• 1

    King CH, 2006. Long-term outcomes of school-based treatment for control of urinary schistosomiasis: a review of experience in Coast Province, Kenya. Mem Inst Oswaldo Cruz 101 (Suppl 1):299–306.

    • Search Google Scholar
    • Export Citation
  • 2

    Koukounari A, Gabrielli AF, Touré S, Bosqué-Oliva E, Zhang Y, Sellin B, Donnelly CA, Fenwick A, Webster JP, 2007. Schistosoma haematobium infection and morbidity before and after large-scale administration of praziquantel in Burkina Faso. J Infect Dis 196 :659–669.

    • Search Google Scholar
    • Export Citation
  • 3

    Midzi N, Sangweme D, Zinyowera S, Mapingure MP, Brouwer KC, Kumar N, Mutapi F, Woelk G, Mduluza T, 2008. Efficacy and side effects of praziquantel treatment against Schistosoma haematobium infection among primary school children in Zimbabwe. Trans R Soc Trop Med Hyg 102 :759–766.

    • Search Google Scholar
    • Export Citation
  • 4

    Rudge JW, Stothard JR, Basáñez MG, Mgeni AF, Khamis IS, Khamis AN, Rollinson D, 2008. Micro-epidemiology of urinary schistosomiasis in Zanzibar: local risk factors associated with distribution of infections among schoolchildren and relevance for control. Acta Trop 105 :45–54.

    • Search Google Scholar
    • Export Citation
  • 5

    Hatz C, Savioli L, Mayombana C, Dhunputh J, Kisumku U, Tanner M, 1990. Measurement of schistosomiasis-related morbidity at community level in areas of different endemicity. Bull World Health Organ 68 :777–787.

    • Search Google Scholar
    • Export Citation
  • 6

    van der Werf MJ, de Vlas SJ, 2004. Diagnosis of urinary schistosomiasis: a novel approach to compare bladder pathology measured by ultrasound and three methods for hematuria detection. Am J Trop Med Hyg 71 :98–106.

    • Search Google Scholar
    • Export Citation
  • 7

    Attallah AM, Ismail H, El Masry SA, Rizk H, Handousa A, El Bendary M, Tabll A, Ezzat F, 1999. Rapid detection of a Schistosoma mansoni circulating antigen excreted in urine of infected individuals by using a monoclonal antibody. J Clin Microbiol 37 :354–357.

    • Search Google Scholar
    • Export Citation
  • 8

    Van Lieshout L, De Jonge N, el Masry NA, Mansour MM, Krijger FW, Deelder AM, 1992. Improved diagnostic performance of the circulating antigen assay in human schistosomiasis by parallel testing for circulating anodic and cathodic antigens in serum and urine. Am J Trop Med Hyg 47 :463–469.

    • Search Google Scholar
    • Export Citation
  • 9

    el Missiry AG, el Serougi AO, Salama MM, Kamal AM, 1990. Evaluation of dot ELISA technique in the serodiagnosis of schistosomiasis in Egypt. J Egypt Soc Parasitol 20 :639–645.

    • Search Google Scholar
    • Export Citation
  • 10

    van Lieshout L, Polderman AM, Deelder AM, 2000. Immunodiagnosis of schistosomiasis by determination of the circulating antigens CAA and CCA, in particular in individuals with recent or light infections. Acta Trop 77 :69–80.

    • Search Google Scholar
    • Export Citation
  • 11

    Ruiz R, Candia P, Garassini M, Tombazzi C, Certad G, Bruces AC, Noya O, Alarcón de Noya B, 2002. Schistosomiasis mansoni in low transmission areas. Abdominal ultrasound. Mem Inst Oswaldo 97 :153–159.

    • Search Google Scholar
    • Export Citation
  • 12

    Amis ES, Cronan JJ, Pfister RC, Yoder IC, 1982. Ultrasonic inaccuracies in diagnosing renal obstruction. Urology 9 :101–105.

  • 13

    Degremont A, Burki A, Burnier E, Schweizer W, Meudt R, Tanner M, 1985. Value of ultrasonography in investigating morbidity due to Schistosoma haematobium infection. Lancet 23 :662–665.

    • Search Google Scholar
    • Export Citation
  • 14

    Etard JF, 2004. Modélisation de la sensibilité, spécificité et valeurs prédictives de la recherche d’une hématurie par bandelettes réactives dans le diagnostic de l’infection par Schistosoma haematobium. Bull Soc Pathol Exot 97 :24–28.

    • Search Google Scholar
    • Export Citation
  • 15

    Taylor P, Chandiwana SK, Matnhire D, 1990. Evaluation of the reagent strip test for haematuria in the control of Schistosoma haematobium infection in school children. Acta Trop 47 :91–100.

    • Search Google Scholar
    • Export Citation
  • 16

    Webb JAW, 1990. Ultrasonography in the diagnosis of renal obstruction: sensitive but not very specific. BMJ 301 :944–946.

  • 17

    Bosompem KM, Owusu O, Okanla EO, Kojima S, 2004. Applicability of a monoclonal antibody-based dipstick in diagnosis of urinary schistosomiasis in the central region of Ghana. Trop Med Int Health 9 :991–996.

    • Search Google Scholar
    • Export Citation
  • 18

    Doenhoff MJ, Chiodini PL, Hamilton JV, 2004. Specific and sensitive diagnosis of schistosome infection: can it be done with antibodies? Trends Parasitol 20 :35–39.

    • Search Google Scholar
    • Export Citation
  • 19

    Begg CB, 1987. Biases in the assessment of diagnostic tests. Stat Med 6 :411–423.

  • 20

    Formann AK, 1994. Measurement errors in caries diagnosis: some further latent class models. Biometrics 50 :865–871.

  • 21

    Oheneba-Sakyi Y, Heaton TB, 1993. Effects of socio-demographic variables on birth intervals in Ghana. J Comp Fam Stud 24 :113–135.

  • 22

    Bosompem KM, Arishima T, Yamashita T, Ayi I, Anyan WK, Kojima S, 1996. Extraction of Schistosoma haematobium antigens from infected human urine and generation of potential diagnostic monoclonal antibodies to urinary antigens. Acta Trop 62 :91–103.

    • Search Google Scholar
    • Export Citation
  • 23

    Bosompem KM, Asigbee J, Otchere J, Haruna A, Kpo KH, Kojima S, 1998. Accuracy of diagnosis of urinary schistosomiasis: comparison of parasitological and a monoclonal antibody-based dip-stick method. Parasitol Int 47 :211–217.

    • Search Google Scholar
    • Export Citation
  • 24

    Weber MC, Blair DM, Clarke VV, 1967. The pattern of schistosome egg distribution in a micturition flow. Cent Afr J Med 13 :75–88.

