Progress from morbidity control to elimination as a public health ... - Parasites & Vectors

Study population

Togo had a population of > 8 million people in 2020, all of whom are at risk for STH and SCH infection [9]. At the time of baseline mapping, there were 35 of 40 districts in the country, which was restructured in 2019 to 39 districts comprising 720 sub-districts, each of which has a health centre that services 1–10 villages. Thirty-seven of the 39 districts were mapped at baseline and the same villages were re-assessed in 2015. The remaining two districts, covering the capital, Lomé, were excluded during the NTD mapping because transmission of the targeted NTDs is very low or non-existent there. To date, 638 of 720 sub-districts have been mapped. Each sub-district or PHU has a dispensary with one nurse, who provides health care to between 1 and 10 villages. In total, 92 sub-districts across ten districts (and four regions) had completed > 10 years of effective MDA against SCH and STH by 2021 and conducted a second impact assessment.

Study design and sampling

SCH is characterised by spatial heterogeneity, and SAC constitutes the highest risk group. Considering the focal nature of SCH and the age group most affected, this survey used a cross-sectional design in a stratified, two-stage cluster survey strategy to estimate the prevalence of SCH among SAC at the sub-district level. The first selection was among villages in each sub-district, and the second selection was SAC. Since the survey aimed to estimate prevalence at the sub-district level, which is probably less ecologically heterogeneous than larger geographical areas such as districts, an estimated intra-cluster correlation coefficient (ICC) of 0.041 was used [11]. The district provided a list of villages in each sub-district. From this list, villages were selected proportional to sub-district size (that equated to approximately 30–40% of communities). In each selected village, a school was selected. If there was no school, then the neighbouring school where SAC from the selected village attended was sampled. In each school, 24 SAC (12 girls and 12 boys) aged between 5 and 14 years were sampled, which was calculated to be adequate to detect a 5% change in prevalence of SCH infection, assuming power of 80% and test size of 5%, and considering the anticipated variance in prevalence. The enrolled students were selected by class from CP1 (cours préparatoire I equivalent to first grade in the US) to CM2 (cours moyen II equivalent to sixth grade in the US) with four SAC (2 girls and 2 boys) chosen by class. To select the SAC, all students who had a signed parental consent were assembled in two lines, one for boys and one for girls. Children were selected systematically from within these two lines, using a sampling interval derived from the target sample size and the number of children.

Sample collection and analysis

The selected schools were visited 3 days prior to data collection to explain the purpose of the survey to the school head teacher. The consent forms were then given to the SAC to give to their parent/guardian to sign and the teacher read information about the survey to the children. On the day of the survey, each selected pupil was given a container labelled with a unique barcode and requested to provide a urine sample. Urine samples were observed for macrohaematuria and tested with a dipstick (Haemastix^©), which was read and graded within 60 s according to the manufacturer's guideline. Only macrohaematuria and dipstick-positive urine samples (defined as trace haemolysed, +, ++, + + +) were kept for later microscopy. Urine filtration was used for egg quantification and examination [5]. Infection was categorized according to the WHO guidance where heavy infections were defined as ≥ 50 eggs per 10 ml urine [5]. Urogenital schistosomiasis infection was defined as having the presence of haematuria and/or S. haematobium eggs in the urine. In a subset of schools, which had any S. mansoni or STH infections in the last 2015 assessment, stool was examined. The stool samples were processed using the Kato-Katz technique in the available laboratories at the sub-district/PHU. Duplicate slides were done for stool samples and read for egg counts, with the average eggs across two slides taken to calculate the eggs per gram (epg) of stool for each organism. Infection of any STH was defined as the presence of at least one egg of A. lumbricoides, T. trichiura, N. americanus or A. duodenale. Thresholds for heavy-intensity infections were ≥ 50,000 epg of stool for A. lumbricoides,  ≥ 4000 for hookworm and ≥ 10,000 for T. trichiura. Infection of any schistosomiasis was defined as presence of haematuria, S. haematobium eggs in the urine and/or S. mansoni in stool (where the thresholds for heavy-intensity infections was ≥ 400 epg of stool) [12].

Data collection and management

Data were collected between 8 November and 4 December 2021, approximately 8 months after the MDA, on Android tablets using ESPEN Collect application and cloud-based databases (https://espen.afro.who.int/tools-resources/espen-collect). Standardized forms were used to gather information about individual student demographic information and information on school-level water, sanitation and hygiene (WaSH) characteristics to help inform sustainability of SCH and STH in Togo. School- and student-level questionnaires were administered face to face, and data collectors observed the WaSH infrastructure at school. The survey team then graded water and sanitation facilities at the surveyed schools using the WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene guidelines[13]. Interviewers observed whether they were wearing shoes. School and student-level data were linked to their parasitological results using unique barcode identifiers.

Data were consolidated in Microsoft Excel (Microsoft Corp, Redmond, WA) and then analysed in R v 4.1.3 (R Core Team (2022), Vienna, Austria). Infection prevalence and average intensity of infection were calculated for schistosomiasis and STH and the 95% confidence intervals (Cis) determined using binomial and negative binomial regression models, respectively, considering clustering by schools. Infection intensities were classified into light, (moderate for STH only) and heavy infections according to WHO guidelines (Additional file 1: Table S1) [12] and the prevalence of light, moderate and heavy infections together with 95% CIs using a binomial regression model.

Association between individual- and school-level variables affecting schistosomiasis and STH infection were included in the analysis. Individual factors included age, sex, handwashing, defecation and urination, and shoe-wearing behaviours at school. School-level factors included interviewer-verified availability and type of school toilet facility and availability and type of handwashing facility equipped with water and soap. WaSH coverage was categorized using the JMP guidelines. Overall, the WaSH factors associated with STH or schistosomiasis prevalence were analysed first with univariate analysis and described as odds ratio (OR) and then mixed effects logistic regression model. All the statistical analyses were carried out using R. Graphs were developed using the ggplot2 package (v. 3.3.5) and school locations were mapped using R.

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