Evidence map›Paper›PMID 36873577›Full record

ArticleFire technology2023

Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking.

Steve M V Gwynne, Enrico Ronchi, Jonathan Wahlqvist, Arturo Cuesta, Javier Gonzalez Villa, Erica D Kuligowski, Amanda Kimball, Guillermo Rein, Max Kinateder, Noureddine Benichou and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Fire technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

0 citing papers in PubMed, 16 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 6 institutions in 6 countries.

Steve M V GwynneMovement Strategies Ltd, London, UK.
Enrico RonchiDepartment of Fire Safety Engineering, Lund University, Lund, Sweden.ORCID 0000-0002-2789-6359
Jonathan WahlqvistDepartment of Fire Safety Engineering, Lund University, Lund, Sweden.
Arturo CuestaGIDAI Group, University of Cantabria, Santander, Spain.
Javier Gonzalez VillaGIDAI Group, University of Cantabria, Santander, Spain.
Erica D KuligowskiRoyal Melbourne Institute of Technology, Melbourne, Australia.
Amanda KimballFire Protection Research Foundation, Quincy, USA.
Guillermo ReinImperial College London, London, UK.
Max KinatederNational Research Council of Canada, Ottawa, Canada.
Noureddine BenichouNational Research Council of Canada, Ottawa, Canada.
Hui XieMovement Strategies Ltd, London, UK.
Lund University · SENational Research Council Canada · CAUniversidad de Cantabria · ESImperial College London · GBNational Fire Protection Association · USThe Royal Melbourne Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland-urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts. Supplementary Information: The online version contains supplementary material available at 10.1007/s10694-023-01371-1.

Indexed as

DrillEgressEvacuationFire safetyWildfireWUI

Identifiers

PMID36873577
PMCPMC9977886
OpenAlexW4319596722

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.