  • 25

    Bartholomew DJ, Knott M, 1999. Latent Variable Models and Factor Analysis. London: Edward Arnold.

  • 26

    Rindskopf D, Rindskopf W, 1986. The value of latent class analysis in medical diagnosis. Stat Med 5 :21–27.

  • 27

    Formann AK, Kohlmann T, 1996. Latent class analysis in medical research. Stat Methods Med Res 5 :179–211.

  • 28

    Clogg CC, Goodman LA, 1984. Latent structure analysis of a set of multidimensional contingency tables. J Am Stat Assoc 79 :762–771.

  • 29

    Wilson RA, van Dam GJ, Kariuki TM, Farah IO, Deelder AM, Coulson PS, 2006. The detection limits for estimates of infection intensity in Schistosomiasis mansoni established by a study in non-human primates. Int J Parasitol 36 :1241–1244.

    • Search Google Scholar
    • Export Citation
  • 30

    Bosompem KM, Bentum IA, Otchere J, Anyan WK, Brown CA, Osada Y, Takeo S, Kojima S, Ohta N, 2004. Infant schistosomiasis in Ghana: a survey in an irrigation community. Trop Med Int Health 9 :917–922.

    • Search Google Scholar
    • Export Citation
  • 31

    Alvord WG, Drummond JE, Arthur LO, Biggar RJ, Goedert JJ, Levine PH, Murphy EL Jr, Weiss SH, Blattner WA, 1988. A method for predicting individual HIV infection status in the absence of clinical information. AIDS Res Hum Retroviruses 4 :295–304.

    • Search Google Scholar
    • Export Citation
  • 32

    Engels EA, Sinclair MD, Biggar RJ, Whitby D, Ebbesen P, Goedert JJ, Gastwirth JL, 2000. Latent class analysis of human herpesvirus 8 assay performance and infection prevalence in sub-Saharan Africa and Malta. Int J Cancer 53 :852–862.

    • Search Google Scholar
    • Export Citation
  • 33

    Hebert MR, Rose JS, Rosengard C, Clarke JG, Stein MD, 2007. Levels of trauma among women inmates with HIV risk and alcohol use disorders: behavioral and emotional impacts. J Trauma Dissociation 8 :27–46.

    • Search Google Scholar
    • Export Citation
  • 34

    Kudel I, Farber SL, Mrus JM, Leonard AC, Sherman SN, Tsevat J, 2006. Patterns of responses on health-related quality of life questionnaires among patients with HIV/AIDS. J Gen Intern Med 21 (Suppl 5):S48–S55.

    • Search Google Scholar
    • Export Citation
  • 35

    Langhi DM Jr, Bordin JO, Castelo A, Walter SD, Moraes-Souza H, Stumpf RJ, 2002. The application of latent class analysis for diagnostic test validation of chronic Trypanosoma cruzi infection in blood donors. Braz J Infect Dis 6 :181–187.

    • Search Google Scholar
    • Export Citation
  • 36

    Strauss SM, Rindskopf DM, Astone-Twerell JM, Des Jarlais DC, Hagan H, 2006. Using latent class analysis to identify patterns of hepatitis C service provision in drug-free treatment programs in the U.S. Drug Alcohol Depend 83 :15–24.

    • Search Google Scholar
    • Export Citation
  • 37

    Booth M, Vounatsou P, N’Goran EK, Tanner M, Utzinger J, 2003. The influence of sampling effort and the performance of the Kato-Katz technique in diagnosing Schistosoma mansoni and hookworm co-infections in rural Côte d’Ivoire. Parasitology 127 :525–531.

    • Search Google Scholar
    • Export Citation
  • 38

    Utzinger J, Vounatsou P, N’Goran EK, Tanner M, Booth M, 2002. Reduction in the prevalence and intensity of hookworm infections after praziquantel treatment for Schistosomiasis infection. Int J Parasitol 32 :759–765.

    • Search Google Scholar
    • Export Citation
  • 39

    Carabin H, Balolong E, Joseph L, McGarvey ST, Johansen MV, Fernandez T, Willingham AL, Olveda R, 2005. Estimating sensitivity and specificity of a faecal examination method for Schistosoma japonicum infection in cats, dogs, water buffaloes, pigs and rats in Western Samar and Sorsogon Provinces, The Philippines. Int J Parasitol 35 :1517–1524.

    • Search Google Scholar
    • Export Citation
  • 40

    World Health Organization, 2006. Preventive Chemotherapy in Human Helminthiasis. Geneva: World Health Organization.

  • 41

    Koukounari A, Sacko M, Keita AD, Gabrielli AF, Landouré A, Dembelé R, Clements AC, Whawell S, Donnelly CA, Fenwick A, Traoré M, Webster JP, 2006. Assessment of ultrasound morbidity indicators of schistosomiasis in the context of large-scale programs illustrated with experiences from Malian children. Am J Trop Med Hyg 75 :1042–1052.

    • Search Google Scholar
    • Export Citation
  • 42

    Dunyo SK, Appawu M, Nkrumah FK, Baffoe-Wilmot A, Pedersen EM, Simonsen PE, 1996. Lymphatic filariasis on the coast of Ghana. Trans R Soc Trop Med Hyg 90 :634–638.

    • Search Google Scholar
    • Export Citation
  • 43

    Doenhoff MJ, Butterworth AE, Hayes RJ, Sturrock RF, Ouma JH, Koech D, Prentice M, Bain J, 1993. Seroepidemiology and serodiagnosis of schistosomiasis in Kenya using crude and purified egg antigens of Schistosoma mansoni in ELISA. Trans R Soc Trop Med Hyg 87 :42–48.

    • Search Google Scholar
    • Export Citation
  • 44

    Xue CG, Taylor MG, Bickle QD, Savioli L, Renganathan EA, 1993. Diagnosis of Schistosoma haematobium infection: evaluation of ELISA using keyhole limpet haemocyanin or soluble egg antigen in comparison with detection of eggs or haematuria. Trans R Soc Trop Med Hyg 87 :654–658.

    • Search Google Scholar
    • Export Citation
  • 45

    Hamilton JV, Klinkert M, Doenhoff MJ, 1998. Diagnosis of schistosomiasis: antibody detection, with notes on parasitological and antigen detection methods. Parasitology 117 (Suppl):S41–S57.

    • Search Google Scholar
    • Export Citation
  • 46

    Albert PS, Dodd LE, 2004. A cautionary note on the robustness of latent class models for estimating diagnostic error without a gold standard. Biometrics 60 :427–435.

