ArticlePloS one2013
A Simulation Optimization Approach to Epidemic Forecasting.
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 23 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
23 citing papers in PubMed.
- A multi-method study evaluating the inference of compartmental model parameters from a generative agent-based model.Infectious Disease Modelling · 2026Article
- From risk factors to predictive modelling: applying machine learning to childhood malaria surveillance in resource-limited settings.BMC infectious diseases · 2025Article
- Graph-Based Prediction of Spatio-Temporal Vaccine Hesitancy From Insurance Claims Data.IEEE access : practical innovations, open solutions · 2025Article
- Mathematical model to predict COVID-19 mortality rate.Infectious Disease Modelling · 2022Article
- Forecasting COVID-19 Confirmed Cases Using Empirical Data Analysis in Korea.Healthcare (Basel, Switzerland) · 2021Article
- Modeling and forecasting of COVID-19 using a hybrid dynamic model based on SEIRD with ARIMA corrections.Infectious Disease Modelling · 2021Article
- Forecasting COVID-19 pandemic in Alberta, Canada using modified ARIMA models.Computer methods and programs in biomedicine update · 2021Article
- Testing the Accuracy of the ARIMA Models in Forecasting the Spreading of COVID-19 and the Associated Mortality Rate.Medicina (Kaunas, Lithuania) · 2020Article
- A multicriteria approach for risk assessment of Covid-19 in urban district lockdown.Safety science · 2020Article
- Estimation of COVID-19 prevalence in Italy, Spain, and France.The Science of the total environment · 2020Article
- Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models.Microorganisms · 2020Article
- Mathematical modeling and the transmission dynamics in predicting the Covid-19 - What next in combating the pandemic.Infectious Disease Modelling · 2020Article
- COVID-19 prevalence estimation: Four most affected African countries.Infectious Disease Modelling · 2020Article
- On the predictability of infectious disease outbreaks.Nature communications · 2019Article
- Article
- Article
- Using Combined Diagnostic Test Results to Hindcast Trends of Infection from Cross-Sectional Data.PLoS computational biology · 2016Article
- EpiCaster: An Integrated Web Application For Situation Assessment and Forecasting of Global Epidemics.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2015Article
- Using prediction markets of market scoring rule to forecast infectious diseases: a case study in Taiwan.BMC public health · 2015Article
- Forecasting the 2013-2014 influenza season using Wikipedia.PLoS computational biology · 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.
Funding
Abstract
Reliable forecasts of influenza can aid in the control of both seasonal and pandemic outbreaks. We introduce a simulation optimization (SIMOP) approach for forecasting the influenza epidemic curve. This study represents the final step of a project aimed at using a combination of simulation, classification, statistical and optimization techniques to forecast the epidemic curve and infer underlying model parameters during an influenza outbreak. The SIMOP procedure combines an individual-based model and the Nelder-Mead simplex optimization method. The method is used to forecast epidemics simulated over synthetic social networks representing Montgomery County in Virginia, Miami, Seattle and surrounding metropolitan regions. The results are presented for the first four weeks. Depending on the synthetic network, the peak time could be predicted within a 95% CI as early as seven weeks before the actual peak. The peak infected and total infected were also accurately forecasted for Montgomery County in Virginia within the forecasting period. Forecasting of the epidemic curve for both seasonal and pandemic influenza outbreaks is a complex problem, however this is a preliminary step and the results suggest that more can be achieved in this area.
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.