Evidence map›Paper›PMID 42453897›Full record

ArticleComputers, environment and urban systems2026

Spatio-Temporal Sensitivity of Healthcare Accessibility: Insights from a System Dynamics Model.

Patrick Danso, Liang Mao

Abstract read
In one paragraph

Article in Computers, environment and urban systems, 2026. 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

2 authors.

Patrick DansoDepartment of Geography, University of Florida.
Liang MaoDepartment of Geography, University of Florida.

Funding

Modeling and validating dynamic accessibility to healthcare with system science approachR03AI185905 · NIAID · UNIVERSITY OF FLORIDA · PI MAO, LIANG · 2025 to 2025
$137k
NIAID NIH HHS R03 AI185905
6 · The paper itself

Abstract

Recent research has increasingly focused on modeling the spatiotemporal dynamics of healthcare accessibility. However, a critical gap remains in understanding the relative influence of underlying factors, such as travel propensity, service availability, and population demand, and particularly how their influence varies across space and time. To address this gap, we proposed an analytic protocol that systematically evaluates these factors through four tiers: general, spatial, temporal, and spatio-temporal global sensitivity analysis (GSA). We demonstrated this framework's utility through a real-world case study in Florida, USA, integrated with a recently developed system dynamics model. The results revealed that disease rate had the greatest overall influence on variations in health accessibility. The spatial GSA showed clear heterogeneity in factor importance: travel propensity plays a more significant role in rural areas, whereas facility discharge rates have greater influence in urban settings. Furthermore, spatiotemporal GSA indicated that the influence of each factor varied substantially by both week and ZIP code. By quantifying factor influence across multiple scales, this framework offers evidence-based guidance for designing interventions tailored to different planning horizons and geographic contexts-such as short-term versus long-term, and local versus statewide strategies.

Indexed as

Health accessibilitysensitivity analysisspatio-temporal modelingsystem dynamics

Identifiers

PMID42453897
PMCPMC13367889

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.