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    Relationship between prevalence of infection and intensity of infection as expressed by geometric mean eggs per gram feces + 1. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

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    Relationships between prevalence of infection in 9- to 12-year-olds and other age groups. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

  • View in gallery

    Relationship between intensity of infection in 9- to 12-year-olds as expressed by geometric mean eggs per gram feces + 1 and the other age groups. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

  • 1.

    Montresor A, Crompton DWT, Hall A, Bundy DAP, Savioli L, 1998. Guidelines for the Evaluation of Soil-Transmitted Helminthiasis and Schistosomiasis at Community Level. Geneva, Switzerland: World Health Organization.

    • Search Google Scholar
    • Export Citation
  • 2.

    Savioli L, Stansfield S, Bundy DA, Mitchell A, Bhatia R, Engels D, Montresor A, Neira M, Shein AM, 2002. Schistosomiasis and soil-transmitted helminth infections: forging control efforts. Trans R Soc Trop Med Hyg 96: 577579.

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization, 2002. Prevention and Control of Schistosomiasis and Soil-Transmitted Helminthiasis. Report of a WHO Expert Committee. Geneva, Switzerland: World Health Organization. Available at: http://whqlibdoc.who.int/trs/WHO_TRS_912.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 4.

    World Health Organization, 2011. Report of an Informal Consultation on Schistosomiasis Control. Geneva, Switzerland: World Health Organization. Available at: www.who.int/iris/bitstream/10665/78066/1/9789241505017_eng.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 5.

    World Health Organization, 2006. Preventive Chemotherapy in Human Helminthiasis. Geneva, Switzerland: World Health Organization. Available at: http://whqlibdoc.who.int/publications/2006/9241547103_eng.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 6.

    World Health Organization, 2011. Helminth Control in School-Age Children: A Guide for Managers of Control Programmes. Geneva, Switzerland: World Health Organization. Available at: whqlibdoc.who.int/publications/2011/9789241548267_eng.pdf.

    • Search Google Scholar
    • Export Citation
  • 7.

    Pereira AP, Favre TC, Galvão AF, Beck L, Barbosa CS, Pieri OS, 2010. The prevalence of schistosomiasis in school-aged children as an appropriate indicator of its prevalence in the community. Mem Inst Oswaldo Cruz 105: 563569.

    • Search Google Scholar
    • Export Citation
  • 8.

    World Health Organization, 2010. Informal Consultation on Expanding Schistosomiasis Control in Africa, 78. Available at: http://www.who.int/schistosomiasis/epidemiology/PZQ_WHO_report_meeting.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 9.

    World Health Organization, 1996. Report of the WHO Informal Consultation on the Use of Chemotherapy for the Control of Morbidity Due to Soil-Transmitted Nematodes in Humans. WHO/CTD/SIP/96.2. Geneva, Switzerland: World health Organization. Available at: http://whqlibdoc.who.int/hq/1996/WHO_CTD_SIP_96.2.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 10.

    Katz N, Chaves A, Pellegrino J, 1972. A simple device for quantitative stool thick-smear technique in schistosomiasis mansoni. Rev Inst Med Trop Sao Paulo 14: 397400.

    • Search Google Scholar
    • Export Citation
  • 11.

    Brooker S, Kabatereine NB, Smith JL, Mupfasoni D, Mwanje MT, Ndayishimiye O, Lwambo NJ, Mbotha D, Karanja P, Mwandawiro C, Muchiri E, Clements AC, Bundy DA, Snow RW, 2009. An updated atlas of human helminth infections: the example of east Africa. Int J Health Geogr 8: 42.

    • Search Google Scholar
    • Export Citation
  • 12.

    Global Atlas of Helminth Infection, 2013. The Global Atlas of Helminth Infections. Available at: http://www.thiswormyworld.org. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 13.

    Countries supported by USAID's NTD program. Available at: http://www.neglecteddiseases.gov/countries/index.html.

  • 14.

    Evans DS, King JD, Eigege A, Umaru J, Adamani W, Alphonsus K, Sambo Y, Miri ES, Goshit D, Ogah G, Richards FO, 2013. Assessing the WHO 50% prevalence threshold in school-aged children as indication for treatment of urogenital schistosomiasis in adults in central Nigeria. Am J Trop Med Hyg 88: 441445.

    • Search Google Scholar
    • Export Citation
  • 15.

    Odiere MR, Opisa S, Odhiambo G, Jura WG, Ayisi JM, Karanja DM, Mwinzi PN, 2011. Geographical distribution of schistosomiasis and soil-transmitted helminths among school children in informal settlements in Kisumu City, western Kenya. Parasitology 138: 15691577.

    • Search Google Scholar
    • Export Citation
  • 16.

    Odiere MR, Rawago FO, Ombok M, Secor WE, Karanja DM, Mwinzi PN, Lammie PJ, Won K, 2013. High prevalence of schistosomiasis in Mbita and its adjacent islands of Lake Victoria, western Kenya. Parasit Vectors 5: 278.

    • Search Google Scholar
    • Export Citation
  • 17.

    Handzel T, Karanja DM, Addiss DG, Hightower AW, Rosen DH, Colley DG, Andove J, Slutsker L, Secor WE, 2003. Geographic distribution of schistosomiasis and soil-transmitted helminths in western Kenya: implications for anthelminthic mass treatment. Am J Trop Med Hyg 69: 318323.

