Abstract

This study’s objective was to analyze the spatial distribution pattern of new leprosy cases under 15 years and their contacts. A cross-sectional descriptive study covering sociodemographic characteristics and spatial analysis was carried out. The participants were from the city of Sobral, Ceará and the study was conducted between August 2014 and September 2015. Contacts were identified by the persons responsible for the children. Seropositivity was determined with the NDO-LID antigen, and positive cases were plotted on Voronoi polygons. Nine new cases of leprosy under 15 years of age have been found. The average number of people living with the cases was higher than the number of people living with non-household contacts. All household contacts were aware of other leprosy cases and had a higher rate of seropositive tests than non-household contacts. The index cases lived in the poorest regions of the municipality and hyper-endemic areas. Spatial analysis revealed a cluster of subclinical infection within a radius of 102 meters, suggesting that non-household transmission is related to proximity with seropositive individuals. In conclusion, the search for new leprosy cases cannot be restricted to household contacts.

Key words:
Leprosy; Child; Mycobacterium leprae; Epidemiology

Resumo

O objetivo deste estudo foi analisar o padrão de distribuição espacial de novos casos de hanseníase em menores de 15 anos e seus contatos. Estudo transversal, descritivo, abrangendo características sociodemográficas e análise espacial. Os participantes eram de Sobral, Ceará e o estudo foi realizado entre agosto de 2014 e setembro de 2015. Os contatos foram identificados pelos responsáveis pelas crianças. A soropositividade foi determinada com o antígeno NDO-LID e os casos positivos foram plotados em polígonos de Voronoi. Nove novos casos de hanseníase em menores de 15 anos foram encontrados. O número médio de pessoas que conviviam com os casos foi superior ao número de pessoas que conviviam com contatos não domiciliares. Todos os contatos domiciliares sabiam de outros casos de hanseníase e apresentaram maior taxa de testes soropositivos do que os contatos não domiciliares. Os casos índice residiam nas regiões mais pobres do município e em áreas hiperendêmicas. A análise espacial revelou um agrupamento de infecção subclínica em um raio de 102 metros, sugerindo que a transmissão não domiciliar está relacionada à proximidade com indivíduos soropositivos. Concluindo, a busca por novos casos de hanseníase não pode se restringir aos contatos domiciliares.

Palavras-chave:
Hanseníase; Criança; Mycobacterium Leprae; Epidemiologia

Introduction

Leprosy, one of the oldest diseases that affects men, remains a public health problem in less-developed countries. A trend analysis shows a gradual decrease in new cases of the disease in the world in the last 10 years, from 228,474 in 2010 to 202,185 in 2019¹1 World Heatlh Organization (WHO). Global leprosy (Hansen disease) update, 2019: Time to step-up prevention initiatives. Geneva: WHO; 2020 [cited 2021 mar 25]. Available from: https://www.who.int/publications/i/item/who-wer9536. This trend, however, is not uniform in all regions. According to data from the World Health Organization (WHO)¹1 World Heatlh Organization (WHO). Global leprosy (Hansen disease) update, 2019: Time to step-up prevention initiatives. Geneva: WHO; 2020 [cited 2021 mar 25]. Available from: https://www.who.int/publications/i/item/who-wer9536, 79% of leprosy cases are concentrated in three countries: India, Brazil and Indonesia.

The WHO has periodically been proposing a set of goals and strategies of global reach to be adopted by countries where leprosy is a relevant public health problem²2 World Heatlh Organization (WHO). Leprosy: Global consultation of National Leprosy Programme managers, partners and affected persons on Global Leprosy Strategy 2021-2030. Geneva: WHO; 2020 [cited 2021 mar 25]. Available from: https://www.who.int/publications/i/item/9789290228226.

In Brazil, the distribution of leprosy is quite uneven and predominant in the poorest regions: Midwest, North, and Northeast. Between 2009 and 2018, 81.0% of new leprosy cases were in these regions³3 Brasil. Ministério da Saúde (MS). Boletim Epidemiológico de Hanseníase. Brasília: MS; 2020.. In 2018, 1,691 new leprosy cases were reported in 153 of the 184 municipalities in Ceará, a state located in Northeastern Brazil which has a high detection rate of 18.6 / 100,000 inhabitants. In the same year, 65 new cases were registered in children under 15 in Ceará, representing 3.8% of new cases⁴4 Brasil. Ministério da Saúde (MS). Hanseníase - Indicadores Operacionais e Epidemiológicos [Internet]. Brasília: MS; 2019 [acessado 2021 mar 25]. Disponível em: http://tabnet.datasus.gov.br/cgi/sinannetbd/hanseniase/hans_indicadores.htm.

The strategy adopted in Brazil to combat leprosy consists of the detection of new cases and the investigation of all household and social contacts⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016.. The goals set by the Ministry of Health for fighting leprosy, until 2022, are: reducing 23% of leprosy cases in children and 12% in adults with degree 2 of physical disability, and to implement channels of notification for discriminatory practices against people affected by leprosy and their families in all units of the federation⁶6 Brasil. Ministério da Saúde (MS). Estratégia Nacional para Enfrentamento da Hanseníase 2019-2022. Brasília: MS; 2019..

