A hybrid forecasting technique for infection and death from the mpox virus.

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dc.contributor.authorIftikhar, Hasnain
dc.contributor.authorDaniyal, Muhammad
dc.contributor.authorQuresh, Moiz
dc.contributor.authorTawaiah, Kassim
dc.contributor.authorAnsah, Richard Kwame
dc.contributor.authorAfriyie, Jonathan Kwaku
dc.contributor.orcid0000-0001-6997-7969
dc.date.accessioned2023-12-11T09:39:50Z
dc.date.available2023-12-11T09:39:50Z
dc.date.issued2023
dc.descriptionThis is an article published in Digital Health, Volume 9: 1–17; DOI: 10.1177/20552076231204748
dc.description.abstractObjectives: The rising of new cases and death counts from the mpox virus (MPV) is alarming. In order to mitigate the impact of the MPV it is essential to have information of the virus’s future position using more precise time series and stochastic models. In this present study, a hybrid forecasting system has been developed for new cases and death counts for MPV infection using the world daily cumulative confirmed and death series. Methods: The original cumulative series was decomposed into new two subseries, such as a trend component and a stochastic series using the Hodrick–Prescott filter. To assess the efficacy of the proposed models, a comparative analysis with several widely recognized benchmark models, including auto-regressive (AR) model, auto-regressive moving average (ARMA) model, non-parametric auto-regressive (NPAR) model and artificial neural network (ANN), was performed. Results: The introduction of two novel hybrid models, HPF1 1 and HPF4 3, which demonstrated superior performance compared to all other models, as evidenced by their remarkable results in key performance indicators such as root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE), is a significant advancement in disease prediction. Conclusion: The new models developed can be implemented in forecasting other diseases in the future. To address the current situation effectively, governments and stakeholders must implement significant changes to ensure strict adherence to standard operating procedures (SOPs) by the public. Given the anticipated continuation of increasing trends in the coming days, these measures are essential for mitigating the impact of the outbreak.
dc.description.sponsorshipKNUST
dc.identifier.citationDigital Health, Volume 9: 1–17; DOI: 10.1177/20552076231204748
dc.identifier.uriDOI: 10.1177/20552076231204748
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/14729
dc.language.isoen
dc.publisherDigital Health
dc.titleA hybrid forecasting technique for infection and death from the mpox virus.
dc.typeArticle
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