    • Search Google Scholar
    • Export Citation
  • 18.

    Verani JR, Abudho B, Montgomery SP, Mwinzi PN, Shane HL, Butler SE, Karanja DM, Secor WE, 2011. Schistosomiasis among young children in Usoma, Kenya. Am J Trop Med Hyg 84: 787791.

    • Search Google Scholar
    • Export Citation
  • 19.

    Wood SN, 2006. Generalized Additive Models: An Introduction with R. Boca Raton, FL: CRC Press.

  • 20.

    Schwarz GE, 1978. Estimating the dimension of a model. Ann Stat 6: 461464.

  • 21.

    Montresor A, Stoltzfus RJ, Albonico M, Tielsch JM, Rice AL, Chwaya HM, Savioli L, 2002. Is the exclusion of children under 24 months from anthelmintic treatment justifiable? Trans R Soc Trop Med Hyg 96: 197199.

    • Search Google Scholar
    • Export Citation
  • 22.

    Stothard JR, Sousa-Figueriredo JC, Betson M, Bustinduy A, Reinhard-Rupp J, 2013. Schistosomiasis in African infants and preschool children: let them now be treated! Trends Parasitol 29: 197205.

    • Search Google Scholar
    • Export Citation
  • 23.

    Coulibaly JT, N'Gbesso YK, N'Guessan NA, Winkler MS, Utzinger J, N'Goran EK, 2013. Epidemiology of schistosomiasis in two high-risk communities of south Côte d'Ivoire with particular emphasis on pre-school-aged children. Am J Trop Med Hyg 89: 3241.

    • Search Google Scholar
    • Export Citation
  • 24.

    Favre TC, Pereira AP, Galvao AF, Zani LC, Barbosa CS, Pieri OS, 2009. A rationale for schistosomiasis control in elementary schools of the rainforest zone of Pernambuco, Brazil. PLoS Negl Trop Dis 3: e395.

    • Search Google Scholar
    • Export Citation
  • 25.

    Rodrigues LC, Wheeler JG, Shier R, Guerra HL, Pimenta F Jr, Lima e Costa MF, 2000. Predicting the community prevalence of schistosomiasis mansoni from the prevalence among 7- to 14-year-olds. Parasitology 121: 507512.

    • Search Google Scholar
    • Export Citation
  • 26.

    Traore M, Maude GH, Bradley DJ, 1998. Schistosomiasis haematobia in Mali: prevalence rate in school-age children as index of endemicity in the community. Trop Med Int Health 3: 214221.

    • Search Google Scholar
    • Export Citation
  • 27.

    Guyatt HL, Brooker S, Donnelly CA, 1999. Can prevalence of infection in school-aged children be used as an index for assessing community prevalence? Parasitology 118: 257268.

    • Search Google Scholar
    • Export Citation
  • 28.

    Brooker S, Donnelly CA, Guyatt HL, 2000. Estimating the number of helminthic infections in the Republic of Cameroon from data on infection prevalence in schoolchildren. Bull World Health Organ 78: 14561465.

    • Search Google Scholar
    • Export Citation
  • 29.

    Samuels AM, Matey E, Mwinzi PN, Wiegand RE, Muchiri G, Ireri E, Hyde M, Montgomery SP, Karanja DM, Secor WE, 2012. Schistosoma mansoni morbidity among school-aged children: a SCORE project in Kenya. Am J Trop Med Hyg 87: 874882.

    • Search Google Scholar
    • Export Citation
  • 30.

    Schall VT, 1994. Environmental and health education for school-age children: a transdisciplinary approach. Cad Saude Publica 10: 259263.

    • Search Google Scholar
    • Export Citation
  • 31.

    Massara CL, Peixoto SV, Enk MJ, da Silva Barros H, dos Santos Carvalho O, Sakurai E, Schall V, 2006. Evaluation of an improved approach using residences of schistosomiasis-positive school children to identify carriers in an area of low endemicity. Am J Trop Med Hyg 74: 495499.

    • Search Google Scholar
    • Export Citation
  • 32.

    Enk MJ, Lima AC, Massara CL, Coelho PM, Schall VT, 2008. A combined strategy to improve the control of Schistosoma mansoni in areas of low prevalence in Brazil. Am J Trop Med Hyg 78: 140146.

    • Search Google Scholar
    • Export Citation
  • 33.

    Barbosa CS, Favre TC, Wanderley TN, Callou AC, Pieri OS, 2006. Assessment of schistosomiasis, through school surveys, in the Forest Zone of Pernambuco, Brazil. Mem Inst Oswaldo Cruz 101 (Suppl 1): 5562.

    • Search Google Scholar
    • Export Citation
  • 34.

    Favre TC, Ximenes RA, Galvao AF, Pereira AP, Wanderlei TN, Barbosa CS, Pieri OS, 2006. Reliability of current estimates of schistosomiasis prevalence in the Rainforest Zone of the state of Pernambuco, northeastern Brazil. Mem Inst Oswaldo Cruz 101 (Suppl 1): 7378.

