COVID-19 trends across borders: Identifying correlations among countries.

IF 1.4 4区医学 Q4 MEDICINE, RESEARCH & EXPERIMENTAL

Journal of International Medical Research Pub Date : 2024-07-01 DOI:10.1177/03000605241266233

Jihan Muhaidat, Aiman Albatayneh

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引用次数: 0

Abstract

Objectives: To enhance the accuracy of forecasting future coronavirus disease 2019 (COVID-19) cases and trends by identifying and analyzing correlations between the daily case counts of different countries reported between January 2020 and January 2023, to uncover significant links in COVID-19 patterns between nations, allowing for real-time, precise predictions of disease spread based on observed trends in correlated countries.

Methods: Daily COVID-19 cases for each country were tracked between January 2020 and January 2023 to identify correlations between nations. Current case data were obtained from reliable sources, such as Johns Hopkins University and the World Health Organization. Data were analyzed in Microsoft Excel using Pearson's correlation coefficient to assess the strength of connections.

Results: Strong correlations (r > 0.80) were revealed between the daily reported COVID-19 case counts of numerous countries across various continents. Specifically, 62 nations showed significant correlations with at least one correlated (connected) country per nation. These correlations indicate a similarity in COVID-19 trends over the past 3 or more years.

Conclusion: This study addresses the gap in country-specific correlations within COVID-19 forecasting methodologies. The proposed method offers essential real-time insights to aid effective government and organizational planning in response to the pandemic.

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COVID-19 跨国趋势：确定国家之间的相关性。

目标：通过识别和分析 2020 年 1 月至 2023 年 1 月期间报告的不同国家每日病例数之间的相关性，发现国家间 COVID-19 模式的重要联系，从而提高预测未来冠状病毒病 2019（COVID-19）病例和趋势的准确性，以便根据在相关国家观察到的趋势实时、准确地预测疾病的传播：方法：在 2020 年 1 月至 2023 年 1 月期间跟踪每个国家的每日 COVID-19 病例，以确定国家之间的相关性。目前的病例数据来自约翰霍普金斯大学和世界卫生组织等可靠来源。数据在 Microsoft Excel 中使用皮尔逊相关系数进行分析，以评估联系的强度：结果：各大洲许多国家每日报告的 COVID-19 病例数之间存在很强的相关性（r > 0.80）。具体来说，有 62 个国家与每个国家至少一个相关（连接）国家之间存在明显的相关性。这些相关性表明，在过去三年或更长时间里，COVID-19 的趋势具有相似性：本研究弥补了 COVID-19 预测方法中特定国家相关性方面的不足。所提出的方法提供了重要的实时见解，有助于政府和组织制定有效的计划来应对大流行病。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of International Medical Research 医学-药学

CiteScore

3.20

自引率

0.00%

发文量

555

审稿时长

1 months

期刊介绍： _Journal of International Medical Research_ is a leading international journal for rapid publication of original medical, pre-clinical and clinical research, reviews, preliminary and pilot studies on a page charge basis. As a service to authors, every article accepted by peer review will be given a full technical edit to make papers as accessible and readable to the international medical community as rapidly as possible. Once the technical edit queries have been answered to the satisfaction of the journal, the paper will be published and made available freely to everyone under a creative commons licence. Symposium proceedings, summaries of presentations or collections of medical, pre-clinical or clinical data on a specific topic are welcome for publication as supplements. Print ISSN: 0300-0605