    • Search Google Scholar
    • Export Citation
  • 47

    Vacek PM, 1985. The effect of conditional dependence on the evaluation of diagnostic tests. Biometrics 41 :959–968.

  • 48

    Nsowah-Nuamah NN, Mensah G, Aryeetey ME, Wagatsuma Y, Bentil G, 2001. Urinary schistosomiasis in southern Ghana: a logistic regression approach to data from a community-based integrated control program. Am J Trop Med Hyg 65 :484–490.

    • Search Google Scholar
    • Export Citation
  • 49

    Amankwa JA, Bloch P, Meyer-Lassen J, Olsen A, Christensen NO, 1994. Urinary and intestinal schistosomiasis in the Tono irrigation scheme, Kassena/Nankana District, upper east region, Ghana. Trop Med Parasitol 45 :319–323.

    • Search Google Scholar
    • Export Citation

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sensitivities and Specificities of Diagnostic Tests and Infection Prevalence of Schistosoma haematobium Estimated from Data on Adults in Villages Northwest of Accra, Ghana

View More View Less
  • 1 Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, and Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College, London, United Kingdom; The Methodology Center, Pennsylvania State University, State College, Pennsylvania; Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore Maryland; Department of Parasitology, Noguchi Memorial Institute for Medical Research, Legon, Accra, Ghana

Substantial uncertainties surround the sensitivities and specificities of diagnostic techniques for urinary schistosomiasis. We used latent class (LC) modeling to address this problem. In this study, 220 adults in three villages northwest of Accra, Ghana were examined using five Schistosoma haematobium diagnostic measures: microscopic examination of urine for detection of S. haematobium eggs, dipsticks for detection of hematuria, tests for circulating antigens, antibody tests, and ultrasound scans of the urinary system. Testing of the LC model indicated non-invariance of the performance of the diagnostic tests across different age groups, and measurement invariance held for males and females and for the three villages. We therefore recommend the use of LC models for comparison between and the identification of the most accurate schistosomiasis diagnostic tests. Furthermore, microscopy and hematuria dipsticks were indicated through these models as the most appropriate techniques for detection of S. haematobium infection.

INTRODUCTION

In spite of the prolific generation of new knowledge in the area of urinary schistosomiasis, such as that of global burden, treatment, and associated morbidity,14 there remains the unsolved practical issue associated with the basic diagnosis of this important parasitic disease. This issue relates to the direct (i.e., microscopic examination of filters used to filter urine for detection of Schistosoma haematobium eggs) as well as with the indirect (i.e., detection of hematuria, schistosome-specific antibodies, and circulating egg antigens, and ultrasound scans of the urinary system) diagnostic methods of this schistosome infection. There are several reasons for limitations in the diagnosis of urinary schistosomiasis, such as daily variation in egg excretion levels and/or duration of infection influencing the potential accuracy of determining the correct current infection status.5

Hematuria (blood in urine) alone has been proposed as a valid indication of current infection in S. haematobium-endemic populations.6 Microhematuria can be detected by reagent strips (dipsticks) that recognize blood and protein. However, for the distinction of an active infection from a previous infection, particularly after treatment, in many populations and persons, circulating schistosome antigen has been proposed as the most reliable test. 7,8 In addition, although serologic diagnosis of schistosomiasis is generally accurate,9 it can also produce false-negative results, particularly in patients with longstanding infections, and elevated antibody levels can be still detectable many years after treatment. 10

Ultrasound is currently the diagnostic tool of choice for detecting pathologic conditions associated with urinary schistosomiasis, such as dilatation of the renal pelvis and bladder wall lesions, although its usefulness has been questioned, particularly in low transmission areas, because of its lack of specificity. 11 In addition, large variations of sensitivity and specificity estimates have been observed among different endemic zones, age groups, and sexes for all the aforementioned diagnostic methods of urinary schistosomiasis in several studies. 1216

One explanation for the inconsistencies between these diagnostic tests relates to the current lack of a definitive gold standard reference test for urinary schistosomiasis. Consequently, diagnosis of schistosomiasis and control of this disease becomes problematic. Diagnostic assays with low sensitivities are unsuitable for evaluation of schistosomiasis control programs, such as those aimed at morbidity reduction through mass human chemotherapy. 17 Methods that enable infections to be correctly diagnosed are a prerequisite for effective disease control. 18 One solution may therefore relate to the need for more sophisticated statistical models to be developed and used to obtain more reliable empirical estimates of sensitivities and specificities of diagnostic tests. 19,20

In the present study, we assessed the performance of five diagnostic tests for S. haematobium infection and estimated the prevalence of this infection in different age and sex groups in three villages northwest of Accra, Ghana. Specifically, we used five diagnostic tests for the prevalence of urinary schistosomiasis: a urine antigen detection test performed on membranes or in enzyme-linked immunosorbent assay plates, a serologic anti-IgG test, an ultrasound assessment by recording the shape and state of the urinary bladder, a dipstick for hematuria using urine reagent strips on all urine specimens for presence of detectable blood, and detection of S. haematobium eggs by microscopy. Through the application of a latent class (LC) model to all five of these tests, the sensitivity and specificity of each test can be determined, and the overall urinary schistosomiasis prevalence levels within the different population groups can be estimated.

MATERIALS AND METHODS

Study sites and participants.

Three villages northwest of Accra, Ghana, Ayiki Doblo, Chento, and Ntoaso, were visited and consenting adults > 19 years of age formed a convenience sample of passers by. However, in general, with regards to the demography in the greater Accra region, the age structure is still a youthful one, characterized by a somewhat high fertility that has begun to show signs of a steep downward trend. 21 The general public in the three aforementioned villages are familiar with the work of the Noguchi Memorial Institute for Medical Research and its personnel. Through discussions with local authorities, the public was alerted, and people were approached and asked to participate. These volunteers were then interviewed and requested to provide specimens of urine, stool, and blood for examination. Praziquantel (40 mg/kg) was offered and taken after diagnosis of all infected cases of schistosomiasis. At subsequent visits, bladder ultrasound scans were performed on most participants. All examinations were performed at village clinics. Participants responded to a questionnaire, most of which were reported to be peasant farmers and persons involved in agriculture. Others responded as traders or vendors, but most reported regular water contact in the nearby river system. Although there was municipal water available in Ntoaso, many residents do not have access to clean running water, and through their daily activities were thereby potentially exposed to risks of schistosome transmission. A total of 220 persons consented to participate, had complete data on the variables examined, and were included in the analysis of the present study. The age, sex structure, and village location of all the sampled persons is shown in Table 1, which shows that a lower proportion of persons who consented to participate and had complete data were < 39 years of age old and were Ayiki Doblo and Chento.

Urine-antigen detection test.

