ArticleF1000Research2020
Online dashboard and data analysis approach for assessing COVID-19 case and death data.
Article in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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
17 citing papers in PubMed.
- Effectiveness of COVID-19 Vaccines in Mahabad, Iran: A Cohort Study.Archives of Razi Institute · 2025Article
- Design, Application, and Actionability of US Public Health Data Dashboards: Scoping Review.Journal of medical Internet research · 2025Article
- Mutations in ace2 gene modulate cytokine levels and alter immune responses inFrontiers in immunology · 2025Article
- Wastewater-integrated pathogen surveillance dashboards enable real-time, transparent, and interpretable public health risk assessment and dissemination.PLOS global public health · 2025Article
- Developing public health surveillance dashboards: a scoping review on the design principles.BMC public health · 2024Article
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- Systematic Guidelines for Effective Utilization of COVID-19 Databases in Genomic, Epidemiologic, and Clinical Research.Viruses · 2023Review
- Characteristics and specifications of dashboards developed for the COVID-19 pandemic: a scoping review.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2023Review
- Article
- PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.International journal of environmental research and public health · 2022Article
- COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods.Bioengineering (Basel, Switzerland) · 2022Review
- Applications, features and key indicators for the development of Covid-19 dashboards: A systematic review study.Informatics in medicine unlocked · 2022Article
- Information Disclosure Contents of the COVID-19 Data Dashboard Websites for South Korea, China, and Japan: A Comparative Study.Healthcare (Basel, Switzerland) · 2021Article
- Development, Implementation, and User Evaluation of COVID-19 Dashboard in a Third-Level Hospital in Iran.Applied clinical informatics · 2021Article
- Using Social Network Analysis to Identify Spatiotemporal Spread Patterns of COVID-19 around the World: Online Dashboard Development.International journal of environmental research and public health · 2021Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 2019-2020 global pandemic has been caused by a disease called coronavirus disease 2019 (COVID-19). This disease has been caused by the Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2). By April 30 2020, the World Health Organization reported 3,096,626 cases and 217,896 deaths, which implies an exponential growth for infection and deaths worldwide. Currently, there are various computer-based approaches that present COVID-19 data through different types of charts, which is very useful to recognise its behavior and trends. Nevertheless, such approaches do not allow for observation of any projection regarding confirmed cases and deaths, which would be useful to understand the trends of COVID-19. In this work, we have designed and developed an online dashboard that presents actual information about COVID-19. Furthermore, based on this information, we have designed a mathematical model in order to make projections about the evolution of cases and deaths worldwide and by country.
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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.