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

应利用来自多个来源的高质量数据作出关于卫生政策和提供的决定。联合国鼓励数据可查找、可解释、可互操作和可重用（FAIR），但非洲的大部分数据尚未达到FAIR数据的标准。人口健康数据对于衡量可持续发展目标（SDG）的许多指标非常重要，包括全民健康覆盖（UHC）。在大多数东非国家，卫生和人口哨点监测站用于收集人口内部的健康数据。阿尔法网络展示了如何利用来自人类发展和社会服务局的艾滋病毒数据来显示艾滋病毒如何影响人口，以及艾滋病毒服务和政策（包括提供抗逆转录病毒疗法）对艾滋病毒感染者健康的影响，该项目的总体目标是在东非建立共享研究实体人口信息执行网络（INSPIRE）。这承认了在不同国家和不同环境下共享协调、公平的数据的价值，并建立了产生这些数据的机制。INSPIRE网络将建立数据平台的关键组成部分。首先，我们将汇集通过HDSS收集原始数据的机构，并概述这样一个网络可以为HDSS带来的好处和支持。拟议的网络将以INDEPTH网络为模型，并以南非的SAPRIN（www.saprin.mrc.ac.za）为例说明其如何运作。这一部分的目标是建立一种伙伴关系，利用不同机构提供的人口健康数据，将其转化为FAIR数据，以便进行高质量的分析，回答与政策有关的问题;第二部分是确定FAIR数据的技术要求，并为编制数据奠定基础。基于ALPHA网络的工作，我们将使用自动化方法为HDSS合作伙伴提取，转换和加载自己的HDSS数据到一个共同的数据库。我们将通过对FAIR数据很重要的行业标准数据文件来保留数据的来源，该项目将开发和解释描述非洲纵向人口健康数据的词汇，为国际标准做出贡献，以便研究人员能够理解和搜索数据。该项目将探讨如何将人口健康数据与东非正在开发的电子健康记录联系起来，第三个组成部分将鼓励使用这些数据，以使该平台可持续发展。该项目将确定数据的价值，改变人口健康数据的文化，展示如何分析数据以回答重要的健康问题，纵向人口健康数据虽然对了解保健服务需求至关重要，但已被数字革命抛在后面。迫切需要改变这种状况，找到一种解决方案，提供统一的公平、公正和可供各国和不同健康状况之间进行比较的数据。该项目将建立发展和维持这一系统所需的伙伴关系，并将建立技术能力，以便能够建立一个FAIR人口健康统一数据库。

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.