    • Search Google Scholar
    • Export Citation

 

 

 

 

Predictive Value of School-Aged Children's Schistosomiasis Prevalence and Egg Intensity for Other Age Groups in Western Kenya

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  • Center for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya; Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia

World Health Organization recommendations for the timing and target population for mass drug administration (MDA) for schistosomiasis are based on the prevalence of infection in school children within a given community. In a large study comparing MDA approaches for Schistosoma mansoni control, we evaluated whether prevalence of infection and egg burdens in 9- to 12-year-old students reflected infection levels in young children and adults in the same community. Cross-sectional surveys of preadolescents (9–12 years old) were compared with those of first year students (5–8 years old) in 225 villages and adults (20–55 years old) in 150 villages along the Kenyan shores of Lake Victoria. Village schistosomiasis prevalence and intensity levels in preadolescents strongly correlated (P < 0.0001) with prevalence and infection intensity for other age groups in the community. Our findings suggest that S. mansoni prevalence and intensity among 9- to 12-year-olds are valid for community sampling purposes in mapping for MDAs.

Introduction

In 1998, the World Health Organization (WHO) formulated an operational model to guide national, regional, and local health authorities with regard to the planning and execution of schistosomiasis surveillance and control programs at the community level.1 This model was further refined2 and incorporated into the recommendations of the Expert Committee of the WHO,3 which focused on endemic countries that were having difficulty attaining their goals. A revised second edition was published in 2011.4 The strategy recommends testing school-aged children (SAC) for both baseline and follow-up surveys to assess the prevalence of schistosomiasis and determine the intervention needs for the community as a whole. The recommendations provide for targeted distribution of praziquantel (PZQ) based on the prevalence of infection in SAC.3,57 Areas where ≥ 50% of SAC have schistosome eggs detected in their stool are considered at high risk, and mass PZQ treatment should be provided to SAC yearly. Furthermore, adults in these areas, from special at-risk groups to the whole community, should also be treated. For moderate risk areas with 10–49% SAC prevalence, mass treatment of SAC is recommended once every 2 years, along with adults considered at risk. For areas with 1–10% prevalence, SAC should be treated at least twice during the primary school years. The strategy also recommends that in the high-risk areas, mass drug administration (MDA) should be combined with sanitation improvement, environmental management, and health education.5,8

Before implementation of any control activities for soil-transmitted helminths (STHs) and schistosomiasis, a baseline survey is needed.9 This allows for a situational analysis and determination of intervention strategies based on prevalence of infection. Thereafter, follow-up surveys are used to monitor the impact of mass treatments. The Kato-Katz test10 on stool collected from representative samples of schoolchildren is the methodology currently recommended by WHO for monitoring prevalence of intestinal schistosomiasis and STH. School children are considered ideal subjects for baseline surveys because schools are easily accessible and SAC bear the highest burden of these infections. Moreover, prevalence and intensity levels in this group are believed to be representative of the community, and therefore, the SAC prevalence can be used to make intervention decisions for other age groups.

Although WHO and other partners have provided basic information for each country online,1113 that information may not be current or sufficiently detailed at the implementation unit level. Individual countries should conduct baseline prevalence surveys to adapt the recommended strategy for local situations and to allow for comparisons in subsequent monitoring and evaluation. The WHO recommendations may not be always applicable to the reality in some settings if the 6- to 15-year-old age group does not truly reflect the prevalence of the disease and the need for intervention in the community as a whole.14

In Kenya, the current control strategy for STHs and schistosomiasis is school-based mass chemotherapy with albendazole (since 2009) and PZQ (since 2012), administered in prioritized areas by a national control team with cascaded support at the county and subcounty levels. Prioritization of targeted areas is based on historical data generated from these areas, and implementation is accompanied by baseline surveys. Because different segments of a community may be infected depending on prevailing economic activities, it is important to determine the extent of disease among age groups that are not targeted by current strategies. Moreover, while there are already vast amounts of data on infection in SAC, there are much less community-based data available to inform intervention decisions at the community level. Therefore, we sought to determine whether SAC constitute an effective reference group to assess the Schistosoma mansoni prevalence in the overall community in endemic areas of western Kenya.

Methods

Ethics statement and eligibility criteria.

This study was reviewed and given scientific and ethical clearance by the departmental and institutional Scientific Steering Committees of Kenya Medical Research Institute (KEMRI) and the KEMRI National Ethics Review Committee. The Institutional Review Boards of both the Centers for Disease Control and Prevention (CDC) and the University of Georgia also reviewed the study protocol and deferred to the KEMRI National Ethics Review Committee. Written informed consent was obtained from parents or guardians of children eligible for inclusion, along with written assent from the 5- to 14-year-old participants. Adults living in the same communities as the primary schools were included into the study once they provided written informed consent.

Study area and inclusion of study villages into the study.

Cross-sectional data were collected from students attending schools within approximately 10 km of Lake Victoria in the Nyanza Province of Kenya based on historical data that showed a high prevalence of S. mansoni, but very few Schistosoma haematobium, infections in the area.1518 No school-based MDA for schistosomiasis had been performed in the study area prior to collection of the data; however, one round of MDA for STHs had been carried out in the area by the national deworming program 1 year prior to the study. As part of two larger Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) projects designed to evaluate the impact of different MDA strategies, 13- to 14-year-old children were screened in 300 schools to determine eligibility of villages for the study. A single stool was examined (two slides per stool) by the Kato-Katz fecal thick smear technique from 50 children in each school. If between 5 and 12 children were positive for S. mansoni eggs, the community was eligible for entrance into the Sm1 study evaluating MDA approaches in villages with moderate prevalence (10–24%); if 13 or more children were positive, the community was eligible for the Sm2 study that was designed to evaluate MDA in high prevalence (> 25%) villages. Based on the S. mansoni infection prevalence in 13- to 14-year-olds and the larger study designs, there were 75 villages included in the Sm1 study and 150 villages included in the Sm2 study. MDA with praziquantel (40 mg/kg) was provided to the villages included in the studies.

