Designing a water quality monitoring system in Sierra Leone with UNICEF

In Sierra Leone, less than 40% of households have access to clean, safe drinking water. Faecal contamination, in particular, poses a serious threat to the health of Sierra Leoneans. A lack of large-scale, reliable data on water quality makes it increasingly difficult for governments to effectively address this problem.

In 2018, the Ministry of Water Resources in Sierra Leone and UNICEF, together with Akvo, began monitoring the quality of drinking water at household level in 1100 communities, and at source level at 600 water sources. With reliable data on the status of drinking water services, decision makers are equipped with the information they need to drive sustainable change.

Above: Training implementing partners in water quality testing in Sierra Leone. Photo by Abdoulaye Rabdo. 


Ministry of Water Resources

Ministry of Health and sanitation




Sierra Leone


Water, sanitation and hygiene (WASH)


Survey design

Tool training

Water quality testing

Data analysis

The challenge

In Sierra Leone, access to safe drinking water is a major challenge, and the quality of drinking water is not regularly tested at household level. In 2017, Statistics Sierra Leone (Stats SL), with the technical support of UNICEF, conducted a Multiple Indicator Cluster Survey (MICS) to collect internationally comparable data on a wide range of indicators. The survey revealed that almost 90% of the drinking water at household level contained the E.coli bacteria, presenting a serious health threat to citizens. Since the water at the source was safe to drink, it was concluded that contamination must occur within the household. This led to a behaviour change intervention in 1100 communities, whereby people were trained on the various aspects of safe water collection and storage.

In order to monitor the impact of the intervention and guide future plans, a wide variety of data needed to be captured at scale. But before data can be captured, a thorough design phase is critical. Which water quality parameters need to be tested? What qualitative data is needed to provide context? How many people need to be trained in data collection and analysis? What sample size will be representative of the population? How can we design a survey that will ensure accuracy and relevance?


people trained


water sources assessed


implementing partners

The partnership

Together with UNICEF and the ministry, Akvo facilitated the design of a sampling strategy, survey design and monitoring framework for the programme. The sampling strategy included 1100 UNICEF supported communities, with three randomly selected households per community tested on the severity of E.coli contamination. With this setup, results will be representative of the 1100 communities with a 99% confidence level. Furthermore, 600 drinking water sources recently built by UNICEF were tested on 11 different parameters, including nitrate, fluoride, iron and potassium.

Besides facilitating the design phase of the programme, Akvo provided the mobile-phone based data platform to capture, monitor, analyse and visualise data at scale. Over a ten-day period, 20 Ministry mappers were trained on the use of mobile water quality testing in combination with Akvo’s data platform. These mappers were then responsible for training the other implementing partners, bolstering the sustainability of the programme.

Water Sample Test
Above: Implementing partners and ministry staff test water samples using Akvo Caddisfly and the Aquagenx Compartment Bag Test to measure E. coli in Sierra Leone. Photo by Abdoulaye Rabdo.

The change

The pilot project is one of the first large scale water quality assessments in Sierra Leone, involving partners from local NGOs to various levels of government. Akvo’s data platform enables this large scale collaboration, aligning dispersed teams and simplifying the data collection process.

The design phase of the programme made it clear that a combination of data from the water source (accessibility, availability, water quality) as well as data from households (demographics, sanitation, water treatment practices, water quality) was needed in order to gain insight into the root cause of contamination. Water and sanitation risk assessments were also combined with actual water quality results. The comprehensive and nuanced datasets provide deep insights into the status of WASH services, insights which can effectively guide the next steps of the project.

By gaining clarity from the start on how data will be captured, understood, and acted upon, as well as how progress will be monitored, a strong foundation is established for the data capture phase.