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

Lead Research Organisation: London Sch of Hygiene and Trop Medicine
Department Name: Epidemiology and Population Health

Abstract

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.

Planned Impact

The INSPIRE network will bring together research entities together to form a way to support health and demographic sentinel surveillance (HDSS) in populations in Eastern Africa. The impact of this project will be felt in several ways. Firstly there will be an impact of data processes and the people who deal with data in Eastern Africa. Next there will an impact on how data are seen, used and analysed in Eastern Africa. In the longer term we expect to see further impact as the data are used to improve the health services, and hence the health of people in Eastern Africa. Finally over the longer term, this project will change the culture and environment towards population data on health.

In Phase 1 of the DIDA call the impact will be limited to building the foundation for the future data, and data processes. The real impact will come from the implementation of the network in Phase 2, which will see the improvements in the data, and the training of data managers, which will in turn lead to the longer term effects. However Phase 1 will provide the means to create the structure on which on the subsequent work will be built. It will provide the crucial foundation to the impact of the network. Even if Phase 2 of the GCRF - DIDA project did not happen, the structures would be there for another funding call.

The first impact will be on the data process used to manage data. Even in Phase 1 this will be seen through the use of data from one disease - HIV - which will be used as the model for the INSPIRE network. By incorporating the metadata into the shared databases, we will be able to bring greater understanding of the data provenance. This will enable us to build better quality into every step of the way. This impact will include the effect on personnel through training of data managers in the latest methods for building Big Data sets. In Phase 1 this will be limited to one data professional in APHRC, but in Phase 2 the impact will be seen in data personnel in every HDSS that joins the network.
The second impact will be in the use of the data. In Phase 1 we will start to use the HIV data to answer questions across Eastern Africa, which will highlight the findability, accessibility, interoperability and reusability of the data. In Phase 2 we will add other data into the network which will enhance the ways that the data can be used.

With the greater use of diverse data to inform policy, there will be better understanding of how to design health services to improve the health of people living in the community. By bringing the data together across Eastern Africa the opportunity to see how these services are accessed, and the effect these have on people's daily lives.

Ultimately this project will change the way we think about data, and how it can be used to inform decision making. This will go beyond the data in the INSPIRE network, but will encourage the sharing of data across disciplines. Population data provide the denominators needed to understand all Government services, and to show their impact on the lives of real people in Eastern Africa.

Publications

10 25 50
 
Description We have established the mechanism for automatically collating and harmonising longitudinal population health data. We have created an OMOP common data model and are working on the vocabularies needed to share HIV data and COVID-19 data from several African partner institutions.
We have established a network that can provide some benefits to the data producers. This is urgently needed since the demise of the INDEPTH network. We have elevn members in the partner and four collaborative partners providing technical and data support.
Exploitation Route Other longitudinal population health data providers are free to join INSPIRE and share the benefits of wider data access.
Sectors Healthcare,Government, Democracy and Justice

 
Description Harnessing heterogeneous COVID-19 data, to build a data hub and apply artificial intelligence (AI) and data science to support public health and economic decision makings in Kenya and Malawi
Amount $1,105,839 (CAD)
Funding ID 109622 
Organisation African Population and Health Research Center 
Sector Academic/University
Country Kenya
Start 01/2021 
End 01/2023
 
Title Microsoft Azure platform as a service 
Description We are developing an OMOP common data model for harmonised longitudinal population data. 
Type Of Material Improvements to research infrastructure 
Year Produced 2020 
Provided To Others? No  
Impact We are developing an OMOP common data model for harmonised longitudinal population data. 
 
Description ALPHA 
Organisation London School of Hygiene and Tropical Medicine (LSHTM)
Country United Kingdom 
Sector Academic/University 
PI Contribution We have developed new programs for collating, sharing and harmonising HIV data from population cohorts in Africa
Collaborator Contribution Partners have already collected HIV data and have expressed willingness to share and analyse together.
Impact This collaboration has resulted in presentations to high level conferences. It has improved the quality of the database for sharing and harmonisation of data. INSPIRE has helped generalise the work of ALPHA and show how it can be expanded and made integral to African institutions through governance and technical advances.
Start Year 2006
 
