Evidence map›Paper›PMID 41781545›Full record

ArticleScientific reports2026

The persistence of behavioral disparities post-pandemic: Insights from activity time series data.

Hongru Du, Shaochong Xu, Naomi Rankin, Hao Frank Yang, Lauren Gardner

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

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.

Hongru Du *Department of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA.
Shaochong Xu *Department of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA.
Naomi RankinDepartment of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA.
Hao Frank YangDepartment of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA.
Lauren GardnerDepartment of Civil and Systems Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA. l.gardner@jhu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic exposed and exacerbated deep-rooted socioeconomic disparities, however there is a gap in our understanding of the persistence and magnitudes of these disparities over time. In efforts to understand how diverse populations adapted their behavior throughout the COVID-19 pandemic, we leveraged large-scale mobile phone data at the census tract level between January 2020 – April 2022 to analyze temporal patterns in trips made to specific destination types. We employ time series clustering to the origin-destination trip data, which consistently identifies two distinct population groups that vary in both their respective behaviors and sociodemographic profiles. Furthermore, each group’s behavioral patterns in response to the local infection dynamics were observed to change over time, indicating a shift in relative risk-responsive behavior across groups. Specifically, in the early stages of COVID-19, the more socio-economically (SES) vulnerable population group was more active, likely capturing this group’s role in essential, lower-wage, in-person jobs and higher levels of social engagement, in contrast to the less vulnerable group, which was more likely to work from home and socially isolate. However, after restrictions lifted and vaccines became widely available, this trend reversed - the more SES vulnerable groups appear less active, especially in times of increased infection activity (e.g., new variant-driven waves), indicating less tolerance towards infection risk. The findings were consistent across all ten states included in the study. This study is the first to characterize and quantify evolving behavioral disparities through population-level activity patterns as captured through mobile phone data.

Indexed as

COVID-19Cell PhoneHumansPandemicsSARS-CoV-2Socioeconomic Disparities in HealthSocioeconomic FactorsActivity patternBehavioral adaptationsDisparitiesPandemic response

Identifiers

PMID41781545
PMCPMC13076639

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.