ArticleEpidemics2015
Seven challenges for model-driven data collection in experimental and observational studies.
Article in Epidemics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 39 citations in OpenAlex.
- Mechanistic models of Rift Valley fever virus transmission: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015).BMC infectious diseases · 2017Pooled it
- User-Centric Proximity Estimation Using Smartphone Radio Fingerprinting.Sensors (Basel, Switzerland) · 2022Article
- Relating Eulerian and Lagrangian spatial models for vector-host disease dynamics through a fundamental matrix.Journal of mathematical biology · 2022Article
- Challenges of using modelling evidence in the visceral leishmaniasis elimination programme in India.PLOS global public health · 2022Article
- Situation assessment and natural dynamics of COVID-19 pandemic in Nigeria, 31 May 2020.Scientific African · 2021Article
- INFEKTA-An agent-based model for transmission of infectious diseases: The COVID-19 case in Bogotá, Colombia.PloS one · 2021Article
- Patch dynamics modeling framework from pathogens' perspective: Unified and standardized approach for complicated epidemic systems.PloS one · 2020Article
- Impact of demographic disparities in social distancing and vaccination on influenza epidemics in urban and rural regions of the United States.BMC infectious diseases · 2019Article
- Modeling the Transmission ofFrontiers in veterinary science · 2019Article
- Improving preparedness for the next flu pandemic.Nature microbiology · 2018Article
- Key data for outbreak evaluation: building on the Ebola experience.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Detecting signals of chronic shedding to explain pathogen persistence: Leptospira interrogans in California sea lions.The Journal of animal ecology · 2017Article
- Comparing nonpharmaceutical interventions for containing emerging epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Temporally Varying Relative Risks for Infectious Diseases: Implications for Infectious Disease Control.Epidemiology (Cambridge, Mass.) · 2017Review
- Review
- Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases.Parasites & vectors · 2015Article
- Article
- Seven challenges for modelling indirect transmission: vector-borne diseases, macroparasites and neglected tropical diseases.Epidemics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 5 institutions in 2 countries.
Funding
Abstract
Infectious disease models are both concise statements of hypotheses and powerful techniques for creating tools from hypotheses and theories. As such, they have tremendous potential for guiding data collection in experimental and observational studies, leading to more efficient testing of hypotheses and more robust study designs. In numerous instances, infectious disease models have played a key role in informing data collection, including the Garki project studying malaria, the response to the 2009 pandemic of H1N1 influenza in the United Kingdom and studies of T-cell immunodynamics in mammals. However, such synergies remain the exception rather than the rule; and a close marriage of dynamic modeling and empirical data collection is far from the norm in infectious disease research. Overcoming the challenges to using models to inform data collection has the potential to accelerate innovation and to improve practice in how we deal with infectious disease threats.
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.