Absolute Space or Relational Space, Which Governs Spatiotemporally Extended Effects in Disease Dispersion?

ABSTRACT Prevailing disease models typically focus on in‐situ effects, that is, the health risks of a location are affected by the transmission‐driving factors of the same location. The ex‐situ effects, in contrast, extend health risks from neighboring locations and earlier days to focal locations and current dates. These effects could be critical but have not received much attention. This study investigates the extended effects in absolute space and relational space. We examine whether the effects exist, whether they differ between the two spaces, and whether they vary with the order of neighbors and the number of prior dates in both spaces. Results show that extended effects are generally present. Mild effects are identified in absolute space, while greater effects are observed in relational space. The effects vary slightly with the neighbor order in absolute space, but considerably in relational space where the second‐order neighbors exert the most prominent effects. In both spaces, the effects diminish at the third‐order and last for up to three days. These findings advocate multiple spatializations that offer an in‐depth understanding of disease dispersion in specific and dynamic geographic phenomena at large.

Authors

Institutions

Publication Details

Journal
Geographical Analysis
Published
2025-04-29
DOI
https://doi.org/10.1111/gean.70007
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
1.37

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Absolute Space or Relational Space, Which Governs Spatiotemporally Extended Effects in Disease Dispersion?

Shiran Zhong, Ling Bian
1 citations
Geographical Analysis
COVID-19 epidemiological studies
1.37
article

Absolute Space or Relational Space, Which Governs Spatiotemporally Extended Effects in Disease Dispersion?

Shiran Zhong, Ling Bian
article en
1 citations

Abstract

ABSTRACT Prevailing disease models typically focus on in‐situ effects, that is, the health risks of a location are affected by the transmission‐driving factors of the same location. The ex‐situ effects, in contrast, extend health risks from neighboring locations and earlier days to focal locations and current dates. These effects could be critical but have not received much attention. This study investigates the extended effects in absolute space and relational space. We examine whether the effects exist, whether they differ between the two spaces, and whether they vary with the order of neighbors and the number of prior dates in both spaces. Results show that extended effects are generally present. Mild effects are identified in absolute space, while greater effects are observed in relational space. The effects vary slightly with the neighbor order in absolute space, but considerably in relational space where the second‐order neighbors exert the most prominent effects. In both spaces, the effects diminish at the third‐order and last for up to three days. These findings advocate multiple spatializations that offer an in‐depth understanding of disease dispersion in specific and dynamic geographic phenomena at large.

Geographical AnalysisVol. 57(4)
Western University (CA), University at Buffalo, State University of New York (US)
National Institutes of Health
Openalex Percentile: Top 22%
COVID-19 epidemiological studies
1.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Absolute Space or Relational Space, Which Governs Spatiotemporally Extended Effects in Disease Dispersion? — Shiran Zhong, Ling Bian · Geographical Analysis (2025) | TGRS Research Map | TGRS