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Methods for WASH in Schools

The following is a brief summary of the JMP methodology for monitoring WASH in schools, which builds on established methods for monitoring WASH in households and will continue to be refined over time.

Water quality testing in Nepal
JMP methods for WASH in schools

 

In 2016, the JMP convened an expert group meeting to develop core questions and indicators for monitoring WASH in schools and subsequently established a methodology for generating internationally comparable estimates to support global monitoring of related SDG targets 6.1, 6.2 and 4.a. In 2018, the JMP published a global baseline report, containing harmonized national, regional and global estimates, followed by a progress update in 2020 and a data update in 2022

Data collection and validation for WASH in schools

The JMP releases updated estimates every two years. The first step is to compile national data sources containing information about drinking water, sanitation and hygiene services in schools. The data search involves systematically visiting the websites of national statistical offices, sector institutions such as ministries of education, health, water and sanitation, and other regional and global databases. UNICEF and WHO regional and country offices also provide support to identify newly available datasets in consultation with national authorities. Data are then extracted, cleaned, analysed and added to JMP country files for WASH in schools.

The second step is to validate national estimates. The JMP country files contain a complete list of national data sources and show how information from each source has been used to generate internationally comparable estimates for each year in the reference period (from 2000 to the year prior to publication). In the last quarter of the year before publication, draft estimates are circulated to WHO and UNICEF country offices for a two-month period of JMP country consultation and technical feedback from national authorities.

The primary purpose of global monitoring is to generate internationally comparable estimates that can be used to benchmark and compare progress across countries. The JMP uses a standard methodology to generate estimates for all countries, and these sometimes differ from national statistics which may use different definitions and/or methods. The purpose of the consultation is not to compare JMP estimates and national statistics but to review the completeness or correctness of the datasets in the JMP country file and to verify the interpretation of national data in the JMP estimates.

The JMP also extracts information on other relevant indicators included in national monitoring systems which are not part of the existing JMP service ladders. These data are used for additional analysis on issues of interest, such as menstrual health, disability and pandemic preparedness and response, but are not included in JMP country files due to limited data availability and lack of commonly agreed indicator definitions and methods for producing national, regional and global estimates.

Data sources

The primary sources of national data on WASH in Schools are routine Education Management Information Systems (EMIS) and periodic (non-EMIS) censuses and school facility surveys. Other sources of national data include regional monitoring initiatives such as the European Protocol on Water and Health, and secondary information compiled by the UNESCO Institute of Statistics. Where available, the JMP uses primary sources rather than secondary sources and uses original microdata or tabulations provided by national authorities rather than summary reports.

The 2022 JMP data update on WASH in schools draws on a total 1,321 data sources (since 2000), 1,029 of which were used to produce estimates for 182 countries. National data are only included if they meet minimum standards for data quality and coverage. For example, EMIS or census data are only used if the response rate is at least 33%. Survey data are only used if there are at least 50 schools per domain. Sub-national surveys are only used if they are representative of rural or urban schools.

The JMP extracts data that are representative of national, urban and rural schools and pre-primary, primary and secondary schools. The JMP relies on official data published by national authorities but detailed information on the overall distribution by education level and by type of school (e.g. public, private, religious, community, and schools for disadvantaged groups) is not always available.

Unless otherwise categorised by national authorities, all schools with primary-level students are counted as ‘primary’, all schools with secondary-level students are counted as ‘secondary’, and all schools with pre-primary-level students are counted as ‘pre-primary’ (where data are available for early childhood development centres, these are counted as ‘pre-primary’). This means some schools may be double-counted and the total number of schools does not necessarily equal the sum of the pre-primary, primary and secondary schools.

The JMP uses UNESCO UIS data on pre-primary, primary and secondary school-age populations and imputes values for countries with incomplete time series and for countries with no school-age data. Urban and rural school-age populations are calculated using the percentage of the population residing in urban areas, as reported by the UN Population Division.

Definitions of basic WASH services in schools

The JMP classifies drinking water and sanitation technologies into improved and unimproved types. Improved drinking water sources are designed to protect against contamination and include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water. Unimproved sources include unprotected wells, unprotected springs and surface water. Improved sanitation facilities are designed to hygienically separate excreta from human contact and include flush/pour-flush toilets, ventilated improved pit latrines, composting toilets and pit latrines with a slab or platform. Unimproved facilities include pit latrines without a slab or platform, hanging latrines and bucket latrines. A handwashing facility is a device designed to contain, transport or regulate the flow of water to facilitate handwashing. It may be fixed or mobile and include sinks with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent and soapy water but does not include ash, soil, sand or other handwashing agents.

Schools with an improved drinking water source with water available at the time of the questionnaire or survey are classified as having ‘basic’ service. Schools without water available, but with an improved source are classified as having ‘limited’ service, and those with unimproved or no water source are classified as having ‘no service’.

Schools with improved sanitation facilities which are single-sex and usable at the time of the survey or questionnaire are classified as having ‘basic’ service. The term ‘usable’ refers to toilets or latrines that are accessible to students (doors are unlocked or a key is available at all times), functional (the toilet is not broken, the toilet hole is not blocked, and water is available for flush/pour-flush toilets), and private (there are closable doors that lock from the inside and no large gaps in the structure). Those using improved sanitation facilities which are either not single-sex or not usable are classified as having ‘limited’ service. However, pre-primary schools without single-sex toilets may still be considered to have ‘basic’ sanitation service if the toilets are usable. Schools with unimproved or no toilets are classified as having ‘no service’.

Schools with handwashing facilities with water and soap available at the time of the questionnaire or survey are considered to have ‘basic’ service. Those with handwashing facilities that have water available at the time of the questionnaire or survey, but no soap, are considered to have ‘limited’ service, while schools with no facilities or no water available for handwashing are classified as having ‘no service’.

Data analysis and country estimates

The JMP uses a simple linear regression to generate estimates from all the available data points for nine primary indicators: any water facility, an improved water source, and a basic water service; any sanitation facility, an improved sanitation facility, and a basic sanitation service: and any handwashing facility, a handwashing facility with water, and a basic hygiene service. These estimates are used to calculate the remaining schools with no facility or unimproved facilities and with a limited service.

Trends are calculated if there are two or more data points available spanning at least four years. If the data points span fewer than four years, an average is used. Separate regressions are made for national, urban and rural, and for pre-primary, primary and secondary schools where data are available. A national estimate can also be calculated from urban and rural estimates or pre-primary, primary and secondary estimates. If data are only available for primary schools, a national estimate may also be calculated.

Regional and global estimates

Regional and global estimates are made by aggregating country-level estimates of the populations of school-age children with and without WASH services in school, and are only made if data are available for at least 30% of the school-age population in each domain (total, urban, rural, and pre-primary, primary and secondary schools). In countries with incomplete trend data, the school-age population is calculated using linear regression. In countries with no data, values are imputed based on an average proportion of the population that is school-age within the relevant M49 sub-region. The JMP does not use these ‘imputed’ statistics to produce country-level estimates. Urban and rural school-age populations are calculated based on the proportion of the national population that lives in urban areas. Global estimates use imputed values based on SDG regional groupings. Estimates for basic, limited and no services are then normalized to ensure they add up to 100%.