ArticleFrontiers in public health2018
Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards.
Article in Frontiers in public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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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.
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Who cites it
27 citing papers in PubMed.
- Employing General-Purpose and Biomedical Large Language Models with Advanced Prompt Engineering for Pharmacoepidemiologic Study Design.Pharmaceutical research · 2026Article
- Integrating environmental and health data: insights and lessons from Australia's water monitoring systems.Journal of water and health · 2025Review
- Ensemble approaches for short-term dengue fever forecasts: A global evaluation study.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Advancing methods for program evaluation in substance use by strengthening the application of epidemiology, economic evaluation, and implementation science: Reflections on the opportunities for synergy.Evaluation and program planning · 2025Article
- Reusability challenges of livestock production data to improve animal health.Scientific data · 2025Article
- Unified framework for the ingestion of early epidemic data for downstream data analytics.Wellcome open research · 2025Article
- Enhancing oral health outcomes through public health policy reform.Frontiers in oral health · 2025Article
- Investigation of Influenza Cases and Risk Factors Associated with Fatality in Türkiye.Sisli Etfal Hastanesi tip bulteni · 2025Article
- EpiFusion: Joint inference of the effective reproduction number by integrating phylodynamic and epidemiological modelling with particle filtering.PLoS computational biology · 2024Article
- Epidemiology of Viral Infectious Diseases Reported in Saudi Arabia.Infectious diseases and therapy · 2024Article
- Beyond diagnostic connectivity: Leveraging digital health technology for the real-time collection and provision of high-quality actionable data on infectious diseases in Uganda.PLOS digital health · 2024Article
- Rehabilitation needs screening to identify potential beneficiaries: a scoping review.BMJ public health · 2024Article
- A global dataset of publicly available dengue case count data.Scientific data · 2024Article
- Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula.Transboundary and emerging diseases · 2024Article
- The urgent need for a policy on epidemiological data on cardiovascular diseases in Bangladesh.Health science reports · 2023Article
- COVID-19 data reporting systems in Africa reveal insights for future pandemics.Epidemiology and infection · 2022Article
- Current Production Capability of Drug-Resistant Pathogen Enables Its Rapid Label-Free Detection Applicable to Wastewater-Based Epidemiology.Microorganisms · 2022Article
- Article
- Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed.Human brain mapping · 2022Review
- The many definitions of multiplicity of infection.Frontiers in epidemiology · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accessible epidemiological data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status quo, however, renders acquiring and using such data difficult in practice. In many cases, a primary way of obtaining epidemiological data is through the internet, but the methods by which the data are presented to the public often differ drastically among institutions. As a result, there is a strong need for better data sharing practices. This paper identifies, in detail and with examples, the three key challenges one encounters when attempting to acquire and use epidemiological data: (1)
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