Risk analysis for occurrences of schistosomiasis in the coastal area of Porto de Galinhas, Pernambuco, Brazil

BMC Infectious Diseases

Constança Simões Barbosa²  Reinaldo Souza-Santos³  Julyana Viegas Campos²  Fernando José Moreira de Oliveira⁴  Onicio Batista Leal-Neto²  Elainne Christine de Souza Gomes¹ 

[1] Laboratory of Parasitology, Vitoria Academic Center, Federal University of Pernambuco, Recife, Pernambuco, Brazil;Schistosomiasis Laboratory and Reference Service, Department of Parasitology, Aggeu Magalhães Research Center, Fiocruz, Recife, Pernambuco, Brazil;Departmant of Endemic Diseases, National School of Public Health, Fiocruz, Rio de Janeiro, Brazil;Department of Public Health, Aggeu Magalhães Research Center, Fiocruz, Recife, Pernambuco, Brazil

关键词: Brazil;    Pernambuco;    Spatial analysis;    Risk analysis;    Schistosomiasis;   

Others  :  1134489
DOI  :  10.1186/1471-2334-14-101

 received in 2013-03-19, accepted in 2014-02-14,  发布年份 2014

【 摘 要 】

Background

Manson’s schistosomiasis continues to be a severe public health problem in Brazil, where thousands of people live under the risk of contracting this parasitosis. In the Northeast of Brazil, schistosomiasis has expanded from rural areas to the coast of Pernambuco State, where the intermediate host is Biomphalaria glabrata snails. This study aims at presenting situational analyses on schistosomiasis at the coastal locality of Porto de Galinhas, Pernambuco, Brazil, by determining the risk factors relating to its occurrence from the epidemiological and spatial perspectives.

Methods

In order to gather prevalence data, a parasitological census surveys were conducted in 2010 in the light of the Kato-Katz technique. Furthermore, malacological surveys were also conducted in the same years so as to define the density and infection rates of the intermediate host. Lastly, socioeconomic-behavioral survey was also conducted to determine the odds ratio for infection by Schistosoma mansoni. Based on these data, spatial analyses were done, resulting in maps of the risk of disease transmission. To predict the risk of schistosomiasis occurrence, a multivariate logistic regression was performed using R 2.13 software.

Results

Based on prevalence, malacological and socioeconomic-behavioural surveys, it was identified a prevalence of 15.7% in the investigated population (2,757 individuals). Due to the malacological survey, 36 breeding sites were identified, of which 11 were classified as foci of schistosomiasis transmission since they pointed out snails which were infected by Schistosoma mansoni. Overall, 11,012 snails (Biomphalaria glabrata) were collected. The multivariate regression model identified six explanatory variables of environmental, socioeconomic and demographic nature. Spatial sweep analysis by means of the Bernoulli method identified one statistically significant cluster in Salinas (RR = 2.2; p-value < 0.000), the district with the highest occurrence of cases.

Conclusions

Based on the resulting information from this study, the epidemiological dimensions of this disease are significant and severe, within the scenario of schistosomiasis in Pernambuco state. The risk factors which were identified in the predictive model made it clear that the environmental and social conditions influence on the schistosomiasis occurrences.

