Abstract
Management and control of pandemic and endemic diseases is one of most important issue in order to deal with unpredicted health emergencies and fatalities all over the world. Covid-19, a new version of corona virus, originated from the Wuhan province of mainland China somewhere in December 2019 and has spread across the globe. Pandemic Covid-19 has affected the life of humans in almost every region of the world. Different strategies were planned by the regulatory bodies of different countries in order to slow down the transmission rate. The transmission rate was not uniform and varied from region to region. This chapter highlights the transmission dynamics of the virus and monitors the transmission among top five countries with highest number of infected persons as on May 31, 2020 and predicts the situation further. Linear regression techniques have been used for the purpose of analysis and prediction. The prediction model obtained is based on the trend of the data with highest R2value and minimum residual. The model helps the authorities to make necessary arrangements during the emergency.
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Kumar, V., Chawla, J., Kumar, R., Saxena, A. (2021). Modelling Covid-19: Transmission Dynamics Using Machine Learning Techniques. In: Bhatia, S., Dubey, A.K., Chhikara, R., Chaudhary, P., Kumar, A. (eds) Intelligent Healthcare. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-67051-1_6
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DOI: https://doi.org/10.1007/978-3-030-67051-1_6
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