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The Impact of Temperature, Humidity, and Precipitation on COVID-19 Cases: A Study Across National and Subnational Levels in Pakistan

Author

Listed:
  • Ishtiaq Ahmad

    (Department of Global Health Research, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan)

  • Mustajab Ali

    (Department of Civil Engineering, Mirpur University of Science and Technology (MUST), Mirpur 10250, Pakistan
    Department of Civil Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan)

  • Hadiya Asghar

    (Department of Health and Medical Sciences, The University of Azad Jammu and Kashmir, Muzaffarabad 13100, Pakistan)

  • Miyoko Okamoto

    (Department of Global Health Research, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan)

  • Yoshihisa Shirayama

    (Department of Global Health Research, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan)

  • Zoofa Talha

    (Health Services Academy, Islamabad 44000, Pakistan)

  • Aida Uzakova

    (Central Campus, International Higher School of Medicine, Bishkek 720054, Kyrgyzstan)

  • Hafiz Sultan Ahmad

    (Faculty of Science and Technology, University of Central Punjab, Lahore 54000, Pakistan)

  • Motoyuki Yuasa

    (Department of Global Health Research, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan)

Abstract

Meteorological variables play a significant role in the transmission of viruses such as influenza and the coronavirus pandemic (COVID-19). Previous studies have identified the relationship between changes in meteorological variables, humidity, rainfall, and temperature, and the infection rate of COVID-19 at the national level in Pakistan. However, the current study applied the logistic regression analysis technique to determine such a relationship on a more detailed scale, that is, subnational levels in addition to the national level in Pakistan, using a long-term analysis of two years of COVID-19 data. At the subnational level, the logistic regression analysis technique was applied, with infection rate as the predictive variable. The results showed an increase in the infection rate of COVID-19 with increasing humidity levels. In contrast, an increase in temperature has slowed the spread of COVID-19 cases at both the national and subnational levels. The minimum temperature was statistically significant ( p < 0.001) for provinces, KPK and Sindh. Also, two federal territories, AJK and Islamabad, showed statistically significant p -values. At the national level, both maximum temperature and humidity showed such values that is, p < 0.001. We believe that this is the first study conducted in Pakistan to explore the direct and indirect relationship between variables such as temperature (min and max), humidity, and rainfall as predictive parameters for COVID-19 infection rates at a detailed level. The pattern observed in this study can help us predict the future spread of COVID-19, subject to climatic parameters in Pakistan at both the national and subnational levels.

Suggested Citation

  • Ishtiaq Ahmad & Mustajab Ali & Hadiya Asghar & Miyoko Okamoto & Yoshihisa Shirayama & Zoofa Talha & Aida Uzakova & Hafiz Sultan Ahmad & Motoyuki Yuasa, 2025. "The Impact of Temperature, Humidity, and Precipitation on COVID-19 Cases: A Study Across National and Subnational Levels in Pakistan," J, MDPI, vol. 8(3), pages 1-11, June.
    • Handle: RePEc:gam:jjopen:v:8:y:2025:i:3:p:21-:d:1685668
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    References listed on IDEAS

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    1. Sachiko Kodera & Essam A. Rashed & Akimasa Hirata, 2020. "Correlation between COVID-19 Morbidity and Mortality Rates in Japan and Local Population Density, Temperature, and Absolute Humidity," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
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