Next Article in Journal
Depressive Symptoms and Its Associated Factors in 13-Year-Old Urban Adolescents
Next Article in Special Issue
NO2 and Cancer Incidence in Saudi Arabia
Previous Article in Journal
Improving the Psychosocial Work Environment at Multi-Ethnic Workplaces: A Multi-Component Intervention Strategy in the Cleaning Industry
Previous Article in Special Issue
Mapping Disease at an Approximated Individual Level Using Aggregate Data: A Case Study of Mapping New Hampshire Birth Defects
Article Menu

Export Article

Open AccessArticle
Int. J. Environ. Res. Public Health 2013, 10(10), 5011-5025; doi:10.3390/ijerph10105011

Spatially Interpolated Disease Prevalence Estimation Using Collateral Indicators of Morbidity and Ecological Risk

School of Geography, Queen Mary University of London, London E1 4NS, UK
Received: 25 August 2013 / Revised: 1 October 2013 / Accepted: 8 October 2013 / Published: 14 October 2013
(This article belongs to the Special Issue Spatial Epidemiology)
View Full-Text   |   Download PDF [1539 KB, uploaded 19 June 2014]   |  

Abstract

This paper considers estimation of disease prevalence for small areas (neighbourhoods) when the available observations on prevalence are for an alternative partition of a region, such as service areas. Interpolation to neighbourhoods uses a kernel method extended to take account of two types of collateral information. The first is morbidity and service use data, such as hospital admissions, observed for neighbourhoods. Variations in morbidity and service use are expected to reflect prevalence. The second type of collateral information is ecological risk factors (e.g., pollution indices) that are expected to explain variability in prevalence in service areas, but are typically observed only for neighbourhoods. An application involves estimating neighbourhood asthma prevalence in a London health region involving 562 neighbourhoods and 189 service (primary care) areas.
Keywords: disease prevalence; spatial interpolation; neighbourhoods; asthma; kernel disease prevalence; spatial interpolation; neighbourhoods; asthma; kernel
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Congdon, P. Spatially Interpolated Disease Prevalence Estimation Using Collateral Indicators of Morbidity and Ecological Risk. Int. J. Environ. Res. Public Health 2013, 10, 5011-5025.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top