Stool examination.

For all villages included in either study, we sought to enroll 100 first-year students (generally 5–8 years old) and 100 students 9- to 12-years old. For the Sm2 study, 50 adults were also enrolled in each village. First year students and adults were given stool containers and asked to provide a single fresh stool sample. The 9- to 12-year-old students were asked to provide stool on 3 consecutive days; however, to provide comparable sensitivity among the different age groups, only the data from the first day's stool was used for the analyses in this study. Samples were transported to the CDC/KEMRI laboratory where they were processed and examined by the Kato-Katz technique for detection of parasite eggs, 41 mg per slide and two slides per stool. The presence of S. mansoni, Ascaris lumbricoides, and Trichuris trichiura eggs was recorded. Egg counts were quantified for S. mansoni only. The arithmetic mean of egg counts was calculated from the two slides and multiplied by 24 to express data as eggs per gram (EPG). Each stool evaluation was performed by trained microscopists blinded to prior stool results.

Data handling and analysis.

EpiCollect Application (Imperial College, London, United Kingdom) was installed on smartphones and was used to collect demographic data that were then uploaded to a dedicated database maintained on a central server. Laboratory data were collected on paper forms and entered via the smartphones into the same database. Data were analyzed using R version 3.1.2 (R Foundation for Statistical Computing, Vienna, Austria). For each participant, the results of testing on a single stool were used for determination of schistosome infection, presence, and intensity. For each village, the proportion of positive test results, an arithmetic mean of the EPG for positive individuals, and a geometric mean of the EPG for all individuals were calculated. For geometric means, 1 was added to all participants to allow for inclusion of those with an EPG of 0. In addition to the overall village data, prevalence and intensity were determined for the age groups of interest. For village age groups with small sample sizes, which occurred most often with the first-year students, we used weighted least squares regression. Village age groups with a sample size of 20 or greater received a weight of one and village age groups with fewer than 20 people sampled were given a weight of the sample size divided by 20. This allowed us to reduce the contribution of villages with age groups that may have unstable estimates and bias model results. Analyses exploring the relationships between village-level data were performed using thin-plate regression splines and cubic regression splines.19 Exploratory analyses revealed that most relationships could be adequately explained with weighted least squares regression models using polynomials of first, second, or third degree. Selection of the optimal degree was performed using the Bayesian information criterion.20 All tests and confidence intervals used the 5% level of significance. At the end of data analysis for each survey, a report containing the results from the survey was provided to the Ministry of Public Health and Sanitation, and the Ministry of Education at the national and district levels. Each school received a report showing prevalence and intensity levels for that school.

Results

The 225 villages selected for the Sm1 and Sm2 studies were distributed through 9 subcounties (formerly districts) along the shores of Lake Victoria. Within these villages, 29,619 individuals were examined for S. mansoni infections. Of these, 6,334 were first-year students, representing 21.4% of the total sample, 16,157 (54.5% of total sample) were children aged 9–12 years in classes 3–6 (preadolescent), and 7,128 (24.1%) were adults ≥ 25 years of age. The prevalence of schistosomiasis varied from 26.51% (95% confidence interval [CI]: 21.44, 31.57) in first-year children to 35.10% (CI: 31.52, 38.68) among preadolescents, and 43.95% (CI: 40.93, 46.98) in adults. Schistosoma mansoni infection intensity (as measured by EPG) varied from a mean (±SD [standard deviation]) of 53.29 (±8.27) in first-year children to 71.98 (±6.87) among preadolescents and 67.76 (±4.99) in adults. Although the prevalence of S. mansoni infections among adults appears higher than that of the 9- to 12-year-olds, it should be noted that the adult data were only collected from the 150 Sm2 schools, that is, those schools with a prevalence > 25% in 13- to 14-year-olds, while the data from the 9- to 12-year-olds includes a total of 225 schools with selection criteria prevalence as low as 10% in 13- to 14-year olds.

The STH prevalence levels were much lower than for S. mansoni. For A. lumbricoides infection, mean (95% CI) prevalence was 4.83% (CI: 3.89, 5.76) for first-year students, 3.25% (CI: 2.72, 3.79) for 9- to 12-year-olds, and 1.85% (CI: 1.39, 2.32) for adults, resulting in an overall prevalence of 3.14% (CI: 2.70, 3.58). The prevalence of T. trichiura infection was 7.45% (CI: 6.19, 8.71) for first-year students, 6.05% (CI: 5.24, 6.86) for 9- to 12-year-olds, and 1.87% (CI: 1.41, 2.33) for adults; the overall prevalence was 5.06% (CI: 4.44, 5.68).

