Unified Region Based Covariates for Investigating the Causes of Early Childhood Adversity, 2010-2017 [Malawi]

A unified data set of covariates for investigating the causes of early childhood primary school level performance. Unified based on school level regions computed as the voronoi cells for all schools (geolocated from the Malawi Spatial Data Platform). Covariates contributing to this data set are from the following sources: The 4th Integrated Household Survey (IHS4) [https://microdata.worldbank.org/index.php/catalog/2936/data-dictionary], two birth cohort studies (IMPROVE and REVAMP), the Malawi Spatial Data Platform [http://www.masdap.mw/] and protein consumption data [an extension of the IHS3 data set: https://microdata.worldbank.org/index.php/catalog/1003 by Molly Muleya, Edward Joy and Kevin Tang from the London School of Hygiene & Tropical Medicine and the University of Nottingham]. The original data is available by request to the data owners. Some, such as the birth cohort data is subject to further restrictions. Access requests to code to build the database from these sources and/or discussions about access to the pre-built database should be sent to the PI of the ESRC Grant: ES/T01010X/1. The school level regions are provided as part of this data collection and full meta-data for all fields in the full dataset is provided. See Section Notes on access for more information.

Like many low-income countries in Sub-Saharan Africa, Malawi is burdened with high rates of maternal, infant and childhood mortality and undernutrition. These are driven by multiple factors that interact over space and time. Coupled with economic and gender inequalities, factors that operate across early childhood (0-8 years) result in many children failing to achieve their educational potential. At a national level this impedes economic development and perpetuates a cycle of poverty. A holistic, unified, approach to data acquisition of key factors impacting early child development, data sharing and linkage to existing datasets, statistical analyses and mathematical modelling, is required to identify which children are at greatest need of intervention. We aim to achieve this by building a new data platform for early child development in Malawi by harmonising geo-temporal data that already exists, courtesy of national surveys conducted by the Government of Malawi, with data from ongoing projects undertaken by our team of researchers and NGO partners, relating to early educational outcomes, maternal and infant health, and micronutrients in soil and crop samples taken from plots where food is grown for consumption in family homes. Integrating these datasets into a large-scale national data platform will enable secondary analyses to be conducted, that have hitherto, not been possible. This will transform early child development and learning outcomes in Malawi, and requires collaboration and cooperation of key stakeholders to bring about long-term, sustainable, change. Current policy for mothers and children in Malawi is covered by three separate government ministries. A lack of joined up planning, acquisition, and sharing of key data means that opportunities to intervene at an early stage may be lost. Currently, it is not possible to track individual children from pregnancy to 8 years and identify those most at risk of adverse outcomes. This leaves Malawi vulnerable to continued poor early child development and the long-term negative impact this has on the country's economic development and welfare. Over the past year, we have established a multidisciplinary team of international researchers from psychology, biosciences, maternal, child, and public health, big data science, and international law on data protection and governance, with NGOs, policy-makers, and policy-enablers from key government sectors in Malawi, all of whom are committed to improving quality of life for young children and their families. We have identified the need for a unified data management system in Malawi, that is compliant with General Data Protection Regulation legislation, and will enable NGO and research data to be integrated with national government survey data. Accordingly, in this project we propose to build a new data platform that will harmonise existing datasets from NGOs, the Government of Malawi, and ongoing research projects in Malawi, to enable secondary analyses to be conducted that will identify causal pathways of adverse outcomes in early childhood. Results from these secondary data analyses will enhance understanding of factors that impact early child development and learning and will be utilised by NGOs and the Government of Malawi to make strategic decisions based on scientific evidence to enhance the effectiveness of their programmes and policies. The new data platform will be hosted within the Ministry of Gender and will be an ongoing, sustainable resource, improving the capacity and methods for secondary data research in Malawi and will act as a demonstration of potential to other developing nations. This project is timely as it will increase high-quality, impactful and relevant research in Malawi and other ODA contexts on factors influencing early childhood outcomes. The results of the project will impact generations of children in Malawi and other countries in the region facing similar development challenges.

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