【 授权许可】

   
2014 de Souza Gomes et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Barbosa CS, Silva CB, Barbosa FS: Esquistossomose: Reprodução e Expansão da Endemia no Estado de Pernambuco no Brasil. Rev Saude Publica 1996, 30(6):609-616.
• [2]Barbosa CS, Pieri O, Barbosa FS: Ecoepidemiologia da Esquistossomose urbana na Ilha de Itamaracá. Rev Saude Publica 2000, 34(4):337-341.
• [3]Kloos H, Correa-Oliveira R, Reis DC, Rodrigues EW, Monteiro LAS, Gazzinelli A: The role of population movement in the epidemiology and control of schistosomiasis in Brazil: a preliminary typology of population movement. Mem Inst Oswaldo Cruz 2010, 105(4):578-586.
• [4]Bundy DAP, Blumenthal U: Human behaviour and the epidemiology of helminth infection. In Parasitism and Host Behaviour. Edited by Barnard C, Behnke JM. London: Taylor & Francis; 1990:264-289.
• [5]Brooker S: Spacial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamic and control. Trop Med Int Health 2007, 101:1-8.
• [6]Paredes H, Souza-Santos R, Resendes APC, Souza MAA, Albuquerque J, Bocanegra S, Gomes ECS, Barbosa CS: Spatial pattern, water use and risk level associated with the transmission of schistosomiasis on the north coast of Pernambuco, Brazil. Cad Saúde Pública 2010, 26:1013-1023.
• [7]Ximenes R, Southgate B, Smith PG, Guimarães-Neto L: Socioeconomic determinants schistosomiasis in an urban area in the Northeast of Brazil. Rev Panam Salud Publica 2003, 14(6):409-421.
• [8]Silva PB, Pieri OS, Travassos A, Florencio L, Barbosa CS: Aspectos físico-químicos e biológicos relacionados a ocorrência de Biomphalaria glabrata em focos litorâneos de esquistossomose em Pernambuco. Quim Nova 2006, 29:901-906.
• [9]Gazzinelli A, Velasquez-Melendez G, Crawford SB, LoVerde PT, Correa-Oliveira R, Kloos H: Socioeconomic determinants of schistosomiasis in a poor rural area in Brazil. Acta Trop 2006, 99:260-271.
• [10]Coura-Filho P: Uso do paradigma de risco para esquistossomose em áreas endêmicas do Brasil. Cad Saúde Pública 1994, 10(4):464-472.
• [11]Carvalho MS, Pina MF, Santos SM: Conceitos básicos de sistemas de informação geográfica e cartografia aplicados à saúde. Brasília: OPAS - MS; 2000.
• [12]Yang GJ, Vounatsou P, Zhou XN, Tanner M, Utzinger J: A Bayesian-based approach for spatio-temporal modeling of county level prevalence of Schistosoma japonicum infection in Jiangsu province, China. Int J Parasitol 2005, 35:155-162.
• [13]Cross ER, Bailey RC: Prediction of areas endemic for schistosomiasis through use of discriminant analysis of environmental data. Mil Med 1984, 149:28-30.
• [14]Cross ER, Bailey RC: Predicting areas endemic for schistosomiasis using weather variables and a Landsat data base. Mil Med 1984, 149:542-543.
• [15]Brooker S, Hay SI, Issae W, Hall A, Kihamia CM, Lwambo NJS, Wint W, Rogers DJ, Bundy DAP: Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data. Trop Med Int Health 2001, 6:998-1007.
• [16]Kulldorff M, Nagarwall A: Spatial disease clusters: detection and inference. Stat Med 1995, 14:799-810.
• [17]Cardim LL, Ferraudo AS, Pacheco STA, Reis RB, Silva MMN, Carneiro DDMT, Bavia ME: Analises espaciais da identificação das áreas de risco para a esquistossomose mansônica no município de Lauro de Freitas, Bahia, Brasil. Cad Saúde Pública 2011, 27(5):899-908.
• [18]Coleman M, Mabuza AM, Kok G, Coetzee M, Durrheim DN: Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes. Malar J 2009, 8:68. BioMed Central Full Text
• [19]Odoi A, Martin SW, Michel P, Middleton D, Holt J, Wilson J: Investigation of clusters of giardiasis using GIS and spatial scan statistic. Int J Health Geogr 2004, 3:11. BioMed Central Full Text
• [20]Brasil. Ministério da Saúde: Guia de Vigilância Epidemiológica. In Secretaria de Vigilância em Saúde. 7th edition. Brasília: Secretaria de Vigilância em Saúde, "Departamento de Vigilância Epidemiológica"; 2010.
• [21]Lambertucci JR: Acute schistosomiasis mansoni: revisited and reconsidered. Mem Inst Oswaldo Cruz 2010, 105(4):422-435.
• [22]Katz N, Peixoto SV: Análise crítica da estimativa do número de portadores de esquistossomose no Brasil. Rev Soc Bras Med Trop 2000, 33:303-308.
• [23]Barbosa CS, Domingues ALC, Abath F, Montenegro SML, Guida U, Carneiro J, Tabosa B, Moraes CNL, Spinelli V: Epidemia de Esquistossomose Aguda na Praia de Porto de Galinhas, Pernambuco, Brasil. Cad. Saúde Pública 2001, 17(3):725-728.
• [24]Barbosa CS, Montenegro SML, Abath FGC, Domingues ALC: Specific situations related to acute schistosomiasis in Pernambuco, Brazil. Mem. Inst.Oswaldo Cruz 2001, 96:169-172.
• [25]Barbosa CS, Araújo KC, Antunes L, Favre T, Pieri OS: Spacial distribution of schistosoma mansoni foci in Itamaracá Island, Pernambuco, Brazil. Mem. Inst.Oswaldo Cruz 2004, 99:79-83.
• [26]Barbosa CS, Araújo KC, Sevilha MAA, Melo F, Gomes ECS, Souza-Santos R: Current epidemiological status of schistosomiasis in the state of Pernambuco, Brazil. Mem. Inst.Oswaldo Cruz 2010, 105(4):549-554.
• [27]Araújo KCGM, Resendes APC, Souza-Santos R, Silveira Júnior JC, Barbosa CS: Análise espacial dos focos de Biomphalaria glabrata e de casos humanos de esquistossomose mansônica em Porto de Galinhas, Pernambuco, Brasil, no ano 2000. Cad. Saúde Pública 2007, 23(2):409-418.
• [28]Barbosa CS, Leal Neto OB, Gomes ECS, Araújo KCGM, Domingues ALC: The endemisation of schistosomiasis in Porto de Galinhas, Pernambuco, Brazil, 10 years after the first epidemic outbreak. Mem Inst Oswaldo Cruz 2011, 106:878-883.
• [29]Gomes ECS, Leal Neto OB, Albuquerque J, Silva HP, Barbosa CS: Schistosomiasis transmission and environmental change: a spatio-temporal analysis in Porto de Galinhas, Pernambuco - Brazil. Int J Health Geogr 2012, 11:51. BioMed Central Full Text
• [30]Kuntz ER: Effect of light and temperature on shedding of Schistosoma mansoni cercarie. Nav Med Res Inst 1946, 7:16.
• [31]Coutinho JO: Índices de infestação natural dos planorbídeos pelas cercárias do Schistosoma mansoni na cidade do Salvador- Bahia. Anais da Faculdade de Medicina de São Paulo 1950, 25:29-53.
• [32]Katz N, Chaves A, Pelegrino J: A simple device for quantitative stool thick smeart technique in schistosomiasis mansoni. Rev. Inst. Med. Trop 1972, 14:371-373.
• [33]Gomes R, Nascimento EF, Araújo FC: Por que os homens buscam menos os serviços de saúde do que as mulheres? As explicações de homens com baixa escolaridade e homens com ensino superior. Cad Saúde Pública 2007, 23(3):565-574.
• [34]Neves DP, Melo AL, Linardi PM, Vitor RWA: Parasitologia Humana. 11th edition. São Paulo: Atheneu; 2005:494.