Leprosy is transmitted from person to person by nasal secretions; however, the mechanism of transmission of the disease is not yet fully understood. The household contacts of multibacillary patients are at higher risk of acquiring the disease⁷7 Teixeira CSS, Pescarini JM, Alves FJO, Nery JS, Sanchez MN, Teles C, Ichihara MYT, Ramond A, Smeeth L, Penna MLF, Rodrigues LC, Brickley EB, Penna GO, Barreto ML, Silva RCR. Incidence of and factors associated with leprosy among domiciliary contacts of patients with leprosy in Brazil. JAMA Dermatol 2020; 156(6):640-648.^,88 Van Beers SM, Hatta M, Klatser PR. Patient Contact is the Major Determinant in Incident Leprosy: Implications for Future Control. Int J Lepr Other Mycobact Dis 1999; 67(2):119-128.. Fine et al.⁹9 Fine PE, Ponnighaus JM, Burgess P, Clarkson JA, Draper CC. Seroepidemiological studies of leprosy in northern Malawi based on an enzyme-linked immunosorbent assay using synthetic glycoconjugate antigen. Int J Lepr Other Mycobact Dis 1988; 56:243-254. found, in a study in Malawi, that only 15% to 30% of new cases had household contacts as a source of infection, suggesting that the majority were infected through contact with non-household cases. Santos et al.¹⁰10 Santos SD, Penna GO, Costa MCN, Natividade MS, Teixeira MG. Leprosy in children and adolescents under 15 years old in an urban centre in Brazil. Mem Inst Oswaldo Cruz 2016; 111:359-364. in a study carried out in Salvador, Bahia, showed that 17% of children and adolescents under 15 years of age with leprosy reported not having had contact with known cases of the disease. Moura et al.¹¹11 Moura MLN, Dupnik KM, Sampaio GAA, Nóbrega PFC, Jeronimo AK, Nascimento Filho JM, Dantas RLM, Queiroz JW, Barbosa JD, Dias G, Jeronimo SMB, Souza MCF, Nobre ML. Active surveillance of Hansen's Disease (leprosy): importance for case finding among extra-domiciliary contacts. PLoS Negl Trop Dis 2013; 7(3):e2093. showed that living next door to a multibacillary case (MB) may present a similar risk to living in the same house as a patient.

The detection of new cases of leprosy in children and adolescents under the age of 15 years has an important epidemiological significance, as it reveals the recent and continuous transmission of Mycobacterium leprae (M. leprae) in the community. Therefore, any investment in the surveillance of contacts in this age group is crucial for the identification and control of the sources of infection¹²1 World Heatlh Organization (WHO). Global leprosy (Hansen disease) update, 2019: Time to step-up prevention initiatives. Geneva: WHO; 2020 [cited 2021 mar 25]. Available from: https://www.who.int/publications/i/item/who-wer9536^,1.

Epidemiological studies on leprosy using spatial analysis techniques have been conducted to identify critical areas and risk groups for disease transmission. Previous studies have been done in Brazil in this line of investigation and using spatial techniques to improve the planning of contact surveillance and to control of the spread of M. leprae¹³13 Monteiro LD, Mota RMS, Martins-Melo FR, Alencar CH, Heukelbach J. Social determinants of leprosy in a hyperendemic State in North Brazil. Rev Saude Publica 2017; 51:70.

14 Freitas LRS, Duarte EC, Garcia LP. Analysis of the epidemiological situation of leprosy in an endemic area in Brazil: spatial distribution in the periods 2001 - 2003 and 2010 - 2012. Rev Bras Epidemiol 2017; 20(4):702-713.

15 Souza CDF, Santos FGB, Marques CS, Leal TC, Paiva JPS, Araújo EMCF. Spatial study of leprosy in Bahia, Brazil, 2001-2012: an approach based on the local empirical Bayesian model. Epidemiol Serv Saúde 2018; 27(4):e2017479.

16 Fernandes MVC, Esteves AVF, Santos CB, Castro DB. Distribuição espacial e temporal da incidência da hanseníase em menores de 15 anos em Manaus. Enferm Bras 2019; 18(2):264-272.

17 Jesus MS, Sandes TA, Lima ACR. Epidemiological characteristics and spatial analysis of leprosy cases in an endemic municipality. Rev Rene 2019; 20:e41257-e41257.^-1818 Souza EA, Ferreira AF, Pinto MSAP, Heukelbach J, Oliveira HX, Barbosa JC, Ramos Junior AN . Performance of leprosy case-contact surveillance: a space-time analysis in Bahia State, Northeast Brazil. Cad Saúde Pública 2019; 35(9):e00209518..

Considering that children and adolescents, in addition to their home contacts, have other contacts (such as neighbors and schoolmates), sources of transmission of leprosy can be found outside their homes.

This study hypothesizes that spatial analysis can be used to reveal that leprosy transmission occurs both through household and non-household contacts; therefore, the investigation should not be restricted to patients’ homes.

Effective strategies for controlling the transmission of leprosy are urgently needed. In this context, this study aims to analyze the spatial distribution pattern of new leprosy cases in children and adolescents under 15 years of age and their household and non-household contacts.

Materials and methods

This is a cross-sectional study with a descriptive analysis of sociodemographic characteristics and spatial analysis of new leprosy cases in children and adolescents under 15 years of age (index cases) and their household and non-household contacts, residing in Sobral, between August 2014 and September 2015.

This study is an excerpt from a larger project entitled “Leprosy in children under 15 years: investigation of potential contacts and use of genetic tools in the study of transmission of Mycobacterium leprae” (notice nº 07/2013) of the Research Program for the SUS (PPSUS), held in Sobral, Ceará, from 2014 to 2015.

