Evidence map›Paper›PMID 34762671›Full record

ArticlePloS one2021

A data fusion approach to the estimation of temporary populations: An application to Australia.

Elin Charles-Edwards, Jonathan Corcoran, Julia Loginova, Radoslaw Panczak, Gentry White, Alexander Whitehead

Abstract read
In one paragraph

Article in PloS one, 2021. 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
–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

0 citing papers in PubMed.

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

6 authors.

Elin Charles-EdwardsQueensland Centre for Population Research, the University of Queensland, St Lucia, QLD, Australia.
Jonathan CorcoranQueensland Centre for Population Research, the University of Queensland, St Lucia, QLD, Australia.
Julia LoginovaQueensland Centre for Population Research, the University of Queensland, St Lucia, QLD, Australia.ORCID 0000-0002-1304-5967
Radoslaw PanczakQueensland Centre for Population Research, the University of Queensland, St Lucia, QLD, Australia.ORCID 0000-0001-5141-683X
Gentry WhiteCentre for Data Science, Queensland University of Technology, Brisbane, QLD, Australia.
Alexander WhiteheadQueensland Centre for Population Research, the University of Queensland, St Lucia, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics. This paper develops a flexible modelling framework to generate APP estimates from an integrated suite of conventional and novel data sources. The resultant APP estimates reveal the considerable seasonality in small area populations across Australia's regions alongside the contribution of domestic and international visitors as well as absent residents to the observed monthly variations. The modelling framework developed in the paper is conceived in a manner such that it can be adapted and re-deployed both for use with alternative data sources as well as other situational contexts for the estimation of temporary populations.

Indexed as

Population DensityAustraliaHumansModels, StatisticalSpatio-Temporal AnalysisTime Factors

Identifiers

PMID34762671
PMCPMC8584718

What OpenQuestion holds

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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.