OpenLink Software

About: OBJECTIVE: To explore socio-demographic data of the population as proxies for risk factors in disease transmission modeling at different geographic scales. METHODS: Patient records of confirmed H1N1 influenza were analyzed at three geographic aggregation levels together with population census statistics. RESULTS: The study confirmed that four population factors were related in different degrees to disease incidence, but the results varied according to spatial resolution. The degree of association actually decreased when data of a higher spatial resolution were used. CONCLUSIONS: We concluded that variables at suitable spatial resolution may be useful in improving the predictive powers of models for disease outbreaks.

 Permalink

an Entity references as follows:

Faceted Search & Find service v1.13.91

Alternative Linked Data Documents: Sponger | ODE     Raw Data in: CXML | CSV | RDF ( N-Triples N3/Turtle JSON XML ) | OData ( Atom JSON ) | Microdata ( JSON HTML) | JSON-LD    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] This material is Open Knowledge Creative Commons License Valid XHTML + RDFa
This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License.
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Copyright © 2009-2025 OpenLink Software