Study area
In 2015, the Ethiopia’s population was estimated at 100 million[19]. The country has three administrative levels. The first level includes nine Regional States: Afar, Amhara, Benishangul-Gumuz, Gambela, Harari, Oromiya, Southern Nations, Nationalities and Peoples' Region (SNNPR), Somali and Tigray; and two chartered City Administrations: Addis Ababa and Dire Dawa. The second and the third administrative levels are zones and woredas (districts), respectively. The woredas are the implementation units for NTD control programs in Ethiopia.
The distribution of STHs and SCH was mapped over two surveys. In the first survey (November2013 to March 2014), eight of the nine Regional States and one of the two City Administrations were included. In the second survey (February and April 2015) both Amhara and Addis Ababa were mapped. In addition, there was a fine-scale mapping survey in Somali Regional State with the aim to cover woredas that were not mapped in the first survey.
Field procedures
The field teams were provided with a list of ten schools per woreda for the regions and ten schools per sub-city for each of the two City Administrations. These ten schools were randomly selected from the list of elementary schools provided by the Federal Ministry of Education. Ultimately, only five schools were purposively selected and included in the survey. This final selection was done by the Woreda Health Office and was biased towards schools that were at-risk for SCH infections (proximity to water bodies, reports on SCH infections, irrigation and fishing practices of the community). Once the school selection was completed, the field team made the necessary pre-visit arrangements with the school directors. On the day of visit, all students of grade 5 (around 12 years of age) were lined up in two lines, one for the girls and one for the boys. A random selection was made of 25 girls and 25 boys, resulting in a total of 50 students per school. In schools with fewer than 25 boys or girls in the appropriate grade, children from lower grades (grade four: roughly 11 years of age) or higher grade (grade six: roughly 13 years of age) were included. The selected students were asked to provide both a stool and a urine sample.
Stool samples were screened for the presence of STHs and S. mansoni eggs, applying a single Kato-Katz thick smear[20].The number of eggs of STHs (A. lumbricoides, T. trichiura, and hookworms) and S. mansoni were multiplied by 24 to obtain the faecal egg counts (FECs) expressed in eggs per gram of stool (EPG) for each of the four helminth species.
Urine specimens were screened for S. haematobium in two consecutive steps. First, the presence of haematuria was assessed using Haemastix®. The results of this test were recorded as either negative, trace, +, ++ or +++. Subsequently, urine samples in which at least a trace of haematuria was detected were subjected to urine filtration to assess the number of S. haematobium eggs in 10 ml of urine.
To ensure the quality of the parasitological results the field team were instructed to randomly archive 10% of the Kato-Katz slides. These slides were re-examined by the team leader. Any discrepancies were discussed with the wider team.
In addition, a questionnaire was completed. This questionnaire was designed to gain information on water; sanitation and hygiene (WASH) at the school level. The results of this questionnaire and parasite infection for the first round of survey are reported elsewhere by Grimes and colleagues[21].
Training of the field teams
In total, 54field teams from the different Regional States and City Administrations were involved in this study. Each team consisted of one health officer (for the questionnaires and treatment) and three laboratory technicians (for the stool and urine sample examinations).Training was given for each survey. The training was provided at the Ethiopian Management Institute (EMI) in Bishoftu. During these trainings, both theoretical and practical sessions were given to 164 Health officers and laboratory technicians. The technical sessions focussed on a variety of aspects of the diseases (life cycles, pathogenesis, laboratory diagnosis, prevention and control strategies), while the practical sessions focussed on the diagnostic methods (the use of Haemastix®, urine filtration, Kato-Katz thick smear), archiving Kato-Katz slides for quality control, completing questionnaires on WASH and using LINKS® (a smart phone-based application to collect data).
Mapping coordination and supervision
Supplementary Fig. 1 provides an overview of the coordination and supervision of this study. EPHI, the technical arm of FMoH, was responsible for the overall coordination of the survey. For this coordination, four central supervisors were assigned. At the Regional States and City Administrations, at least one supervisor from either the Regional Health or Education Office for each Regional State (and City Administration) was assigned throughout the mapping period. In addition, external supervisors from the Ugandan Vector Control Division (Uganda) and the Kenyan Medical Research Institute (Kenya) conducted monitoring visits. These supervisors independently evaluated the survey coordination and communication flow between the central level (EPHI), the regional supervisors (Regional States and City Administration) and the field teams. They also monitored the operational procedures at the schools, providing feedback to the field teams, correcting those that were not adhering to the mapping protocol.