In 2019, Sobral had an estimated population of 208.953 inhabitants and a Human Development Index of 0.714, measured in 2010 by the Brazilian Institute of Geography and Statistics¹⁹19 Instituto Brasileiro de Geografia e Estatística (IBGE). Censos Demográficos. Brasil em Síntese. Municípios Ceará: Sobral [Internet]. Brasília: IBGE; 2017 [acessado 2021 mar 25]. Disponível em: https://cidades.ibge.gov.br/brasil/ce/sobral/panorama. The general rate of leprosy detection in the municipality in 2019 was 39.7 new cases / 100,000 inhabitants, with neighborhood detection rates ranging from 0 to 169.2 cases / 100,000 inhabitants. This rate characterizes the municipality as having a very high endemicity (20,00 to 39,99 / 100,000 inhab.). The leprosy detection rate in children and adolescent under 15 years of age was 17.9 cases / 100,000 inhabitants in 2019²⁰20 Brasil. Ministério da Saúde (MS). Banco de dados do Sistema de Informação de Notificação de Agravos - Hanseníase (2005-2019). Brasília: MS; 2020., which characterizes the endemicity of the municipality as high (≥10.00 per 100 mil inhab.)⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016..

Between August 2014 and September 2015, nine leprosy cases were diagnosed in children and adolescents under 15 years. Four cases were identified in routine consultations, three by active search in homes located in hyper-endemic areas, and two by active search in public schools.

The active search for new cases started in the homes of people with leprosy diagnosed in the year before the study and extended to each case’s neighboring homes. Trained community health agents (CHA) did this search, and suspected cases were referred to the primary care centers located closest to the residences. A trained physician made the diagnostic confirmation. The active search among students was carried out in public schools in Sobral²¹21 Brasil. Ministério da Saúde (MS). Informe Técnico: Campanha Nacional de Hanseníase, Verminoses, Tracoma e Esquistossomose [Internet]. Brasília: Ministério da Saúde; 2015 [cited 2021 Mar 25]. Available from: http://portalarquivos2.saude.gov.br/images/pdf/2015/agosto/19/Informe-Campanha-2-2015-maio.pdf
http://portalarquivos2.saude.gov.br/imag... . Parents or guardians should mark the location of the dermatological lesions found on the student’s body using a tracking card. Children and adolescents under the age of 15 with injuries were referred to the primary care centers. All cases were confirmed by clinical examination, smear test, and skin biopsy.

The index cases, according to the operational classification of the World Health Organization (WHO), were defined as multibacillary (MB) and paucibacillary (PB) and, based on the clinical classification of Madrid, as dimorphic (D), virchowian (V) indeterminate (I), and tuberculoid (T)²²22 Brasil. Ministério da Saúde (MS). Guia prático sobre a hanseníase. Brasília: Departamento de Vigilância das Doenças Transmissíveis; 2017..

Parents or guardians indicated the household and non-household contacts of the index cases. People who lived with the index cases in the five years before their diagnosis were considered household contacts. Anyone who did not live in the same household but had regular contact with the index cases was considered a non-household contact. Regular contact was defined as meetings with a minimum frequency of once every three months in the five years before the index case diagnosis, and who had personal contact with him, such as eating or sleeping together, having an affective relationship, or talking regularly.

Those responsible for index cases (parents or guardians) answered specific semi-structured questionnaires with socioeconomic and demographic information, family composition, social contacts, number of people living with the index cases, and clinical and laboratory data (variables of interest). The economic class of the head of the family was classified using the Brazilian Economic Classification Criteria²³23 Associação Brasileira de Empresas de Pesquisa (ABEP). Critério Brasil 2015 e atualização da distribuição de classes para 2016. São Paulo: ABEP; 2016.. All study participants underwent the NDO-LID rapid qualitative serological test²⁴24 Duthie MS, Balagon MF, Maghanoy A, Orcullo FM, Cang M, Dias RF, Collovati M, Reed SG. Rapid quantitative serological test for detection of infection with Mycobacterium leprae, the causative agent of leprosy. J Clin Microbiol 2014; 52(2):613-619., for diagnosis of anti-PGL-1 IgM and anti-LID-1 IgG, according to the manufacturer’s recommendations (Orange Life®, Rio de Janeiro, Brazil).

The average leprosy detection rates in Sobral neighborhoods and districts, from 2005 to 2016, were estimated by new cases registered in the National Disease Notification System²⁰20 Brasil. Ministério da Saúde (MS). Banco de dados do Sistema de Informação de Notificação de Agravos - Hanseníase (2005-2019). Brasília: MS; 2020. and on linear interpolation data from the 2000 and 2010 censuses of the IBGE²⁵25 Instituto Brasileiro de Geografia e Estatística (IBGE). Índice de Censos Demográfico 2010 - Dados do Universo_Meso_Microregioes_Distritos_Subdistritos_Bairros [Internet]. Brasília: IBGE; 2016 [acessado 2021 mar 25]. Disponível em: ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2000/Dados_do_Universo/Meso_Microregioes_Distritos_Subdistritos_Bairros/. The following endemicity categories were adopted: 1) hyperendemic, detection rate of new cases ≥ 40.00 / 100,000 inhabitants; 2) very high, between 39.99 and 20.00 / 100,000; 3) high, between 19.99 and 10.00 / 100,000; 4) medium, from 9.99 to 2.00 / 100,000; and 5) low <2.0 / 100,000 inhabitants⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016..

