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时间序列分析及十大猴痘疫情国疫情趋势短期预测。

Time series analysis and short-term forecasting of monkeypox outbreak trends in the 10 major affected countries.

机构信息

Department of Anaesthesiology, Aga Khan University Hospital, Private Wing, Second Floor, Stadium Road, PO. Box 3500, Karachi, 74800, Pakistan.

Department of Applied Sciences, National Textile University, Faisalabad, 37610, Pakistan.

出版信息

BMC Infect Dis. 2024 Jan 2;24(1):16. doi: 10.1186/s12879-023-08879-5.

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.

摘要

背景

鉴于猴痘疫情迅速蔓延,世界卫生组织宣布全球进入卫生紧急状态。猴痘仍属于地方病,其临床表现与天花有许多共同特征。本研究旨在确定自回归综合移动平均模型的最佳组合,以封装病毒的时变流动行为,并进行短期预测。

方法

本研究包括 2022 年 5 月 18 日至 12 月 31 日期间全球八个受影响最严重国家的确诊报告病例和累计病例数据。数据来自 Our World in Data 网站,涉及美国、巴西、西班牙、法国、哥伦比亚、墨西哥、秘鲁、英国、德国和加拿大等国家。通过使用自回归综合移动平均模型来进行建模和短期预测。通过提供多个模型性能指标,如均方根误差、平均绝对误差和平均绝对预测误差,来论证估计模型的合理性。

结果

通过使用猴痘感染确诊报告病例数据,为每个国家推导出最佳拟合模型。根据不同的性能评估标准,然后使用最佳拟合模型来提供未来二十天的预测。我们的结果表明,美国预计将是受影响最严重的国家,平均每天有 58 例病例,95%置信区间为(00-400)。巴西仍然是受影响第二严重的国家,预计平均每天有 23 例病例(00-130)。西班牙和法国的情况也不容乐观,预计平均每天有 52 例病例(00-241)和 24 例病例(00-121)。

结论

本研究提供了全球猴痘传播最严重的十个国家的概况,从而有助于进行流行病学管理。预测趋势表明,美国的确诊病例可能会超过其他国家。根据本研究的结果,仍然有理由建议需要采取更有力的卫生监测策略来控制病毒的传播,特别是在美国。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df00/10762824/3eaf1ec2802b/12879_2023_8879_Fig1_HTML.jpg

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