• View in gallery

    Schistosomiasis distribution in Brazil and location of Rio Grande do Norte state and Pureza municipality.

  • View in gallery

    Multivariate profiles of standardized hemogram variables by groups.

  • 1.

    Siqueira LDP, Fontes DAF, Aguilera CSB, Timóteo TRR, Ângelos MA, Silva LCPBB, de Melo CG, Rolim LA, da Silva RMF, Neto PJR, 2017. Schistosomiasis: drugs used and treatment strategies. Acta Trop 176: 179187.

    • Search Google Scholar
    • Export Citation
  • 2.

    Bergquist R, Utzinger J, Keiser J, 2017. Controlling schistosomiasis with praziquantel: how much longer without a viable alternative? Infect Dis Poverty 6: 110.

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization, 2018. Schistosomiasis. Fact Sheets. Available at: https://www.who.int/en/news-room/fact-sheets/detail/schistosomiasis. Accessed September 4, 2018.

    • Search Google Scholar
    • Export Citation
  • 4.

    Colley DG, Bustinduy AL, Secor WE, King CH, 2014. Human schistosomiasis. Lancet 383: 22532264.

  • 5.

    Gazzinelli A, Oliveira-Prado R, Matoso LF, Veloso BM, Andrade G, Kloos H, Bethony JM, Assunção RM, Correa-Oliveira R, 2017. Schistosoma mansoni reinfection: analysis of risk factors by classification and regression tree (CART) modeling. PLoS One 12: e0182197.

    • Search Google Scholar
    • Export Citation
  • 6.

    Ministério da Saúde, 2014. Vigilância da Esquistossomose Mansoni - Diretrizes Técnicas, 4th edition. Brasília, Brazil. Available at: http://bvsms.saude.gov.br/bvs/publicacoes/vigilancia_esquistossome_mansoni_diretrizes_tecnicas.pdf. Accessed August 29, 2018.

    • Search Google Scholar
    • Export Citation
  • 7.

    Martins-Melo FR, Pinheiro MCC, Ramos AN, Alencar CH, Bezerra FSDM, Heukelbach J, 2015. Spatiotemporal patterns of schistosomiasis- related deaths, Brazil, 2000–2011. Emerg Infect Dis 21: 18201823.

    • Search Google Scholar
    • Export Citation
  • 8.

    Grimes JET, Croll D, Harrison WE, Utzinger J, Freeman MC, Templeton MR, 2014. The relationship between water, sanitation and schistosomiasis: a systematic review and meta-analysis. PLoS Negl Trop Dis 8: e3296.

    • Search Google Scholar
    • Export Citation
  • 9.

    Uniting to Combat Neglected Tropical Diseases, 2012. London Declaration on Neglected Topical Diseases. London Declar NTDs, 2020.

  • 10.

    Soares Magalhaes RJ, Downs PW, Kabore A, Zhang Y, Ottesen EA, Biritwum N-K, 2013. Predictive vs. Empiric assessment of schistosomiasis: implications for treatment projections in Ghana. PLoS Negl Trop Dis 7: e2051.

    • Search Google Scholar
    • Export Citation
  • 11.

    Watson M, 2009. Praziquantel. J Exot Pet Med 18: 229231.

  • 12.

    Vázquez LI, Valera E, Villalobos M, Tous M, Arija V, 2019. Prevalence of anemia in children from Latin america and the caribbean and effectiveness of nutritional interventions: systematic review and meta–analysis. Nutrients 11: 183.

    • Search Google Scholar
    • Export Citation
  • 13.

    Butler SE, Muok EM, Montgomery SP, Odhiambo K, Mwinzi PMN, Secor WE, Karanja DMS, 2012. Mechanism of anemia in Schistosoma mansoni-infected school children in Western Kenya. Am J Trop Med Hyg 87: 862867.

    • Search Google Scholar
    • Export Citation
  • 14.

    Yenilmez ED, Tuli A, 2018. Laboratory approach to anemia. Khan J, ed. Current Topics in Anemia. Vol. I. London, UK: InTech Open, 235–253.

  • 15.

    Scholte RGC, Gosoniu L, Malone JB, Chammartin F, Utzinger J, Vounatsou P, 2014. Predictive risk mapping of schistosomiasis in Brazil using bayesian geostatistical models. Acta Trop 132: 5763.

    • Search Google Scholar
    • Export Citation
  • 16.

    Remais JV, Zeng G, Li G, Tian L, Engelgau MM, 2013. Convergence of non-communicable and infectious diseases in low- and middle-income countries. Int J Epidemiol 42: 221227.

    • Search Google Scholar
    • Export Citation
  • 17.

    World Health Organization, 2000. Obesity: Preventing and Managing the Global Epidemic. Geneva, Switzerland: WHO.

  • 18.

    World Health Organization, 2007. BMI-for-Age Girls Thinness Severe Thinness. Geneva, Switzerland: WHO.

  • 19.

    World Health Organization, 2007. BMI-for-Age Boys Thinness Severe Thinness. Geneva, Switzerland: WHO.

  • 20.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2014. Pesquisa Suplementar de Segurança Alimentar PNAD 2013. A percepção das família em relação ao acesso aos Alimentos. Rio de Janeiro, Brasil: IBGE, 134.

    • Search Google Scholar
    • Export Citation
  • 21.

    Timm NH, 2002. Applied Multivariate Analysis. New York, NY: Springer.

  • 22.

    Johnson RA, Wichern DW, 2007. Applied Multivariate Statistical Analysi, 6th edition. Upper Saddle River, NJ: Pearson Education.

  • 23.

    Casavechia GM et al. 2018. Systematic review and meta-analysis on Schistosoma mansoni infection prevalence, and associated risk factors in Brazil. Parasitology 145: 10001014.

    • Search Google Scholar
    • Export Citation
  • 24.

    Hailu T, Alemu M, Abera B, Mulu W, Yizengaw E, Genanew A, Bereded F, 2018. Multivariate analysis of factors associated with Schistosoma mansoni and hookworm infection among primary school children in rural Bahir Dar, Northwest Ethiopia. Trop Dis Trav Med Vaccines 4: 4.

    • Search Google Scholar
    • Export Citation
  • 25.

    Majorin F, Torondel B, Routray P, Rout M, Clasen T, 2017. Identifying potential sources of exposure along the child feces management pathway: a cross-sectional study among urban slums in Odisha, India. Am J Trop Med Hyg 97: 861869.

    • Search Google Scholar
    • Export Citation
  • 26.

    Fenwick A, Jourdan P, 2016. Schistosomiasis elimination by 2020 or 2030? Int J Parasitol 46: 385388.

  • 27.

    Gazzinelli A, Velasquez-Melendez G, Crawford S, LoVerde P, Correa-Oliveira R, Kloos H, 2006. Socioeconomic determinants of schistosomiasis in a poor rural area in Brazil. Running short title: socioeconomic determinants of schistosomiasis in Brazil. Acta Trop 2–3: 260271.

    • Search Google Scholar
    • Export Citation
  • 28.

    Kloos H, Correa-Oliveira R, Quites HF, Souza MC, Gazzinelli A, 2008. Socioeconomic studies of schistosomiasis in Brazil: a review. Acta Trop 108: 194201.

