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Time Series Analysis and Short-term Forecasting of Monkeypox Outbreak Trends in the 10 Major Affected Countries

Overview
Journal BMC Infect Dis
Publisher Biomed Central
Date 2024 Jan 3
PMID 38166831
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Abstract

Background: Considering the rapidly spreading monkeypox outbreak, WHO has declared a global health emergency. Still in the category of being endemic, the monkeypox disease shares numerous clinical characters with smallpox. This study focuses on determining the most effective combination of autoregressive integrated moving average model to encapsulate time dependent flow behaviour of the virus with short run prediction.

Methods: This study includes the data of confirmed reported cases and cumulative cases from eight most burdened countries across the globe, over the span of May 18, 2022, to December 31, 2022. The data was assembled from the website of Our World in Data and it involves countries such as United States, Brazil, Spain, France, Colombia, Mexico, Peru, United Kingdom, Germany and Canada. The job of modelling and short-term forecasting is facilitated by the employment of autoregressive integrated moving average. The legitimacy of the estimated models is argued by offering numerous model performance indices such as, root mean square error, mean absolute error and mean absolute prediction error.

Results: The best fit models were deduced for each country by using the data of confirmed reported cases of monkeypox infections. Based on diverse set of performance evaluation criteria, the best fit models were then employed to provide forecasting of next twenty days. Our results indicate that the USA is expected to be the hardest-hit country, with an average of 58 cases per day with 95% confidence interval of (00-400). The second most burdened country remained Brazil with expected average cases of 23 (00-130). The outlook is not much better for Spain and France, with average forecasts of 52 (00-241) and 24 (00-121), respectively.

Conclusion: This research provides profile of ten most severely hit countries by monkeypox transmission around the world and thus assists in epidemiological management. The prediction trends indicate that the confirmed cases in the USA may exceed than other contemporaries. Based on the findings of this study, it remains plausible to recommend that more robust health surveillance strategy is required to control the transmission flow of the virus especially in USA.

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Time series modelling and forecasting of Monkeypox outbreak trends Africa's in most affected countries.

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Human monkeypox disease prediction using novel modified restricted Boltzmann machine-based equilibrium optimizer.

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References
1.
Ceylan Z . Estimation of COVID-19 prevalence in Italy, Spain, and France. Sci Total Environ. 2020; 729:138817. PMC: 7175852. DOI: 10.1016/j.scitotenv.2020.138817. View

2.
Petersen E, Kantele A, Koopmans M, Asogun D, Yinka-Ogunleye A, Ihekweazu C . Human Monkeypox: Epidemiologic and Clinical Characteristics, Diagnosis, and Prevention. Infect Dis Clin North Am. 2019; 33(4):1027-1043. PMC: 9533922. DOI: 10.1016/j.idc.2019.03.001. View

3.
Tsan Y, Chen D, Liu P, Kristiani E, Nguyen K, Yang C . The Prediction of Influenza-like Illness and Respiratory Disease Using LSTM and ARIMA. Int J Environ Res Public Health. 2022; 19(3). PMC: 8835266. DOI: 10.3390/ijerph19031858. View

4.
Di Giulio D, Eckburg P . Human monkeypox: an emerging zoonosis. Lancet Infect Dis. 2004; 4(1):15-25. PMC: 9628772. DOI: 10.1016/s1473-3099(03)00856-9. View

5.
Bunge E, Hoet B, Chen L, Lienert F, Weidenthaler H, Baer L . The changing epidemiology of human monkeypox-A potential threat? A systematic review. PLoS Negl Trop Dis. 2022; 16(2):e0010141. PMC: 8870502. DOI: 10.1371/journal.pntd.0010141. View