Arithmetic means of S. mansoni infection prevalence and intensity of village-level data (Table 1) were similar to the individual-level data. Mean village-level prevalence was 21.17% (±21.44) in first-year children, 32.92% (±25.25) among preadolescents, and 43.94% (±18.88) in adults. The S. mansoni infection intensity was 39.69 (±69.82) in first-year children, 65.99 (±88.88) in preadolescents, and 67.83 (±61.25) in adults. We observed a strong, statistically significant correlation (r2 ≥ 0.96; P < 0.001) between prevalence and geometric mean EPG for all age categories (Figure 1). The village mean prevalence levels of the 9- to 12-year-old age group were also significantly correlated to those of the first-year students (r2 = 0.74;P < 0.001), adults (r2 = 0.26; P < 0.001), and combined groups (r2 = 0.52; P < 0.001) (Figure 2). When we compared the correlation between the geometric mean egg intensity of each age group with that of the 9- to 12-year-old age group, there was again a positive correlation with the adults and first-year populations (r2 = 0.67; P < 0.001) as well as with the first-year students (r2 = 0.82; P < 0.001) and adults (r2 = 0.26; P < 0.001) (Figure 3). Adults (Table 2) and first-year students (Table 3) living in villages with 9- to 12-year-olds with S. mansoni prevalence > 50% had significantly higher infection levels than those living in villages with < 50% prevalence among 9- to 12-year-olds.

Table 1

Means and SDs of village-level prevalence and intensity of infection for schistosomiasis among different age groups in western Kenya

 First year students mean ± SD (N)9- to 12-year-old children mean ± SD (N)Adults mean ± SD (N)Overall mean ± SD (N)
Schistosoma mansoni mean prevalence21.17 ± 21.44 (225)32.92 ± 25.25 (225)43.94 ± 18.88 (150)30.66 ± 22.11 (225)
S. mansoni intensity (arithmetic mean EPG)39.69 ± 69.82 (225)65.99 ± 88.88 (225)67.83 ± 61.25 (150)56.07 ± 66.25 (225)
S. mansoni intensity (geometric mean EPG)8.36 ± 25.45 (225)13.15 ± 29.20 (225)10.64 ± 13.33 (150)8.39 ± 16.43 (225)
S. mansoni intensity (positives only, arithmetic mean EPG)178.27 ± 77.69 (182)172.47 ± 91.79 (222)145.00 ± 75.06 (150)160.41 ± 73.99 (222)
S. mansoni intensity (positives only, geometric mean EPG)101.10 ± 54.47 (182)87.57 ± 53.45 (222)73.34 ± 35.56 (150)76.76 ± 40.26 (222)

EPG = eggs per gram; SDs = standard deviations.

Estimates are at the village level and are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Fewer (150) villages were used for calculating village mean prevalence and intensity for adults as only the Sm2 study collected adult data. For 43 villages, there were no S. mansoni egg–positive first-year students; 31 of these villages were in Sm1 and 12 were in Sm2.

Figure 1.
Figure 1.

Relationship between prevalence of infection and intensity of infection as expressed by geometric mean eggs per gram feces + 1. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

Citation: The American Society of Tropical Medicine and Hygiene 93, 6; 10.4269/ajtmh.15-0467

Figure 2.
Figure 2.

Relationships between prevalence of infection in 9- to 12-year-olds and other age groups. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

Citation: The American Society of Tropical Medicine and Hygiene 93, 6; 10.4269/ajtmh.15-0467

Figure 3.
Figure 3.

Relationship between intensity of infection in 9- to 12-year-olds as expressed by geometric mean eggs per gram feces + 1 and the other age groups. Village-level estimates are weighted by the sample size, where villages with a sample size ≥ 20 receive a weight of one and village with a sample size < 20 receive a weight of the sample size divided by 20. Each dot represents one village with the size of the dot proportional to the number of participants in that village. The legend provides examples of symbol size for a given number of village participants.

Citation: The American Society of Tropical Medicine and Hygiene 93, 6; 10.4269/ajtmh.15-0467

Table 2

Prevalence and intensity of infection in adult group compared with 9- to 12-year-olds

% Positive 9- to 12-year-olds in villageVillagesAdults tested% Positive0 EPG1–99 EPG100–399 EPG400 + EPG
< 10%314230.28 (8.50, 52.06)69.72 (47.94, 91.50)26.76 (7.87, 45.65)2.82 (0.50, 5.13)0.70 (0.00, 1.84)
10–49%884,17338.27 (34.85, 41.69)61.73 (58.31, 65.15)24.63 (22.59, 26.67)9.73 (8.04, 11.42)3.91 (2.70, 5.11)
≥ 50%592,80053.25 (48.43, 58.07)46.75 (41.93, 51.57)31.61 (28.94, 34.27)15.68 (13.07, 18.28)5.96 (4.19, 7.73)
χ2 (P)24.64 (< 0.0001)56.81 (< 0.0001)

EPG = eggs per gram.

Both tests are Rao–Scott χ2 values to account for village-level clustering. Analyses are at the individual level, and no weights are included.

Table 3

Prevalence and intensity of infection in first-year student group compared with 9- to 12-year-olds

% Positive 9- to 12-year-oldsVillagesFirst-year students tested% Positive0 EPG1–99 EPG100–399 EPG400 + EPG
< 10%439135.82 (4.31, 7.34)94.18 (92.66, 95.69)3.42 (2.19, 4.66)1.94 (1.02, 2.86)0.46 (0.03, 0.88)
10–49%1223,18513.38 (11.25, 15.50)86.62 (84.50, 88.75)9.64 (7.99, 11.29)2.61 (1.94, 3.27)1.13 (0.67, 1.59)
≥ 50%602,23653.71 (46.48, 60.95)46.29 (39.05, 53.52)25.89 (22.90, 28.89)17.40 (13.80, 0.99)10.42 (7.09, 13.75)
χ2 (P)1,337.05 (< 0.0001)1,406.26 (< 0.0001)

EPG = eggs per gram.

