The Prevalence and Severity Comparison of COVID-19 Disease in SAARC Affiliated Countries: Pattern Analysis during the First Wave in 2020

Autores

DOI:

https://doi.org/10.12662/2317-3076jhbs.v9i1.3679.p1-7.2021

Palavras-chave:

SAARC, COVID-19, Pandemic, Fatality, Infection

Resumo

Objectives: This study aimed to explore the prevalence and severity of COVID-19 disease in SAARC affiliated countries and show the comparison by analyzing the patterns of infections, recoveries, and deaths among the countries. Methods: The data related to COVID-19 of SAARC affiliated countries were collected from Worldometer in which the dataset consists of daily confirmed, recovery, and death cases. To compare the prevalence and severity of COVID-19 among these countries, we consider three parameters such as case fatality rate (CFR), recovery-to-death ratio (RDR), and percent active case (PAC). Results: The highest daily CFR among the SAARC affiliated countries was in Bangladesh followed by Afghanistan, India, Sri Lanka, Pakistan, Nepal and the Maldives according to the maximum CFR of the countries until 24 October 2020. The highest RDR among the SAARC affiliated countries was in Nepal followed by the Maldives, Sri Lanka, India, Bangladesh, Pakistan, Afghanistan until 24 October. The most prevalent country according to infection per million people by COVID-19 among the SAARC affiliated countries is the Maldives followed by India, Nepal, Bangladesh, Pakistan, Afghanistan, Bhutan, and Sri Lanka as of October 24. The most death prevalent country per million people is India followed by the Maldives, Afghanistan, Bangladesh, Pakistan, Nepal, Sri Lanka, and no people died in Bhutan until October 24, 2020. Conclusion: This study shows that the severity of COVID-19 is high in the Maldives in terms of infections and India in terms of deaths per million in SAARC, so India is at high risk among the countries.

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Biografia do Autor

Abdul Muyeed, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh-2224, Bangladesh.

Department of Computer Science and Engineering

Tushar Kanti Saha, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh-2224, Bangladesh.

Department of Computer Science and Engineering

Rubya Shaharin, Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh

Department: Statistics Area: Public Health and Data Mining

Uzzal Kumar Prodhan, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh-2224, Bangladesh.

Department of Computer Science and Engineering

Publicado

2021-06-07