2018
DOI: 10.1098/rsif.2018.0220
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Use of daily Internet search query data improves real-time projections of influenza epidemics

Abstract: Seasonal influenza causes millions of illnesses and tens of thousands of deaths per year in the USA alone. While the morbidity and mortality associated with influenza is substantial each year, the timing and magnitude of epidemics are highly variable which complicates efforts to anticipate demands on the healthcare system. Better methods to forecast influenza activity would help policymakers anticipate such stressors. The US Centers for Disease Control and Prevention (CDC) has recognized the importance… Show more

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Cited by 17 publications
(12 citation statements)
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References 35 publications
(79 reference statements)
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“…To deal with parameter uncertainty, a common approach is to perform sensitivity analyses in which model parameters are repeatedly sampled from a range of plausible values, and the resulting model predictions compared; both classical and Bayesian statistical approaches can be employed [158][159][160]. Methods of uncertainty quantification provide a framework in which uncertainties in model structure, epidemiological parameters and data can be considered together.…”
Section: (C) What Is the Role Of Children In Sars-cov-2 Transmission?mentioning
confidence: 99%
“…To deal with parameter uncertainty, a common approach is to perform sensitivity analyses in which model parameters are repeatedly sampled from a range of plausible values, and the resulting model predictions compared; both classical and Bayesian statistical approaches can be employed [158][159][160]. Methods of uncertainty quantification provide a framework in which uncertainties in model structure, epidemiological parameters and data can be considered together.…”
Section: (C) What Is the Role Of Children In Sars-cov-2 Transmission?mentioning
confidence: 99%
“…Generous, et al (2014) propose that Wikipedia has the ability to respond to the major challenges that currently face disease monitoring-openness, breadth, transferability, and forecasting [83]. There is evidence to support the feasibility of Wikipedia in disease monitoring in relation to seasonal changes in mood [84] and seasonal fluctuations in influenza [85][86][87]. However, while the work on the development of a plausible means to use Wikipedia's access log data to monitor and forecast disease continues [88], one study actually proposes Google data could be more useful [89] and another study struggles to prove the utility of Wikipedia for this purpose [90], although this is likely due to the fact that the researchers used a sample of 1,633 diseases rather than focus on a single disease as other studies have done.…”
Section: Utility In Researchmentioning
confidence: 99%
“…We then compared the performance of forecasts based on ITS data to forecasts based on other data sources with timelier availability. First, we compared against Wikipedia data [ 23 ] which has successfully been used for forecasting in several previous publications [ 5 , 24 ]. Fig 4 (second row) shows that ITS data improves the majority of forecasting target—region combinations.…”
Section: Resultsmentioning
confidence: 99%