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. 2013 Jul 5:6:198.
doi: 10.1186/1756-3305-6-198.

Monitoring and evaluating the impact of national school-based deworming in Kenya: study design and baseline results

Charles S Mwandawiro  1 , Birgit Nikolay, Jimmy H Kihara, Owen Ozier, Dunstan A Mukoko, Mariam T Mwanje, Anna Hakobyan, Rachel L Pullan, Simon J Brooker, Sammy M Njenga
Affiliations

Monitoring and evaluating the impact of national school-based deworming in Kenya: study design and baseline results

Charles S Mwandawiro et al. Parasit Vectors. .

Abstract

Background: An increasing number of countries in Africa and elsewhere are developing national plans for the control of neglected tropical diseases. A key component of such plans is school-based deworming (SBD) for the control of soil-transmitted helminths (STHs) and schistosomiasis. Monitoring and evaluation (M&E) of national programmes is essential to ensure they are achieving their stated aims and to evaluate when to reduce the frequency of treatment or when to halt it altogether. The article describes the M&E design of the Kenya national SBD programme and presents results from the baseline survey conducted in early 2012.

Methods: The M&E design involves a stratified series of pre- and post-intervention, repeat cross-sectional surveys in a representative sample of 200 schools (over 20,000 children) across Kenya. Schools were sampled based on previous knowledge of STH endemicity and were proportional to population size. Stool (and where relevant urine) samples were obtained for microscopic examination and in a subset of schools; finger-prick blood samples were collected to estimate haemoglobin concentration. Descriptive and spatial analyses were conducted. The evaluation measured both prevalence and intensity of infection.

Results: Overall, 32.4% of children were infected with at least one STH species, with Ascaris lumbricoides as the most common species detected. The overall prevalence of Schistosoma mansoni was 2.1%, while in the Coast Province the prevalence of S. haematobium was 14.8%. There was marked geographical variation in the prevalence of species infection at school, district and province levels. The prevalence of hookworm infection was highest in Western Province (25.1%), while A. lumbricoides and T. trichiura prevalence was highest in the Rift Valley (27.1% and 11.9%). The lowest prevalence was observed in the Rift Valley for hookworm (3.5%), in the Coast for A. lumbricoides (1.0%), and in Nyanza for T. trichiura (3.6%). The prevalence of S. mansoni was most common in Western Province (4.1%).

Conclusions: The current findings are consistent with the known spatial ecology of STH and schistosome infections and provide an important empirical basis on which to evaluate the impact of regular mass treatment through the school system in Kenya.

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Figures

Figure 1
Figure 1
Schematic of M&E programme design. Three tiers of monitoring are conducted: i) a national baseline survey; ii) pre-post surveys, and iii) high frequency surveys.
Figure 2
Figure 2
Prevalence of infection and mean intensity of infection by age and sex for hookworm (A, D), A. lumbricoides (B, E), and T. trichiura (C, F). 95% Confidence intervals were obtained by binomial regression and negative binomial regression, respectively taking into account school clusters.
Figure 3
Figure 3
Spatial distribution of hookworm prevalence and intensity, by school and district. Spatial distribution of hookworm school prevalence (A) and average school infection intensity (C), school prevalence distribution (B), and average district prevalence (D).
Figure 4
Figure 4
Spatial distribution of A. lumbricoides prevalence and intensity, by school and district. Spatial distribution of A. lumbricoides school prevalence (A) and average school infection intensity (C), school prevalence distribution (B), and average district prevalence (D).
Figure 5
Figure 5
Spatial distribution of T. trichiura prevalence and intensity, by school and district. Spatial distribution of T. trichiura school prevalence (A) and average school infection intensity (C), school prevalence distribution (B), and average district prevalence (D).
Figure 6
Figure 6
S. mansoni and S. haematobium prevalence (A-B) and mean infection intensity (C-D) by age and sex. 95% Confidence intervals of prevalence were obtained by binomial regression and confidence intervals of infection intensity by negative binomial regression, both taking into account school clusters.
Figure 7
Figure 7
Spatial distribution of S. mansoni prevalence and intensity, by school and district. Spatial distribution of S. mansoni school prevalence (A) and average school infection intensity (C), school prevalence distribution (B), and average district prevalence (D).
Figure 8
Figure 8
Spatial distribution of S. haematobium prevalence and intensity, by school and district. Spatial distribution of S. haematobium school prevalence (A) and average school infection intensity (C), school prevalence distribution (B), and average district prevalence (D).
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