# 5750
In epidemiology, a Line Listing is one the most basic methods used to collect, display, and analyze outbreak information.
It is essentially a table that displays individual cases in rows, and their characteristics in columns. If you’ve ever prepared a spreadsheet, you know the format.
A simple example might look something like this:
Photo Credit – CDC Excite Epidemiology in the Classroom
Today, in what may be the most comprehensive line listing of human H5N1 avian flu cases published to date, researchers from the Robert Koch Institute have released data describing nearly 300 H5N1 infections from around the globe.
Their research appears in today’s edition of the Eurosurveillance journal. With the release of this data the authors call for the creation and maintenance of a publicly accessible line list of anonymized human AI cases by an internationally renowned organization such as the World Health Organization.
A motion I would enthusiastically second.
The Eurosurveillance article is available at the link below.
L Fiebig , J Soyka, S Buda, U Buchholz, M Dehnert, W Haas Euro Surveill. 2011;16(32):pii=19941.
You can download this spreadsheet/database in MS-EXCEL (xls) format from the RKI website.
Avian influenza A(H5N1) in humans
New insights from a line list of WHO confirmed cases, September 2006 to August 2010
The Robert Koch Institute (RKI) had established a routine monitoring instrument condensing information on all human avian influenza cases worldwide reported from the following sources into a line list.
- WHO Global Alert and Response System
- ECDC: Avian influenza
- Global Electronic Reporting System for emerging infectious disease outbreaks (ProMED)
- Reuters Alertnet: Bird flu
A scientific article evaluating confirmed avian influenza cases in humans captured from September 2006 to August 2010 September 2006 to August 2010, as well as the established line list and the description of variables are available online:
The Eurosurveillance article is long, detailed, and would be impossible to summarize here and do it justice. It really deserves reading in its entirety.
But a few choice excerpts from the abstract (below) provide a glimpse of some of the data gleaned from this line list.
The 235 confirmed AI cases captured from September 2006 to August 2010 had a case fatality rate of 56% (132/235), ranging from 28% (27/98) in Egypt to 87% (71/82) in Indonesia.
In a multivariable analysis, odds of dying increased by 33% with each day that passed from symptom onset until hospitalisation (OR: 1.33, p=0.002).
In relation to children of 0–9 years, odds of fatal outcome were more than six times higher in 10–19 year-olds and 20–29 year-olds (OR: 6.06, 95% CI: 1.89–19.48, p=0.002 and OR: 6.16, 95% CI: 2.05–18.53, p=0.001, respectively), and nearly five times higher in patients of 30 years and older (OR: 4.71, 95% CI: 1.56–14.27, p=0.006) irrespective of the country, which had notified WHO of the cases.
The situation in Egypt was special in that case number and incidence in children were more than twice as high as in any other age group or country. With this study, we show that data from the public domain yield important epidemiological information on the global AI situation.
I expect that this release of data will be welcomed by many interested observers in Flublogia, and around the world.