Detection of schistosome antigen in urine was performed according to the method of Bosompem and others, 22 which has shown that S. haematobium antigen complexed with complement C3 can be isolated from the urine of infected persons by using a mouse monoclonal antibody. These investigators demonstrated that goat-antihuman C3 would also detect schistosome antigen/ complement complex in the urine of infected persons, but not in non-infected persons used as case-controls, and subsequently developed a monoclonal antibody dipstick test on the basis of these findings. 23 Briefly, methanol-treated poly-vinylidene difluoride membrane strips were incubated in test urine for 30 minutes at room temperature (21–25°C), rinsed with Tris-buffered saline (TBS) (50 mM Tris, 200 mM NaCl, pH 7.4), and blocked for 15 minutes in 5% skimmed milk in TBS. The strips were then incubated in a reagent mixture of S. haematobium species-specific monoclonal antibody (1:100) and goat anti-mouse-immunoglobulins conjugated to horse-radish peroxidase (1:10) in 0.1% skimmed milk in TBS for one hour. The strips were washed three times (10 minutes/wash) by incubation in TBS and incubated in substrate solution (0.05% [w/v] 3,3-diaminobenzidine), 0.15% (v/v) H2O2 and 5 mM Co (NO3)2.6H2O in TBS for 1 minute. A blue-black reaction indicated positive results and a colorless reaction indicated negative results.

Anti-IgG test.

Detection of anti-schistosome IgG in serum was performed on serum eluted from dried blood spots on Whatman (Maidstone, United Kingdom) no.1 filter paper. Blood spots that filled a 1-cm diameter circle were taken at the time of examination, desiccated, and kept dry until analysis. These were eluted in 1 mL of phosphate-buffered saline, diluted 1:100, and tested in enzyme-linked immunosorbent assay plates (Immunolon-2) in triplicate. Analyses were repeated if there was more than 10% discrepancy. Plates were sensitized with soluble worm antigen preparation (6.44 mg/mL) prepared from S. mansoni adult worms provided by the Biomedical Research Institute (Rockville, MD). Antigen dilution was optimized against sera from known positive S. haematobium infections and known schistosome negative sera. Optical densities were read from a Vmax kinetic microplate reader (Molecular Devices, Sunnyvale, CA).Results were scored positive when the optical density exceeded 2× the SD of negative controls.

Ultrasound examination.

A portable ultrasound apparatus (Aloka SSD-500 portable ultrasound with a 3.5-MHz curvilinear probe; Aloka, Tokyo, Japan) was used for ultrasound examination, with the diagnoses made by a medically qualified person with prior training in ultrasound examination and interpretation. Examinations were performed using a curvilinear probe and recorded photographically. Diagnosis of pathological lesions was made in situ, and later confirmed by review of the ultraradiograph. For the purpose of this study, lesions were classified as positive or negative. Positive cases were registered when any two of the following situations were evident: epithelium enlarged > 5 mm, evidence of polyps in the bladder wall, calcification of the epithelium, and evidence of hydronephrosis.

Parasitologic examination.

Classic parasitologic methods usually used by field clinicians were used and evaluated in this study. Microscopy was performed on the product of one measure of filtration of 10 mL of urine taken from a specimen passed between 10:00 am and 2:00 pm, the time of optimum egg passage. 24 Urine specimens were kept cool in an insulated ice box and processed in the laboratory within four hours of passing. The presence of any S. haematobium eggs was recorded as positive. Hematuria was detected by the use of a standard hemastix, with any positive reaction being designated positive for urinary schistosomiasis (Multistix; Bayer Diagnostics, Leverkusen, Germany).

Statistical analysis.

By considering the true S. haematobium infection status of a sample of adults in Ghana as a latent variable with two categories (infected and non-infected), we validated the five diagnostic tests. We considered the observed data of the five diagnostic tests (urine antigen detection, anti-IgG test, ultrasound, dipstick for hematuria, and microscopy) as indicators of an underlying, not directly observable variable (i.e., S. haematobium infection). Results of the five diagnostic tests are directly observed and are known as manifest variables and S. haematobium infection is the unobservable latent variable. 25

Given a sample of persons with unknown infection status, for whom results from several diagnostic tests are available, LC analysis can model the probability of each combination of tests results conditional on LC (i.e., infection status). The manifest binary variables (x1j, x2j, x3j, x4j, and x5j) were defined such that xij = 0 represents a negative result for test i and xij = 1 represents a positive test result for test i for person j. We tested whether correlations between these manifest variables could be accounted for by one latent dichotomous variable Y (i.e., the absence Y = 0 or presence Y = 1 of S. haematobium infection) and we defined η = P(Y = 1) as the probability of being in the infected LC. We divided the studied population into two classes (i.e., non-infected and infected) assuming that the xijs were mutually independent within each class (i.e., true infection status). It is expected that the xijs are correlated because they are attempting to measure the presence of the same infection; the model assumes that these correlations are negligibly small only once one has accounted for the true infection status of a person (i.e., LC membership). This assumption results in a more parsimonious model compared with one in which residual correlations are estimated, and one that is often adequate for the data. In the unlikely case that there are substantial residual correlations between the xijs, additional LCs would likely be required for an adequate fit to the data.

The likelihood function of the LC model was

Such a model has two types of parameters. First, there is the unconditional probability η that a person is in the infected LC.

The second type of parameters are the conditional probabilities πi1 and πi0 that a person in a particular LC has a specified value of each of the manifest variables. 26 πi1 represents the sensitivity and is the conditional probability P(xi = 1|yj = 1) and (1 − πi0) represents the specificity and is the conditional probability P(xi = 0|yj = 0). Thus, the LC model produces an estimate of disease prevalence because η is the proportion of persons in the population of which our sample is expected to be in infection class Y = 1. It also provides direct estimates of sensitivity and specificity for all diagnostic tests. 27

A natural way to extend LC model 1 is to include stratification or grouping variables and examine group differences of measurement invariance. In this study, such group differences are examined for males/females, different village locations, and age groups. Likelihood ratio tests between less and more restrictive models were used to examine differences in infection prevalence and measurement invariance between groups. A significant measurement invariance tests suggests that specificities and sensitivities of the diagnostic tests vary by group and should be estimated for each group. Such an approach is referred to in the literature as multigroup LC analysis (LCA) and comparisons of this sort are useful for at least two purposes: 1) to test whether the distribution of the latent variable is the same in each group and 2) to test whether the manifest observed variables are equally reliable indicators of the latent variable in each group. 28

An expectation-maximization algorithm was applied to produce maximum likelihood estimates for all parameters in the model by using PROC LCA in SAS Version 9.1 (SAS Institute, Cary, NC). Identifiability of maximum likelihood parameter estimates was checked by using several different seed values.

