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- W4367011691 abstract "COVID-19 is a rapidly spreading virus, which was encountered first in December 2019 in Wuhan, China. Being a severe virus that dominantly targets the respiratory tract of the human body has taken a toll over nearly 120 million people. The vaccination process around the world against COVID-19 started around January 2021, and the world has seen a steady decrease ever since. However, new variants keep coming into picture, deadlier than the previous making it difficult to overcome this deadly disease. Many factors that range from the availability of hospital beds in particular areas to the GDP Index have been taken into consideration while performing this experiment. Thus, this study aims to model and predict COVID-19 outbreak in Albania, Chile, Georgia, Malaysia, Panama, Sri Lanka, Turkey, Ukraine, and Uruguay. An analysis is performed to see the correlation between various socio-economic factors and the COVID-19 spread. Furthermore, prediction was performed using various algorithms to see which algorithm gives the best result. Data was accumulated from February 2020 to 16 August 2021. The data contained COVID-19 infection spread related statistics and data related to various socio-economic factors. Various machine learning algorithms like XGBoost, Light GBM, Lasso regression, and support vector machine were considered during the study. The central focus of our prediction model was around finding which algorithm gives a better prediction going forward into the pandemic as every country has started vaccination in one form or another. Countries that have extensively used the AstraZeneca vaccine were only considered in this study. Our analysis is focused on the direct correlation between the spread of COVID-19 and socio-economic factors like the availability of hospital beds, handwashing facilities, population density, etc." @default.
- W4367011691 created "2023-04-27" @default.
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- W4367011691 date "2023-01-01" @default.
- W4367011691 modified "2023-09-25" @default.
- W4367011691 title "Analysis of Spread of COVID-19 Based on Socio-economic Factors: A Comparison of Prediction Models" @default.
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- W4367011691 doi "https://doi.org/10.1007/978-981-19-5191-6_33" @default.
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