Evidence map›Paper›PMID 36006256›Full record

ReviewTropical medicine and infectious disease2022

How Spatial Epidemiology Helps Understand Infectious Human Disease Transmission.

Chia-Hsien Lin, Tzai-Hung Wen

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Tropical medicine and infectious disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
6.9field-weighted citation impact, top 2% 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 47 citations in OpenAlex.

  1. Pooled it
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  3. Observational
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  12. Emerging Trends and Issues in Geo-Spatial Environmental Health: A Critical Perspective.International journal of environmental research and public health · 2025
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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 at 2 institutions in 1 country.

Chia-Hsien LinDepartment of Health Promotion and Health Education, National Taiwan Normal University, Taipei City 10610, Taiwan.ORCID 0000-0001-8325-648X
Tzai-Hung WenDepartment of Geography, National Taiwan University, Taipei City 10617, Taiwan.ORCID 0000-0002-9151-8336
National Taiwan Normal University · TWNational Taiwan University · TW

Funding

Ministry of Science and Technology MOST 108-2638-H-002-002-MY2, MOST 110-2410-H-002-131-MY3
6 · The paper itself

Abstract

Both directly and indirectly transmitted infectious diseases in humans are spatial-related. Spatial dimensions include: distances between susceptible humans and the environments shared by people, contaminated materials, and infectious animal species. Therefore, spatial concepts in managing and understanding emerging infectious diseases are crucial. Recently, due to the improvements in computing performance and statistical approaches, there are new possibilities regarding the visualization and analysis of disease spatial data. This review provides commonly used spatial or spatial-temporal approaches in managing infectious diseases. It covers four sections, namely: visualization, overall clustering, hot spot detection, and risk factor identification. The first three sections provide methods and epidemiological applications for both point data (i.e., individual data) and aggregate data (i.e., summaries of individual points). The last section focuses on the spatial regression methods adjusted for neighbour effects or spatial heterogeneity and their implementation. Understanding spatial-temporal variations in the spread of infectious diseases have three positive impacts on the management of diseases. These are: surveillance system improvements, the generation of hypotheses and approvals, and the establishment of prevention and control strategies. Notably, ethics and data quality have to be considered before applying spatial-temporal methods. Developing differential global positioning system methods and optimizing Bayesian estimations are future directions.

Indexed as

hot spotneighbourhood effectspatial epidemiologyspatial heterogeneityspatial patternspatial regressionspatial-temporal analysisvisualization

Identifiers

PMID36006256
PMCPMC9413673
OpenAlexW4289524650

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.