Spatial Analysis

The index cases’ addresses and their household and non-household contacts were georeferenced on MyGeoPosition.com to define the latitude and longitude values, which were inserted in an SPSS database and transferred to QGIS 2.18 to generate maps. Two layers of maps were superimposed, the first with a thematic map with the divisions of Sobral neighborhoods and districts and their respective average rates of detection of new cases per 100 thousand inhabitants, categorized by the leprosy endemic parameters of the Ministry of Health⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016.. The second layer consisted of a map with georeferenced data for the residences of the index cases and their household and non-household contacts, identified with the individual history of leprosy illness and the results of the NDO-LID rapid test. The maps’ overlapping allowed the visualization of the index cases’ location and their household and non-household contacts in the areas according to the endemic level of leprosy. The positivity for anti-M. leprae was analyzed in the Voronoi polygons to estimate the proximity between NDO-LID positive contacts.

Nearest neighbor interpolation (NNI)²⁶26 Etherington TR. Discrete natural neighbour interpolation with uncertainty using cross-validation error-distance fields. PeerJ Computer Sci 2020; 6:e282. was used to characterize the disease’s spatial patterns and assess cases’ clustering in an area. The distance between each point and its closest point was examined using the NNI and compared with the expected values ​​for a random sample of points in a complete spatial randomness (CSR) pattern. The null hypothesis of CSR was tested using the Z statistic. A negative Z score indicates clustering, while a positive score indicates dispersion. The grouping check was performed for NDO-LID-positive contacts and index cases. The bivariate analysis was performed between the variables of interest to the household and non-household contacts. A non-parametric test was performed, specifically, the Mann-Whitney test for comparing the distributions between household and non-household contacts. A significance level of 5% was adopted in all analyzes. The questionnaire data were presented with absolute and relative frequencies and analyzed in SSPS v. 23.0.

Ethical considerations

The study was approved by the Research Ethics Committee of the University in which the study was undertaken, following the Declaration of Helsinki’s ethical recommendations. Written consent was obtained from the participants or their guardians. The identity of the cases was not revealed to non-household contacts.

Results

Nine new leprosy cases were studied in children and adolescents under 15 years of age and a total of 151 contacts (36 household and 115 non-household). Index cases had an average of four household, and 12 non-household contacts, with a range of 7 to 25 non-household contacts reported. Each household contact reported regular contact with 6 to 30 people, and each non-household contact reported regular contact with 6 to 23 people. It was not possible to identify school contacts due to refusal from parents or guardians of index cases. One of the participants’ fathers did not allow the researchers to access all non-household contacts of the index case.

The index cases’ age ranged from 3 to 14 years, and the age range of household and non-household contacts was higher (Table 1). Most of the participants were female, and most families were headed by illiterate parents, mainly among non-household contacts. Most of the participants’ families received up to 2 minimum wages and belonged to the lowest economic class. No answers were obtained from two non-household contacts regarding the head of the family’s education and income. An average number of 5.9 (1.9) and 4.6 (2.0) people living in the houses of index cases and non-household contacts were observed, respectively (p <0.001). Most houses (137/160; 85.7%) were located on a paved road; they had access to electricity and communication by landline or cell phone. Most houses were made of bricks and had running water, a sewage network, and access to public waste collection (data not shown).

As for the WHO operational classification of index cases, five were PB and four MB. According to the Madrid classification, three cases were tuberculoid (T), two indeterminate (I), two dimorphic (D), and two virchowian (V).

The data in Table 2 indicate no statistical difference between household and non-household contacts concerning current or previous leprosy. The index cases knew someone who has/had leprosy, eight maintained regular contact with these people, and four maintained contact inside and outside the home. All household contacts knew people with leprosy in addition to index cases (p <0.001), and 38.9% (14/36) reported having regular contact with these people. Among the household contacts, regular contact with people with a current or previous leprosy history ranged from 1 to 7. Most of the non-household contacts knew other leprosy cases, and 59.1% (68/115) reported having regular contact with these cases. The rapid NDO-LID test was positive in only three of the nine index cases and was not statistically different for household and non-household contacts (p = 0.116).

Figure 1, Map 1A, shows the location of the nine index cases. The distance between the residences of the index cases was an average of 1,701 (390) meters. It is observed that the index cases are located in the peripheral neighborhoods in the urban area of ​​Sobral. The NNI indicated spatial randomness in the distribution of cases (NNI = 1.4; Z-score = 2.3) with an average distance between neighboring cases closer to 643 meters. Map 1B shows index cases and non-household contacts in Sobral and other nearby municipalities (Acaraú, Granja, Massapê, Meruoca, Cariré, and Forquilha). These municipalities are, on average, 53.3 (40.9) km distant from Sobral. On the 1C map, it is possible to see that the houses of all index cases are located in areas classified as hyper-endemic according to the Ministry of Health’s parameters.

Figure 2 shows the cases’ spatial distribution and negative (n = 122) and positive (N = 25) household and non-household contacts based on the NDO-LID rapid test, distributed in 35 households in 16 Voronoi polygons. The NNI calculated for the positive NDO-LID resulted in a pattern of grouped cases (NNI = 0.3; Z-score = -7.5), with an average distance between the nearest neighbors of 102.3 meters. The groupings of positive NDO-LID participants, however, occurred randomly; that is, the positive NDO-LID individuals were close to both a positive and a negative NDO-LID case.