RESULTS

Table 2 shows the observed positive results expressed as percentages of S. haematobium infection for the five diagnostic tests. Different diagnostic tests gave different proportions of positive results.

Table 3 shows the results of one LC model as it was dictated by likelihood ratio tests. Specifically, this model, denoted in Table 3 as LC Model 1, is a LC model in which measurement invariance was found to hold among males and females. Because of the measurement invariance found here, we obtain a common set of specificities and sensitivities for males and females. The best diagnostic test for the detection of the prevalence of S. haematobium infection among the five diagnostic tests examined here was microscopy with a specificity estimated as 97.9% and a sensitivity estimated as 92.5%. In addition, LC Model 1 yielded high specificities and sensitivities for hematuria and ultrasound. From this same model, estimates of prevalence of S. haematobium infection by sex were also obtained. It is estimated that the prevalence of S. haematobium infection was highest among males (20.6%) than females (9.7%).

LC Model 2 (Table 4) is an LC analysis model where measurement invariance was found to hold among different village locations and this is again the reason why we obtain only a set of specificities and sensitivities for this group of sampled persons. Results of this model agree with results of LC Model 1 in Table 3 . The best diagnostic test for the detection of the prevalence of S. haematobium infection was microscopy with a specificity estimated as 94.6% and a sensitivity as 100.0%. In addition, LC Model 2 yielded high specificities and sensitivities for hematuria and ultrasound. Furthermore, LC Model 2 also indicated Chento as the village with the highest prevalence of S. haematobium infection (38.9%) among the three examined villages.

LC Model 3 (Table 5) is an LC model where measurement non-invariance was found for different age groups. This is the reason why different specificities and sensitivities are calculated for each of these groups. Using this model, diagnostic tests that could be characterized as acceptable for detection of the prevalence of S. haematobium infection were those of ultrasound, hematuria, and microscopy in the age groups 19–29 and 40–49 years of age; hematuria and microscopy were indicated as good diagnostic tests in the age group 30–39 years of age because both had high specificities and sensitivities at the same time. Finally, in the age group ≥ 60 years of age, estimates of specificity and sensitivity were sufficiently high (93.2% and 100.0%, respectively) only for hematuria. For the age group 50–59 years of age, when estimates of specificity and sensitivity were considered, none of the diagnostic tests examined was indicated as appropriate. From this same model, estimates of prevalence of S. haematobium infection by age group were also obtained. LC model 3 shows that the highest prevalence of active, i.e., by egg passage, S. haematobium infection was determined among the youngest age group of the sampled persons in this study (29.8%).

DISCUSSION

Current estimates of the prevalence of schistosomiasis depend on the use of well-established, but imperfect, diagnostic tests. 29 Appropriate diagnosis of schistosomiasis becomes increasingly important for several reasons. For example, clinical diagnosis might lose its value because of lack of specificity and mass treatment might only remain cost effective through the use of appropriate diagnostic tools to only target further drug treatment to those groups of people actually infected. 10 The purpose of the epidemiologic survey reported here was to assess the performance of five diagnostic tests for S. haematobium infection and examine if the prevalence of this infection varied across different age and sex groups of sampled persons from three villages northwest of Accra, Ghana, where there has been reported previously medium S. haematobium prevalence.30 We have addressed this specific problem by taking into account the absence of a gold standard diagnostic test for S. haematobium infection and by fitting LC models with a frequentist approach to these data obtained from adults northwest of Accra, Ghana.

Although LC models have been used extensively in the epidemiologic literature of several infectious diseases, 3136 they have rarely been used in parasite epidemiology and particularly in the area of schistosomiasis. More precisely, to our knowledge, only two previously published studies, both in Côte d’ Ivoire, have used LC models through a Bayesian approach to assess performance of the Kato-Katz technique in diagnosing S. mansoni and hookworm co-infections and to estimate reduction of prevalence and intensity for hookworm infection in humans post-praziquantel treatment. 37,38 Only one study in the Philippines has provided estimates of sensitivity and specificity of a fecal examination method for S. japonicum infection in mammals by also using a similar statistical modeling approach within a Bayesian framework. 39

Our study therefore provides the first, to our knowledge, evaluation of the performance of multiple diagnostic criteria and estimation of the prevalence of S. haematobium infection in Africa and raises important implications to consider with reference to reliable tests for the diagnosis of urinary schistosomiasis. Such findings should also be of direct relevance and application to current mass chemotherapeutic control programs. Nevertheless, because the current dataset focuses on adults, we would recommend additional similar studies aimed to assess the application of such LC models on data from school age children across various schistosomiasis-endemic regions within sub-Saharan Africa because schoolchildren form the major target age group of current mass chemotherapeutic control in human helminthiasis 40

Results of this study clearly demonstrate that in adults, microscopic detection of parasite eggs in urine is the best currently available diagnostic tool for S. haematobium infection (Tables 3–5), except for the age group ≥ 50 years of age, in which low specificities were estimated (Table 5). Standard errors of the estimates were larger for the older age groups than for the younger age groups because of smaller sample sizes (Table 1). Therefore, such results should be interpreted cautiously. On the basis of these findings, we recommend inclusion of microscopic examination in the monitoring process of human mass chemotherapy programs whenever financial resources allow for this option, mainly because of its relatively low operational cost compared with other urinary schistosomiasis diagnostic techniques and its feasibility under most conditions. Furthermore, because microscopic examination can quantify the intensity of the S. haematobium infection, it enables evaluation of important indicators in the control planning, such as possible risk factors, presence of severe clinical forms, degree of transmission and reinfection in the area, and intervals for necessary re-treatments.

