Implementation Network for Sharing Population Information from Research Entities in East Africa (INSPIRE-EA)

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Decisions on health policy and provision should be made using high quality data from multiple sources. The UN have encouraged data to be Findable, Accessible, Interoperable, and Reusable (FAIR) but much of the data in Africa has not reached the standards of FAIR data. Population data on health are important to measure many of the indicators for the Sustainable Development Goals (SDG), including the Universal Health Coverage (UHC). In most Eastern African countries, health and demographic sentinel surveillance (HDSS) sites are used to collect health data from within populations. The ALPHA network has demonstrated how HIV data from HDSS can be used to show how HIV affected the population, and the impact of HIV services and policies (including the delivery of anti-retroviral therapy) on the health of people living with HIV.The overall aim of this project is to create the Implementation Network for Sharing Population Information from Research Entities (INSPIRE) network in East Africa. This recognises the value of sharing harmonised, FAIR data across countries and across settings, and it sets up the mechanism by which these data can be produced. The INSPIRE network will build the key components for the data platform. Firstly we will bring together the institutions that collect primary data through HDSS, and to outline the benefits and support that such a network could bring to HDSS. The proposed network would be modelled on the INDEPTH network, and use SAPRIN in South Africa (www.saprin.mrc.ac.za) as an example of how it could work. The goal of this component is to establish a partnership which leverages population health data from different institutions into FAIR data that enables high quality analysis to answer policy relevant questions.The second component is to establish the technical requirements of FAIR data and to make the foundations to produce the data. Building on the work of ALPHA network, we will use automated methods for HDSS partners to extract, transform and load their own HDSS data into a common database. We will retain the provenance of the data through industry standard data documentation which is important for FAIR data.The project will develop and standardise the vocabulary to describe longitudinal population health data in Africa, contributing to international standards so that researchers can understand and search the data. The project will explore the way in which the population health data can be linked with the electronic health records (EHR), which are being developed in Eastern Africa.The third component will encourage the use of the data in order to make the platform sustainable. The project will identify the value of the data, and change the culture towards population health data, demonstrating how the data can be analysed to answer important health questions.Longitudinal, population data on health, while essential to understanding the demand for health services, has been left behind by the digital revolution. There is an urgent need to change this situation and find a solution which will provide harmonized FAIR data that can be compared across countries and across different health conditions. This project would establish the partnerships that are needed to develop and maintain such a system, and will set up the technical capacity to be able to set up a FAIR harmonised database for population health.