Evidence map›Paper›PMID 25142528›Full record

ArticleJournal of the Royal Society, Interface2014

Theory and data for simulating fine-scale human movement in an urban environment.

T Alex Perkins, Andres J Garcia, Valerie A Paz-Soldán, Steven T Stoddard, Robert C Reiner, Gonzalo Vazquez-Prokopec, Donal Bisanzio, Amy C Morrison, Eric S Halsey, Tadeusz J Kochel and 4 more

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
  2. Article
  3. Gaussian Process Emulation for Exploring Complex Infectious Disease Models.medRxiv : the preprint server for health sciences · 2025
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Extensively drug-resistant tuberculosis 'hotspots' and sociodemographic associations in Durban, South Africa.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2019
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Using Google Location History data to quantify fine-scale human mobility.International journal of health geographics · 2018
    Article
  20. 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

14 authors.

T Alex PerkinsFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Entomology and Nematology, University of California, Davis, CA, USA taperkins@nd.edu.
Andres J GarciaEmerging Pathogens Institute, University of Florida, Gainesville, FL, USA Department of Geography, University of Florida, Gainesville, FL, USA.
Valerie A Paz-SoldánDepartment of Global Health Systems and Development, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
Steven T StoddardDepartment of Entomology and Nematology, University of California, Davis, CA, USA.
Robert C ReinerFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Entomology and Nematology, University of California, Davis, CA, USA.
Gonzalo Vazquez-ProkopecDepartment of Environmental Sciences, Emory University, Atlanta, GA, USA.
Donal BisanzioDepartment of Environmental Sciences, Emory University, Atlanta, GA, USA.
Amy C MorrisonDepartment of Entomology and Nematology, University of California, Davis, CA, USA.
Eric S HalseyUnited States Naval Medical Research Unit No. 6, Lima, Peru.
Tadeusz J KochelUnited States Naval Medical Research Unit No. 6, Lima, Peru.
David L SmithFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Uriel KitronFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Environmental Sciences, Emory University, Atlanta, GA, USA.
Thomas W ScottFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Entomology and Nematology, University of California, Davis, CA, USA.
Andrew J TatemFogarty International Center, National Institutes of Health, Bethesda, MD, USA Department of Geography and Environment, University of Southampton, Southampton, UK Flowminder Foundation, Stockholm, Sweden.

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Joaniter Immaculate Nankabirwa · 2010 to 2026
$29.3M
Measuring Entomological Risk for DengueR01AI069341 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SCOTT, THOMAS WALLACE · 2006 to 2010
$2.3M
NIAID NIH HHS R01 AI069341-01NIAID NIH HHS U19AI089674
6 · The paper itself

Abstract

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it.

Indexed as

CitiesGeographic MappingModels, TheoreticalComputer SimulationGeographic Information SystemsHumansInterviews as TopicMotor ActivityPeruSpatial BehaviorTime Factorsactivity spaceagent-based modelco-location and contact networkshuman mobilitysimulationsynthetic population

Identifiers

PMID25142528
PMCPMC4233749

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.