Data collection and data management
Data was collected using the LINKS® data collection system developed by the Task Force for Global Health (Atlanta, USA). This is an android-based application that allows standardized entry of epidemiological data across the different teams. At the school level, the teams collected the GPS coordinates, the total number of students, the total number of boys and girls in the school, the availability of toilets, water supplies and hand washing facilities. At the level of the student, the teams collected the age, sex, the number of Ascaris, Trichuris, hookworm, S. mansoni eggs, the presence of haematuria, and the number of S. haematobium eggs. Raw data was downloaded from the LINKS system server and was subsequently curated using Microsoft Excel (Microsoft Corporation, Redmond, WA, USA).
Statistical data analysis
The prevalence and intensity of infections were calculated for any STH and SCH, and the individual helminth species, separately. Prevalence was estimated by the proportion of children for whom eggs of a particular helminth species were detected. Unweighted prevalence was calculated at regional and woreda level, to this end the proportion of children excreting eggs over the total number screened in the region / woreda was calculated. For treatment, mean prevalence of the five schools was used to decide the eligibility of that woreda for treatment.
Intensity of infection was measured as the arithmetic mean FECs and as the proportion of low and moderate-to-heavy intensity infections. The criteria for the classification of infection intensities are summarized in Table 1. In addition, we determined the prevalence of mixed infections (the proportion of children who were excreting eggs of at least two different helminths).
Table 1
Infection intensity criteria for: A. lumbricoides, T. trichiura, hookworms, S. mansoni and S. haematobium infections.
Helminth | Light | Moderate | Heavy |
A. lumbricoides | 1–4 999 EPG | 5 000–49 999 EPG | ≥ 50 000 EPG |
T. trichiura | 1–999 EPG | 1 000–9 999 EPG | ≥ 10 000 EPG |
Hookworms | 1–1 999 EPG | 2 000–3 999 EPG | ≥4 000 EPG |
S. mansoni | 1–99 EPG | 100–399 EPG | ≥ 400 EPG |
S. haematobium | 1–50 eggs/10 ml of urine | | > 50 eggs/10 ml of urine |
These infection parameters (prevalence, infection intensity and mixed infections) were calculated at the different administrative levels (national, Regional States/City Administrations, woredas and schools). Subsequently, the point estimates of the different parameters were plotted on a geographical map of Ethiopia using ArcGIS version 10.4 (ESRI, Inc). To gain insights into to the recommended MDA strategy we classified the endemicity of any STH and SCH at the woreda level into low, moderate and high. The criteria for the classification of endemicity, and the corresponding recommended MDA strategies, are summarized in Table 2.
Table 2
The prevalence criteria defining endemicity for soil-transmitted helminths and schistosomes, with corresponding control strategies.
Endemicity | Any soil-transmitted helminth | | Any schistosomes |
Prevalence | Control strategy | | Prevalence | Control strategy |
Low | ≥ 1% and < 20% | Case-to-case treatment | | ≥ 1% and < 10% | 1x MDA/ year for first 2 primary school years |
Moderate | ≥ 20% and < 50% | 1 x MDA / year | | ≥ 10%and < 50% | 1x MDA / 2 years |
High | ≥ 50% | 2x MDA / year | | ≥ 50% | 1x MDA / year |
Quality control result analysis for the Kato-Katz thick smear
Quality control of the FECs of any STHs and S. mansoni was performed for 6,042 individuals. For this, Kato-Katz thick smears were re-examined by a team leader. The proportions of both false positives and false negatives were assessed. To this end, we assumed that the team leader was correct. In cases where both results indicated presence of eggs the agreement in egg counts was assessed. There was a disagreement in egg counts where the difference in eggs counts was greater than 10 when the team leader counted fewer than 100, or when the difference in egg counts was more than 20% when the team leader counted more than 100.