This article is written by Claire Melamed, CEO, Global Partnership for Sustainable Development Data

We’re all data enthusiasts now, tracking statistics and awaiting the latest figures — even people who thought data really wasn’t for them are now paying full attention. Twitter is awash with amateur statisticians producing their own models and predictions.

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For the members of Global Partnership for Sustainable Development Data and the other data for development practitioners we work with, data has always been the lifeblood of the fight for better lives for all people, everywhere. Its importance for emergency crisis response is clear today, but it is just as crucial for tackling the ongoing economic, social, and environmental challenges that will be the focus of any post-Covid-19 recovery.

But all too often, data is poor quality, out of date, or incomplete.

When it comes to Covid-19, being invisible in data can be deadly

In these cases, the data might do more harm than good. In particular, data can hide the deep divisions within our societies, and further marginalise the poorest and most vulnerable people who are typically invisible in data.

Disaggregated data is a tool for justice and accountability

Take race, for example. About one-quarter of the population of Latin America are Afro-descendants. But in the majority of Latin American countries, questions about ethnicity and race were asked for the first time in the latest round of censuses.

This has revealed that poverty is over twice as high for Afro-descendants in Brazil, three times higher in Uruguay, and over 10 percentage points higher in Colombia, Ecuador, and Peru. These groups have fewer years of education, and are more often victims of crime and violence. Until this census round, this huge group was not identified in official data, and thus their specific situation was excluded from policy decisions for decades.

When it comes to Covid-19, being invisible in data can be deadly. Invisible populations are not considered when deciding where to send nurses or ventilators, how to allocate financial support, or when to lift lockdowns. If someone in a rural area dies at home, their death might not be recorded, and the spread of the virus won’t be accurately captured in the modelling used to inform response.

If gender, disability, or race, for example, aren’t included in how populations are measured, it’s impossible to see if there are different infection or death rates among different groups. We know that black and Hispanic people are dying at higher rates in the US, though this information was not disaggregated or released early enough to prevent or mitigate these outcomes.

It’s great that everyone wants data now, but also, frankly, a little frustrating

The pandemic brings other hardships, and while it has infiltrated communities regardless of wealth or status, it has hit marginalised people the hardest: from the 70,000 street children in Delhi who can’t access any support, to the two billion informal workers globally who face hunger under lockdown, to the women who live in fear as gender-based violence soars by 20%.

How can data be made a more effective tool for justice and accountability for these marginalised groups?

Plugging the data gap

In the short term, we need to integrate existing data from ministries, statistical offices, and civil society organisations, which can help to identify vulnerable populations and develop effective policy responses.

We can also use citizen-generated data to better understand the realities on the ground, as we’ve seen from the almost 3 million users of the Covid-19 System Tracker app in the UK.

In the long term, we need strong and inclusive systems: strong data infrastructures and well-resourced statistical offices that are committed to data as a tool for reducing inequalities.

The heart of an inclusive data system will be comprehensive censuses and household surveys that capture vulnerable and hard-to-reach populations. Data must be interoperable and shared across government, so the administrative data other departments and ministries are already producing can be leveraged for social good.

We need trained and engaged people: these systems must be staffed with people who have the technical capacity to anonymise and protect people’s privacy, while keeping the granularity needed to address their specific needs. It’s not just technical skills — a good system needs people who can engage with the people in the data, so data is something that is done with people and not to them. When communities understand why data is important and how to use it, and can trust that it won’t be used to exploit them, great things can happen.

It’s great that everyone wants data now, but also, frankly, a little frustrating. The fact that data is a necessary and yet still woefully inadequate input for policymaking is not news — but over decades, in too many countries, data and statistics have been consistently underfunded. The latest reporting of official development assistance (ODA) to data and statistics puts it at $689 million USD — 0.34% of total development support. This number has grown slightly over the last few years, but is still only about half of what it needs to be, [according to experts from Paris21](https://paris21.org/sites/default/files/2019-01/Financing%20challenges%20for%20developing%20statistical%20systems%20(DP14%29.pdf), a UN-backed organisation promoting better statistics. No surprise then that there is not a single low-income country that has an adequate system for registering the causes of death, according to the WHO.

The world after Covid-19

The message is getting through, and it is inspiring and heartening to see a global effort around Covid-19 data.

If you’re a policymaker or a producer or user of data, we hope you’ll advocate for more, better disaggregated data in your own organisation or community

If this is to be part of building a better world afterwards, we need to focus on data that reveals and can tackle the inequalities that warp our societies.

There are promising examples from our network of Inclusive Data Charter champions, a group of organisations who committed to inclusive, disaggregated data. Work like this can and must be scaled and expanded.

If you’re a donor, we call on you to be part of the solution to make stories like these the norm. If you’re a policymaker or a producer or user of data, we hope you’ll advocate for more, better disaggregated data in your own organisation or community. We have an opportunity now to choose a different path in response to Covid-19, an inclusive path that leaves no one behind. We hope you’ll join us. — Claire Melamed

(Picture credit: Unsplash)