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Covid-19 and the Sociology of Risk and Uncertainty pp 217–244Cite as

Palgrave Macmillan

Living the Modern Dream: Risk Quantification and Modeling During the Covid-19 Pandemic in Chile

Part of the Critical Studies in Risk and Uncertainty book series (CRSTRU)

Abstract

The concept of risk became ubiquitous with the development of modern sciences and its new perspectives on human agency and the possibilities for knowledge. Today, any damage or losses due to extreme natural events are seen primarily as a product of human action and social dynamics. Congruently, the “Modern Dream” (Zinn, Understanding risk-taking. Palgrave Macmillan, 2020) includes the promise to rely on evidence-based decision-making, which usually means risk quantification and modeling. However, decision-making is generally messier and more complicated in practice. Moreover, quantification presents challenges for risk communication since models, particularly their assumptions and uncertainty, are not always easy to comprehend for the public and policy-makers. In this chapter, we explore these issues by examining the role of quantification and modeling during the ongoing COVID-19 pandemic in Chile. Using the COVID-19 epidemic as a case study, we analyze some of the challenges and limitations of the risk colonization of decision-making during disasters drawing on various data sources. These sources include 26 interviews with scientists who have been part of modeling initiatives, an analysis of the discussions at four COVID-19 modeling webinars, and a collection of various documentary sources (press, official documents, and scientific reports).

Keywords

  • Expert knowledge
  • Politics
  • Risk modeling
  • Science communication
  • Uncertainty

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Notes

  1. 1.

    For sociological analysis of this event see Farías, I. (2014). Misrecognizing Tsunamis: Ontological Politics and Cosmopolitical Challenges in Early Warning Systems. The Sociological Review, 62, 61–87, Kane, S., Medina, E. & Michler, D. 2014. Infrastructural Drift in Seismic Cities: Chile, Pacific Rim, 27 February, 2010. Rochester, NY: Social Science Research Network.

  2. 2.

    For example, the Imperial College COVID Response team: https://spiral.imperial.ac.uk:8443/handle/10044/1/78555

  3. 3.

    For example, the Covid Resource Center created by Johns Hopkins University has become broadly used by the press (https://coronavirus.jhu.edu/map.html). Local initiatives, such as ICOVID have also influenced media reports (https://www.icovidchile.cl/).

  4. 4.

    “Greater Santiago” does not fit perfectly into any administrative division. It contains 37 municipalities in four different provinces, and about 7 million people (~40% of the Chilean population).

  5. 5.

    Most experts interviewed for this work agree.

  6. 6.

    The Centers represented in this task force were all from Santiago: the Center of Mathematical Modeling and the Institute of Public Health, University of Chile; the Millennium Institute for Foundational Research on Data, Universidad Católica de Chile; the Institute of Complex Systems, University of Santiago; and the nonprofit organization “Ciencia y Vida.”

  7. 7.

    Brandt (2016) finds something similar in his work about the emerging field of data-science. In this chapter, we refer to them as experts, scientists, or (data)-scientists.

  8. 8.

    For example, https://www.icovidchile.cl/ (P. Universidad Católica de Chile, Universidad de Chile and Universidad de Concepción), http://covid-19vis.cmm.uchile.cl/geo (Center for Mathematical Modelling), and https://coronavirus.mat.uc.cl/ (Data-UC). Repositories: https://github.com/MinCiencia/Datos-COVID19 and https://www.cov2.cl/

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Acknowledgments

The authors wish to thank the 26 (data)-scientists that agreed to be a part of this project. We also thank Diego Cárcamo for his valuable help in developing this chapter. This work was partially funded by the Socioeconomic Transformations Observatories [ANID/PCI/MAX PLANCK INSTITUTE FOR THE STUDY OF SOCIETIES/MPG190012], the Research Center for Integrated Disaster Risk Management (CIGIDEN), [ANID/FONDAP/15110017], and the ANID Millennium Science Initiative Program [Grant NCN17_081 and NCS17_062]. The study sponsors had no role in the study design, collection, analysis, and interpretation of data; in the writing of the chapter; and in the decision to submit for publication.

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Authors and Affiliations

  1. School of Government, Pontificia Universidad Católica de Chile, Santiago, Chile

    Magdalena Gil

  2. Research Center for Integrated Disaster Risk Management (CIGIDEN) [ANID/FONDAP/15110017], Santiago, Chile

    Magdalena Gil & Eduardo A. Undurraga

  3. School of Government, Pontificia Universidad Católica de Chile, Santiago, Chile

    Eduardo A. Undurraga

  4. Millennium Initiative for Collaborative Research in Bacterial Resistance (MICROB-R) [NCN17_081], Santiago, Chile

    Eduardo A. Undurraga

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  1. Magdalena Gil
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Correspondence to Magdalena Gil .

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Editors and Affiliations

  1. Department of Sociology, University of Amsterdam, Amsterdam, Noord-Holland, The Netherlands

    Dr. Patrick R. Brown

  2. School of Social and Political Sciences, University of Melbourne, Parkville, VIC, Australia

    Jens O. Zinn

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Gil, M., Undurraga, E.A. (2022). Living the Modern Dream: Risk Quantification and Modeling During the Covid-19 Pandemic in Chile. In: Brown, P.R., Zinn, J.O. (eds) Covid-19 and the Sociology of Risk and Uncertainty . Critical Studies in Risk and Uncertainty. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-95167-2_9

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