    • Search Google Scholar
    • Export Citation
  • 29.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2017. Rendimento Domiciliar Per Capita 2017. Rio de Janeiro, Brazil: IBGE.

  • 30.

    Ministério da Fazenda, 2017. Decreto No 9.255, de 29 de Dezembro de 2017. Brasília, Brazil.

  • 31.

    Ministério do Desenvolvimento Social, 2016. Bolsa Família e Cadastro Único Município Pureza/RN. Brasília, Brazil: Ministério do Desenvolvimento Social. Available at: http://mds.gov.br/bolsafamilia. Accessed October 18, 2018.

    • Search Google Scholar
    • Export Citation
  • 32.

    Martins APB, Monteiro CA, 2016. Impact of the Bolsa Família program on food availability of low-income Brazilian families: a quasi experimental study. BMC Public Health 16: 111.

    • Search Google Scholar
    • Export Citation
  • 33.

    Moradi S, Mirzababaei A, Dadfarma A, Rezaei S, Mohammadi H, Jannat B, Mirzaei K, 2019. Food insecurity and adult weight abnormality risk: a systematic review and meta-analysis. Eur J Nutr 58: 4561.

    • Search Google Scholar
    • Export Citation
  • 34.

    Kushitor MK, Boatemaa S, 2018. The double burden of disease and the challenge of health access: evidence from access, bottlenecks, cost and equity facility survey in Ghana. PLoS One 13: 111.

    • Search Google Scholar
    • Export Citation
  • 35.

    Martins-Melo FR, Carneiro M, Ramos AN, Heukelbach J, Ribeiro ALP, Werneck GL, 2018. The burden of neglected tropical diseases in Brazil, 1990–2016: a subnational analysis from the global burden of disease study 2016. PLoS Negl Trop Dis 12: 124.

    • Search Google Scholar
    • Export Citation
  • 36.

    Marinho F et al. 2018. Burden of disease in Brazil, 1990–2016: a systematic subnational analysis for the global burden of disease study 2016. Lancet 392: 760775.

    • Search Google Scholar
    • Export Citation
  • 37.

    Olds GR et al. 1999. Double-blind placebo-controlled study of concurrent administration of albendazole and praziquantel in schoolchildren with schistosomiasis and geohelminths. J Infect Dis 179: 9961003.

    • Search Google Scholar
    • Export Citation
  • 38.

    Ministério da Saúde, 2016. Pce - Programa de Controle da Esquistossomose - Rio Grande do Norte. Brasília, Brazil: Mininistério da Saúde. Available at: http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sinan/pce/cnv/pceRN.def. Accessed October 4, 2018.

    • Search Google Scholar
    • Export Citation
  • 39.

    Katz N, 2018. Inquérito Nacional de Prevalência Da Esquistossomose Mansoni e Geo-Helmintoses. Belo Horizonte, Brazil.

  • 40.

    Tarafder M, Carabin H, Joseph L, Balolong E Jr., Olveda R, McGarvey ST, 2010. Estimating the sensitivity and specificity of Kato-Katz stool examination technique for detection of hookworms, Ascaris lumbricoides and Trichuris trichiura infections in humans in the absence of a ‘gold standard’. Int J Parasitol 40: 399404.

    • Search Google Scholar
    • Export Citation
  • 41.

    Bärenbold O, Raso G, Coulibaly JT, N’Goran EK, Utzinger J, Vounatsou P, 2017. Estimating sensitivity of the Kato-Katz technique for the diagnosis of Schistosoma mansoni and hookworm in relation to infection intensity. PLoS Negl Trop Dis 11: 114.

    • Search Google Scholar
    • Export Citation
  • 42.

    Machado GCXMP, Haguenauer CJ, Ruprecht T, Sobrinho FX, Gallo E, 2018. Livros. Filho WL, Freitas LEde, eds. Climate Change Adaption in Latin American. Cham, Switzerland: Springer, 103130.

    • Search Google Scholar
    • Export Citation
  • 43.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2017. Pureza: Trabalho, Território e Ambiente. Rio de Janeiro, Brazil: IBGE. Available at: https://cidades.ibge.gov.br/brasil/rn/pureza. Accessed October 8, 2018.

    • Search Google Scholar
    • Export Citation
  • 44.

    Figueiredo FF, Federal U, 2017. O Saneamento Básico no nordeste e no Rio Grande no Norte: avanços e constrangimentos Sanitation in the northeast and Rio Grando do Norte: advances and constraints. Xvii Enanpur DESENVOLVIMENTO, Cris E Resist QUAIS OS CAMINHOS DO Planej URBANO E Reg. Available at: http://www.repositorio.ufrn.br:8080/jspui/bitstream/123456789/23431/1/Saneamento basico no NE e RN.pdf.

    • Search Google Scholar
    • Export Citation
  • 45.

    Howard G, 2002 Excreta disposal. Heal Villages a Guid Communities Community Health, 3847. Available at: http://www.who.int/water_sanitation_health/hygiene/settings/hvchap4.pdf?ua=1.

    • Search Google Scholar
    • Export Citation
  • 46.

    Bethony J et al. 2001 Exposure to Schistosoma mansoni infection in a rural area in Brazil. II: household risk factors. Trop Med Int Health 6: 136145.

    • Search Google Scholar
    • Export Citation
  • 47.

    Sow S, de Vlas SJ, Stelma F, Vereecken K, Gryseels B, Polman K, 2011. The contribution of water contact behavior to the high Schistosoma mansoni Infection rates observed in the Senegal River Basin. BMC Infect Dis 11: 111.

    • Search Google Scholar
    • Export Citation
  • 48.

    Sokolow SH et al. 2015 Reduced transmission of human schistosomiasis after restoration of a native river prawn that preys on the snail intermediate host. Proc Natl Acad Sci USA 112: 96509655.

    • Search Google Scholar
    • Export Citation
  • 49.

    World Health Organization, 2008. The social context of schistosomiasis and its control an introduction and annotated bibliography. Bruun B, Aagaard-Hansen J, Watts S, ed. Geneva, Switzerland: WHO, 75–126. doi: 10.2471/TDR.08.978924159718 0.

    • Search Google Scholar
    • Export Citation
  • 50.

    Calasans TAS, Souza GTR, Melo CM, Madi RR, de Lourdes Sierpe Jeraldo V, 2018. Socioenvironmental factors associated with Schistosoma mansoni infection and intermediate hosts in an urban area of northeastern Brazil. PLoS One 13: 115.

