Humans as Animal Sentinels for Forecasting Asthma Events: Helping Health Services Become More Responsive

Ireneous N Soyiri and Daniel D Reidpath

PLOS ONE, 2012, vol. 7, issue 10, 1-6

Abstract: The concept of forecasting asthma using humans as animal sentinels is uncommon. This study explores the plausibility of predicting future asthma daily admissions using retrospective data in London (2005–2006). Negative binomial regressions were used in modeling; allowing the non-contiguous autoregressive components. Selected lags were based on partial autocorrelation function (PACF) plot with a maximum lag of 7 days. The model was contrasted with naïve historical and seasonal models. All models were cross validated. Mean daily asthma admission in 2005 was 27.9 and in 2006 it was 28.9. The lags 1, 2, 3, 6 and 7 were independently associated with daily asthma admissions based on their PACF plots. The lag model prediction of peak admissions were often slightly out of synchronization with the actual data, but the days of greater admissions were better matched than the days of lower admissions. A further investigation across various populations is necessary.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0047823 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 47823&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0047823

DOI: 10.1371/journal.pone.0047823

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().