Page 59 - PowerPoint Presentation

1 International Congress of Artificial Intelligence
st
in Medical Sciences Posters

Analyzing Science and Innovation-Related Indicators and Their Rela-
tionship with COVID-19 Pandemic Control Using Statistical and Ma-

chine Learning Experiments

Ali Nadi Khorasgani1, Sharareh R. Niakan Kalhori2 , 3

1 Isfahan university of medical science, Isfahan, Iran
2 Peter L. Reichertz Institute for Medical Informatics, Technical University of Braunschweig and Hannover Medical School, Braunschweig, Germany
3 Associate Professor, Health Information Management and Medical Informatics Department, School of Allied Medical Sciences, Tehran University of
Medical Sciences, Tehran, Iran

Background and aims: The COVID-19 outbreak was one of many global illnesses and was
declared a pandemic by the World Health Organization. When the pandemic was announced,
scientific research and innovations were swiftly proposed, created, and carried out worldwide to
manage the disease. Nevertheless, it is unclear whether these scientific research and innovations
were effective in helping countries control the COVID-19 pandemic. The purpose of this article
is to address this question.

Method: This study aims to determine if the level of science and innovation in a country, meas-
ured by H-index and GII_Score, can predict the effectiveness of controlling the COVID-19 pan-
demic. Data were collected from 102 countries in 2020 and 2021, including COVID-19 death
and case numbers, test ratios, case fatality ratio (CFR), and test positivity ratio (TPR). H index
and GII_Score were obtained in 2020 using SCImago and WIPO. The data was analyzed using
Python 3.9.

Results: The study’s results showed a significant and decreasing correlation between GII_Score
and TPR (P-value < 0.001, r=-0.37), as well as GII_Score and CFR (P-value < 0.001, r=-0.40).
Additionally, there was a significant and decreasing correlation between H-index and TPR (P-val-
ue < 0.016, r=-0.23), as well as H-index and CFR (P-value < 0.005, r=-0.27). Moreover, the
K-means algorithm categorized countries into three clusters, and the study obtained the average
H-index, GII_Score, TPR, and CFR values for each cluster.
Conclusion: This study examined the relationship between innovation and scientific indicators of
countries and COVID-19 control. The study found that countries with higher GII_Score and H-in-
dex in 2020 had better COVID-19 control in 2021. The K-means algorithm clustered countries
based on innovation and scientific indicators, and countries in the group with the highest indica-
tors had lower CFR and TPR. The study suggests investing in innovation and scientific research
can help control pandemics, and governments should have a coherent plan to guide innovation
toward crisis resolution.

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