Discussion

The results of the descriptive analysis carried out in the present study show that most index cases and their non-household contacts belong to the lower socioeconomic classes and live in households with a high family density. It was also observed that the presence of disease and subclinical infection, confirmed by the rapid NDO-LID test, did not show any significant difference between household and non-household contacts. The results of the spatial analysis indicated that the index cases reside close to cases with subclinical infection, which present a pattern of clustering among the nearest neighbors of up to 102.3 meters. It is noteworthy that the grouping was random both for cases with a positive NDO-LID test and for those with a negative result.

The neighborhoods where index cases and most of their non-household contacts reside are located in hyper-endemic regions of Sobral, with a high population density and poor socioeconomic conditions¹¹11 Moura MLN, Dupnik KM, Sampaio GAA, Nóbrega PFC, Jeronimo AK, Nascimento Filho JM, Dantas RLM, Queiroz JW, Barbosa JD, Dias G, Jeronimo SMB, Souza MCF, Nobre ML. Active surveillance of Hansen's Disease (leprosy): importance for case finding among extra-domiciliary contacts. PLoS Negl Trop Dis 2013; 7(3):e2093.^,2727 Bakker MI, Hatta M, Kwenang A, Van Mosseveld P, Faber WR, Klatser PR, Oskam L. Risk factors for developing leprosy - a population-based cohort study in Indonesia. Lepr Rev 2006; 77(1):48-61.. It was found that the household group had a significantly higher home density than the non-household group; however, both live, on average, with more people in the same house than the general average of the city, which was 3.7 inhabitants in 2010²⁸28 Instituto Brasileiro de Geografia e Estatística (IBGE). Caracteristicas da População e dos Domicílios: Resultados do Universo-Censo 2010 [Internet]. Brasília: IBGE; 2017 [acessado 2021 mar 25]. Disponível em: ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_do_Universo/Agregados_por_Setores_Censitarios/. Fabri²⁹29 Fabri ACOC. Prevalência de infecção pelo Mycobacterium leprae na população da microrregião de Almenara [dissertação]. Belo Horizonte: Universidade Federal de Minas Gerais; 2011. and Gomes et al.³⁰30 Gomes LC, Cortela DDCB, Silva EA, Silva AMCD, Ferreira SMB. Leprosy: prevalence and factors associated with seropositivity for anti-NDO-LID antibodies in children under 15 years of age. An Bras Dermatol 2019; 94:405-410. showed that a high family density is associated with a high risk of M. leprae infection.

Sobral presents a spatial distribution with well-marked social differences. According to the 2010 census²⁵25 Instituto Brasileiro de Geografia e Estatística (IBGE). Índice de Censos Demográfico 2010 - Dados do Universo_Meso_Microregioes_Distritos_Subdistritos_Bairros [Internet]. Brasília: IBGE; 2016 [acessado 2021 mar 25]. Disponível em: ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2000/Dados_do_Universo/Meso_Microregioes_Distritos_Subdistritos_Bairros/, the average number of houses at Sobral headquarters with monthly per capita income of up to 1/4 of a minimum wage was 16.2%. However, some neighborhoods vary between 18% and 25% with this income value. The neighborhoods of the index cases show homogeneity in terms of schooling, income, and social class. The index cases and most non-household contacts are located within the Voronoi polygons, highlighting the association between leprosy and low socioeconomic level, which can be understood as a grouping of contiguous areas, covering the disease and its risk factors. These data may explain the absence of significant differences in the sociodemographic variables between household and non-household contacts. Kerr-Pontes et al.³¹31 Kerr-Pontes LR, Montenegro AC, Barreto ML, Werneck GL, Feldmeier H. Inequality and leprosy in Northeast Brazil: an ecological study. Int J Epidemiol 2004; 33:262-269. already found this association in Sobral city. Several authors have already shown that the low social status of families is an important risk factor for leprosy³²32 Kerr-Pontes LRS, Barreto ML, Evangelista CMN, Rodrigues LC, Heukelbach J, Feldmeier H. Socioeconomic, environmental, and behavioural risk factors for leprosy in North-east Brazil: results of a case-control study. Int J Epidemiol 2006; 35(4):994-1000.

33 Arraes MLBM, Holanda MV, Lima LNGC, Beltrão Sabadia JAB, Duarte CR, Almeida RLF, Kendall C, Kerr LRS, Frota CC. Natural environmental water sources in endemic regions of northeastern Brazil are potential reservoirs of viable Mycobacterium leprae. Mem Inst Oswaldo Cruz 2017; 112(2):805-811.