    • Search Google Scholar
    • Export Citation
 
 
 

 

 

 

 

 

 

Factors Associated with Schistosoma mansoni Infestation in Northeast Brazil: A Need to Revisit Individual and Community Risk Factors

View More View Less
  • 1 Institute of Tropical Medicine of Rio Grande do Norte, Natal, Brazil;
  • | 2 Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Natal, Brazil;
  • | 3 Department of Nutrition, Federal University of Rio Grande do Norte, Natal, Brazil;
  • | 4 Department of Infectious Diseases, Federal University of Rio Grande do Norte, Natal, Brazil;
  • | 5 Departament of Biochemistry, Federal University of Rio Grande do Norte, Natal, Brazil;
  • | 6 Institute of Science and Technology of Tropical Diseases, INCT-DT, Salvador, Brazil

ABSTRACT

In Brazil, schistosomiasis continues to be an important health issue. The aim of this study was to identify factors associated with Schistosoma mansoni infestation. A cross-sectional study was performed to assess factors associated with S. mansoni endemicity in a municipality in Northeast Brazil with a history of reporting schistosomiasis. Participants were divided into four groups: 1) new S. mansoni cases (n = 44), 2) past history of S. mansoni treatment (n = 78), 3) immediate neighbors (n = 158), and 4) nearby controls (n = 35). Multiple comparisons analysis was performed. Subjects had a mean of 6.6 ± 3.9 years of education, and no difference was observed regarding family income (one-way analysis of variance, P = 0.215). A total of 95.9% of the individuals had rudimentary cesspit as sanitary wastewater. The mean body mass index was 28.3 ± 5.1, with 41.0% and 24.1% overweight and obesity, respectively. Of note, 28.9% of adults had hypertension. Hemoglobin, mean corpuscular volume, and mean corpuscular hemoglobin were higher in the recent S. mansoni treated group (Wilks’ lambda, P < 0.001). Male gender was more prevalent in new S. mansoni cases (likelihood ratio, P < 0.001), close proximity to water collections was a risk for S. mansoni infestation (likelihood ratio, P < 0.001), and a better hematological status was observed in individuals recently treated with praziquantel. This study indicates the need to maintain surveillance for S. mansoni in low-transmission areas and the need to establish community-based interventions to control transmission.

INTRODUCTION

Schistosomiasis is a disease caused by a waterborne pathogen which affects vulnerable populations or tourists entering contaminated water.1,2 Disease can be caused by six species of the Schistosoma genus: Schistosoma mansoni, Schistosoma japonicum, Schistosoma mekongi, Schistosoma haematobium, Schistosoma intercalatum, and Schistosoma guineensis.3 An estimated 230 million people are infected worldwide.4 In Brazil, the disease is caused by S. mansoni whose eggs are expelled in freshwater collections through the feces of infected humans; the eggs hatch and release miracidia that then infect snails of the genus Biomphalaria. Eventually, cercariae are expelled by snails and infest humans, completing the transmission cycle.2,5,6

Despite advances in schistosomiasis control measures, mainly after mass treatment and improvement in sanitation with construction of toilets, in the past 40 years, the disease is still a serious public health problem in Brazil.3,5,7 There are approximately 6 million people currently infested with S. mansoni in the country and 25 million at risk of infestation.5 The highest risk areas for schistosomiasis comprise the coastal region of the northeast from Rio Grande do Norte advancing toward the southeast region along watersheds and freshwater bodies.6 These areas have conditions favorable to Schistosoma: the presence and proliferation of the intermediate snail host, poverty, and inadequate sanitation.7 Lack of sanitation considerably increases the risk of S. mansoni transmission.8 Furthermore, considering its focal infestation pattern, the factors associated with transmission are particular for each outbreak area and must be considered for control and eventual elimination.9,10

Chemotherapy with praziquantel is the recommended treatment against all forms of schistosomiasis by the WHO and could support its control and potential elimination.5 Praziquantel is a highly effective antihelminthic drug with a wide range of use against many species of trematodes and cestodes.11 Schistosoma mansoni and geohelminths such as hookworm infestations are both associated with anemia in children, and these are frequent in Brazil1,12 In schistosomiasis, mechanisms driving anemia include iron deficiency, splenic erythrocyte retention, autoimmune hemolysis, and decreased intestinal absorption with sequestration of iron in macrophages.13 The hemogram is a useful test to observe hematological parameters associated with anemia.14

Schistosomiasis was one of 10 neglected diseases proposed to be controllable by the end of 20209; however, this goal will not be attained because it continues to undergo active transmission in many areas of the world.15 In Brazil, despite an apparent decrease in schistosomiasis, there is still S. mansoni transmission, and continuous surveillance is needed. Parallel to the lasting transmission of infectious diseases, an increase in noncommunicable diseases, such as diabetes, obesity, and hypertension, has been observed. This phenomenon has been seen intensely in low- and middle-income countries such as Brazil.16 Thus, identification of factors associated with S. mansoni infestation can help support effective local control programs and consequently contribute to the global goal of control. This study was designed to understand the factors associated with S. mansoni infestation in an endemic area of Brazil.

MATERIALS AND METHODS

Study area and design.

The municipality of Pureza, a town of 9,568 people, is located in a S. mansoni–endemic area of the state of Rio Grande do Norte, as shown in Figure 1. The municipality has several freshwater collection bodies that sustain Biomphalaria glabrata and lacks basic sanitation. This is a cross-sectional study conducted between October 2017 and July 2018.

Figure 1.
Figure 1.

Schistosomiasis distribution in Brazil and location of Rio Grande do Norte state and Pureza municipality.

Citation: The American Journal of Tropical Medicine and Hygiene 104, 4; 10.4269/ajtmh.19-0513

Participant selection.

The municipal health department has regularly performed active case detection for S. mansoni. The diagnosis is through parasitological examination by Kato–Katz using a single fecal sample. A total of 220 cases were diagnosed and treated in the last 5 years; 76% of those individuals were male, 58% were adults, 35% were children, and 7% were elderly. Of the 220 cases, 61 individuals had stool parasitological examination performed during the year of the study (2017–2018) and were sought for recruitment; 17 had left the area, were absent at the time of data collection, or declined participation in the study, yielding 44 cases (allocated in the new S. mansoni cases group). Individuals examined during the year of the study, which presented the negative parasitological examination for S. mansoni, also were recruited (n = 271). Those individuals were allocated into three groups according to their current and past medical histories: treated for schistosomiasis more than 5 years ago (past history of S. mansoni, n = 78), never treated for schistosomiasis and living in the same area (immediate neighbor group, n = 158), and never treated for schistosomiasis and living far apart from the water collection areas but in the same municipality (nearby control group, n = 35). People who were treated more than 5 years ago who were also recently treated were allocated to the new S. mansoni case group. We divided the groups in this way to verify whether the absence or presence of previous treatment as well as whether proximity to water collections were factors associated with S. mansoni infestation. In short, there were 315 people recruited, about 3.3% of the municipality population, and they were classified into four groups: 1) new S. mansoni cases (n = 44), 2) past history of S. mansoni treatment (n = 78), 3) immediate neighbors (n = 158), and 4) nearby controls (n = 35).

Data collection.

We applied a demographic, socioeconomic, environmental, clinical, and behavioral questionnaire to all participants (in Supplemental Material) which included information on gender, age, years of education, occupation, monthly per capita income, receipt of Bolsa Família (a social program of income transfer), sanitary wastewater canalization, anti-hypertensive use, other parasitoses, and use of water collections, frequency, and for which activities. Other pathogens found in the Kato–Katz fecal examination were also included in the “other parasitoses” variable.

Nutritional status was determined by means of weight in kilograms (kg) and height in meters (m) and used to calculate body mass index (BMI) (kg/m2) for adults and BMI for age (years and months) for children and adolescents. The BMI was classified according to the WHO.1719 Body mass index data were compiled for each age-group and classified as underweight, eutrophic, overweight, or obese. We also applied the Brazilian Scale of Food and Nutrition Security (Escala Brasileira de Segurança Alimentar, EBIA) to verify household food insecurity.20

Blood samples from participants were used to perform blood counts to compare hemoglobin, hematocrit, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), MCH concentration (MCHC), and eosinophils between study groups. The frequency of use of water collection was classified as never use, sporadically (annually or semiannually), frequently (quarterly, bimonthly, or monthly), or very frequently (weekly, two or three times a week, or daily).

