From COVID-19 to Data Revolution: Lessons from Geospatial Data Partnerships
Photo Credit: SDSN TReNDS
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National Statistical Offices have been challenged by the pandemic outbreak to generate, share, match and disseminate geospatial and statistical vital data in a timely and reliable manner.

The concept of data partnership is rooted in SDG 17 (partnership for the Goals).

Monitoring of the SDG indicators in an inclusive and communicative manner can help revive implementation of the 2030 Agenda.

As the fierce coronavirus leaves a deadly trail behind, it also reveals major gaps in official data and statistics. Integrating geospatial data with statistics can help 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 achieving the 2030 Agenda for Sustainable Development over the next ten-and-a-half years.

Although governments and NSOs have been restrained in their ability to generate, share, match, and disseminate geospatial and statistical data in a timely and reliable manner, partnering with external parties could prove to be an effective solution.

Data Partnerships and NSOs’ Geospatial Responses to COVID-19

Fortunately for the many people whose lives have been saved already, NSOs have embraced the geospatial data challenge. However, their offered solutions have had varying levels of value for decision-making.

Different strategies for responding to COVID-19 using geospatial data and statistics are found in all kind of countries around the world, and have been made possible through data partnerships – both government-to-government (G2G) and government-to-business (G2B) – as indicated in the table below. 

NSO

Type of Analysis / Visualization

Kind of Partnership (per classification here)

Source Data Layer

Data reusability

CSO Ireland

Geo Hive Hub / SDG chart

G2G+ (additional  partners)

Several

Linked Open Statistical Data (LOSD)

Eurostat

Travel time to health services

G2G

Geo Data Base of health services

Open

DANE Colombia

Vulnerability Index

G2G

2018 + Census

Proprietary

INE Spain

Population Mobility

G2B

Real time

Proprietary

Statistics Estonia

Population Mobility

G2B

Real time

Proprietary

INEGI Mexico

Mapping of infected and Other

G2G+

N/A

Open

GSS Ghana

Population Mobility

G2B

Real time

Proprietary

 

These “geo statistical” data partnerships are not only found in developed countries. Not only has the European Union Statistics Office (Eurostat) procured the location of most health care centres in the continent but also NSOs from Latin America (Mexico and Colombia) have mapped statistics on health-related issues in close partnership with government agencies.

The Spanish Institute of Statistics, Statistics Estonia, and the Ghanaian Statistical Service (GSS) ordered real-time studies using the location of mobile phones to understand country-wide mobility during the lockdown period. With the partnership of telecommunication companies, they managed to produce mobility indicators out of aggregated data.

All the above cases were developed through a data partnership inspired by SDG 17 of the 2030 Agenda (partnership for the Goals). This kind of partnership is meant to mobilize and share knowledge, expertise, technology, and financial resources to support the achievement of the SDGs, in particular developing countries. The practical impact of these partnerships for COVID response have proved effective for saving lives in the respective territory.

Seven observations from COVID-19 data partnering

While the number and variety of initiatives is limited at this time, they suggest ample opportunity to support issues related to the SDGs through inclusive data partnerships. 

Among the preliminary observations from these case studies:

  1. The identified examples do not incorporate real-time geospatial analysis of contact tracing for those infected; available information is provided only in an aggregated fashion.
  2. Before the outbreak, no cases of data partnerships between health statistics offices and NSOs were identified.
  3. The experiences and geospatial response laboratories noted here showed in a short time a great potential for integrating sources from different origins.
  4. It was possible for some initiatives to involve private actors to organize data partnerships.
  5. Commendable efforts have been made by statistical offices of developing countries by using administrative records or surveys from other sectors of government.
  6. Some examples employed targeted communication campaigns to prevent confusion among the public.
  7. Finally, although the private sector has demonstrated the capacity to partner with NSOs, no cases of data collaboration between civil society and NSOs in providing geospatial responses to COVID-19 have been found.

What do these lessons teach us?

With these observations in mind, it could be argued that partnering with external sources can be a suitable solution in the context of a pandemic – and also for the data revolution – especially if pressures strike at the right moment and place. By integrating sources of diverse geospatial and statistical natures, innovative data partnership approaches could effectively help in the understanding of the territorial behavior of many other “pandemics” like poverty or climate change, not just the coronavirus pandemic. Cases also suggest that the necessary institutional arrangements can be worked out in the short term, if necessary incentives are in place, and possibly with the condition of demand pressure for vital data.

The mobilization and sharing of knowledge and data amid limiting conditions can be achieved through greater leadership of NSOs in data partnerships, especially if inclusiveness and flexibility is at their core of the strategy. This could be especially useful when economic and social issues emerge in the future during the transition to a new normality. The statistical domain should capitalize as well on the costly lessons learned in the heat of this pandemic, including comprehensive communication plans and the recruiting of civil society in data collection exercises. These should consider innovative remote spatial techniques, i.e. crowdsourcing of data in grassroots levels, and “armchair mapping.”

Monitoring coronavirus with an inclusive and communicative approach can revive implementation of the 2030 Agenda by helping to provide many of the indicators for all SDGs. An intelligent strategy for both COVID-19 and SDG monitoring will be marked by a healthy emphasis on effective data partnerships so that no one is left behind.

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The author of this guest article, Javier Carranza Torres, is Director of GeoCensos. GeoCensos is an NGO with networks in the Latin American and Caribbean region, with a core community composed of technology activists with strong ethical values and commitment to sustainable development. Its experiences include contributions to the 2010 and 2020 census processes, and contributing ideas and solutions to more than ten national statistical offices (NSOs) in support of the 2030 Agenda.

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