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Biomed Res Int ; 2015: 1-16, 2015. ilus
Article in English | SES-SP, LILACS, SESSP-IALPROD, SES-SP, SESSP-IALACERVO | ID: biblio-1022429

ABSTRACT

Schistosomiasis constitutes a major public health problem, with an estimated 200 million people infected worldwide. Many areas of Brazil show low endemicity of schistosomiasis, and the current standard parasitological techniques are not sufficiently sensitive to detect the low-level helminth infections common in areas of low endemicity (ALEs). This study compared the Kato-Katz (KK); Hoffman, Pons, and Janer (HH); enzyme-linked immunosorbent assay- (ELISA-) IgG and ELISA-IgM; indirect immunofluorescence technique (IFT-IgM); and qPCR techniques for schistosomiasis detection in serum and fecal samples, using the circumoval precipitin test (COPT) as reference. An epidemiological survey was conducted in a randomized sample of residents from five neighborhoods of Barra Mansa, RJ, with 610 fecal and 612 serum samples. ELISA-IgM (21.4%) showed the highest positivity and HH and KK techniques were the least sensitive (0.8%). All techniques except qPCR-serum showed high accuracy (82­95.5%), differed significantly from COPT in positivity , and showed poor agreement with COPT. Medium agreement was seen with ELISA-IgG (Kappa = 0.377) and IFA (Kappa = 0.347). Parasitological techniques showed much lower positivity rates than those by other techniques. We suggest the possibility of using a combination of laboratory tools for the diagnosis of schistosomiasis in ALEs.


Subject(s)
Schistosomiasis mansoni/diagnosis , Schistosomiasis mansoni/parasitology , Schistosomiasis mansoni/epidemiology , Aged, 80 and over , Brazil/epidemiology , Aged , Humans , Immunoassay/methods , Immunoassay/statistics & numerical data , Precipitin Tests/methods , Child , Child, Preschool , Population Surveillance/methods , Prevalence , Reproducibility of Results , Sensitivity and Specificity , Risk Assessment/methods , Adult , Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques/statistics & numerical data , Endemic Diseases/statistics & numerical data , Young Adult , Infant , Middle Aged
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