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| 003 | OSt | ||
| 005 | 20240305193719.0 | ||
| 008 | 221031b |||||||| |||| 00| 0 eng d | ||
| 028 | _b Phone: +255 28 298 3384 | ||
| 028 | _b Fax: +255 28 298 3386 | ||
| 028 | _b Email: vc@bugando.ac.tz | ||
| 028 | _b Website: www.bugando.ac.tz | ||
| 040 | _cDLC | ||
| 041 | _aEnglish | ||
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_a Deodatus Mwombeki Ruganuza _944898 |
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| 245 | _aPrevalence intensity and the factors associated with intestinal schistosomiasis in preschool children in Ukerewe island Mwanza region Tanzania | ||
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_aMwanza: _b JKUAT COHES & _b Tanzania Catholic University of Health and Allied Sciences [CUHAS – Bugando] _c2016/11/9 |
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| 520 | _aRecent evidence indicates that preschool children (PSC) living in S. mansoni highly endemic areas are at similar risk of schistosomiasis infection and morbidity as their school aged counterparts. Recognizing this fact, the World Health Organization (WHO) is considering including this age group in control programs using mass drug administration (MDA), in the highly endemic areas. However, detailed epidemiological information on S. mansoni infection among PSC is lacking for many endemic areas, including in Tanzania. This study was conducted to determine the prevalence and intesnsity of S. mansoni infection among PSC in Lake Victoria’s Ukerewe Island, in North-Western Tanzania, and the factors associated with infection in this age group.This was a cross-sectional study involving 400 PSC aged 1- 6 years of age. The Kato-Katz (K-K) technique and the point of care circulating cathodic antigen (CCA) immunodiagnostic test were used to diagnose S. mansoni infection in stool and urine samples, respectively, and a pre-tested questionnaire was used to collect demographic data and water contact behaviour of the children through their parents/guardians. GPS data of the households of study participants and water contact points nearest to their homesteads was obtained. Data collected was entered into data collection forms, notebooks, and then transferred into the Microsoft Excel software for consistency data checks and data cleaning. Analysis was done using STATA 13 and ArcGIS ArcMap 10.2.2. Chi squared test for difference in frequencies were performed. Potential associations were assessed at a bivariate level; then, factors with P-value … | ||
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