Data entry and analysis.

Data were stored and managed in REDCap (Research Eletronic Data Capture, Nashville, TN) version 6.14.2, a web-based data capture system. Categorical and discrete variables such as gender, occupation, and nutritional status were evaluated under the null hypothesis of homogeneous probability distributions or nonassociation between groups. For this, the chi-square test of the likelihood ratio was applied because it is less sensitive to missing data. As a complementary test, multiple comparisons between proportions of the groups were made using the z-test with Bonferroni correction. For comparison of means of continuous variables such as age and income between groups, a one-way analysis of variance (ANOVA) with multiple comparisons of Tukey honestly significant difference (HSD) was used. A multivariate analysis of covariance (MANCOVA) model was used to compare multivariate mean profiles of hematological variables according to the adjustment of a multivariate linear model as follows:
Y=Xβ+Error,
where Y is the reduced score’s matrix of the six hematological parameters considered, X is the planning matrix of the model with columns X1 = (1, 1, 1, ..., 1) for the intercept, X2 and X3 are the factors group and gender, and X4 is the coverable age. β is the array of parameters to be estimated assessing the effect or association with groups, and Error is the array for potential random error.21,22 The multivariate hypothesis of the profile’s coincidence and the effect of covariables were evaluated by Wilks’ lambda statistic. In case of rejection of the first, one-way ANOVA was applied for each parameter profile and Tukey’s HSD tests were used for multiple comparisons between groups (Supplemental Table S1). Planned comparisons between profiles such as past history of treatment versus immediate neighbor were also made. After analyzing the presence of confounding factors such as group, local, and gender, a logistic model was used to evaluate the influence of age on the risk of occurrence of other parasitoses. Odds ratios (OR) and 95% CIs were calculated as a measurement of the strengths of associations. The hypotheses were tested at a significance level of 5%. Statistical analysis was performed using the SPSS (Statistical Package for the Social Sciences, Armonk, NY) version 23 and profile analysis using the Statistica release 7 and R version 3.6.1.

Ethical considerations.

The protocol was reviewed and approved by the Federal University of Rio Grande do Norte Ethical Committee under protocol 12584513.1.0000.5537. The Brazilian Ethical Guidelines regarding studies with human subjects incorporated the set of rules present in the Helsinki Declaration, with a clear statement of confidentiality and no harm for all study participants. All participants or their legal guardians provided a signed informed consent.

RESULTS

The demographic, socioeconomic, environmental, nutritional, and clinical characteristics of study groups are shown in Table 1. The new S. mansoni cases presented a higher frequency of males: 77.3% (likelihood ratio, P < 0.001). Among the new S. mansoni cases, 17 (38.6%) had been treated five years earlier, indicating reinfestation. The past history of S. mansoni treatment group had the highest mean age compared with new cases and immediate neighbors (Tukey HSD, P < 0.05) and higher mean years of education than immediate neighbors (Tukey HSD, P = 0.025).

Table 1

Demographic, socioeconomic, environmental, nutritional and clinical characteristics of study groups.

CharacteristicP-valueTotalNew casesPast history of treatmentImmediate neighborNearby controls
DemographicMales, no. (%)< 0.001*161 (51.1)34 (77.3)‡41 (52.6)§71 (44.9)§15 (42.9)§
Age (years), mean ± SD< 0.00133.8 ± 19.035.0 ± 16.644.8 ± 14.326.9 ± 18.838.9 ± 18.7
SocioeconomicYears of education (mean ± SD)0.0106.6 ± 3.97.5 ± 3.37.5 ± 3.86.0 ± 4.06.0 ± 4.0
Occupation, n (%)0.041*
Farming and fishing25 (25.0)6 (30.0)‡§6 (16.7)‡6 (18.2)‡7 (63.6)§
Industry7 (7.0)3 (15.0)‡3 (8.3)‡1 (3.0)‡0 (0.0)‡
Commerce and service20 (20.0)5 (25.0)‡7 (19.4)‡8 (24.2)‡0 (0.0)‡
Education, health, and social services11 (11.0)0 (0.0)‡6 (16.7)‡4 (12.1)‡1 (9.1)‡
Others37 (37.0)6 (30.0)‡14 (38.9)‡14 (42.4)‡3 (27.3)‡
Monthly per capita income (mean in reais ± SD)0.215372.0 ± 225.9396.9 ± 239.5412.9 ± 226.2349.1 ± 234.9358.5 ± 148.3
Income from social program (Bolsa Família), n (%)0.189*142 (45.1)16 (36.4)‡30 (38.5)‡77 (48.7)‡19 (54.3)‡
Environmental, n (%)Rudimentary cesspit10.056*302 (95.9)44 (100.0)‡73 (93.6)‡150 (94.9)‡35 (100.0)‡
Nutritional, n (%)Household food insecurity< 0.001*200 (64.3)35 (79.5)‡45 (57.7)‡111 (71.6)‡9 (26.5)§
Nutritional status by body mass index0.002*
Eutrophic2105 (33.3)18 (40.9)‡13 (16.7)§64 (40.5)‡10 (28.6)‡§
Overweight2129 (41.0)19 (43.2)‡39 (50.0)‡56 (35.4)‡15 (39.5)‡
Obesity276 (24.1)7 (15.9)‡26 (33.3)‡33 (20.9)‡10 (28.9)‡
Clinical, no. (%)High blood pressure0.003*67 (21.3)5 (11.4)‡§25 (32.1)§25 (15.8)‡12 (34.3)‡§
Other parasitoses< 0.000*50 (15.9)1 (2.3)‡12 (15.4)‡§37 (23.4)§0 (0.0)‡

Bold values indicate P < 0.05.

Chi-square test’s likelihood ratio with Bonferroni correction. Different symbols (‡ and §) indicate significantly different values between groups.

ANOVA one-way test.

(1) Other answer: trench.

(2) Other answer: underweight.

Among individuals who declared an occupation, the control group presented a higher frequency of farming or fishing than the groups with a previous history of treatment for S. mansoni and immediate neighbors (likelihood ratio, P = 0.041). The three groups living near water collections had similar occupations.

There was no difference among the groups for monthly family income (one-way ANOVA, P = 0.215), with a mean of 372.0 ± 225.9 reais per capita (∼92 US$), with a similar rate of income from social programs among the groups (likelihood ratio, P = 0.189). About the environmental characteristic, 95.9% of the individuals reported having rudimentary cesspit as sanitary wastewater canalization and 4.1% used a trench. None of the households had proper septic tanks.

With respect to nutritional findings, the study groups living in areas near the water collection presented a higher frequency of household food insecurity in comparison to the control group (likelihood ratio, P < 0.001). The mean BMI of the participants was 28.3 ± 5.1 in adults. Overall, the prevalence of being overweight and obese was 41.0% and 24.1%, respectively. The groups did not differ with respect to overweight or obese, but the past history of treatment group had a lower frequency of people within ideal body weight than cases and immediate neighbors (likelihood ratio, P = 0.002). Obesity was seen in 15.9% of new S. mansoni cases, 33.3% of those with past history of treatment, 20.9% of immediate neighbors, and 28.9% of nearby controls.

