Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile
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Abstract
We study the spatio-temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data from 1.4 million users, 22% of the whole population in the area, characterizing the effects of non-pharmaceutical interventions (NPIs) on the epidemic dynamics. We integrate these data into a mechanistic epidemic model calibrated on surveillance data. As of August 1, 2020, we estimate a detection rate of 102 cases per 1000 infections (90% CI: [95–112 per 1000]). We show that the introduction of a full lockdown on May 15, 2020, while causing a modest additional decrease in mobility and contacts with respect to previous NPIs, was decisive in bringing the epidemic under control, highlighting the importance of a timely governmental response to COVID-19 outbreaks. We find that the impact of NPIs on individuals’ mobility correlates with the Human Development Index of comunas in the city. Indeed, more developed and wealthier areas became more isolated after government interventions and experienced a significantly lower burden of the pandemic. The heterogeneity of COVID-19 impact raises important issues in the implementation of NPIs and highlights the challenges that communities affected by systemic health and social inequalities face adapting their behaviors during an epidemic.
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The mobility result is consistent with analyses of New York City neighborhoods and with findings from other studies conducted in Santiago that used different socioeconomic and mobility metrics.
“Our result is consistent with analyses of New York City neighborhoods (11) and with findings from other studies conducted in Santiago that used different socioeconomic and mobility metrics (12–14).”
From Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile (2021) · cites this paper as [14]
The study's results are consistent with other studies in Santiago that used different socioeconomic and movement measurements.
“Although Facebook mobility data can be biased in this way, our results are consistent with other studies in Santiago that used different socioeconomic and movement measurements [see (12–14) and supplementary materials].”
From Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile (2021) · cites this paper as [14]
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Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile
Mena, G. E., Martinez, P. P., Mahmud, A. S., Marquet, P. A., Buckee, C. O., & Santillana, M. (2021) · Science · doi:10.1126/science.abg5298 · Cited by 431 · see citing works
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- Authors
- Gozzi, N., Tizzoni, M., Chinazzi, M., Ferres, L., Vespignani, A., & Perra, N.
- Affiliations
- University of Greenwich (GB)
- Institute for Scientific Interchange (IT)
- Northeastern University (US)
- Universidad del Desarrollo (CL)
- Corresponding author
- Perra, Nicola
- Venue
- Nature Communications
- Published
- 2021-04-23
- Volume
- 12
- Issue
- 1
- Pages
- 2429-2429
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC8065143
- OpenAlex
- W3158720366
- Cited by
- 142
- References
- 64
- Citations by year
- 2026: 10 · 2025: 18 · 2024: 24 · 2023: 24 · 2022: 39 · 2021: 24 · 2020: 2
- FWCI
- 10.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Greenwich Academic Literature Archive (University of Greenwich) (acceptedVersion)
- Iris (University of Trento) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
- Funders
- Bill and Melinda Gates Foundation (INV-006010)
- Cisco Systems
- Fondazione CRT
- Institute for Scientific Interchange
- Horizon 2020 Framework Programme (H2020-SC1)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Keywords
- COVID-19 pandemic, SARS-CoV-2, social inequality, non-pharmaceutical interventions, lockdown, mobility, Human Development Index, epidemic modeling, case detection rate, Santiago de Chile
- MeSH terms
- COVID-19, SARS-CoV-2, Algorithms, Chile, Communicable Disease Control, Humans, Models, Theoretical, Socioeconomic Factors, Time Factors, Incidence, Disease Transmission, Infectious, Pandemics
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