Analyzing the Impact of Vaccination on COVID-19 Confirmed Cases and Deaths in Azerbaijan Using Machine Learning Algorithm
Автор: Makrufa Sh. Hajirahimova, Aybeniz S. Aliyeva
Журнал: International Journal of Education and Management Engineering @ijeme
Статья в выпуске: 1 vol.12, 2022 года.
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For almost two years, the world has been battling a global trouble- the COVID-19 pandemic. The disease, which has spread to about 225 countries around the world, has devastated the healthcare system of even the most developed countries. Governments have found the only way out is to impose a strict quarantine regime and state of emergency. Scientists immediately began testing the vaccine. Vaccination would still be the only savior of the planet's inhabitants.Because many of these pandemic infections have exactly been prevented thanks to vaccines in the past. Although the reduction in the number of infections after strict quarantine measures allowed the restrictions to be eased, the next wave was starting soon. This made it necessary the preparation of the vaccine as soon as possible. At the end of last year, the expected news came. Thus, in December 2020, the vaccination process has been launched in a number of countries. Azerbaijan is also one of the first countries to join the vaccination. The vaccination process, which began on January 18, 2021 continues, provided that 4 types of vaccines are available to the population. As a result of vaccination, the epidemiological situation in Azerbaijan is under control, as in many countries. In this article has been attempted to find a correlation between vaccination and COVID-19-confirmed cases and deaths. For this purpose, the k-means cluster-based machine learning method has been used in the Azerbaijan data collection obtained from the GitHub repository of the Center for Systems Science and Engineering at Johns Hopkins University. This research can benefit governments, stakeholders, and relevant institutions in the health care sector in monitor the vaccination process and more detally assess the epidemiological situation , and make important decisions to control and manage the spread of the disease.
Coronavirus, SARS-CoV-2, COVID-19 pandemic, machine learning, k-means clustering
Короткий адрес: https://sciup.org/15018273
IDR: 15018273 | DOI: 10.5815/ijeme.2022.01.01
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