Immediate neighbors presented with a higher frequency of high blood pressure than past history of treatment group (likelihood ratio, P = 0.003). High blood pressure was found in 21.3% of participants, but when considering age, 28.9% of adults showed hypertension.

Immediate neighbors presented a higher frequency of other parasitoses than new cases and control group (likelihood ratio, P < 0.001). Interestingly, age was associated with other parasitoses when using logistic bivariate analysis, with lower risk associated with increased age (P = 0.001; OR = 0.969; CI = 0.952–0.987), with a 3.1% decrease in the risk of other infestation with each additional year of life. These results were independent of the factors group, location, and gender, the most likely confounding factors that were not significantly associated with response in a preliminary model that included them as independent variables.

The average profiles of the standardized hematological variables hemoglobin, hematocrit, MCV, MCH, MCHC, and eosinophils according to the groups are shown in Figure 2. The new S. mansoni treated cases had a higher score for the hematological profile than the other groups. In a MANCOVA adjusted model (1), the coincidence hypothesis for the hematological findings was tested and rejected by the multivariate Wilks test (Wilks’ lambda = 0.8436, P = 0.00015), considering gender (Wilks’ lambda = 0.9117, P = 0.0002), and age (Wilks’ lambda = 0.7783, P < 0.0001). In the first part of Table 2, the components of the beta parameter vector (β), that indicate the differential effect of each hematological variable on the group, with reference to the control group, showed that hemoglobin (β = 0.2446; P = 0.0001), hematocrit (β = 0.2285; P = 0.0004), MCV (β = 0.3028; P = 0.0001), and MCH (β = 0.2071; P = 0.0012) were higher in the new S. mansoni group. However, there was no significant difference in MCHC (β = −0.0697; P = 0.3106) or eosinophils (β = −0.0512; P = 0.4508). Subjects with a past history of treatment had a significantly lower MCV level than the control group (β = −0.1517) and a significantly higher MCHC (β = 0.2013), whereas immediate neighbors displayed no significantly different hematologic values compared with controls. Males had significantly higher values than females for hemoglobin (β = 0.2978), hematocrit (β = 0.2566), and eosinophils (β = 0.1463). In addition, for each additional year increment in age, there was a significant increase in the levels of the first four variables.

Figure 2.
Figure 2.

Multivariate profiles of standardized hemogram variables by groups.

Citation: The American Journal of Tropical Medicine and Hygiene 104, 4; 10.4269/ajtmh.19-0513

Table 2

Estimates of the beta parameters of MANCOVA model 1 (Reference: nearby controls group) and planned profiler comparisons

Main effectsHemoglobinHematocritMean corpuscular volumeMean corpuscular hemoglobinMean corpuscular hemoglobin concentrationEosinophils
GroupNew casesBeta0.24460.22850.30280.2071−0.0697−0.0512
P-value0.00010.00040.00010.00120.31060.4508
Past history of treatmentBeta0.0266−0.0927−0.15170.00750.2013−0.0969
P-value0.65770.13530.01030.90270.00260.1397
Immediate neighborBeta−0.01800.0213−0.1094−0.06040.03880.0855
P-value0.76810.73480.06810.33330.56530.2004
GenderMaleBeta0.29780.2566−0.01050.05090.07280.1463
P-value0.00010.00010.84330.35830.22460.0139
AgeYearBeta0.19610.23360.42000.3528−0.0047−0.1322
P-value0.00080.00010.00010.00010.94130.0379
Planned profiler comparisons
 Past history of treatment vs. immediate neighbor(1)Beta0.0709−0.1919−0.10200.09980.2867−0.2749
P-value0.61890.20250.47380.49510.07070.0660
 New cases vs. past history of treatment(2)Beta0.45070.63400.88770.4087−0.48450.0581
P-value0.01710.00150.00010.03490.02090.7679
 New cases vs. past history of treatment + immediate neighbor(3)Beta0.97231.07611.67340.9172−0.6822−0.1588
P-value0.00380.00240.00010.00780.06630.6493
 New cases + past history of treatment vs. immediate neighbor + controls(4)Beta1.08170.62560.72690.86850.4018−0.5135
P-value0.00010.02360.00560.00130.16590.0606

Bold values indicate P < 0.05.

Test multivariate:

(1) Wilks’ lambda = 0.9716; P = 0.2308.

(2) Wilks’ lambda = 0.9067; P = 0.0001.

(3) Wilks’ lambda = 0.9159; P = 0.0004.

(4) Wilks’ lambda = 0.9228; P = 0.0009.

In the section Planned profiler comparisons in Table 2, when comparing the new cases group versus past history of treatment(2), the coincidence hypothesis of profiles was rejected (Wilks’ Lambda = 0.9067, P = 0.0001) with significantly higher betas in all hematological variables except eosinophils. Two other planned comparisons were made: the first “new cases versus past history of treatment + immediate neighbor”(3) and the second, “new cases + past history of treatment versus immediate neighbor + controls.”(4) Both showed significant betas in all parameters, except MCHC and eosinophils.

Concerning the use of freshwater collections, the frequency of use differed between groups notably in the category “never use” (likelihood ratio, P < 0.001) whose frequency of response was 78.4% in the control group (Table 3). All groups reported use for recreational activities; however, the control group presented less frequency of use than new cases and immediate neighbors and a similar frequency to past history of treatment (likelihood ratio, P < 0.001). There was a difference between groups in the use of water for irrigation purposes (P = 0.014). Subjects in the control group did not use freshwater bodies for fishing, but new cases had the highest frequency (11.4%). Similarly, 11.4% of controls (likelihood ratio, P = 0.001) and 4.5% of new cases (likelihood ratio, P = 0.046) used freshwater bodies for irrigation and laundering, respectively.

Table 3

Frequency of use of freshwater bodies and activities in the study groups

CharacteristicTotalNew casesPast history of treatmentImmediate neighborNearby controlsP-value*
Frequency of use of water collection, no. (%)< 0.001
 Never use139 (44.1)15 (34.1)†‡45 (57.7)‡§52 (32.9)†27 (77.1)§
 Sporadically48 (15.2)4 (9.1)†14 (17.9)†28 (17.7)†2 (5.7)†
 Frequently88 (27.9)16 (36.4)†11 (14.1)‡56 (35.4)†5 (14.3)†‡
 Very frequently40 (12.7)9 (20.5)†8 (10.3)†22 (13.9)†1 (2.9)†
Activities, no. (%)
 Recreational bathing163 (51.7)22 (50.0)†‡30 (38.5)‡,c104 (65.8)†7 (20.0)§< 0.001
 Irrigation10 (3.2)5 (11.4)†3 (3.8)†‡2 (1.3)‡0 (0.0)†‡0.014
 Fishing6 (1.9)5 (11.4)†0 (0.0)†,‡1 (1.3)†‡0 (0.0)‡0.001
 Laundering2 (0.6)2 (4.5)†0 (0.0)†‡0 (0.0)‡0 (0.0)†‡0.046

Bold values indicate P < 0.05.

* Chi-square test’s likelihood ratio with Bonferroni correction. Different symbols (†, ‡ and §) indicate significantly different values between groups.

