Using data to support the most vulnerable children

The COVID-19 pandemic is a threat to each and every community around the world. While children seem to be less directly affected by the virus, they might be the biggest victims of its social and economic consequences. And it will be the world’s poorest and most vulnerable children who bear the brunt of this crisis.  

Currently it’s estimated that between 42 and 66 million children globally could fall into poverty due to the economic consequences of the coronavirus, more than half of those in Sub-Saharan Africa alone. It’s vital that we can identify the most deprived children within countries in order to provide support. And whilst our most recent updates to GRID – Save the Children’s Child Inequality Tracker – have been long time in the making, these updates which will enable us to do just that are more important than ever.

GRID helps us to identify and track inequalities for child-focused Sustainable Development Goals (SDGs) indicators across health, nutrition, education and child protection. It compares group-based inequalities across income, gender, and location.

Our tools give everybody free access to reliable data from over 400 publicly available household surveys for more than 100 low- and middle-income countries. This data helps us to identify children furthest behind, track their progress over time, and build public and political understanding why it is so important to put the most deprived and marginalised children at the centre of what we do.

While GRID does not include currently COVID-19-specific data, its insights and analysis are especially important in understanding who the most vulnerable children are and how policies and programmes can target those who need help the most in the current crisis. We also believe that GRID can play an essential role to ensure that the response and recovery efforts, which will follow in the next months and years, do actively close gaps between the most marginalised and their more advantaged peers.

Take child mortality as an example. Even before the current health crisis, 37 countries (out of 68 low- and middle-income where sufficient data exists) were not on track to reach the goals set out in the SDGs. Another ten countries were reaching those targets for some groups within the country, often children living in the richest quintiles or in urban areas, but other groups lag significantly behind and miss the goals. This violates the pledge to leave no one behind at the heat of the SDGs, which requires governments to reach goals for all segments of society, and actively to reach out to those furthest behind first.

Comparing the different trajectories of Bangladesh and India using the GRID tools illustrate exactly this. Starting from a similar mortality rate, Bangladesh saw much more inclusive progress with gaps between the poorest and richest closing and all groups set to reach the target by 2030. In contrast, while gaps slowly closed in India as well, current projections show the poorest missing the 2030 goal, while the national average and the richest are reaching the targets. COVID-19 could dramatically alter those trajectories, with some estimates suggesting hundreds of thousands of additional child deaths globally this year, in effect reversing the progress made in infant mortality in the last 2-3 years. Given that children in the poorest quintiles are twice as likely to die before their fifth birthday than those in the richest quintiles, there is a risk that the gaps in mortality are widening again as a consequence of COVID-19.

As a consequence of the threat of coronavirus, 188 countries have imposed national school closures, resulting in more than 1.5 billion children out of school. This will deepen the existing learning crisis and losses of future human capital will be substantial. But there is also a worry that some children will not return back to school. After the Ebola epidemic in Sierra Leone, school enrolment rates for adolescent girls in some heavily impacted villages fell by a third.

Should schools remain closed due to lockdowns or shelter-in-place policies, this may also increase the risk of teenage pregnancy as adolescent girls out of school are more than twice as likely to become pregnant than those in school. Data in GRID shows that this too would affect disproportionally the most marginalised children. For instance, in Nigeria girls which are both living in rural settings and are part of the poorest 40% are twice as likely to be pregnant than the national average (and even ten times more likely than the richest girls living in urban centres).

We hope that GRID – and the many updates we have incorporated in the last few weeks including many new tools, multilingual dashboards and a renewed focus on subnational regions – will contribute important insights and evidence to the COVID-19 response and help to keep the most deprived and marginalised children at the centre of everything we do.

In the meantime, please do explore GRID further here.