Ethiopia has almost half of the world’s trachoma burden, with 76.2 million people needing health interventions. Sightsavers is supporting the country’s ministry of health in its efforts to eliminate neglected tropical diseases (NTDs), including trachoma, by integrating data to deliver more effective healthcare.
Biruck Kebede, who leads Sightsavers’ NTD work in Ethiopia, explains how data can help to eliminate diseases.
We gather and analyse numbers on everything and, recently, we’ve seen a lot of discussion about data in relation to COVID-19.
But we’ve always needed data to look after our health, and with NTDs it’s no different. NTDs affect more than one billion people and are most prevalent in rural regions, poor urban areas and conflict zones. Among them is trachoma, which starts off as an eye infection that can be easily treated. But if it’s not treated, it can lead to a painful advanced form of the disease that can cause blindness. Comprehensive data is needed to consign NTDs such as trachoma to the history books.
Using data, we can look at how many people suffer from a disease. Alone this is of little to no use if we want to stop an infection from spreading and cure people. But put it together with more data, such as people’s locations, and bingo: data becomes a powerful decision-making tool because we can then decide to send out further support in their direction.
In NTDs, we’ve been doing this for years. But if we can instantly pair the number of people affected and their location with many different types of data, such as information about the different trachoma interventions that are already being carried out, the value of this data becomes greater than the sum of its parts.
In fact, if we use this resource well, it can change people’s lives.
NTD data includes information about a disease; for example how many people have trachoma in different locations over time. It also provides information about interventions addressing a disease, such as where, when and how many treatments have been distributed, and whether these have stopped it from spreading.
As part of our work at Sightsavers, we support ‘data integration’. While this simply means bringing sets of data together, it’s a very complex and time-consuming piece of work to do, and it requires collaboration and innovation to make it a success.
Data integration can be a challenge as information is often spread across many different databases. It’s also often described differently across platforms and so it can’t be processed together. For example, we’ve experienced different spellings of place names, and a mixture of dates from the Ethiopian calendar and from the international Gregorian calendar. This all means that a lot of energy is needed to identify and transform the data before you can integrate it.
Establishing a single, reliable source of data that all NTD stakeholders (including national government officials from different departments, regional government officials and non-governmental organisations) can use to guide work is extremely complicated. Yet it’s potentially a huge gamechanger when it comes to progress towards eliminating a disease like trachoma.
Ethiopia is leading the way on establishing an integrated NTD database (access acquired through the ministry). We have supported the ministry of health to integrate NTD data into the national health information system and bring critical NTD data together into a single comprehensive source, which is accessible by stakeholders at national, regional, and even global levels.
First, like in many countries, NTD datasets were stored in separate places, and so there wasn’t a full picture of the country’s NTD-related health and interventions in one place. Datasets from work such as mass drug administration (MDA) campaigns, which treat millions of people for trachoma each year, and impact surveys, which assess where trachoma remains a public health problem after MDA has been carried out, were managed on different platforms. This made it extremely complex for programme managers to provide a comprehensive overview of the NTD situation to key stakeholders, such as high-level officials, because they had to merge data from multiple data sources. Additionally, the data from each activity was not combined with previous data to identify trends over time. Now that all NTD programmatic data across multiple years is accessible in a single national database, it’s easier for key stakeholders to monitor and correctly interpret.
Second, survey data was often stored in editable formats such as Excel or Word, where data was at risk of being incorrectly edited, and multiple versions were often created. At worst, it was at risk of being deleted and lost. Now, programme managers can access accurate NTD survey data in the database, and so there is only one, standardised version of the data that they know they can rely on.
We have worked to make this database a useful and attractive resource for all stakeholders and have also fed in other data important to NTDs, including mWater, WHO ESPEN, Tropical Data and NTDeliver. Integration of these datasets ensures that valuable water, sanitation and hygiene (WASH), treatment and survey forecasting, prevalence survey and drug procurement data can be viewed together. We hope that equipping this system with these powerful tools will encourage all stakeholders to use it, and to input their data into the database going forward.
In these ways, the single platform will allow the ministry and other actors to confidently look at the full picture with different datasets together to determine – with relative ease and speed – what kinds of resources are needed and where they are needed as a priority.