34 Imbiriba EB, Hurtado-Guerrero JC, Garnelo L, Levino A, Cunha MG, Pedrosa V. Epidemiological profile of leprosy in children under 15 in Manaus (Northern Brazil), 1998-2005. Rev Saude Publica 2008; 42(6):1021-1026.^-3535 Bakker MI, Hatta M, Kwenang A, Faber WR, Van Beers SM, Klatser PR, Oskam L. Population survey to determine risk factors for Mycobacterium leprae transmission and infection. Int J Epidemiol 2004; 33(6): 1329-1336.. In this respect, it is important to comment on the study of Nery et al.³⁶36 Nery JS, Ramond A, Pescarini JM, Alves A, Strina A, Ichihara MY, Penna MLF, Smeeth L, Rodrigues LC, Barreto ML, Brickley EB, Penna GO. Socioeconomic determinants of leprosy new case detection in the 100 Million Brazilian Cohort: a population-based linkage study. Lancet Glob Health 2019; 7(9):e1226-e1236., which showed an association between the reduction of leprosy cases in Brazil and the implementation of the “Bolsa Família” income transfer program, almost two decades ago. These authors draw attention to the current government policies to reduce social and economic safety net programs at a time of economic decline and high unemployment and poverty rates³⁷37 Neri MC. A Escalada da Desigualdade - Qual foi o Impacto da Crise sobre Distribuição de Renda e Pobreza? Rio de Janeiro: FGV Social; 2019.. These political and economic changes generate a high risk of leprosy for a substantial number of Brazilians. After a 13-year decline in leprosy prevalence, the detection of new leprosy cases has already increased by 14% between 2016 and 2018³3 Brasil. Ministério da Saúde (MS). Boletim Epidemiológico de Hanseníase. Brasília: MS; 2020..

Household and non-household contacts should not be treated as populations without the disease. It is necessary to reinforce the importance of investigating contacts beyond the cases’ homes. The investigation of leprosy cases’ contacts is a regular activity of disease control programs, with the primary objective of detecting cases early among those who live or have lived with the newly diagnosed cases and aims to discover new possible sources of infection⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016.. As of 2016, according to the Ministry of Health, the investigation of contacts, in addition to households, should include non-household contacts⁵5 Brasil. Ministério da Saúde (MS). Diretrizes para vigilância, atenção e eliminação da Hanseníase como problema de saúde pública: Manual técnico-operacional. Brasília: MS; 2016.. Despite this change in the recommendation regarding contacts investigation, references about this practice appear only in studies by researchers, and there are no specific publications from the Ministry of Health about the investigation of contacts of leprosy cases. It is possible to infer that this practice is not yet being developed in all Brazilian municipalities. Public health professionals and managers need to be encouraged to use strategies that facilitate access to these non-household contacts.

The fact that household and non-household contacts know and maintain regular contact with other people who have/have already had leprosy indicates other potential sources of infection. One of the leprosy characteristics in endemic areas is the high power of spread¹¹11 Moura MLN, Dupnik KM, Sampaio GAA, Nóbrega PFC, Jeronimo AK, Nascimento Filho JM, Dantas RLM, Queiroz JW, Barbosa JD, Dias G, Jeronimo SMB, Souza MCF, Nobre ML. Active surveillance of Hansen's Disease (leprosy): importance for case finding among extra-domiciliary contacts. PLoS Negl Trop Dis 2013; 7(3):e2093.^,3838 Reis AS, Souza EA, Ferreira AF, Silva GV, Macedo SF, Araújo OD, Cruz JR, García GSM, Carneiro MAG, Barbosa JC, Ramos Júnior AN. Overlapping of new leprosy cases in household contact networks in two municipalities in North and Northeast Brazil, 2001-2014. Cad Saude Publica 2019; 35(10):e00014419.. This, too, explains the broad pattern of the spatial distribution of leprosy found in this study.

Van Beers et al.⁸8 Van Beers SM, Hatta M, Klatser PR. Patient Contact is the Major Determinant in Incident Leprosy: Implications for Future Control. Int J Lepr Other Mycobact Dis 1999; 67(2):119-128. in a study in Indonesia, reported that of 101 new cases of leprosy over 25 years, 78% could be associated to contact with another leprosy patient (28% of these were identified as household contacts, 36% as neighbors, and the remaining 15% as social contacts). Besides, the authors concluded that 72% of contacts were non-household. These results reinforce the hypothesis that, in hyper-endemic areas, the entire population is exposed to M. leprae. Thus, it is important to expand the scope for investigating contacts of leprosy cases.

The non-household investigation encounters many barriers. The stigma of leprosy is still a problem and addressing non-household contacts is difficult. In this study, some parents or guardians did not recognize schoolmates and teachers of index cases as regular contacts.

The NDO-LID test proved to be a practical method in identifying MB and PB leprosy cases³⁹39 Marçal PHF, Fraga LAO, Mattos AMM, Menegati L, Coelho ACOC, Pinheiro RO, Sarno EN, Duthie MS, Teixeira HC. Utility of immunoglobulin isotypes against LID-1 and NDO-LID for, particularly IgG1, confirming the diagnosis of multibacillary leprosy. Mem Inst Oswaldo Cruz 2018; 113(5):e170467.. The LID-1reactivity allows leprosy diagnosis 6 to 8 months before the disease’s clinical diagnosis, significantly anticipating treatment, and reducing transmission rates⁴⁰40 Duthie MS, Goto W, Ireton GC, Reece ST, Cardoso LPV, Martelli CMT, Stefani MMA, Nakatani M, Jesus RC, Netto EM, Balagon MVF, Tan E, Gelber RH, Maeda Y, Makino M, Hoft D, Reed SG. Use of protein antigens for early serological diagnosis of leprosy. Clin Vaccine Immunol 2007; 14(11):1400-1408..

