Title |
Influenza associated excess mortality in Germany, 1985 – 2001
|
---|---|
Published in |
Emerging Themes in Epidemiology, June 2005
|
DOI | 10.1186/1742-7622-2-6 |
Pubmed ID | |
Authors |
Phillip Zucs, Udo Buchholz, Walter Haas, Helmut Uphoff |
Abstract |
Influenza-associated excess mortality is widely used to assess the severity of influenza epidemics. In Germany, however, it is not yet established as a routine component of influenza surveillance. We therefore applied a simple method based on the annual distribution of monthly relative mortality (relative mortality distribution method, RMDM) to a time-series of German monthly all-cause mortality data from 1985-2001 to estimate influenza-associated excess mortality. Results were compared to those obtained by cyclical regression. Both methods distinguished stronger from milder influenza seasons, but RMDM gave the better fit (R2 = 0.80). For the years after reunification, i.e. 1990/91 through 2000/01, RMDM yielded an average of 6900 (conservative estimate) to 13,600 influenza-associated excess deaths per season (crude estimate). The most severe epidemics occurred during subtype A/H3N2 seasons. While German all-cause mortality declined over the study period, the number of excess deaths displayed an upward trend, coinciding with an increase of the proportion of the elderly population. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 17% |
Finland | 1 | 17% |
Thailand | 1 | 17% |
Uruguay | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 83% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Estonia | 1 | 2% |
Germany | 1 | 2% |
Unknown | 39 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 7 | 17% |
Researcher | 7 | 17% |
Student > Doctoral Student | 3 | 7% |
Other | 3 | 7% |
Student > Postgraduate | 3 | 7% |
Other | 9 | 22% |
Unknown | 9 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 16 | 39% |
Immunology and Microbiology | 3 | 7% |
Agricultural and Biological Sciences | 3 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
Psychology | 2 | 5% |
Other | 6 | 15% |
Unknown | 9 | 22% |