Both tests use Pearson χ2 values because the design effect was not positive. Analyses are at the individual level, and no weights are included.

Discussion

We took advantage of the large ongoing SCORE projects in western Kenya to revisit the question of whether SAC are a suitable reference group for predicting infection levels in the overall community. Such a reference group needs to be representative of the MDA target population and the community. The strong correlations between the prevalence and EPG of all the age groups as well as correlation in both prevalence and intensity of the other age groups to the 9- to 12-year-old age group confirmed the validity of the WHO recommendation to use the 9- to 12-year-old age group as a reference.1,3,21 The sharp increase in first-year student infection prevalence and intensity (Table 3, Figure 2) in villages where S. mansoni infection prevalence was greater than 50% in 9- to 12-year-olds is particularly noteworthy and supports calls to provide treatment to preschool-aged children, in those villages.22,23

Because logistic and economic issues are a large consideration in parasitologic surveys, obtaining community prevalence and infection intensities has to be considered against accessibility of the sampling group, ease of specimen collection, and cost–benefit ratios. Specimens from children were collected at schools with the help of a health teacher. Only one project staff person was required to be present at each school to collect up to 100 specimens per age category, per school per day. Schoolchildren and their parents/guardians, as well as the school administration, were generally accessible and receptive to testing. In addition, the participation rate was high, with only minimal refusals from either parents/guardians (declined consent) or children (declined assent). By contrast, adult samples were collected from home compounds and involved door-to-door walking to seek out adults. It took up to 3 days for project staff members accompanied by a village elder or community health worker to collect 50 samples from adults. Many adults contacted at their homes declined to participate in the study. Collecting specimen from adults therefore required more personnel, took longer hours, and it was more difficult to obtain follow-up specimens. Even though the prevalence and infection intensity among the adult group was very similar to that of the overall population, the logistical challenges and cost implications make this group less appropriate for baseline surveys.

Previous studies have reported reduced costs in school-based studies where activities are concentrated in a specific physical space.24 With school enrollment in Kenya currently very high because of a policy regarding provision of free primary education, the SAC group is most appropriate as the target group for baseline surveys. Furthermore, this age group was very representative for both prevalence and intensity levels in comparison to the overall population. Other studies, including Rodrigues and others reporting data collected in Minas Gerais, Brazil, validate the use of prevalence among SAC in the 7- to 14-year-old age group to predict S. mansoni infection prevalence in the community and confirm that it can be used to guide treatment strategies in the endemic areas.25 Traore and others surveyed 323 villages in Mali and showed a strong relationship between the community prevalence of infection with S. haematobium and the prevalence rate in the 7–14 years age group.26 Guyatt and others observed a consistent relationship between community prevalence and SAC prevalence for different parasites from varied sites.27 They further showed that degrees of overestimation of community prevalence were dependent on the parasite species and the intensity level of infection, and even though this can be reduced by more age-specific surveys,28 the SAC still provide a reliable reference and cost-effective group for estimating level of risk of infection in the community and for making intervention decisions.27

By contrast, the study of Evans and others of S. haematobium infections in Nigeria demonstrated similar adult levels of infection and hematuria in villages with SAC prevalence between 20% and 49% as in villages with SAC prevalence > 50%.14 However, in both settings the median adult prevalence was lower than for SAC (~20% for both groups) whereas in our study the adult prevalence was more similar to the SAC prevalence. This may represent differences in the longevity of S. haematobium and S. mansoni worms, increased resistance to reinfection in adults infected with S. haematobium, or simply differences in age-related water contact patterns between the two study settings. Despite the differences in the pattern of the data in the two sites, we are in agreement with the authors' call for greater access to treatment of adults.14

Using 9- to 12-year-old SAC in baseline surveys may also facilitate measurement of the impact of treatment, especially with nested cohorts to follow for detailed monitoring and evaluation.29 Furthermore, the school setting provides an environment to empower children as agents of health behavior change and an entry point for other community members to access MDA benefits.3032 Because several other health programs also operate from schools, it is possible to incorporate these surveys into the routine activities.33,34

In conclusion, our findings show that prevalence and intensity indicators among the 9- to 12-year-olds are comparable to other population groups in the same settings as well as overall community prevalence and are a valid age group to use for sampling purposes for baseline data to determine MDA. However, because of possible regional differences, it is advisable for program managers in other settings to conduct similar operational research assessments where resources permit to determine how WHO guidelines apply to their particular circumstances.

ACKNOWLEDGMENTS

We appreciate the support from the Ministry of Education, Ministry of Public Health and Sanitation, and the Provincial administration in Nyanza province. We thank the head teachers, teachers, and pupils in each of the schools that participated in this study, as well as the community health workers and adults in the community based study. We also thank all the SCORE Kenya staff for their assistance in the field and laboratory work. We would like to acknowledge the help of Division of Vector-Borne and Neglected Tropical Diseases (DVBNTD) personnel, Kisumu, and in particular Blasto Kwanya, Otieno Oloo, and Charles Odah for their assistance with microscopy.

  • 1.

    Montresor A, Crompton DWT, Hall A, Bundy DAP, Savioli L, 1998. Guidelines for the Evaluation of Soil-Transmitted Helminthiasis and Schistosomiasis at Community Level. Geneva, Switzerland: World Health Organization.

    • Search Google Scholar
    • Export Citation
  • 2.

