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Quantification of the effects of climatic conditions on French hospital admissions and deaths induced by SARS-CoV-2

Author

Listed:
  • Hippolyte d'Albis

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Dramane Coulibaly

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • Alix Roumagnac

    (Predict Services [Castelnau-le-Lez])

  • Eurico de Carvalho Filho

    (Predict Services [Castelnau-le-Lez])

  • Raphaël Bertrand

    (Predict Services [Castelnau-le-Lez])

Abstract
An estimation of the impact of climatic conditions—measured with an index that combines temperature and humidity, the IPTCC—on the hospitalizations and deaths attributed to SARS-CoV-2 is proposed. The present paper uses weekly data from 54 French administrative regions between March 23, 2020 and January 10, 2021. Firstly, a Granger causal analysis is developed and reveals that past values of the IPTCC contain information that allow for a better prediction of hospitalizations or deaths than that obtained without the IPTCC. Finally, a vector autoregressive model is estimated to evaluate the dynamic response of hospitalizations and deaths after an increase in the IPTCC. It is estimated that a 10-point increase in the IPTCC causes hospitalizations to rise by 2.9% (90% CI 0.7–5.0) one week after the increase, and by 4.1% (90% CI 2.1–6.4) and 4.4% (90% CI 2.5–6.3) in the two following weeks. Over ten weeks, the cumulative effect is estimated to reach 20.1%. Two weeks after the increase in the IPTCC, deaths are estimated to rise by 3.7% (90% CI 1.6–5.8). The cumulative effect from the second to the tenth weeks reaches 15.8%. The results are robust to the inclusion of air pollution indicators.

Suggested Citation

  • Hippolyte d'Albis & Dramane Coulibaly & Alix Roumagnac & Eurico de Carvalho Filho & Raphaël Bertrand, 2021. "Quantification of the effects of climatic conditions on French hospital admissions and deaths induced by SARS-CoV-2," Post-Print halshs-03672103, HAL.
    • Handle: RePEc:hal:journl:halshs-03672103
    DOI: 10.1038/s41598-021-01392-2
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03672103v1
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    References listed on IDEAS

    as
    1. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    2. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    3. Hippolyte d'Albis & Ekrame Boubtane & Dramane Coulibaly, 2018. "Macroeconomic evidence suggests that asylum seekers are not a “burden” for Western European countries," Working Papers halshs-01821515, HAL.
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