Study type

Study topic

Disease /health condition
Other

Study topic, other

Disease/Epidemiology study

Study type

Non-interventional study

Scope of the study

Disease epidemiology
Effectiveness study (incl. comparative)

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Other

Non-interventional study design, other

Case-series
Study drug and medical condition

Medical condition to be studied

Avian influenza
Population studied

Short description of the study population

All patients who developed influenza-like symptoms and who are considered to be epidemiologically linked by time, place, and exposure to a probable or confirmed avian influenza or human pandemic influenza case (in poultry, wild birds, animals or humans). In addition, patients with documented seroconversion (positive serological test in a national, regional or international influenza laboratory whose test results confirm infection with avian influenza), who either remain asymptomatic or experience only mild illness will be eligible for inclusion. All cases identified in the literature, by treating physicians and other health care providers or by local government or international agencies will be pursued for inclusion in the registry.

Age groups

Term newborn infants (0 – 27 days)
Infants and toddlers (28 days – 23 months)
Children (2 to < 12 years)
Adolescents (12 to < 18 years)
Adults (18 to < 46 years)
Adults (46 to < 65 years)
Adults (65 to < 75 years)
Adults (75 to < 85 years)
Adults (85 years and over)

Special population of interest

Other

Special population of interest, other

Patients infected with avian influenza A (H5N1)

Estimated number of subjects

647
Study design details

Main study objective

To better understand the clinical course of infection with H5N1, and the effectiveness of curently treatments used in humans

Outcomes

survival, discharge from hospital with serious impairments

Data analysis plan

Analyses are primarily descriptive. Relative risks are used to compare survival in patients receiving antivirals and other treatments compared to those who did not receive those treatments, and to understand the impact of various effect modifiers and potential confounders. Multivariate modeling may be used to examine the relationship between survival and a variety of clinical and epidemiologic factors. Multiple imputation may be used for important missing data.
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