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Effect of Geospatial Weather Features on COVID-19 Spread in Maharashtra State Using Machine Learning

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Recent Trends in Communication and Intelligent Systems

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

COVID-19 has become the most pestilential disease that has severely spread all over the world with several variants where the second wave of COVID-19 (2.0) has devastated India and worldwide most. This research is focused to assess the association among COVID-19 confirmed cases, weather features, mainly temperature (T), relative humidity (RH), and precipitation (P). The most affected populated state Maharashtra is considered as the research area for which we have collected newly confirmed COVID-19 cases and weather data that were considered for the first variant (COVID-19 1.0) and second variant (COVID-19 2.0) from March, 2020 to June, 2021. In this work, regression techniques have been applied to investigate daily new confirmed COVID-19 cases where the decision tree predicts the most accurate results. Outcomes demonstrate that temperature and relative humidity played an important role in this forecasting scheme as relative humidity is negative, and the temperature has positive correlation with COVID-19 affected cases. This application could be used for displaying and anticipating confirmed cases every day.

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Author information

Authors and Affiliations

  1. Department of Computer Applications, Manipal University Jaipur, Jaipur, Rajasthan, India

    Ranu Sewada

  2. Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Hemlata Goyal

Authors
  1. Ranu Sewada
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  2. Hemlata Goyal
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Corresponding author

Correspondence to Hemlata Goyal .

Editor information

Editors and Affiliations

  1. Arya College of Engineering & IT, Jaipur, Rajasthan, India

    Aditya Kumar Singh Pundir

  2. Department of Mathematics, National Institute of Technology, Hamirpur, Himachal Pradesh, India

    Neha Yadav

  3. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Sewada, R., Goyal, H. (2022). Effect of Geospatial Weather Features on COVID-19 Spread in Maharashtra State Using Machine Learning. In: Pundir, A.K.S., Yadav, N., Sharma, H., Das, S. (eds) Recent Trends in Communication and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1324-2_4

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