In addition, this study confirms that hematuria dipsticks can be sufficiently sensitive and specific indicators (Tables 3–5), except for the age group 50–59 years of age, in which hematuria dipsticks yielded a low sensitivity (45%) for detection of S. haematobium infection in disease-endemic areas (Table 5). Therefore, we would also recommend inclusion of hematuria dipsticks in the monitoring process of human mass chemotherapy programs. Recent studies have also showed that semiquantitative reading of dipsticks correlates well with intensity of S. haematobium infection and ultrasound pathology. 2,41

Conversely, although the urine antigen detection test showed similar sensitivity to microscopy ( Tables 3–5 ), it was also suggested that false-positive results in urine antigen detection tests may be more common than previously reported. 23 One potential explanation for the low specificity of this test might be that potentially cross-reactive parasites are more prevalent in the age group studied here, and polyparasitism is common in these areas. Dunyo and others 42 found filarial infections in towns or villages east of Accra in a similar age group, and we would thus recommend further studies to define the prevalence of such parasites in this same disease-endemic area and examine any potential cross-reactivity between helminth species in the urine antigen detection test. Results from the current study suggest that the urine-antigen detection tests we evaluated should not be used for identification of high-risk groups, which because of the possibility of false-positive reactions produced by such tests, could artificially inflate the actual numbers of people targeted for mass chemotherapy. Furthermore, estimates from all LC models presented yielded low sensitivities and specificities for anti-IgG tests. The observation that antibody detection lacks specificity is consistent with findings of other epidemiologic studies, which reported that antibody is often found without concomitant parasitologic evidence of infection. 43,44

Furthermore, antigen detection methods are generally more expensive than antibody detection methods. 45 Conversely, microscopy and hematuria dipsticks require relatively unsophisticated equipment and, in areas of high endemicity, personnel with only basic training. These two diagnostic tests could therefore constitute the lowest cost option when technical assistance is plentiful. Thus, the current findings, if combined with consideration of costs involved, which is a critical issue in the economically developing countries, leads us to the conclusion that antibody and antigen detection tests should not be used in the determination of the prevalence of long-term urinary schistosomiasis.

With reference to detection of urinary schistosomiasis through ultrasound examination, results of this study indicated that the performance of this diagnostic tool was acceptable in all age groups except in those 30–39 years of age and ≥ 50 years of age. An explanation for the variability in these results among different age groups might be that successive episodes of infection would result in recrudescence of urinary tract abnormalities and more severe pathology caused by urinary schistosomiasis would be expected to be observed because of continuing reinfection. Thus, we conclude that ultrasound examination is not a reasonable substitute for microscopy or dipsticks in regards to determining the prevalence of S. haematobium infection. Nevertheless, we would still support the argument that the best currently available diagnostic tool for morbidity assessment in S. haematobium infections is the visualization of urinary tract pathology through ultrasound examination.

Finally, with statistical analysis alone, one can never be certain about the validity of a dependence model because it is not known from the observed data how each of the examined diagnostic tests relates to the others conditional on disease status. 46 Consequently, we recognize that the results of this study depend upon the assumption of conditional independence assumed by the models fitted here. In addition, LC models based on current assumptions may not be appropriate for some similar alternative datasets because large correlations (if these are present after accounting for LC membership, i.e., the true infection status) could potentially bias parameter estimates and result in an underestimation of the error rates of the examined tests. 47

Through the use of LC models, we assessed the prevalence of S. haematobium infection because accurate sensitive and specific measures for this indicator are imperative, particularly at later stages of successful mass chemotherapy control programs. We demonstrate that LC models proved to be a useful tool for validation research in the absence of a perfect gold-standard diagnostic technique. These models have suggested microscopy and hematuria dipsticks as sensitive and specific indicators of prevalence of S. haematobium infection in adults in Ghana. In addition, they have provided estimated prevalences of S. haematobium infection that fit well with those previously obtained by Nsowah-Nuamah and others 48 in southern Ghana and Amankwa and others 49 in the upper eastern region of Ghana, as well as focality of this infection even in small areas of this country. However, it must be also considered that in the general context of chemotherapy programs, if monitoring and evaluation results are based exclusively on determining infection prevalence, the impact data obtained may inaccurately reflect the success of any program. Therefore, it is also fundamental to monitor the impact of such control programs on the intensity of infection and morbidity changes in the treated population, particularly because modern chemotherapy programs are aimed at reducing morbidity and infection intensity. Thus, further research in this area is thereby warranted.

Table 1

Age class, sex, and village of study participants

Table 1
Table 2

Positive results expressed as percentages by each of the five diagnostic tests among the 220 adults in Ghana studied

Table 2
Table 3

Specificity (Spec) and sensitivity (Sens) diagnostic tests estimated from latent class (LC) model 1 when measurement invariance was imposed across males and females

Table 3
Table 4

Specificity (Spec) and sensitivity (Sens) of diagnostic tests estimated from latent class (LC) model 2 when measurement invariance was imposed across different village locations

Table 4
Table 5

Specificity (Spec) and sensitivity (Sens) of diagnostic tests estimated from latent class (LC) model 3 when measurement invariance was not imposed across different age groups

Table 5

*

Address correspondence to Artemis Koukounari, Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College Faculty of Medicine, St. Mary’s Campus, Norfolk Place, London, W2 1PG, United Kingdom. E-mail: artemis.koukounari@imperial.ac.uk

Authors’ addresses: Artemis Koukounari and Joanne P. Webster, Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College, St. Mary’s Campus, Norfolk Place, London W2 1PG, United Kingdom, E-mails: artemis.koukounari@imperial.ac.uk and joanne.webster@imperial.ac.uk. Christl A. Donnelly, Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College, St. Mary’s Campus, Norfolk Place, London W2 1PG, United Kingdom, E-mail: c.donnelly@imperial.ac.uk. Bethany C. Bray, The Methodology Center, Pennsylvania State University, 204 E. Calder Way, Suite 400, State College, PA 16801, E-mail: bcbray@psu.edu. Jean Naples and Clive Shiff, Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD 21205, E-mails: jnaples@jhsph.edu and cshiff@jhsph.edu. Kwabena Bosompem, Department of Parasitology, Noguchi Memorial Institute for Medical Research, Legon, Accra, Ghana, E-mail: kbosompem@noguchi.mimcom.net.

Acknowledgments: We thank the adults for participating in the study and the numerous members of the field research team for their hard work.

Financial support: This study was supported by funds from the Schistosomiasis Control Initiative to Artemis Koukounari and Joanne P. Webster, Medical Research Council to Christl A. Donnelly and grant no. 1RO3CA103497-01 from the National Cancer Institute to Clive Shiff. Bethany Bray was supported by Award Number P50-DA-010075 from the National Institute on Drug Abuse. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health.

REFERENCES

  • 1

    King CH, 2006. Long-term outcomes of school-based treatment for control of urinary schistosomiasis: a review of experience in Coast Province, Kenya. Mem Inst Oswaldo Cruz 101 (Suppl 1):299–306.

    • Search Google Scholar
    • Export Citation
  • 2

    Koukounari A, Gabrielli AF, Touré S, Bosqué-Oliva E, Zhang Y, Sellin B, Donnelly CA, Fenwick A, Webster JP, 2007. Schistosoma haematobium infection and morbidity before and after large-scale administration of praziquantel in Burkina Faso. J Infect Dis 196 :659–669.

    • Search Google Scholar
    • Export Citation
  • 3

    Midzi N, Sangweme D, Zinyowera S, Mapingure MP, Brouwer KC, Kumar N, Mutapi F, Woelk G, Mduluza T, 2008. Efficacy and side effects of praziquantel treatment against Schistosoma haematobium infection among primary school children in Zimbabwe. Trans R Soc Trop Med Hyg 102 :759–766.

