IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i23p9059-d456881.html
   My bibliography  Save this article

Predicting SARS-CoV-2 Weather-Induced Seasonal Virulence from Atmospheric Air Enthalpy

Author

Listed:
  • Angelo Spena

    (Department of Enterprise Engineering, Tor Vergata University of Rome, 00133 Rome, Italy)

  • Leonardo Palombi

    (Department of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy)

  • Massimo Corcione

    (Department of Astronautical, Electrical and Energy Engineering, Sapienza University of Rome, 00184 Rome, Italy)

  • Alessandro Quintino

    (Department of Astronautical, Electrical and Energy Engineering, Sapienza University of Rome, 00184 Rome, Italy)

  • Mariachiara Carestia

    (Department of Industrial Engineering, Tor Vergata University of Rome, 00133 Rome, Italy)

  • Vincenzo Andrea Spena

    (Department of Astronautical, Electrical and Energy Engineering, Sapienza University of Rome, 00184 Rome, Italy)

Abstract

Following the coronavirus disease 2019 (COVID-19) pandemic, several studies have examined the possibility of correlating the virulence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, to the climatic conditions of the involved sites; however, inconclusive results have been generally obtained. Although neither air temperature nor humidity can be independently correlated with virus viability, a strong relationship between SARS-CoV-2 virulence and the specific enthalpy of moist air appears to exist, as confirmed by extensive data analysis. Given this framework, the present study involves a detailed investigation based on the first 20–30 days of the epidemic before public health interventions in 30 selected Italian provinces with rather different climates, here assumed as being representative of what happened in the country from North to South, of the relationship between COVID-19 distributions and the climatic conditions recorded at each site before the pandemic outbreak. Accordingly, a correlating equation between the incidence rate at the early stage of the epidemic and the foregoing average specific enthalpy of atmospheric air was developed, and an enthalpy-based seasonal virulence risk scale was proposed to predict the potential danger of COVID-19 outbreak due to the persistence of weather conditions favorable to SARS-CoV-2 viability. As an early detection tool, an unambiguous risk chart expressed in terms of coupled temperatures and relative humidity (RH) values was provided, showing that safer conditions occur in the case of higher RHs at the highest temperatures, and of lower RHs at the lowest temperatures. Despite the complex determinism and dynamics of the pandemic and the related caveats, the restriction of the study to its early stage allowed the proposed risk scale to result in agreement with the available infectivity data highlighted in the literature for a number of cities around the world.