DISCUSSION

Demographic, socioeconomic, environmental, and behavioral factors are conditions involved in the occurrence of schistosomiasis around the world.2326 Gender, age, education level, family income, the presence of the intermediate host snail, and contact with water collections are major risk factors associated with S. mansoni infestation in Brazil.23 In this study, we aimed to understand the main factors associated with S. mansoni infestation.

We found that among the new S. mansoni cases, the majority were males. The new S. mansoni cases group reported more frequent freshwater use for fishing. This could be due to males have frequent gender-related activities, such as agriculture and fishing.23 Typically, children and adolescents have the highest prevalence of infestation which decreases in adulthood.4 In our study, we did not identify this age infestation pattern. High prevalence of S. mansoni can persist among adults who have frequent contact with freshwater.4 The lower prevalence in children in this setting could be due to difficulty of sample collection or less exposure to contaminated water because there is knowledge of the disease in the area.

Poverty and lack of education synergize to increase the risk of S. mansoni infestation.27,28 A low mean years of education was observed in our study population. The mean monthly income per capita was less than half of the mean observed for the state of Rio Grande do Norte.29 The town income and the state income are below the monthly Brazilian minimal wage, which in 2018 was R$ 954.00 (about $ 200.00).30 Nearly 47% of the municipality is supported by Bolsa Família, a social program of income transfer to vulnerable families.31,32

The study population presented a high frequency of household food insecurity. Although at first, this appears to be more related to malnutrition, food insecurity has been associated with obesity, especially in women.33,34 A high prevalence of overweight, obesity, and high blood pressure were found in our study population, even higher than in the adult Brazilian population (54.0%, 18.9%, and 24.7%, respectively).

The coexistence of chronic noncommunicable and infectious disease is called the double burden of diseases.16 In Brazil, this phenomenon occurred earlier in the south and southeast regions, but many states in the north and northeast regions are moving toward similar trends for noncommunicable diseases. An increase in neglected disease burden is expected in the coming years, which are already increased because of recent economic crises which widened poverty and social inequalities.35 Therefore, intervention strategies need to deal with this diversity which is a big challenge for policies at the local and national levels.36

The hematological status in our study was defined through the blood count. The blood count is the most sensitive measure in routine use to obtain information about the presence and severity of anemia.14 To better diagnose anemia, some specific tests could have been used, such as serum Fe, serum transferrin, serum B12, and serum folate levels. So, this is a limitation of our study. However, the blood count was a useful tool considering that the study needed a reference point to investigate anemia in a population.14

After correcting for the effects of gender and age, hematological parameters of anemia were different among the groups, revealing a better hematological status among new S. mansoni cases after treatment. In children treated with praziquantel, Olds and others37 observed an increase in hemoglobin levels. Based on this, they proposed an argument for mass treatment and the importance of schistosomiasis as a cause of childhood anemia in settings with mixed helminthic infestations.37 In our study, age was inversely associated with other parasitoses, which implies other parasitoses were more likely in children. Because of these findings, mass treatment for a range of parasites could be suggested for this population. However, a better understanding of the causal mechanisms underlying the relationship between anemia and schistosomiasis would be helpful to determine the frequency of anthelmintic treatment necessary to prevent schistosomiasis-associated anemia in this critical age-group and the real need of chemotherapy recommendations even in low endemic areas.13 Currently in Brazil, only areas with more than 25% S. mansoni positivity receive mass treatment.6 Rio Grande do Norte has less than 1.0% of positivity, and the town of Pureza/RN had 2.1% in 2015. However, it was 15% in 2005, indicating the need for continuous surveillance.38,39 For areas with less than 15% positivity, the Ministry of Health recommends treating only individuals with positive parasitological confirmation, as this was the case.6

The recent elimination of other helminthic infestations by praziquantel could have contributed to the lower frequency of other parasitoses seen in the new cases group than the immediate neighbor group. However, other infectious agents can cause anemia such as malaria and hookworms.13 The Kato–Katz technique can be performed with reasonable accuracy with 1 day’s stool collection for Ascaris lumbricoides and Trichuris trichiura but has low sensitivity for hookworm infestation.40 Therefore, hookworms may not have been detected in the study population. Although the Kato–Katz technique has been used as the gold standard to diagnose S. mansoni in high endemic areas, it has a poor sensitivity in low-prevalence areas, which could be a limitation of this study.41

Lack of proper sanitation directly contributes to the dissemination of waterborne diseases such as schistosomiasis.42 Just 1.3% of the town has adequate sanitary sewage.43 Rudimentary cesspit, the major way of wastewater canalization verified in this study, does not safely prevent sewage contamination of freshwater. Septic tanks linked to a sewage system could represent an adopted measure to improve sanitation.44,45

The place of residence is a water contact behavior determinant.46 The control group, far from water collections, responded “never use” more frequently than the others and use for recreational bathing, wisely the riskier behavior in terms of body exposure, less frequently than two of the three groups near freshwater collections.47 The classification of areas according to the risk of transmission is a precondition for the implementation of effective surveillance and control strategies.39

In this study, about one-third of people in the new S. mansoni cases group had already been infested by S. mansoni previously. In some endemic areas, reinfestation occurs after re-exposure to contaminated water collections.23,48 Low socioeconomic conditions are also an important determinant for the transmission and reinfestation.49 This probably happens because low socioeconomic conditions reduce access to safe water supplies, sanitation, and health care.5 There are some limitations of our study including a more frequent screening for S. mansoni infestation and the use of serological assay to better assess prior exposure.

Together, our data indicated male gender and proximity to water collections as factors associated with S. mansoni infestation. Low socioeconomic and sanitation conditions were observed in the study population as expected. People recently treated with praziquantel had a better hematological status. High prevalence of overweight, obesity, and hypertension were verified.

As S. mansoni infestation has a focal distribution, control programs should be focused on areas with continuous S. mansoni exposure. Specific programs are required in each affected area for its control and elimination.50 In addition, long-term screening for subclinical infestations is required, considering severe forms of the disease are not as prevalent as they once were. Finally, there is a high frequency of noncommunicable diseases such as hypertension, overweight, and obesity in a poor population, indicating the need for interventions to promote dietary knowledge, attitudinal, behavioral, and nutritional changes in people.

Supplemental material and table

ACKNOWLEDGMENTS

We thank the staff of the health and education departments of Pureza for the availability of the data of S. mansoni infestation and for their help in participants’ recruitment and also availability of the health post center for subjects’ examination. We also thank Breana Scorza, (University of Iowa) for her helpful suggestions and revision of this manuscript.

REFERENCES

  • 1.

    Siqueira LDP, Fontes DAF, Aguilera CSB, Timóteo TRR, Ângelos MA, Silva LCPBB, de Melo CG, Rolim LA, da Silva RMF, Neto PJR, 2017. Schistosomiasis: drugs used and treatment strategies. Acta Trop 176: 179187.

    • Search Google Scholar
    • Export Citation
  • 2.

    Bergquist R, Utzinger J, Keiser J, 2017. Controlling schistosomiasis with praziquantel: how much longer without a viable alternative? Infect Dis Poverty 6: 110.

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization, 2018. Schistosomiasis. Fact Sheets. Available at: https://www.who.int/en/news-room/fact-sheets/detail/schistosomiasis. Accessed September 4, 2018.

    • Search Google Scholar
    • Export Citation
  • 4.