    Savioli L, Stansfield S, Bundy DA, Mitchell A, Bhatia R, Engels D, Montresor A, Neira M, Shein AM, 2002. Schistosomiasis and soil-transmitted helminth infections: forging control efforts. Trans R Soc Trop Med Hyg 96: 577579.

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization, 2002. Prevention and Control of Schistosomiasis and Soil-Transmitted Helminthiasis. Report of a WHO Expert Committee. Geneva, Switzerland: World Health Organization. Available at: http://whqlibdoc.who.int/trs/WHO_TRS_912.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 4.

    World Health Organization, 2011. Report of an Informal Consultation on Schistosomiasis Control. Geneva, Switzerland: World Health Organization. Available at: www.who.int/iris/bitstream/10665/78066/1/9789241505017_eng.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 5.

    World Health Organization, 2006. Preventive Chemotherapy in Human Helminthiasis. Geneva, Switzerland: World Health Organization. Available at: http://whqlibdoc.who.int/publications/2006/9241547103_eng.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 6.

    World Health Organization, 2011. Helminth Control in School-Age Children: A Guide for Managers of Control Programmes. Geneva, Switzerland: World Health Organization. Available at: whqlibdoc.who.int/publications/2011/9789241548267_eng.pdf.

    • Search Google Scholar
    • Export Citation
  • 7.

    Pereira AP, Favre TC, Galvão AF, Beck L, Barbosa CS, Pieri OS, 2010. The prevalence of schistosomiasis in school-aged children as an appropriate indicator of its prevalence in the community. Mem Inst Oswaldo Cruz 105: 563569.

    • Search Google Scholar
    • Export Citation
  • 8.

    World Health Organization, 2010. Informal Consultation on Expanding Schistosomiasis Control in Africa, 78. Available at: http://www.who.int/schistosomiasis/epidemiology/PZQ_WHO_report_meeting.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 9.

    World Health Organization, 1996. Report of the WHO Informal Consultation on the Use of Chemotherapy for the Control of Morbidity Due to Soil-Transmitted Nematodes in Humans. WHO/CTD/SIP/96.2. Geneva, Switzerland: World health Organization. Available at: http://whqlibdoc.who.int/hq/1996/WHO_CTD_SIP_96.2.pdf. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 10.

    Katz N, Chaves A, Pellegrino J, 1972. A simple device for quantitative stool thick-smear technique in schistosomiasis mansoni. Rev Inst Med Trop Sao Paulo 14: 397400.

    • Search Google Scholar
    • Export Citation
  • 11.

    Brooker S, Kabatereine NB, Smith JL, Mupfasoni D, Mwanje MT, Ndayishimiye O, Lwambo NJ, Mbotha D, Karanja P, Mwandawiro C, Muchiri E, Clements AC, Bundy DA, Snow RW, 2009. An updated atlas of human helminth infections: the example of east Africa. Int J Health Geogr 8: 42.

    • Search Google Scholar
    • Export Citation
  • 12.

    Global Atlas of Helminth Infection, 2013. The Global Atlas of Helminth Infections. Available at: http://www.thiswormyworld.org. Accessed April 3, 2013.

    • Search Google Scholar
    • Export Citation
  • 13.

    Countries supported by USAID's NTD program. Available at: http://www.neglecteddiseases.gov/countries/index.html.

  • 14.

    Evans DS, King JD, Eigege A, Umaru J, Adamani W, Alphonsus K, Sambo Y, Miri ES, Goshit D, Ogah G, Richards FO, 2013. Assessing the WHO 50% prevalence threshold in school-aged children as indication for treatment of urogenital schistosomiasis in adults in central Nigeria. Am J Trop Med Hyg 88: 441445.

    • Search Google Scholar
    • Export Citation
  • 15.

    Odiere MR, Opisa S, Odhiambo G, Jura WG, Ayisi JM, Karanja DM, Mwinzi PN, 2011. Geographical distribution of schistosomiasis and soil-transmitted helminths among school children in informal settlements in Kisumu City, western Kenya. Parasitology 138: 15691577.

    • Search Google Scholar
    • Export Citation
  • 16.

    Odiere MR, Rawago FO, Ombok M, Secor WE, Karanja DM, Mwinzi PN, Lammie PJ, Won K, 2013. High prevalence of schistosomiasis in Mbita and its adjacent islands of Lake Victoria, western Kenya. Parasit Vectors 5: 278.

    • Search Google Scholar
    • Export Citation
  • 17.

    Handzel T, Karanja DM, Addiss DG, Hightower AW, Rosen DH, Colley DG, Andove J, Slutsker L, Secor WE, 2003. Geographic distribution of schistosomiasis and soil-transmitted helminths in western Kenya: implications for anthelminthic mass treatment. Am J Trop Med Hyg 69: 318323.

    • Search Google Scholar
    • Export Citation
  • 18.

    Verani JR, Abudho B, Montgomery SP, Mwinzi PN, Shane HL, Butler SE, Karanja DM, Secor WE, 2011. Schistosomiasis among young children in Usoma, Kenya. Am J Trop Med Hyg 84: 787791.

    • Search Google Scholar
    • Export Citation
  • 19.

    Wood SN, 2006. Generalized Additive Models: An Introduction with R. Boca Raton, FL: CRC Press.

  • 20.

    Schwarz GE, 1978. Estimating the dimension of a model. Ann Stat 6: 461464.

  • 21.