Suggested Citation

  • Angelo Spena & Leonardo Palombi & Massimo Corcione & Alessandro Quintino & Mariachiara Carestia & Vincenzo Andrea Spena, 2020. "Predicting SARS-CoV-2 Weather-Induced Seasonal Virulence from Atmospheric Air Enthalpy," IJERPH, MDPI, vol. 17(23), pages 1-14, December.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:23:p:9059-:d:456881
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/23/9059/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/23/9059/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2020. "The relationship between air pollution and COVID-19-related deaths: An application to three French cities," Applied Energy, Elsevier, vol. 279(C).
    2. Konstantinos Demertzis & Dimitrios Tsiotas & Lykourgos Magafas, 2020. "Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach Based on Complex Network Defined Splines," IJERPH, MDPI, vol. 17(13), pages 1-17, June.
    3. Angelo Spena & Leonardo Palombi & Massimo Corcione & Mariachiara Carestia & Vincenzo Andrea Spena, 2020. "On the Optimal Indoor Air Conditions for SARS-CoV-2 Inactivation. An Enthalpy-Based Approach," IJERPH, MDPI, vol. 17(17), pages 1-15, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Angelo Spena & Leonardo Palombi & Mariachiara Carestia & Vincenzo Andrea Spena & Francesco Biso, 2023. "SARS-CoV-2 Survival on Surfaces. Measurements Optimisation for an Enthalpy-Based Assessment of the Risk," IJERPH, MDPI, vol. 20(12), pages 1-16, June.
    2. Tareq Hussein & Jakob Löndahl & Sara Thuresson & Malin Alsved & Afnan Al-Hunaiti & Kalle Saksela & Hazem Aqel & Heikki Junninen & Alexander Mahura & Markku Kulmala, 2021. "Indoor Model Simulation for COVID-19 Transport and Exposure," IJERPH, MDPI, vol. 18(6), pages 1-16, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chaharborj, Sarkhosh Seddighi & Nabi, Khondoker Nazmoon & Feng, Koo Lee & Chaharborj, Shahriar Seddighi & Phang, Pei See, 2022. "Controlling COVID-19 transmission with isolation of influential nodes," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    2. Angelo Spena & Leonardo Palombi & Mariachiara Carestia & Vincenzo Andrea Spena & Francesco Biso, 2023. "SARS-CoV-2 Survival on Surfaces. Measurements Optimisation for an Enthalpy-Based Assessment of the Risk," IJERPH, MDPI, vol. 20(12), pages 1-16, June.
    3. Marta Baselga & Juan J. Alba & Alberto J. Schuhmacher, 2022. "The Control of Metabolic CO 2 in Public Transport as a Strategy to Reduce the Transmission of Respiratory Infectious Diseases," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    4. Tomasz Wołowiec & Iuliia Myroshnychenko & Ihor Vakulenko & Sylwester Bogacki & Anna Maria Wiśniewska & Svitlana Kolosok & Vitaliy Yunger, 2022. "International Impact of COVID-19 on Energy Economics and Environmental Pollution: A Scoping Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    5. Florentina Villanueva & Fátima Felgueiras & Alberto Notario & Beatriz Cabañas & Marta Fonseca Gabriel, 2024. "Indoor Environmental Quality and Effectiveness of Portable Air Cleaners in Reducing Levels of Airborne Particles during Schools’ Reopening in the COVID-19 Pandemic," Sustainability, MDPI, vol. 16(15), pages 1-19, July.
    6. Zaffar Ahmed Shaikh & Polina Datsyuk & Laura M. Baitenova & Larisa Belinskaja & Natalia Ivolgina & Gulmira Rysmakhanova & Tomonobu Senjyu, 2022. "Effect of the COVID-19 Pandemic on Renewable Energy Firm’s Profitability and Capitalization," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    7. Samany, Najmeh Neysani & Toomanian, Ara & Maher, Ali & Hanani, Khatereh & Zali, Ali Reza, 2021. "The most places at risk surrounding the COVID-19 treatment hospitals in an urban environment- case study: Tehran city," Land Use Policy, Elsevier, vol. 109(C).
    8. Mohamed Khalis & Aly Badara Toure & Imad El Badisy & Kenza Khomsi & Houda Najmi & Oumnia Bouaddi & Abdelghafour Marfak & Wael K. Al-Delaimy & Mohamed Berraho & Chakib Nejjari, 2022. "Relationship between Meteorological and Air Quality Parameters and COVID-19 in Casablanca Region, Morocco," IJERPH, MDPI, vol. 19(9), pages 1-13, April.
    9. Ai, Hongshan & Zhong, Tenglong & Zhou, Zhengqing, 2022. "The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China," Energy Economics, Elsevier, vol. 105(C).
    10. Soytas, Ugur & Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2022. "Economic and environmental implications of the nuclear power phase-out in Belgium: Insights from time-series models and a partial differential equations algorithm," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 241-256.
    11. Przemysław Śleszyński & Amir Reza Khavarian-Garmsir & Maciej Nowak & Paulina Legutko-Kobus & Mohammad Hajian Hossein Abadi & Noura Al Nasiri, 2023. "COVID-19 Spatial Policy: A Comparative Review of Urban Policies in the European Union and the Middle East," Sustainability, MDPI, vol. 15(3), pages 1-30, January.
    12. Magazzino, Cosimo & Alola, Andrew Adewale & Schneider, Nicolas, 2021. "The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: a quantile regression evidence," LSE Research Online Documents on Economics 117654, London School of Economics and Political Science, LSE Library.
    13. Lorenzo Gianquintieri & Maria Antonia Brovelli & Andrea Pagliosa & Rodolfo Bonora & Giuseppe Maria Sechi & Enrico Gianluca Caiani, 2021. "Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)," IJERPH, MDPI, vol. 18(22), pages 1-18, November.
    14. Shahzad, Umer & Schneider, Nicolas & Ben Jebli, Mehdi, 2021. "How coal and geothermal energies interact with industrial development and carbon emissions? An autoregressive distributed lags approach to the Philippines," Resources Policy, Elsevier, vol. 74(C).
    15. Becchetti, Leonardo & Beccari, Gabriele & Conzo, Gianluigi & Conzo, Pierluigi & De Santis, Davide & Salustri, Francesco, 2022. "Particulate matter and COVID-19 excess deaths: Decomposing long-term exposure and short-term effects," Ecological Economics, Elsevier, vol. 194(C).
    16. Himeur, Yassine & Ghanem, Khalida & Alsalemi, Abdullah & Bensaali, Faycal & Amira, Abbes, 2021. "Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives," Applied Energy, Elsevier, vol. 287(C).
    17. Raúl Jiménez-Cruz & José-Luis Velázquez-Rodríguez & Itzamá López-Yáñez & Yenny Villuendas-Rey & Cornelio Yáñez-Márquez, 2021. "Supervised Classification of Diseases Based on an Improved Associative Algorithm," Mathematics, MDPI, vol. 9(13), pages 1-25, June.
    18. Dunfrey Pires Aragão & Davi Henrique dos Santos & Adriano Mondini & Luiz Marcos Garcia Gonçalves, 2021. "National Holidays and Social Mobility Behaviors: Alternatives for Forecasting COVID-19 Deaths in Brazil," IJERPH, MDPI, vol. 18(21), pages 1-24, November.
    19. Jos Lelieveld & Frank Helleis & Stephan Borrmann & Yafang Cheng & Frank Drewnick & Gerald Haug & Thomas Klimach & Jean Sciare & Hang Su & Ulrich Pöschl, 2020. "Model Calculations of Aerosol Transmission and Infection Risk of COVID-19 in Indoor Environments," IJERPH, MDPI, vol. 17(21), pages 1-18, November.
    20. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2021. "A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions," Renewable Energy, Elsevier, vol. 167(C), pages 99-115.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:23:p:9059-:d:456881. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.