    Colley DG, Bustinduy AL, Secor WE, King CH, 2014. Human schistosomiasis. Lancet 383: 22532264.

  • 5.

    Gazzinelli A, Oliveira-Prado R, Matoso LF, Veloso BM, Andrade G, Kloos H, Bethony JM, Assunção RM, Correa-Oliveira R, 2017. Schistosoma mansoni reinfection: analysis of risk factors by classification and regression tree (CART) modeling. PLoS One 12: e0182197.

    • Search Google Scholar
    • Export Citation
  • 6.

    Ministério da Saúde, 2014. Vigilância da Esquistossomose Mansoni - Diretrizes Técnicas, 4th edition. Brasília, Brazil. Available at: http://bvsms.saude.gov.br/bvs/publicacoes/vigilancia_esquistossome_mansoni_diretrizes_tecnicas.pdf. Accessed August 29, 2018.

    • Search Google Scholar
    • Export Citation
  • 7.

    Martins-Melo FR, Pinheiro MCC, Ramos AN, Alencar CH, Bezerra FSDM, Heukelbach J, 2015. Spatiotemporal patterns of schistosomiasis- related deaths, Brazil, 2000–2011. Emerg Infect Dis 21: 18201823.

    • Search Google Scholar
    • Export Citation
  • 8.

    Grimes JET, Croll D, Harrison WE, Utzinger J, Freeman MC, Templeton MR, 2014. The relationship between water, sanitation and schistosomiasis: a systematic review and meta-analysis. PLoS Negl Trop Dis 8: e3296.

    • Search Google Scholar
    • Export Citation
  • 9.

    Uniting to Combat Neglected Tropical Diseases, 2012. London Declaration on Neglected Topical Diseases. London Declar NTDs, 2020.

  • 10.

    Soares Magalhaes RJ, Downs PW, Kabore A, Zhang Y, Ottesen EA, Biritwum N-K, 2013. Predictive vs. Empiric assessment of schistosomiasis: implications for treatment projections in Ghana. PLoS Negl Trop Dis 7: e2051.

    • Search Google Scholar
    • Export Citation
  • 11.

    Watson M, 2009. Praziquantel. J Exot Pet Med 18: 229231.

  • 12.

    Vázquez LI, Valera E, Villalobos M, Tous M, Arija V, 2019. Prevalence of anemia in children from Latin america and the caribbean and effectiveness of nutritional interventions: systematic review and meta–analysis. Nutrients 11: 183.

    • Search Google Scholar
    • Export Citation
  • 13.

    Butler SE, Muok EM, Montgomery SP, Odhiambo K, Mwinzi PMN, Secor WE, Karanja DMS, 2012. Mechanism of anemia in Schistosoma mansoni-infected school children in Western Kenya. Am J Trop Med Hyg 87: 862867.

    • Search Google Scholar
    • Export Citation
  • 14.

    Yenilmez ED, Tuli A, 2018. Laboratory approach to anemia. Khan J, ed. Current Topics in Anemia. Vol. I. London, UK: InTech Open, 235–253.

  • 15.

    Scholte RGC, Gosoniu L, Malone JB, Chammartin F, Utzinger J, Vounatsou P, 2014. Predictive risk mapping of schistosomiasis in Brazil using bayesian geostatistical models. Acta Trop 132: 5763.

    • Search Google Scholar
    • Export Citation
  • 16.

    Remais JV, Zeng G, Li G, Tian L, Engelgau MM, 2013. Convergence of non-communicable and infectious diseases in low- and middle-income countries. Int J Epidemiol 42: 221227.

    • Search Google Scholar
    • Export Citation
  • 17.

    World Health Organization, 2000. Obesity: Preventing and Managing the Global Epidemic. Geneva, Switzerland: WHO.

  • 18.

    World Health Organization, 2007. BMI-for-Age Girls Thinness Severe Thinness. Geneva, Switzerland: WHO.

  • 19.

    World Health Organization, 2007. BMI-for-Age Boys Thinness Severe Thinness. Geneva, Switzerland: WHO.

  • 20.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2014. Pesquisa Suplementar de Segurança Alimentar PNAD 2013. A percepção das família em relação ao acesso aos Alimentos. Rio de Janeiro, Brasil: IBGE, 134.

    • Search Google Scholar
    • Export Citation
  • 21.

    Timm NH, 2002. Applied Multivariate Analysis. New York, NY: Springer.

  • 22.

    Johnson RA, Wichern DW, 2007. Applied Multivariate Statistical Analysi, 6th edition. Upper Saddle River, NJ: Pearson Education.

  • 23.

    Casavechia GM et al. 2018. Systematic review and meta-analysis on Schistosoma mansoni infection prevalence, and associated risk factors in Brazil. Parasitology 145: 10001014.

    • Search Google Scholar
    • Export Citation
  • 24.

    Hailu T, Alemu M, Abera B, Mulu W, Yizengaw E, Genanew A, Bereded F, 2018. Multivariate analysis of factors associated with Schistosoma mansoni and hookworm infection among primary school children in rural Bahir Dar, Northwest Ethiopia. Trop Dis Trav Med Vaccines 4: 4.

    • Search Google Scholar
    • Export Citation
  • 25.

    Majorin F, Torondel B, Routray P, Rout M, Clasen T, 2017. Identifying potential sources of exposure along the child feces management pathway: a cross-sectional study among urban slums in Odisha, India. Am J Trop Med Hyg 97: 861869.

    • Search Google Scholar
    • Export Citation
  • 26.

    Fenwick A, Jourdan P, 2016. Schistosomiasis elimination by 2020 or 2030? Int J Parasitol 46: 385388.

  • 27.

    Gazzinelli A, Velasquez-Melendez G, Crawford S, LoVerde P, Correa-Oliveira R, Kloos H, 2006. Socioeconomic determinants of schistosomiasis in a poor rural area in Brazil. Running short title: socioeconomic determinants of schistosomiasis in Brazil. Acta Trop 2–3: 260271.

    • Search Google Scholar
    • Export Citation
  • 28.

    Kloos H, Correa-Oliveira R, Quites HF, Souza MC, Gazzinelli A, 2008. Socioeconomic studies of schistosomiasis in Brazil: a review. Acta Trop 108: 194201.

    • Search Google Scholar
    • Export Citation
  • 29.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2017. Rendimento Domiciliar Per Capita 2017. Rio de Janeiro, Brazil: IBGE.

  • 30.

    Ministério da Fazenda, 2017. Decreto No 9.255, de 29 de Dezembro de 2017. Brasília, Brazil.

  • 31.

    Ministério do Desenvolvimento Social, 2016. Bolsa Família e Cadastro Único Município Pureza/RN. Brasília, Brazil: Ministério do Desenvolvimento Social. Available at: http://mds.gov.br/bolsafamilia. Accessed October 18, 2018.

    • Search Google Scholar
    • Export Citation
  • 32.

    Martins APB, Monteiro CA, 2016. Impact of the Bolsa Família program on food availability of low-income Brazilian families: a quasi experimental study. BMC Public Health 16: 111.

    • Search Google Scholar
    • Export Citation
  • 33.

    Moradi S, Mirzababaei A, Dadfarma A, Rezaei S, Mohammadi H, Jannat B, Mirzaei K, 2019. Food insecurity and adult weight abnormality risk: a systematic review and meta-analysis. Eur J Nutr 58: 4561.