    Montresor A, Stoltzfus RJ, Albonico M, Tielsch JM, Rice AL, Chwaya HM, Savioli L, 2002. Is the exclusion of children under 24 months from anthelmintic treatment justifiable? Trans R Soc Trop Med Hyg 96: 197199.

    • Search Google Scholar
    • Export Citation
  • 22.

    Stothard JR, Sousa-Figueriredo JC, Betson M, Bustinduy A, Reinhard-Rupp J, 2013. Schistosomiasis in African infants and preschool children: let them now be treated! Trends Parasitol 29: 197205.

    • Search Google Scholar
    • Export Citation
  • 23.

    Coulibaly JT, N'Gbesso YK, N'Guessan NA, Winkler MS, Utzinger J, N'Goran EK, 2013. Epidemiology of schistosomiasis in two high-risk communities of south Côte d'Ivoire with particular emphasis on pre-school-aged children. Am J Trop Med Hyg 89: 3241.

    • Search Google Scholar
    • Export Citation
  • 24.

    Favre TC, Pereira AP, Galvao AF, Zani LC, Barbosa CS, Pieri OS, 2009. A rationale for schistosomiasis control in elementary schools of the rainforest zone of Pernambuco, Brazil. PLoS Negl Trop Dis 3: e395.

    • Search Google Scholar
    • Export Citation
  • 25.

    Rodrigues LC, Wheeler JG, Shier R, Guerra HL, Pimenta F Jr, Lima e Costa MF, 2000. Predicting the community prevalence of schistosomiasis mansoni from the prevalence among 7- to 14-year-olds. Parasitology 121: 507512.

    • Search Google Scholar
    • Export Citation
  • 26.

    Traore M, Maude GH, Bradley DJ, 1998. Schistosomiasis haematobia in Mali: prevalence rate in school-age children as index of endemicity in the community. Trop Med Int Health 3: 214221.

    • Search Google Scholar
    • Export Citation
  • 27.

    Guyatt HL, Brooker S, Donnelly CA, 1999. Can prevalence of infection in school-aged children be used as an index for assessing community prevalence? Parasitology 118: 257268.

    • Search Google Scholar
    • Export Citation
  • 28.

    Brooker S, Donnelly CA, Guyatt HL, 2000. Estimating the number of helminthic infections in the Republic of Cameroon from data on infection prevalence in schoolchildren. Bull World Health Organ 78: 14561465.

    • Search Google Scholar
    • Export Citation
  • 29.

    Samuels AM, Matey E, Mwinzi PN, Wiegand RE, Muchiri G, Ireri E, Hyde M, Montgomery SP, Karanja DM, Secor WE, 2012. Schistosoma mansoni morbidity among school-aged children: a SCORE project in Kenya. Am J Trop Med Hyg 87: 874882.

    • Search Google Scholar
    • Export Citation
  • 30.

    Schall VT, 1994. Environmental and health education for school-age children: a transdisciplinary approach. Cad Saude Publica 10: 259263.

    • Search Google Scholar
    • Export Citation
  • 31.

    Massara CL, Peixoto SV, Enk MJ, da Silva Barros H, dos Santos Carvalho O, Sakurai E, Schall V, 2006. Evaluation of an improved approach using residences of schistosomiasis-positive school children to identify carriers in an area of low endemicity. Am J Trop Med Hyg 74: 495499.

    • Search Google Scholar
    • Export Citation
  • 32.

    Enk MJ, Lima AC, Massara CL, Coelho PM, Schall VT, 2008. A combined strategy to improve the control of Schistosoma mansoni in areas of low prevalence in Brazil. Am J Trop Med Hyg 78: 140146.

    • Search Google Scholar
    • Export Citation
  • 33.

    Barbosa CS, Favre TC, Wanderley TN, Callou AC, Pieri OS, 2006. Assessment of schistosomiasis, through school surveys, in the Forest Zone of Pernambuco, Brazil. Mem Inst Oswaldo Cruz 101 (Suppl 1): 5562.

    • Search Google Scholar
    • Export Citation
  • 34.

    Favre TC, Ximenes RA, Galvao AF, Pereira AP, Wanderlei TN, Barbosa CS, Pieri OS, 2006. Reliability of current estimates of schistosomiasis prevalence in the Rainforest Zone of the state of Pernambuco, northeastern Brazil. Mem Inst Oswaldo Cruz 101 (Suppl 1): 7378.

    • Search Google Scholar
    • Export Citation

Author Notes

* Address correspondence to W. Evan Secor, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Rd, MS-D65, Atlanta, GA 30329. E-mail: was4@cdc.gov

Financial support: This study was made possible by the generous support from the University of Georgia Research Foundation, Inc., which is funded by the Bill and Melinda Gates Foundation for this SCORE project.

Authors' addresses: Pauline N. M. Mwinzi, Geoffrey Muchiri, Martin Omedo, Bernard Abudho, and Diana M. S. Karanja, Neglected Tropical Diseases Branch, Centre for Global Health Research, Kenya Medical Research Institute (KEMRI), E-mails: pmwinzi@kemricdc.org, martowino007@yahoo.com, geoffmosh@yahoo.com, babudho@kemricdc.org, and dkaranja@kemricdc.org. Ryan E. Wiegand, Susan P. Montgomery, and W. Evan Secor, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA, E-mails: fwk2@cdc.gov, zqu6@cdc.gov, and was4@cdc.gov.

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