ArticleSustainable cities and society2021
A city cluster risk-based approach for Sars-CoV-2 and isolation barriers based on anonymized mobile phone users' location data.
Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- An analytical tool to support public policies and isolation barriers against SARS-CoV-2 based on mobility patterns and socio-economic aspects.Applied soft computing · 2023Article
- A real-time web tool for monitoring and mitigating indoor airborne COVID-19 transmission risks at city scale.Sustainable cities and society · 2022Article
- Exploring the nexus between social vulnerability, built environment, and the prevalence of COVID-19: A case study of Chicago.Sustainable cities and society · 2021Article
- Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review.Sustainable cities and society · 2021Article
- What determines city's resilience against epidemic outbreak: evidence from China's COVID-19 experience.Sustainable cities and society · 2021Article
- ReCognizing SUspect and PredictiNg ThE SpRead of Contagion Based on Mobile Phone LoCation DaTa (COUNTERACT): A system of identifying COVID-19 infectious and hazardous sites, detecting disease outbreaks based on the internet of things, edge computing, and artificial intelligence.Sustainable cities and society · 2021Article
- Leveraging artificial intelligence to analyze the COVID-19 distribution pattern based on socio-economic determinants.Sustainable cities and society · 2021Article
- A novel social distancing analysis in urban public space: A new online spatio-temporal trajectory approach.Sustainable cities and society · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given the recent outbreak of Sars-CoV-2, several countries started to seek different strategies to control contamination and minimize fatalities, which are usually the primary objectives for all strategies. Secondary objectives are related to economic factors, therefore ensuring that society would be able is to keep its essential activities and avoid supply disruptions. This paper presents an application of anonymized mobile phone users' location data to estimate population flow amongst cities with an origin-destination matrix. The work includes a clustering analysis of cities, which may enable policymakers (and epidemiologists) to develop public policies giving the appropriate consideration for each set of cities within a Province or State. Risk measures are included to analyze the severity of the spread among the clusters, which can be ranked. Then, intelligence can be obtained from the analysis, and some clusters could be isolated to avoid contagion while keeping their economic activities. Therefore, this analysis is reproducible for other states of Brazil and other countries and can be adapted for districts within a city, especially considering the possibility of a second wave COVID-19 pandemic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.