Description ALPHA 
Organisation Malawi Epidemiology & Intervention Research Unit
Country United Kingdom 
Sector Learned Society 
PI Contribution We have developed new programs for collating, sharing and harmonising HIV data from population cohorts in Africa
Collaborator Contribution Partners have already collected HIV data and have expressed willingness to share and analyse together.
Impact This collaboration has resulted in presentations to high level conferences. It has improved the quality of the database for sharing and harmonisation of data. INSPIRE has helped generalise the work of ALPHA and show how it can be expanded and made integral to African institutions through governance and technical advances.
Start Year 2006
 
Description ALPHA 
Organisation National Institute for Medical Research, Tanzania
Country Tanzania, United Republic of 
Sector Public 
PI Contribution We have developed new programs for collating, sharing and harmonising HIV data from population cohorts in Africa
Collaborator Contribution Partners have already collected HIV data and have expressed willingness to share and analyse together.
Impact This collaboration has resulted in presentations to high level conferences. It has improved the quality of the database for sharing and harmonisation of data. INSPIRE has helped generalise the work of ALPHA and show how it can be expanded and made integral to African institutions through governance and technical advances.
Start Year 2006
 
Description INSPIRE 
Organisation African Population and Health Research Center
Country Kenya 
Sector Academic/University 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation Ifakara Health Institute
Country Tanzania, United Republic of 
Sector Charity/Non Profit 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation Kenyan Institute for Medical Research (KEMRI)
Department KEMRI/CDC Research and Public Health Collaboration
Country Kenya 
Sector Charity/Non Profit 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation Makerere University
Department Child Health and Development Centre
Country Uganda 
Sector Academic/University 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation Malawi Epidemiology & Intervention Research Unit
Country United Kingdom 
Sector Learned Society 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation National Institute for Medical Research, Tanzania
Country Tanzania, United Republic of 
Sector Public 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description INSPIRE 
Organisation The Committee on Data for Science and Technology (CODATA)
Country United Kingdom 
Sector Private 
PI Contribution The INSPIRE network have established the infrastructure to share longitudinal population-based health data within East Africa. The shared data will be available to effectively address research gaps in different areas. The infrastructure uses a common data model built on the well used OMOP (Observational Medical Outcomes Partnerships) used for many medical databases. Specifically the shared data will be FAIR (findable, accessible, interoperable and reusable) in accordance with the best practice defined by CODATA and Go-FAIR. The data are a resource for evidence-based health planning across Eastern Africa.
Collaborator Contribution The partners all have longitudinal population based data around health themes. The data include areas of mutual cooperation around fertility, mortality, migration and morbidity. The health data include HIV, non-communicable diseases and neglected tropical diseases. Socio-demographic data and other social data will be included in the data that will be shared by the partners.
Impact Demography Public Health Maternal Health Biostatistics Data Science
Start Year 2020
 
Description Live panel session for discussion on the session "Multi-Stakeholder Data Bridges: making data work for cross-domain grand challenges" 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact The structured discussion features a short statement of the way data can be brought together for monitoring infectious diseases worldwide, but most importantly in Africa. The panel included Dr Chifundo Kanjala who showed how this has started and where the work was going. Much of what he talked about is new areas where collaboration between diverse actors on the international stage are needed in order to build the models for the future.
Year(s) Of Engagement Activity 2020
URL https://vimeo.com/469702557
 
Description Presentation to the UN Data Forum in the session "Multi-Stakeholder Data Bridges: making data work for cross-domain grand challenges" 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Dr Chifundo Kanjala presented the work from the INSPIRE network for a pre-recorded session in the UN Data Forum. Dr Kanjala then participated in a question and answer forum responding the questions from a high level audience of data professionals (which will be entered as a separate engagement activity).
The presentation was part of a panel, and Dr Kanjala's contribution comes 35 minutes into the panel and ends at 49 minutes (in the URL below). The recorded session can also be see on the CODATA Vimeo channel https://vimeo.com/465263347
The presentation by Dr Kanjala is entitled "Infectious diseases cross-site data harmonisation in Africa" and outlines how diverse data from longitudinal population-based studies can be brought together for comparative analyses. The presentations outlines the necessary components to make this successful, and gives the background to the successful use of the harmonisation processes.
The purpose of the presentation was to outline how diverse data can be brought together into a Common Data Model. This feeds into the decisions being made under the SENDAI Framework, and will be crucial to building an Early Warning system for infectious disease surveillance.
Year(s) Of Engagement Activity 2020
URL https://ve.attendify.com/index/e19y30/s_e19y30/schedule/9yx2dgHJCUx0XFsM09/9yx6rE0JWGcUiEIChV