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. 2021 May 13:9:602353.
doi: 10.3389/fpubh.2021.602353. eCollection 2021.

Data-Driven and Machine-Learning Methods to Project Coronavirus Disease 2019 Pandemic Trend in Eastern Mediterranean

Wenbo Huang  1   2 , Shuang Ao  1 , Dan Han  3 , Yuming Liu  4 , Shuang Liu  1   4 , Yaojiang Huang  1   5
Affiliations

Data-Driven and Machine-Learning Methods to Project Coronavirus Disease 2019 Pandemic Trend in Eastern Mediterranean

Wenbo Huang et al. Front Public Health. .

Abstract

Background: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health crisis worldwide, and the Eastern Mediterranean is one of the most affected areas. Materials and Methods: We use a data-driven approach to assess the characteristics, situation, prevalence, and current intervention actions of the COVID-19 pandemic. We establish a spatial model of the spread of the COVID-19 pandemic to project the trend and time distribution of the total confirmed cases and growth rate of daily confirmed cases based on the current intervention actions. Results: The results show that the number of daily confirmed cases, number of active cases, or growth rate of daily confirmed cases of COVID-19 are exhibiting a significant downward trend in Qatar, Egypt, Pakistan, and Saudi Arabia under the current interventions, although the total number of confirmed cases and deaths is still increasing. However, it is predicted that the number of total confirmed cases and active cases in Iran and Iraq may continue to increase. Conclusion: The COVID-19 pandemic in Qatar, Egypt, Pakistan, and Saudi Arabia will be largely contained if interventions are maintained or tightened. The future is not optimistic, and the intervention response must be further strengthened in Iran and Iraq. The aim of this study is to contribute to the prevention and control of the COVID-19 pandemic.

Keywords: COVID-19; assessment; data-driven; machine learning; projection.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Total confirmed cases, deaths, active cases, and total confirmed cases per million people: (A) number of total confirmed coronavirus disease 2019 (COVID-19) cases, (B) number of deaths in six Eastern Mediterranean countries, (C) number of active cases in six Eastern Mediterranean countries, and (D) total confirmed cases per million people.
Figure 2
Figure 2
Evaluated daily changes in the number of confirmed cases: (A–F) subgraph showing the daily changes Iran, Saudi Arabia, Pakistan, Iraq, Qatar, and Egypt, respectively—the daily changes in the number of confirmed cases in linear scale (bottom thin line, left y-axis) and log scale (upper thicker line, right y-axis)—and (G) heatmap drawn to compare daily changes in confirmed cases (horizontal axis) in the different countries (vertical axis).
Figure 3
Figure 3
Government intervention index and its relationship to confirmed cases: (A) government or societal intervention index, (B) bar plot of intervention score since January 2020, and (C) relationship between government response index and the number of confirmed cases.
Figure 4
Figure 4
Forecast of overall trends in the coronavirus disease 2019 (COVID-19) pandemic: (A–F) trends of the number of total COVID-19 confirmed cases forecast by machine-learning methods in Iran, Saudi Arabia, Pakistan, Iraq, Qatar, and Egypt, respectively.
Figure 5
Figure 5
Forecast of trends in daily confirmed cases of the coronavirus disease 2019 (COVID-19) pandemic: (A–F) trends of the daily number of confirmed cases forecast by machine learning in Iran, Saudi Arabia, Pakistan, Iraq, Qatar, and Egypt, respectively—the top panel forecasts the daily number of confirmed cases obtained by machine learning, the bottom panel forecasts the trend of the number of daily confirmed cases, the ds-coordinates in the figure represent the date, and the y-coordinates correspond to the predicted values.
See this image and copyright information in PMC

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