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. 2024 Jul;52(7):3000605241266233.
doi: 10.1177/03000605241266233.

COVID-19 trends across borders: Identifying correlations among countries

Jihan Muhaidat  1 , Aiman Albatayneh  2
Affiliations

COVID-19 trends across borders: Identifying correlations among countries

Jihan Muhaidat et al. J Int Med Res. 2024 Jul.

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.

Keywords: COVID-19; COVID-19 trends; correlated country; correlation; future cases; prediction.

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Conflict of interest statement

Declaration of conflicting interestThe Authors declare that there is no conflict of interest.

Figures

Figure 1.
Figure 1.
A screenshot showing a representative sample of the Pearson’s correlation coefficient results regarding the relationship of coronavirus disease 2019 case numbers between nations, calculated within Microsoft Excel.
Figure 2.
Figure 2.
Figures showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between: (a) Austria and Italy; and (b) Italy and India.
Figure 3.
Figure 3.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between Ukraine, Romania, North Macedonia, and Poland.
Figure 4.
Figure 4.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between Rwanda and Zambia.
Figure 5.
Figure 5.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between Russia and Belarus.
Figure 6.
Figure 6.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between different non-neighboring countries: (a) Jordan, Hungary, Bulgaria, and Poland; (b) Indonesia and Rwanda; and (c) Bahrain and the Maldives.
Figure 7.
Figure 7.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between three non-neighboring countries: Serbia with Occupied Palestinian Territory and Hungary.
Figure 8.
Figure 8.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between Bulgaria, Bosnia and Herzegovina, Jordan, North Macedonia, Poland, and Romania.
Figure 9.
Figure 9.
Figure showing smoothed data for new weekly coronavirus disease 2019 case peaks per 1 million of the population in Argentina and Colombia.
Figure 10.
Figure 10.
Figure showing differences in smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between different correlated countries: (a) Albania and Montenegro; (b) Morocco and Myanmar; and (c) Czechia and Lebanon.
Figure 11.
Figure 11.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between Azerbaijan and Serbia, Croatia and Georgia.
Figure 12.
Figure 12.
Figure showing smoothed data for surge in new weekly coronavirus disease 2019 cases per 1 million of the population in the UK that were not reflected in the USA.
Figure 13.
Figure 13.
Figure showing smoothed data for new weekly coronavirus disease 2019 cases per 1 million of the population between the USA and Lithuania.
See this image and copyright information in PMC

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