ArticlePloS one2013
An IDEA for short term outbreak projection: nearcasting using the basic reproduction number.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Rnaught: a web tool for estimating the basic reproduction number.BMC global and public health · 2025Article
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- An early warning approach to monitor COVID-19 activity with multiple digital traces in near real time.Science advances · 2021Article
- A simple model for fitting mild, severe, and known cases during an epidemic with an application to the current SARS-CoV-2 pandemic.Infectious Disease Modelling · 2021Article
- Characterizing network dynamics of online hate communities around the COVID-19 pandemic.Applied network science · 2021Article
- Estimation of parameters for a humidity-dependent compartmental model of the COVID-19 outbreak.PeerJ · 2021Article
- Modeling and tracking Covid-19 cases using Big Data analytics on HPCC system platformm.Journal of big data · 2021Article
- The COVID-19 social media infodemic.Scientific reports · 2020Article
- Estimating the Cumulative Incidence of COVID-19 in the United States Using Four Complementary Approaches.medRxiv : the preprint server for health sciences · 2020Article
- Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak.Journal of the Royal Society, Interface · 2020Article
- Integer Versus Fractional Order SEIR Deterministic and Stochastic Models of Measles.International journal of environmental research and public health · 2020Article
- Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China.Journal of clinical medicine · 2020Article
- Article
- A novel IDEA: The impact of serial interval on a modified-Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases.Infectious Disease Modelling · 2020Article
- The exacerbation of Ebola outbreaks by conflict in the Democratic Republic of the Congo.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- The Final Size of a Serious Epidemic.Bulletin of mathematical biology · 2019Article
- Estimation of Pneumonic Plague Transmission in Madagascar, August-November 2017.PLoS currents · 2018Article
- High reproduction number of Middle East respiratory syndrome coronavirus in nosocomial outbreaks: mathematical modelling in Saudi Arabia and South Korea.The Journal of hospital infection · 2018Article
- Anatomy of a Hotspot: Chain and Seroepidemiology of Ebola Virus Transmission, Sukudu, Sierra Leone, 2015-16.The Journal of infectious diseases · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCommunicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth. METHODOLOGY: The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R0, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts). PRINCIPAL
findingsCompared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R0 is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1(th) serial interval using data from the i(th) serial interval within an average of 20% of actual incidence. CONCLUSIONS AND SIGNIFICANCE: This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists.
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