    • Search Google Scholar
    • Export Citation
  • 34.

    Kushitor MK, Boatemaa S, 2018. The double burden of disease and the challenge of health access: evidence from access, bottlenecks, cost and equity facility survey in Ghana. PLoS One 13: 111.

    • Search Google Scholar
    • Export Citation
  • 35.

    Martins-Melo FR, Carneiro M, Ramos AN, Heukelbach J, Ribeiro ALP, Werneck GL, 2018. The burden of neglected tropical diseases in Brazil, 1990–2016: a subnational analysis from the global burden of disease study 2016. PLoS Negl Trop Dis 12: 124.

    • Search Google Scholar
    • Export Citation
  • 36.

    Marinho F et al. 2018. Burden of disease in Brazil, 1990–2016: a systematic subnational analysis for the global burden of disease study 2016. Lancet 392: 760775.

    • Search Google Scholar
    • Export Citation
  • 37.

    Olds GR et al. 1999. Double-blind placebo-controlled study of concurrent administration of albendazole and praziquantel in schoolchildren with schistosomiasis and geohelminths. J Infect Dis 179: 9961003.

    • Search Google Scholar
    • Export Citation
  • 38.

    Ministério da Saúde, 2016. Pce - Programa de Controle da Esquistossomose - Rio Grande do Norte. Brasília, Brazil: Mininistério da Saúde. Available at: http://tabnet.datasus.gov.br/cgi/tabcgi.exe?sinan/pce/cnv/pceRN.def. Accessed October 4, 2018.

    • Search Google Scholar
    • Export Citation
  • 39.

    Katz N, 2018. Inquérito Nacional de Prevalência Da Esquistossomose Mansoni e Geo-Helmintoses. Belo Horizonte, Brazil.

  • 40.

    Tarafder M, Carabin H, Joseph L, Balolong E Jr., Olveda R, McGarvey ST, 2010. Estimating the sensitivity and specificity of Kato-Katz stool examination technique for detection of hookworms, Ascaris lumbricoides and Trichuris trichiura infections in humans in the absence of a ‘gold standard’. Int J Parasitol 40: 399404.

    • Search Google Scholar
    • Export Citation
  • 41.

    Bärenbold O, Raso G, Coulibaly JT, N’Goran EK, Utzinger J, Vounatsou P, 2017. Estimating sensitivity of the Kato-Katz technique for the diagnosis of Schistosoma mansoni and hookworm in relation to infection intensity. PLoS Negl Trop Dis 11: 114.

    • Search Google Scholar
    • Export Citation
  • 42.

    Machado GCXMP, Haguenauer CJ, Ruprecht T, Sobrinho FX, Gallo E, 2018. Livros. Filho WL, Freitas LEde, eds. Climate Change Adaption in Latin American. Cham, Switzerland: Springer, 103130.

    • Search Google Scholar
    • Export Citation
  • 43.

    Instituto Brasileiro de Geografia e Estatística - IBGE, 2017. Pureza: Trabalho, Território e Ambiente. Rio de Janeiro, Brazil: IBGE. Available at: https://cidades.ibge.gov.br/brasil/rn/pureza. Accessed October 8, 2018.

    • Search Google Scholar
    • Export Citation
  • 44.

    Figueiredo FF, Federal U, 2017. O Saneamento Básico no nordeste e no Rio Grande no Norte: avanços e constrangimentos Sanitation in the northeast and Rio Grando do Norte: advances and constraints. Xvii Enanpur DESENVOLVIMENTO, Cris E Resist QUAIS OS CAMINHOS DO Planej URBANO E Reg. Available at: http://www.repositorio.ufrn.br:8080/jspui/bitstream/123456789/23431/1/Saneamento basico no NE e RN.pdf.

    • Search Google Scholar
    • Export Citation
  • 45.

    Howard G, 2002 Excreta disposal. Heal Villages a Guid Communities Community Health, 3847. Available at: http://www.who.int/water_sanitation_health/hygiene/settings/hvchap4.pdf?ua=1.

    • Search Google Scholar
    • Export Citation
  • 46.

    Bethony J et al. 2001 Exposure to Schistosoma mansoni infection in a rural area in Brazil. II: household risk factors. Trop Med Int Health 6: 136145.

    • Search Google Scholar
    • Export Citation
  • 47.

    Sow S, de Vlas SJ, Stelma F, Vereecken K, Gryseels B, Polman K, 2011. The contribution of water contact behavior to the high Schistosoma mansoni Infection rates observed in the Senegal River Basin. BMC Infect Dis 11: 111.

    • Search Google Scholar
    • Export Citation
  • 48.

    Sokolow SH et al. 2015 Reduced transmission of human schistosomiasis after restoration of a native river prawn that preys on the snail intermediate host. Proc Natl Acad Sci USA 112: 96509655.

    • Search Google Scholar
    • Export Citation
  • 49.

    World Health Organization, 2008. The social context of schistosomiasis and its control an introduction and annotated bibliography. Bruun B, Aagaard-Hansen J, Watts S, ed. Geneva, Switzerland: WHO, 75–126. doi: 10.2471/TDR.08.978924159718 0.

    • Search Google Scholar
    • Export Citation
  • 50.

    Calasans TAS, Souza GTR, Melo CM, Madi RR, de Lourdes Sierpe Jeraldo V, 2018. Socioenvironmental factors associated with Schistosoma mansoni infection and intermediate hosts in an urban area of northeastern Brazil. PLoS One 13: 115.

    • Search Google Scholar
    • Export Citation

Author Notes

Address correspondence to Selma M. B. Jerônimo, Institute of Tropical Medicine of Rio Grande do Norte, Av Senador Salgado Filho 3000, Lagoa Nova, Natal 59078900, Brazil. E-mail: smbj@cb.ufrn.br

Financial support: This study was supported in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil (Finance Code 001) and CNPq (440893/2016-0).

Authors’ addresses: Danielle V. F. Bezerra, Institute of Tropical Medicine of Rio Grande do Norte, Brazil and Postgraduate in Health Sciences of Federal University of Rio Grande do Norte, Natal, Brazil, E-mail: danielleviviannefb@gmail.com. José W. Queiroz, Institute of Tropical Medicine of Rio Grande do Norte, Natal, Brazil, E-mail: jwq.wil@gmail.com. Victor A. V. Câmara, Institute of Tropical Medicine of Rio Grande do Norte, Natal, Brazil, E-mail: victorcamara.rn@gmail.com. Bruna L. L. Maciel, Nutrition Department of Federal University of Rio Grande do Norte, Natal, Brazil, E-mail: brunalimamaciel@gmail.com. Eliana L. T. Nascimento, Institute of Tropical Medicine of Rio Grande do Norte and Department of Infectious Diseases, Federal University of Rio Grande do Norte, Natal, Brazil, E-mail: eltomaz@gmail.com. Selma M. B. Jerônimo, Institute of Tropical Medicine of Rio Grande do Norte, Natal, Brazil, Postgraduate in Health Sciences of Federal University of Rio Grande do Norte, Natal, Brazil, Departament of Biochemistry, Federal University of Rio Grande do Norte, Natal, Brazil, and Institute of Science and Technology of Tropical Diseases, INCT-DT, Salvador, Brazil, E-mail: smbj@cb.ufrn.br.

Save