ReviewGaceta sanitaria2022
[Lessons learnt from COVID-19 surveillance. Urgent need for a new public health surveillance. SESPAS Report 2022].
Review in Gaceta sanitaria, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Global, Regional, and National Burden of Adolescent Polycystic Ovary Syndrome from 1990 to 2021, with Projections of Disease Burden to 2041: A Systematic Analysis Based on the Global Burden of Disease Study 2021.International journal of women's health · 2026Article
- Syphilis and Tuberculosis as Mimickers of Autoimmune Diseases: Diagnostic Overlap and Surveillance Implications in Mexico.Diseases (Basel, Switzerland) · 2025Review
- Underreporting of Cases in the COVID-19 Outbreak of Borriana (Spain) during Mass Gathering Events in March 2020: A Cross-Sectional Study.Epidemiologia (Basel, Switzerland) · 2024Article
- [Open data for monitoring COVID-19 in Spain: descriptive study].Enfermedades infecciosas y microbiologia clinica · 2022Article
- [Public Health and Health Administration in the COVID-19 pandemic. SESPAS Report 2022].Gaceta sanitaria · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this article we provide the most important epidemiological aspects in the first phases of the pandemic and some preliminary reflections from the Coordinating Centre for Health Alerts and Emergencies, the unit that has coordinated surveillance at the national level. COVID-19 has brought to light the weaknesses in the surveillance system and how difficult it is to manage a health crisis in the absence of a robust public health structure. The commitment of public health professionals during this epidemic has made up for the lack of resources in many occasions, and has evidenced the need to incorporate new professional profiles to surveillance teams. The need to rapidly adapt has achieved an improvement in existing systems and the development of new tools and new systems. These need to turn into structural changes that improve the quality of surveillance, decreasing territorial gaps and ensuring a better and coordinated response to future health crises. It is urgent to incorporate tools for process automation and to grant timely availability of data. To that end, public health and epidemiological surveillance must participate in the process of digital development within the National Health System. Profound changes are needed in public health surveillance, which has to be integrated in all healthcare levels. It is also important to strengthen the capacity for analysis by promoting alliances and joint actions. During this alert, the importance of coordination in public health in a decentralized country has been evident. At international level, it is necessary to review the tools to share data to coordinate an alert from the early stages.
Indexed as
Identifiers
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.