Evidence map›Paper›PMID 42049949›Full record

ArticleScientific reports2026

Understanding how mobility and spatial disparities shape COVID-19 transmission under rotational and localized lockdowns.

Mauricio Santos-Vega, Jaime Cascante Vega, Felipe Aramburo Jaramillo, Catalina González-Uribe, Juan Manuel Cordovez

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mauricio Santos-Vega *Departamento de Ciencias Biológicas, Universidad de los Andes, COL, Bogotá, D.C, USA. om.santos@uniandes.edu.co.
Jaime Cascante Vega *Center for Genomics & Systems Biology (CGSB), Department of Biology, New York University, New York, USA. jaime.cascante.vega@nyu.edu.
Felipe Aramburo JaramilloGrupo de Biología y Matemática Computacional (BIOMAC), Departamento de Ingeniería Biomédica, Universidad de los Andes, Bogotá, D.C, USA.
Catalina González-UribeCentro de los Objetivos de Desarrollo Sostenible para América Latina y el Caribe, Universidad de los Andes, Bogotá, D.C, USA.
Juan Manuel CordovezGrupo de Biología y Matemática Computacional (BIOMAC), Departamento de Ingeniería Biomédica, Universidad de los Andes, Bogotá, D.C, USA.

Funding

Swedish International Development Cooperation Agency (SIDA) 109582
6 · The paper itself

Abstract

Non-pharmaceutical interventions (NPIs) such as city-level curfews and local lockdowns were implemented to control SARS-CoV-2 transmission, yet their effectiveness at fine spatial scales remains uncertain. We evaluated a rotational lockdown policy in Bogotá, Colombia, applied at the locality level-an administrative aggregation of neighborhoods. Mobility patterns derived from mobile phone data were analyzed to quantify commuting changes, defined as relative variations in movement compared to a pre-intervention baseline (one month before restrictions). We distinguished between external mobility (between localities) and internal mobility (within localities). Using epidemiological surveillance data, we estimated the effective reproductive number ([Formula: see text]) and assessed its association with mobility reductions. A compartmental transmission model simulated counterfactual epidemic trajectories without NPIs, comparing predicted and observed infections, mortality, and [Formula: see text]. The intervention reduced inter-locality mobility by up to 40% but only minimally affected within-locality movement (median change < 5%), a descriptive result based on mobility data. Early lockdown cycles produced the largest declines in transmission (up to 27% reduction in cases), while subsequent rounds showed diminishing effects. Socioeconomic heterogeneity explained substantial spatial variability in transmission dynamics, revealing stronger associations between mobility and [Formula: see text] in localities with lower socioeconomic status. Our findings demonstrate that fine-scale NPIs can transiently reduce community transmission, but their impact depends on the spatial distribution of mobility and socioeconomic inequalities across the urban landscape.

Indexed as

COVID-19QuarantineColombiaHumansSARS-CoV-2Transportation

Identifiers

PMID42049949
PMCPMC13216546

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.