As the fierce coronavirus leaves a deadly trail behind, it also creates challenges and opportunities to innovate in official data and statistics. Integration of geospatial data with statistics can help to better understand the spatial behaviour of a global phenomenon like a pandemic. This makes it a great tool for decision making in the short term as well as for the achievement of the 2030 Agenda for Sustainable Development over the next decade.

Fortunately for the many people whose lives have been saved already, a handful of NSOs have embraced the geospatial and statistical integration data challenge. Data strategies for responding to COVID-19 are found in countries all around the world, and have been made possible through partnerships -- both government-to-government (G2G) and government-to-business (G2B).

Geo-statistical responses to COVID-19 by NSOs in the world

In association with third parties, not only has the European Union Statistics Office (Eurostat)¹ procured the location of most health care centres in the continent but also NSOs from Latin America (México and Colombia) have mapped statistics and spatial objects on health related issues.

In addition, the Spanish Institute of Statistics², Statistics Estonia³and the Ghanaian Statistical Service (GSS)⁴ ordered real-time studies using the location of mobile phones to gain an understanding of country-wide mobility when lockdown was in place. With the partnership of telecommunication companies, they managed to produce mobility indicators and to visualize aggregated data.

All the above cases have been developed through different kind of data partnerships inspired by Goal 17 of the 2030 Agenda (Partnerships for the Goals). They are actively responding to the recommendation to mobilize and share knowledge, experience, technology and financial resources supported by solid partners.

These data partnerships, created in the midst of the COVID-19 disaster response, suggest that a data revolution is possible even in the most pressing circumstances. Such synergistic association of stakeholders may well represent the first signs of the “data revolution” promised in Agenda 2030⁵.

What are these data partnerships suggesting?

In order to respond to COVID-19, and to embrace the data revolution, users of data require statistical agencies to demonstrate leadership by providing timely, efficient and quality data.

While many governments in the world are already taking action to prevent and mitigate the impact of COVID-19, by the beginning of May 2020 only 14 NSOs from countries around the world had been able to publish any visualizations, documentation, studies or data mash-ups regarding COVID-19. This is documented in the UN Department of Economic and Social Affairs, Statistics for COVID-19 response Hub⁶.

Three important points arise from the reviewed cases:

1. It is difficult to identify the resilient spirit of the data revolution in most of statistical agencies around the world, at least judging by the reduced number of NSOs producing data partnerships and compared with the total number of countries with infected cases (rate of 14/188).
2. The desirable leadership that the document “A World That Counts”⁷ reserves for NSOs in the setting of the data revolution is a work in progress. Nevertheless, it is commendable how NSOs from least developed countries are conducting data partnerships out of scarce resources, open data technologies and limited institutional conditions.
3. No cases of data collaboration between civil society and NSOs were found to provide geospatial responses from NSOs for COVID-19. This kind of data partnerships are especially recommended in the 2030 Agenda and are being actively studied by others to implement similar successful and inclusive data partnerships⁸.

A possible explanation of the leadership shortcomings shown by most NSOs -- during COVID-19 and in the 2030 Agenda -- might be found in a Policy Brief⁹ issued by Paris21¹⁰ in recent months: It argues that as developing countries adopt more focused containment measures, the COVID-19 crisis causes a double disruption that “squeezes” statistical offices with, 1) pressure from the demand-side of statistics coming from both governments and citizens that need prompt data to decide and; 2) pressure from the supply side, as a result of limited operational and technical resources in statistical agencies, who may be planning for a more or less stable generation of data in the short and medium terms. This might be creating interruptions in the value chain of official data and statistics.

Reinforcing data partnership leadership of NSOs is key for the data revolution

Partnering with external sources can be a suitable solution in the context of COVID-19 and the data revolution as well, especially if pressures stem from technical and financial limitations. Besides, reinforcing leadership and resilience of NSOs does not mean inaugurating an oligopoly over data, neither does it hamper NSOs role in the official statistics endeavour. It means mobilising and sharing knowledge along with resources in the context of limited conditions. After all, any effective leadership -- in data, in this case -- requires inclusiveness at its core.

Monitoring COVID-19 aided by effective visualizations and geographic disaggregation has proven to be of a great value. The many lessons coming from these experiences can revive the implementation of the 2030 Agenda and possibly inspire improvements in the processes already in place at NSOs to provide many of the indicators for the 17 Goals of the 2030 Agenda. A geospatial and statistical data integration strategy for this endeavour should also be marked by a healthy emphasis on effective data partnerships -- including not only governments and private companies but also civil society -- so that no one is left behind.

To demonstrate commitment and witness the value of leadership, the NSOs, the National Statistical System, other statistical government agencies, private actors and civil society have a unique opportunity to talk the walk at the next World Data Forum to map together a better world.

^{1. See https://statswiki.unece.org/download/attachments/279775891/2%20Eurostat.pptx?version=1&modificationDate=1590066891007&api=v2 ↩}

^{2. See https://www.ine.es/covid/covid_movilidad.htm ↩}

^{3. See https://news.err.ee/1072672/statistics-estonia-mobility-has-decreased-during-the-emergency-situation ↩}

^{4. See See https://statsghana.gov.gh/COVID-19%20press%20release%20report%20-%20analysis%20overview%20-%20final.pdf ↩}

^{5. See https://sustainabledevelopment.un.org/post2015/transformingourworld ↩}

^{6. See UN Statistics Division website: https://covid-19-response.unstatshub.org/useful-links/resources-from-national-statistical-offices/ ↩}

^{7. https://www.undatarevolution.org/wp-content/uploads/2014/11/A-World-That-Counts.pdf ↩}

^{8. See EuroStat website: https://ec.europa.eu/eurostat/documents/3888793/9393549/KS-TC-18-007-EN-N.pdf/513c6ca6-fbb3-4928-afdd-691285401e5f ↩}

^{9. See PARIS21 website: https://paris21.org/news-center/news/New-Policy-Brief-COVID-19 ↩}

^{10. See PARIS21 website: https://paris21.org/about-paris21 ↩}