    • Search Google Scholar
    • Export Citation
  • 4

    Rudge JW, Stothard JR, Basáñez MG, Mgeni AF, Khamis IS, Khamis AN, Rollinson D, 2008. Micro-epidemiology of urinary schistosomiasis in Zanzibar: local risk factors associated with distribution of infections among schoolchildren and relevance for control. Acta Trop 105 :45–54.

    • Search Google Scholar
    • Export Citation
  • 5

    Hatz C, Savioli L, Mayombana C, Dhunputh J, Kisumku U, Tanner M, 1990. Measurement of schistosomiasis-related morbidity at community level in areas of different endemicity. Bull World Health Organ 68 :777–787.

    • Search Google Scholar
    • Export Citation
  • 6

    van der Werf MJ, de Vlas SJ, 2004. Diagnosis of urinary schistosomiasis: a novel approach to compare bladder pathology measured by ultrasound and three methods for hematuria detection. Am J Trop Med Hyg 71 :98–106.

    • Search Google Scholar
    • Export Citation
  • 7

    Attallah AM, Ismail H, El Masry SA, Rizk H, Handousa A, El Bendary M, Tabll A, Ezzat F, 1999. Rapid detection of a Schistosoma mansoni circulating antigen excreted in urine of infected individuals by using a monoclonal antibody. J Clin Microbiol 37 :354–357.

    • Search Google Scholar
    • Export Citation
  • 8

    Van Lieshout L, De Jonge N, el Masry NA, Mansour MM, Krijger FW, Deelder AM, 1992. Improved diagnostic performance of the circulating antigen assay in human schistosomiasis by parallel testing for circulating anodic and cathodic antigens in serum and urine. Am J Trop Med Hyg 47 :463–469.

    • Search Google Scholar
    • Export Citation
  • 9

    el Missiry AG, el Serougi AO, Salama MM, Kamal AM, 1990. Evaluation of dot ELISA technique in the serodiagnosis of schistosomiasis in Egypt. J Egypt Soc Parasitol 20 :639–645.

    • Search Google Scholar
    • Export Citation
  • 10

    van Lieshout L, Polderman AM, Deelder AM, 2000. Immunodiagnosis of schistosomiasis by determination of the circulating antigens CAA and CCA, in particular in individuals with recent or light infections. Acta Trop 77 :69–80.

    • Search Google Scholar
    • Export Citation
  • 11

    Ruiz R, Candia P, Garassini M, Tombazzi C, Certad G, Bruces AC, Noya O, Alarcón de Noya B, 2002. Schistosomiasis mansoni in low transmission areas. Abdominal ultrasound. Mem Inst Oswaldo 97 :153–159.

    • Search Google Scholar
    • Export Citation
  • 12

    Amis ES, Cronan JJ, Pfister RC, Yoder IC, 1982. Ultrasonic inaccuracies in diagnosing renal obstruction. Urology 9 :101–105.

  • 13

    Degremont A, Burki A, Burnier E, Schweizer W, Meudt R, Tanner M, 1985. Value of ultrasonography in investigating morbidity due to Schistosoma haematobium infection. Lancet 23 :662–665.

    • Search Google Scholar
    • Export Citation
  • 14

    Etard JF, 2004. Modélisation de la sensibilité, spécificité et valeurs prédictives de la recherche d’une hématurie par bandelettes réactives dans le diagnostic de l’infection par Schistosoma haematobium. Bull Soc Pathol Exot 97 :24–28.

    • Search Google Scholar
    • Export Citation
  • 15

    Taylor P, Chandiwana SK, Matnhire D, 1990. Evaluation of the reagent strip test for haematuria in the control of Schistosoma haematobium infection in school children. Acta Trop 47 :91–100.

    • Search Google Scholar
    • Export Citation
  • 16

    Webb JAW, 1990. Ultrasonography in the diagnosis of renal obstruction: sensitive but not very specific. BMJ 301 :944–946.

  • 17

    Bosompem KM, Owusu O, Okanla EO, Kojima S, 2004. Applicability of a monoclonal antibody-based dipstick in diagnosis of urinary schistosomiasis in the central region of Ghana. Trop Med Int Health 9 :991–996.

    • Search Google Scholar
    • Export Citation
  • 18

    Doenhoff MJ, Chiodini PL, Hamilton JV, 2004. Specific and sensitive diagnosis of schistosome infection: can it be done with antibodies? Trends Parasitol 20 :35–39.

    • Search Google Scholar
    • Export Citation
  • 19

    Begg CB, 1987. Biases in the assessment of diagnostic tests. Stat Med 6 :411–423.

  • 20

    Formann AK, 1994. Measurement errors in caries diagnosis: some further latent class models. Biometrics 50 :865–871.

  • 21

    Oheneba-Sakyi Y, Heaton TB, 1993. Effects of socio-demographic variables on birth intervals in Ghana. J Comp Fam Stud 24 :113–135.

  • 22

    Bosompem KM, Arishima T, Yamashita T, Ayi I, Anyan WK, Kojima S, 1996. Extraction of Schistosoma haematobium antigens from infected human urine and generation of potential diagnostic monoclonal antibodies to urinary antigens. Acta Trop 62 :91–103.

    • Search Google Scholar
    • Export Citation
  • 23

    Bosompem KM, Asigbee J, Otchere J, Haruna A, Kpo KH, Kojima S, 1998. Accuracy of diagnosis of urinary schistosomiasis: comparison of parasitological and a monoclonal antibody-based dip-stick method. Parasitol Int 47 :211–217.

    • Search Google Scholar
    • Export Citation
  • 24

    Weber MC, Blair DM, Clarke VV, 1967. The pattern of schistosome egg distribution in a micturition flow. Cent Afr J Med 13 :75–88.

  • 25

    Bartholomew DJ, Knott M, 1999. Latent Variable Models and Factor Analysis. London: Edward Arnold.

  • 26

    Rindskopf D, Rindskopf W, 1986. The value of latent class analysis in medical diagnosis. Stat Med 5 :21–27.

  • 27

    Formann AK, Kohlmann T, 1996. Latent class analysis in medical research. Stat Methods Med Res 5 :179–211.

  • 28

    Clogg CC, Goodman LA, 1984. Latent structure analysis of a set of multidimensional contingency tables. J Am Stat Assoc 79 :762–771.

  • 29

    Wilson RA, van Dam GJ, Kariuki TM, Farah IO, Deelder AM, Coulson PS, 2006. The detection limits for estimates of infection intensity in Schistosomiasis mansoni established by a study in non-human primates. Int J Parasitol 36 :1241–1244.