There was no significant difference between the household and non-household groups concerning the anti-NDO-LID test positivity, which can be explained by the area’s high endemicity. Frota et al.⁴¹41 Frota CC, Freitas MVC, Foss NT, Lima LNC, Rodrigues LC, Barreto ML, Kerr LRS. Seropositivity to anti-phenolic glycolipid-I in leprosy cases, contacts and no known contacts of leprosy in an endemic and a non-endemic area in northeast Brazil. Trans R Soc Trop Med Hyg 2010; 104:490-495. conducted a case-control study in Sobral using ELISA (anti-PGL-1) and found no significant difference in seropositivity between contacts and non-contacts of leprosy cases. Marçal et al.³⁹39 Marçal PHF, Fraga LAO, Mattos AMM, Menegati L, Coelho ACOC, Pinheiro RO, Sarno EN, Duthie MS, Teixeira HC. Utility of immunoglobulin isotypes against LID-1 and NDO-LID for, particularly IgG1, confirming the diagnosis of multibacillary leprosy. Mem Inst Oswaldo Cruz 2018; 113(5):e170467. and Fabri et al.⁴²42 Fabri ACOC, Carvalho APM, Araujo S, Goulart LR, Mattos AMM, Teixeira HC, Goulart IMB, Duthie MS, Correa-Oliveira R, Lana FCF. Antigen-specific assessment of the immunological status of various groups in a leprosy endemic region. BMC Infect Dis 2015; 15:218. found similar results in studies carried out in Rio de Janeiro and Uberlândia. Moet et al. ^43, in a review article on risk factors for the development of clinical leprosy between contacts, showed that leprosy control could be achieved by identifying the positive contacts for anti-PGL-1 tests.

The study’s spatial analysis showed that the index cases were related to non-household contacts, many of them residing in neighboring municipalities (Forquilha, Massapê, Meruoca, Cariré, Granja, Acaraú). From 2014 to 2018, these municipalities had average leprosy detection rates that characterized a medium to very high endemicity²2 World Heatlh Organization (WHO). Leprosy: Global consultation of National Leprosy Programme managers, partners and affected persons on Global Leprosy Strategy 2021-2030. Geneva: WHO; 2020 [cited 2021 mar 25]. Available from: https://www.who.int/publications/i/item/9789290228226. This result highlights leprosy expansion in other areas outside Sobral and the idea that the investigation of contacts should not be restricted to geopolitical limits.

Another result of the spatial analysis was that all index cases lived within the urban perimeter and in Sobral neighborhoods, with an average distance between them of approximately 2 km. Although an average distance was found between the index cases, a clustering pattern (Z-score = -7.5) of subclinical infection within a radius of up to 102 meters was observed, suggesting that non-household transmission may be associated with proximity to seropositive individuals. This result suggests that there may be other cases of undiagnosed leprosy in the studied areas. Barreto et al.⁴⁴44 Barreto JG, Bisanzio D, Guimarães LS, Spencer JS, Vazquez-Prokopec GM, Kitron U, Salgado CG. Spatial analysis spotlighting early childhood leprosy transmission in a hyperendemic municipality of the Brazilian Amazon region. PLoS Negl Trop Dis 2014; 8:e2665., in a study, carried out in the city of Castanhal, Pará, found PGL-1seropositive individuals living within 200 meters of the index case. In Indonesia, Bakker et al.³⁵35 Bakker MI, Hatta M, Kwenang A, Faber WR, Van Beers SM, Klatser PR, Oskam L. Population survey to determine risk factors for Mycobacterium leprae transmission and infection. Int J Epidemiol 2004; 33(6): 1329-1336., in a study conducted in Mar das Flores islands, showed that living at 75 meters or less from a PGL-1 positive person increases subclinical infection risk (OR 1.24).

In Sobral, a study by Arraes et al. ^33,   using the Voronoi diagrams, demonstrated the presence of M. leprae mRNA in open water samples close to the homes of leprosy cases. A case-control study carried out in this city by Kerr-Pontes et al.³²32 Kerr-Pontes LRS, Barreto ML, Evangelista CMN, Rodrigues LC, Heukelbach J, Feldmeier H. Socioeconomic, environmental, and behavioural risk factors for leprosy in North-east Brazil: results of a case-control study. Int J Epidemiol 2006; 35(4):994-1000. showed that the habit of bathing in natural streams increases the risk of leprosy. Turankar et al.⁴⁵45 Turankar RP, Lavania M, Singh M, Sengupta U, Sai KS, Jadhav RS. Presence of viable Mycobacterium leprae in environmental specimens around houses of leprosy patients. Indian J Med Microbiol 2016; 34(3):315-321., in a study with samples collected from patients and soil from different environments in the endemic region of Purulia district, West Bengal, India, demonstrated the presence of M. leprae mRNA in the peri-household soil of the cases. Bakker et al.³⁵35 Bakker MI, Hatta M, Kwenang A, Faber WR, Van Beers SM, Klatser PR, Oskam L. Population survey to determine risk factors for Mycobacterium leprae transmission and infection. Int J Epidemiol 2004; 33(6): 1329-1336., in a metagenome study conducted in Asia, found that the presence of airborne bacteria was demonstrated at 3 to 5 km from the point of origin, comprising 30% of the phylum Actinobacteria belonging to the genus Mycobacterium. These studies indicate that the disease’s prevalence may be related to direct transmission and that the characteristics of the environment may contribute to the high endemicity of some regions.

One of the study’s limitations was that there was no comparison between positivity cases for NDO-LID and other specific M. leprae antigens. Another limitation was the restriction of the school population in the study. The stigma hindered the inclusion of more contacts, so some parents or guardians did not feel free to reveal all non-household contacts of the index cases.

