2017
DOI: 10.1111/irv.12442
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Temporal cross‐correlation between influenza‐like illnesses and invasive pneumococcal disease in The Netherlands

Abstract: BackgroundWhile the burden of community‐acquired pneumonia and invasive pneumococcal disease (IPD) is still considerable, there is little insight in the factors contributing to disease. Previous research on the lagged relationship between respiratory viruses and pneumococcal disease incidence is inconclusive, and studies correcting for temporal autocorrelation are lacking.ObjectivesTo investigate the temporal relation between influenza‐like illnesses (ILI) and IPD, correcting for temporal autocorrelation.Metho… Show more

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Cited by 14 publications
(15 citation statements)
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“…Our study focused on the potential application of CUSUM for early detection of any change/aberration on the time series of the ILI cases. Published literature has reported adequacy of the CUSUM performance [36][37][38][39]. However, such similar studies did not report the appropriate timeliness of CUSUM.…”
Section: Discussionmentioning
confidence: 99%
“…Our study focused on the potential application of CUSUM for early detection of any change/aberration on the time series of the ILI cases. Published literature has reported adequacy of the CUSUM performance [36][37][38][39]. However, such similar studies did not report the appropriate timeliness of CUSUM.…”
Section: Discussionmentioning
confidence: 99%
“…When properly controlled for confounding variables, they have proved very useful tools to detect signals of associations. Other methods have been proposed through the deployment of seasonal autoregressive integrated moving average (SARIMA) models to analyse time series [ 91 ], Granger causality [ 92 , 93 ], or seasonality patterns [ 94 ]. However, these models do not formalize the transmission process or biological mechanism of interaction, so the interaction mechanism cannot be determined nor the strength of interaction quantified.…”
Section: Impact Of Interactions At the Population Levelmentioning
confidence: 99%
“…Published studies have demonstrated a healthy performance of the respective algorithm. 25 , 26 , 27 Another study showed that the performance of Bayesian outbreak detection algorithm in the detection of influenza outbreaks was better than the modified CUSUM algorithm 28 . However, owing to its simplicity and comprehensibility, the CUSUM algorithm can be very beneficial for early warnings of aberrations in the usual trend.…”
Section: Discussionmentioning
confidence: 99%