    • Search Google Scholar
    • Export Citation
  • 30

    Bosompem KM, Bentum IA, Otchere J, Anyan WK, Brown CA, Osada Y, Takeo S, Kojima S, Ohta N, 2004. Infant schistosomiasis in Ghana: a survey in an irrigation community. Trop Med Int Health 9 :917–922.

    • Search Google Scholar
    • Export Citation
  • 31

    Alvord WG, Drummond JE, Arthur LO, Biggar RJ, Goedert JJ, Levine PH, Murphy EL Jr, Weiss SH, Blattner WA, 1988. A method for predicting individual HIV infection status in the absence of clinical information. AIDS Res Hum Retroviruses 4 :295–304.

    • Search Google Scholar
    • Export Citation
  • 32

    Engels EA, Sinclair MD, Biggar RJ, Whitby D, Ebbesen P, Goedert JJ, Gastwirth JL, 2000. Latent class analysis of human herpesvirus 8 assay performance and infection prevalence in sub-Saharan Africa and Malta. Int J Cancer 53 :852–862.

    • Search Google Scholar
    • Export Citation
  • 33

    Hebert MR, Rose JS, Rosengard C, Clarke JG, Stein MD, 2007. Levels of trauma among women inmates with HIV risk and alcohol use disorders: behavioral and emotional impacts. J Trauma Dissociation 8 :27–46.

    • Search Google Scholar
    • Export Citation
  • 34

    Kudel I, Farber SL, Mrus JM, Leonard AC, Sherman SN, Tsevat J, 2006. Patterns of responses on health-related quality of life questionnaires among patients with HIV/AIDS. J Gen Intern Med 21 (Suppl 5):S48–S55.

    • Search Google Scholar
    • Export Citation
  • 35

    Langhi DM Jr, Bordin JO, Castelo A, Walter SD, Moraes-Souza H, Stumpf RJ, 2002. The application of latent class analysis for diagnostic test validation of chronic Trypanosoma cruzi infection in blood donors. Braz J Infect Dis 6 :181–187.

    • Search Google Scholar
    • Export Citation
  • 36

    Strauss SM, Rindskopf DM, Astone-Twerell JM, Des Jarlais DC, Hagan H, 2006. Using latent class analysis to identify patterns of hepatitis C service provision in drug-free treatment programs in the U.S. Drug Alcohol Depend 83 :15–24.

    • Search Google Scholar
    • Export Citation
  • 37

    Booth M, Vounatsou P, N’Goran EK, Tanner M, Utzinger J, 2003. The influence of sampling effort and the performance of the Kato-Katz technique in diagnosing Schistosoma mansoni and hookworm co-infections in rural Côte d’Ivoire. Parasitology 127 :525–531.

    • Search Google Scholar
    • Export Citation
  • 38

    Utzinger J, Vounatsou P, N’Goran EK, Tanner M, Booth M, 2002. Reduction in the prevalence and intensity of hookworm infections after praziquantel treatment for Schistosomiasis infection. Int J Parasitol 32 :759–765.

    • Search Google Scholar
    • Export Citation
  • 39

    Carabin H, Balolong E, Joseph L, McGarvey ST, Johansen MV, Fernandez T, Willingham AL, Olveda R, 2005. Estimating sensitivity and specificity of a faecal examination method for Schistosoma japonicum infection in cats, dogs, water buffaloes, pigs and rats in Western Samar and Sorsogon Provinces, The Philippines. Int J Parasitol 35 :1517–1524.

    • Search Google Scholar
    • Export Citation
  • 40

    World Health Organization, 2006. Preventive Chemotherapy in Human Helminthiasis. Geneva: World Health Organization.

  • 41

    Koukounari A, Sacko M, Keita AD, Gabrielli AF, Landouré A, Dembelé R, Clements AC, Whawell S, Donnelly CA, Fenwick A, Traoré M, Webster JP, 2006. Assessment of ultrasound morbidity indicators of schistosomiasis in the context of large-scale programs illustrated with experiences from Malian children. Am J Trop Med Hyg 75 :1042–1052.

    • Search Google Scholar
    • Export Citation
  • 42

    Dunyo SK, Appawu M, Nkrumah FK, Baffoe-Wilmot A, Pedersen EM, Simonsen PE, 1996. Lymphatic filariasis on the coast of Ghana. Trans R Soc Trop Med Hyg 90 :634–638.

    • Search Google Scholar
    • Export Citation
  • 43

    Doenhoff MJ, Butterworth AE, Hayes RJ, Sturrock RF, Ouma JH, Koech D, Prentice M, Bain J, 1993. Seroepidemiology and serodiagnosis of schistosomiasis in Kenya using crude and purified egg antigens of Schistosoma mansoni in ELISA. Trans R Soc Trop Med Hyg 87 :42–48.

    • Search Google Scholar
    • Export Citation
  • 44

    Xue CG, Taylor MG, Bickle QD, Savioli L, Renganathan EA, 1993. Diagnosis of Schistosoma haematobium infection: evaluation of ELISA using keyhole limpet haemocyanin or soluble egg antigen in comparison with detection of eggs or haematuria. Trans R Soc Trop Med Hyg 87 :654–658.

    • Search Google Scholar
    • Export Citation
  • 45

    Hamilton JV, Klinkert M, Doenhoff MJ, 1998. Diagnosis of schistosomiasis: antibody detection, with notes on parasitological and antigen detection methods. Parasitology 117 (Suppl):S41–S57.

    • Search Google Scholar
    • Export Citation
  • 46

    Albert PS, Dodd LE, 2004. A cautionary note on the robustness of latent class models for estimating diagnostic error without a gold standard. Biometrics 60 :427–435.

    • Search Google Scholar
    • Export Citation
  • 47

    Vacek PM, 1985. The effect of conditional dependence on the evaluation of diagnostic tests. Biometrics 41 :959–968.

  • 48

    Nsowah-Nuamah NN, Mensah G, Aryeetey ME, Wagatsuma Y, Bentil G, 2001. Urinary schistosomiasis in southern Ghana: a logistic regression approach to data from a community-based integrated control program. Am J Trop Med Hyg 65 :484–490.

    • Search Google Scholar
    • Export Citation
  • 49

    Amankwa JA, Bloch P, Meyer-Lassen J, Olsen A, Christensen NO, 1994. Urinary and intestinal schistosomiasis in the Tono irrigation scheme, Kassena/Nankana District, upper east region, Ghana. Trop Med Parasitol 45 :319–323.

    • Search Google Scholar
    • Export Citation
Save