Despite the limitations mentioned above, the study showed that transmission sources go beyond geopolitical limits, reaching areas recognized or not as endemic. Spatial analysis techniques can be an important tool to identify groups with a given disease or subclinical infection, and critical areas for leprosy control. Using spatial analysis techniques in their studies, Mencaroni et al.⁴⁶46 Mencaroni DA, Pinto Neto JM,Villa TCS, Oliveira MHPD. Análise espacial da endemia hansênica na área urbana do município de Fernandópolis/SP. Hansen Int 2004; 29(1):12-20., Cury et al.⁴⁷47 Cury MRCO, Paschoal VD, Nardi SMT, Chierotti AP, Rodrigues Júnior AL, Chiaravalloti-Neto F. Spatial analysis of leprosy incidence and associated socioeconomic factors. Rev Saude Publica 2012; 46(1):110-118., and Jesus et al.¹⁷17 Jesus MS, Sandes TA, Lima ACR. Epidemiological characteristics and spatial analysis of leprosy cases in an endemic municipality. Rev Rene 2019; 20:e41257-e41257. identified that the areas and groups at greatest risk for leprosy were associated with low socioeconomic status. The use of spatial analysis techniques made it possible to verify that the geographical distribution of leprosy cases was not exactly that identified in campaigns and in the routine investigation of cases and contacts⁴⁷47 Cury MRCO, Paschoal VD, Nardi SMT, Chierotti AP, Rodrigues Júnior AL, Chiaravalloti-Neto F. Spatial analysis of leprosy incidence and associated socioeconomic factors. Rev Saude Publica 2012; 46(1):110-118.

48 Dias MCFDS, Dias GH, Nobre ML. Spatial Distribuition of hansen disease in the municipality of Mossoró/RN, using the Geographic Infromation System - (GIS). An Bras Dermatol 2005; 80:S289-S294.

49 Amaral EP, Lana FCF. Spacial analysis of Leprosy in the microregion of Almenara, MG, Brazil. Rev Bras Enferm 2008; 61:701-707.

50 Duarte-Cunha M, Souza-Santos R, Matos HJD, Oliveira MLWD. Epidemiological aspects of leprosy: a spatial approach. Cad Saude Publica 2012; 28:1143-1155.^-5151 Gracie R, Peixoto JNDB, Soares FBDR, Hacker MDAVB. Analysis of the geographical distribution of cases of leprosy. Rio de Janeiro, 2001-2012. Cien Saude Colet 2017; 22:1695-1704.. These findings highlight the importance of directing the actions of identifying cases and investigating contacts with greater precision to prioritize resources and reduce costs. It is worth mentioning that the studies by Queiroz and Scatena⁵²52 Queiroz M, Scatena J. Temporal and spatial distribution of Hansen's disease in the state of Mato Grosso, from 1996 to 2007. Cad Saude Coletiva 2009; 17(1):145-161., Santos et al.⁵³53 Santos ES, Magalhães MDCC, Queiroz MDL, Borges RCM, Lima ML, Souza MS, Ramos Junior AN. Space-time distribution of the Hansen disease in Mato Grosso. Hygeia 2010; 6(10):53-62., and Garcia et al.⁵⁴54 Garcia DR, Ignotti E, Cortela DCB, Xavier DR, Barelli CSGAP. Spatial analysis of leprosy cases with focus for risk area in a basic health unit, Cáceres (MT). Cad Saude Colet 2013, 21(2):168-172., whose main objective was to accompany the space-time expansion of leprosy in the process of urban cluster formation, were better understood when employing spatial techniques.

The leprosy control strategy through the investigation of contacts should not be restricted to homes. The assessment of neighbors and non-household contacts is essential to identify sources of disease infection in the community. In Brazil, where primary health care is based on the Family Health Strategy, professionals who work in this care model are essential in conducting an active search for new leprosy cases and tracking contacts. Barreto et al.⁵⁵55 Barreto ICHC, Pessoa VM, Sousa MFA, Nuto SAS, Freitas RWJF, Ribeiro KG, Vieira-Meyer APGF, Andrade LOM. Complexity and potentiality of the Community Health Workers' labor in contemporary Brazil. Saude Debate 2018; 42(1):114-129., in a study carried out in four municipalities in Ceará, showed that the CHAs, in their home visits, are frequently unable to carry out the entire programmed action agenda. Permanent education strategies in leprosy are essential to increase the active search for suspected cases in the territories and the investigation of household and non-household contacts⁵⁶56 Carlos J, Ribeiro MDA, Oliveira SB. Avaliação do nível de informação sobre hanseníase dos agentes comunitários de saúde. Rev Bras Promoc Saúde 2016; 29:364-370..

Conclusion

The use of spatial analysis techniques with the application of Voronoi polygons proved to be appropriate to identify the distribution pattern of leprosy cases and their household and non-household contacts in Sobral. It was also possible to show the clusters of cases with subclinical leprosy infection, with random distribution of positive and negative NDO-LID cases, all of whom are close neighbors, highlighting the importance of proximity for the transmission of M. leprae.

The spatial distribution pattern of leprosy cases in children and adolescents under 15 years of age and their household and non-household contacts, with active or subclinical leprosy, may indicate M. leprae foci transmission not recognized previously. Given these findings, the search for new leprosy cases cannot be limited to homes or by geopolitical borders. The study reinforced the strong association between low socioeconomic conditions and leprosy.

Acknowledgments

We thank the families of the participants and the health agents of Sobral for making this study possible.

References

Publication Dates

History