Evidence map›Paper›PMID 37237051›Full record

ArticleScientific reports2023

Intermunicipal travel networks of Mexico during the COVID-19 pandemic.

Oscar Fontanelli, Plinio Guzmán, Amilcar Meneses-Viveros, Alfredo Hernández-Alvarez, Marisol Flores-Garrido, Gabriela Olmedo-Alvarez, Maribel Hernández-Rosales, Guillermo de Anda-Jáuregui

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

8 authors.

Oscar FontanelliCINVESTAV-IPN, Irapuato, Mexico.
Plinio GuzmánAstronomer LTD, Cincinnati, USA.
Amilcar Meneses-ViverosDepartment of Computer Science, CINVESTAV-IPN, Mexico City, Mexico.
Alfredo Hernández-AlvarezCentro de Ciencias Genómicas, UNAM, Cuernavaca, Mexico.
Marisol Flores-GarridoENES Morelia, UNAM, Morelia, Mexico.
Gabriela Olmedo-AlvarezCINVESTAV-IPN, Irapuato, Mexico.
Maribel Hernández-RosalesCINVESTAV-IPN, Irapuato, Mexico. maribel.hr@cinvestav.mx.
Guillermo de Anda-JáureguiComputational Genomics Division, National Institute of Genomics Medicine, Mexico City, Mexico. gdeanda@inmegen.edu.mx.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human mobility networks are widely used for diverse studies in geography, sociology, and economics. In these networks, nodes usually represent places or regions and links refer to movement between them. They become essential when studying the spread of a virus, the planning of transit, or society's local and global structures. Therefore, the construction and analysis of human mobility networks are crucial for a vast number of real-life applications. This work presents a collection of networks that describe the human travel patterns between municipalities in Mexico in the 2020-2021 period. Using anonymized mobile location data, we constructed directed, weighted networks representing the volume of travels between municipalities. We analysed changes in global, local, and mesoscale network features. We observe that changes in these features are associated with factors such as COVID-19 restrictions and population size. In general, the implementation of restrictions at the start of the COVID-19 pandemic in early 2020, induced more intense changes in network features than later events, which had a less notable impact in network features. These networks will result very useful for researchers and decision-makers in the areas of transportation, infrastructure planning, epidemic control and network science at large.

Indexed as

COVID-19HumansMexicoPandemicsTransportationTravel

Identifiers

PMID37237051
PMCPMC10214328

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.