ReviewThe Lancet. Infectious diseases2023
Lessons from COVID-19 for rescalable data collection.
Review in The Lancet. Infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United States: Descriptive Study.JMIR public health and surveillance · 2026Article
- Enhancing epidemic forecast usability for policymakers: A global mixed-methods study.PLOS global public health · 2026Article
- Nowcasting epidemic trends using hospital- and community-based virologic test data.Nature communications · 2025Article
- A Cloud-Based Platform for Harmonized COVID-19 Data: Design and Implementation of the Rapid Acceleration of Diagnostics (RADx) Data Hub.JMIR public health and surveillance · 2025Article
- Embedding public health intelligence into the global public health architecture.BMJ public health · 2024Article
- Policy impact of the Imperial College COVID-19 Response Team: global perspective and United Kingdom case study.Health research policy and systems · 2024Article
- Theoretical Epidemiology Needs Urgent Attention in China.China CDC weekly · 2024Article
- Phylogeny and molecular evolution of the first local monkeypox virus cluster in Guangdong Province, China.Nature communications · 2023Article
- Lessons identified for a future pandemic.The Journal of antimicrobial chemotherapy · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
15 authors.
Funding
Abstract
Novel data and analyses have had an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances new systems were developed to meet the challenges posed by the magnitude of the pandemic. We describe the routine and novel data that were used to address urgent public health questions during the pandemic, underscore the challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision making during a public health crisis. As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, SARS-CoV-2 resurgence remains a threat to global health security; therefore, a minimal cost-effective system needs to remain active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.