rodrigues, Rodrigo de Carvalho Santana, Marco Andrey Cipriani Frade

Abstract read
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In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Hidden burden of leprosy in incarcerated populations in northeast Brazil: active case detection and serological assessment.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Filipe Rocha LimaLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. rfilipelima@gmail.com.
Mateus Mendonça Ramos SimõesLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Bruno VitirittiLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Cláudia Maria Lincoln SilvaLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Natália Aparecida de PaulaLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Vanderson Mayron Granemann AntunesLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Josafá Gonçalves BarretoSpatial Epidemiology Laboratory, Federal University of Pará, Castanhal, Pará, Brazil.
Fernando Bellissimo-RodriguesDepartment of Social Medicine, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Rodrigo de Carvalho SantanaDivision of Infectious and Tropical Diseases, Department of Internal Medicine, Clinical Hospital of the Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Marco Andrey Cipriani FradeLaboratory for Skin Studies and Alternative Models, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. mandrey@fmrp.usp.br.

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/13429-1
6 · The paper itself

Abstract

backgroundCOVID-19 has created a significant global health emergency and triggered numerous seroepidemiological field tracing initiatives. The use of these samples becomes a timely tool for intensifying active case finding and early diagnosis of leprosy. This study aimed to conduct a seroepidemiological evaluation using leprosy biomarker antibodies against the Mce1A and PGL-I antigens, and to analyze the spatial distribution of both actively detected cases and antibody levels, thereby characterizing the geoepidemiological pattern of bacillary circulation, combined with case-screening strategies.

methodsA cross-sectional and geoepidemiological study was carried out using the biorepository of samples from the COVID-19 serosurvey in a municipality in southeastern Brazil. Screening diagnosis using LSQ and the artificial intelligence system MaLeSQs® was applied to investigate neurodermatological signs and symptoms of leprosy (n = 224). IgA, IgM, and IgG anti-Mce1A and IgM anti-PGL-I antibodies were measured using indirect ELISA (n = 195). Georeferencing was employed to create the distribution maps of individuals within the municipality. Global spatial autocorrelation analysis was performed and applied to the serological scores.

resultsThe responses to the clinical questionnaire reported the predominance of neurological signs and symptoms. Twelve new cases were diagnosed (32.4%), and the detection rate in the population sample evaluated was 6.15%. The IgA anti-Mce1A ELISA showed the highest seropositivity (55.3%), the highest rates [median = 0.93 (IQR = 0.59–1.41)]. The IgM and IgG anti-Mce1A serology showed higher rates (P < 0.0001) as compared to the anti-PGL-I serology. The overlap of positivity with the antibodies tested highlights the greater involvement of double or triple positives when Mce1A serology was used. IgM anti-Mce1A serology was positive in 66.7% [8/12 cases; median = 1.25 (IQR = 0.70–1.68)] of new cases detected. IgM anti-Mce1A showed the best serological performance, and its combination with MaLeSQs® (OR condition) achieved 100% sensitivity and NPV, with 68% specificity. Serology with the IgA antibody presented the highest rates in georeferencing analysis and served as an alert for contact with the bacillus. The sociodemographic variables tested did not exhibit statistical difference in spatial autocorrelation (p > 0.05), indicating the absence of a spatially clustered pattern for serological values in the analyzed territory.

conclusionThese findings identify IgM anti-Mce1A and MaLeSQs® as key tools to strengthen leprosy case-finding and screening efficiency. The study also revealed a diffuse pattern of transmission and exposure within the municipality and highlights the value of integrating serological biomarkers and digital diagnostic platforms to support earlier detection of leprosy.

Indexed as

Antibodies, BacterialCOVID-19LeprosyAdolescentAdultAgedAntigens, BacterialBiomarkersBrazilCross-Sectional StudiesFemaleGlycolipidsHumansImmunoglobulin GImmunoglobulin MMaleAntibodies, BacterialAntigens, BacterialBiomarkersGlycolipidsImmunoglobulin GImmunoglobulin Mphenolic glycolipid I, Mycobacterium lepraeAntibodiesBiomarkersGeoreferencingLeprosySerological testSurveillance

Identifiers

PMID41501696
PMCPMC12870420

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.