Evidence map›Paper›PMID 36901366›Full record

ArticleInternational journal of environmental research and public health2023

Epidemic Diffusion Network of Spain: A Mobility Model to Characterize the Transmission Routes of Disease.

Javier Del-Águila-Mejía, David García-García, Ayelén Rojas-Benedicto, Nicolás Rosillo, María Guerrero-Vadillo, Marina Peñuelas, Rebeca Ramis, Diana Gómez-Barroso, Juan de Mata Donado-Campos

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In one paragraph

Article in International journal of environmental research and public health, 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

9 authors.

Javier Del-Águila-MejíaDepartamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid. C. Arzobispo Morcillo 4, 28029 Madrid, Spain.ORCID 0000-0001-5697-5980
David García-GarcíaCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.
Ayelén Rojas-BenedictoCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.ORCID 0000-0003-3197-0731
Nicolás RosilloServicio de Medicina Preventiva, Hospital Universitario 12 de Octubre, Avenida de Córdoba s/n, 28041 Madrid, Spain.ORCID 0000-0002-4046-8092
María Guerrero-VadilloCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.ORCID 0000-0003-0575-789X
Marina PeñuelasCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.ORCID 0000-0002-5909-7957
Rebeca RamisCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.ORCID 0000-0001-6154-9142
Diana Gómez-BarrosoCentro Nacional de Epidemiología, Instituto de Salud Carlos IIII, Calle de Melchor Fernández Almagro 5, 28029 Madrid, Spain.ORCID 0000-0001-7388-1767
Juan de Mata Donado-CamposDepartamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid. C. Arzobispo Morcillo 4, 28029 Madrid, Spain.

Funding

Instituto de Salud Carlos III COV20-00881
6 · The paper itself

Abstract

Human mobility drives the geographical diffusion of infectious diseases at different scales, but few studies focus on mobility itself. Using publicly available data from Spain, we define a Mobility Matrix that captures constant flows between provinces by using a distance-like measure of effective distance to build a network model with the 52 provinces and 135 relevant edges. Madrid, Valladolid and Araba/Álaba are the most relevant nodes in terms of degree and strength. The shortest routes (most likely path between two points) between all provinces are calculated. A total of 7 mobility communities were found with a modularity of 63%, and a relationship was established with a cumulative incidence of COVID-19 in 14 days (CI14) during the study period. In conclusion, mobility patterns in Spain are governed by a small number of high-flow connections that remain constant in time and seem unaffected by seasonality or restrictions. Most of the travels happen within communities that do not completely represent political borders, and a wave-like spreading pattern with occasional long-distance jumps (small-world properties) can be identified. This information can be incorporated into preparedness and response plans targeting locations that are at risk of contagion preventively, underscoring the importance of coordination between administrations when addressing health emergencies.

Indexed as

Communicable DiseasesCOVID-19EpidemicsHumansSpainTraveldisease modellingepidemiologyinfectious diseasesmobilitynetworksspatial epidemiologytransmission

Identifiers

PMID36901366
PMCPMC10001675

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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.