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Identification of COVID-19 Waves: Considerations for Research and Policy

Author

Listed:
  • Andrés Ayala

    (Departamento de Matemática y Ciencia de la Computación, Facultad de Ciencias, Universidad de Santiago, Santiago 9170022, Chile)

  • Pablo Villalobos Dintrans

    (Programa Centro Salud Pública, Facultad de Ciencias Médicas, Universidad de Santiago, Santiago 9170022, Chile)

  • Felipe Elorrieta

    (Departamento de Matemática y Ciencia de la Computación, Facultad de Ciencias, Universidad de Santiago, Santiago 9170022, Chile)

  • Claudio Castillo

    (Programa Centro Salud Pública, Facultad de Ciencias Médicas, Universidad de Santiago, Santiago 9170022, Chile)

  • Claudio Vargas

    (Departamento de Matemática y Ciencia de la Computación, Facultad de Ciencias, Universidad de Santiago, Santiago 9170022, Chile)

  • Matilde Maddaleno

    (Programa Centro Salud Pública, Facultad de Ciencias Médicas, Universidad de Santiago, Santiago 9170022, Chile)

Abstract

The identification of COVID-19 waves is a matter of the utmost importance, both for research and decision making. This study uses COVID-19 information from the 52 municipalities of the Metropolitan Region, Chile, and presents a quantitative method—based on weekly accumulated incidence rates—to define COVID-19 waves. We explore three different criteria to define the duration of a wave, and performed a sensitivity analysis using multivariate linear models to show their commonalities and differences. The results show that, compared to a benchmark definition (a 100-day wave), the estimations using longer periods of study are worse in terms of the model’s overall fit (adjusted R 2 ). The article shows that defining a COVID-19 wave is not necessarily simple, and has consequences when performing data analysis. The results highlight the need to adopt well-defined and well-justified definitions for COVID-19 waves, since these methodological choices can have an impact in research and policy making.

Suggested Citation

  • Andrés Ayala & Pablo Villalobos Dintrans & Felipe Elorrieta & Claudio Castillo & Claudio Vargas & Matilde Maddaleno, 2021. "Identification of COVID-19 Waves: Considerations for Research and Policy," IJERPH, MDPI, vol. 18(21), pages 1-8, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11058-:d:661300
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    References listed on IDEAS

    as
    1. Pablo Villalobos Dintrans & Claire Chaumont, 2017. "Examining the relationship between human resources and mortality: the effects of methodological choices," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(3), pages 361-370, April.
    2. Thomas Hale & Noam Angrist & Andrew J Hale & Beatriz Kira & Saptarshi Majumdar & Anna Petherick & Toby Phillips & Devi Sridhar & Robin N Thompson & Samuel Webster & Yuxi Zhang, 2021. "Government responses and COVID-19 deaths: Global evidence across multiple pandemic waves," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-14, July.
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    Cited by:

    1. Warren S. Vaz, 2022. "COVID-19 Impact on the Energy Sector in the United States (2020)," Energies, MDPI, vol. 15(21), pages 1-23, October.
    2. Tomer Mevorach & Gil Zur & Noa Benaroya-Milshtein & Alan Apter & Silvana Fennig & Shira Barzilay, 2023. "A Following Wave Pattern of Suicide-Related Pediatric Emergency Room Admissions during the COVID-19 Pandemic," IJERPH, MDPI, vol. 20(2), pages 1, January.
    3. Teddy Lazebnik & Svetlana Bunimovich-Mendrazitsky & Shai Ashkenazi & Eugene Levner & Arriel Benis, 2022. "Early Detection and Control of the Next Epidemic Wave Using Health Communications: Development of an Artificial Intelligence-Based Tool and Its Validation on COVID-19 Data from the US," IJERPH, MDPI, vol. 19(23), pages 1-17, November.

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