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As the ongoing global crisis related to the COVID-19 pandemic continues to unfold, there is an increasing risk of less production and dissemination of disaggregated, high quality foundational data in National Statistical Systems (NSS) in developing and least-developed countries, already facing a capacity squeeze. While those NSSs adjust their operations in the face of lockdowns and other mitigation policies, policymakers and citizens need to take quick, informed actions to tackle the crisis--ideally based on quality data accessible to everyone. Consequently, the combination of rising demands and constrained supply of official statistics reduces NSS capacity to contribute to response and recovery activities.

In this context, private data producers, civil society organisations and academia might step in and provide a complementary supply of data to policymakers. In a crisis more than in any other time, NSSs thus need to reach beyond their traditional mandate as a data producer, and engage in data stewardship. Capacity development efforts should refocus on developing coordination, governance and quality management capabilities.

Please see PARIS21 initiative for further analysis and recommendations.

Recommendations and country examples

1. Scale up teleworking arrangements: Wherever possible, NSS institutions should work with policymakers and development partners to improve operational conditions for remote work. Without these capabilities, risks of critical data shortages will increase over time. Colombia (DANE) took early steps to ensure staff connectivity such as VPN access, free antivirus licenses and increased data-processing capacities.

2. Accelerate innovation and digitalisation: As opportunities for traditional, field-based approaches to data collection wane, National Statistical Offices (NSOs) and other NSS institutions should prioritise transitions to new technologies for official statistics. Senegal (ANSD) is pursuing options to replace field operations with phone and web-based survey production. Lesotho (NBS) solicited support from the World Bank to develop alternative approaches to census production using big data.

3. Package existing data sources for decision-makers: While options to collect new data are constrained, policymakers and partners can use existing data sources to develop evidence-based approaches to pandemic response and identify populations at greatest risk. The Dominican Republic (ONE) responded to data demands by establishing a central data repository of all information related to COVID-19 in their country. Maldives (NBS) is collaborating with UNDP to undertake a rapid livelihood assessment of populations most at risk in the context of the epidemic.

4. Engage in the global debate and communicate to citizens: Even under limited operational conditions, NSOs and other NSS institutions serve an important function in communicating trusted information to the public. It is thus essential to publish press releases, update the website and communicate information related to COVID-19 and its impact on data production and dissemination to the public. This might spur further opportunities of engagement.

5. Strengthen mechanisms for collaboration and coordination: NSOs and NSSs need act as the central data repository and advise policymakers on best response and recovery operations – as part of a crisis committee for example. To provide precise and actionable information, NSOs need to understand the government’s information requirements. Often existing coordination bodies could serve as a forum for exchange between institutions. Colombia (DANE) created an administrative data committee with members from the National Planning Department and the Ministry of ICT to understand the data needs of their policy makers.

This article was contributed by the Partnership in Statistics for Development in the 21st Century (PARIS21)