Evidence map›Paper›PMID 32905053›Full record

ArticleNonlinear dynamics2020

Human mobility and COVID-19 initial dynamics.

Stefano Maria Iacus, Carlos Santamaria, Francesco Sermi, Spyros Spyratos, Dario Tarchi, Michele Vespe

Open access · hybridAbstract read
In one paragraph

Article in Nonlinear dynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
3.6field-weighted citation impact, top 5% of its field
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

44 citing papers in PubMed, 120 citations in OpenAlex.

  1. Article
  2. Review
  3. Exploring Human Mobility: A Time-Informed Approach to Pattern Mining and Sequence Similarity.International journal of geographical information science : IJGIS · 2025
    Article
  4. The economic linkages of Covid-19 across sectors and regions in Europe.SERIEs : journal of the Spanish Economic Association · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Ecosystem degradation and the spread of Covid-19.Environmental monitoring and assessment · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. Article
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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

6 authors at 1 institution in 1 country.

Stefano Maria IacusJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.ORCID 0000-0002-4884-0047
Carlos SantamariaJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Francesco SermiJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Spyros SpyratosJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Dario TarchiJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Michele VespeJoint Research Centre, Via Enrico Fermi 2749, 21027 Ispra, VA Italy.
Joint Research Centre · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Countries in Europe took different mobility containment measures to curb the spread of COVID-19. The European Commission asked mobile network operators to share on a voluntarily basis anonymised and aggregate mobile data to improve the quality of modelling and forecasting for the pandemic at EU level. In fact, mobility data at EU scale can help understand the dynamics of the pandemic and possibly limit the impact of future waves. Still, since a reliable and consistent method to measure the evolution of contagion at international level is missing, a systematic analysis of the relationship between human mobility and virus spread has never been conducted. A notable exceptions are France and Italy, for which data on excess deaths, an indirect indicator which is generally considered to be less affected by national and regional assumptions, are available at department and municipality level, respectively. Using this information together with anonymised and aggregated mobile data, this study shows that mobility alone can explain up to 92% of the initial spread in these two EU countries, while it has a slow decay effect after lockdown measures, meaning that mobility restrictions seem to have effectively contribute to save lives. It also emerges that internal mobility is more important than mobility across provinces and that the typical lagged positive effect of reduced human mobility on reducing excess deaths is around 14-20 days. An analogous analysis relative to Spain, for which an IgG SARS-Cov-2 antibody screening study at province level is used instead of excess deaths statistics, confirms the findings. The same approach adopted in this study can be easily extended to other European countries, as soon as reliable data on the spreading of the virus at a suitable level of granularity will be available. Looking at past data, relative to the initial phase of the outbreak in EU Member States, this study shows in which extent the spreading of the virus and human mobility are connected. The findings will support policymakers in formulating the best data-driven approaches for coming out of confinement and mostly in building future scenarios in case of new outbreaks.

Indexed as

CoronavirusCOVID-19 dynamicsHuman mobilityMobility data

Identifiers

PMID32905053
PMCPMC7463099
OpenAlexW3082790551

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.