Australian influenza national surveillance data (2009 to 2014) : variations by sex, age group, and influenza type

Objectives: The World Health Organization evaluation on the first wave of 2009 H1N1 pandemics revealed that the outcome of infection was generally worse for females, but sex disparity in influenza infection has not been explored extensively. This study investigates sex disparity in laboratory-confirmed influenza notifications by age and influenza type. Methods: The Australian National Notifiable Diseases Surveillance System Influenza Public Dataset (http://www9.health.gov. au/cda/source/pub_influ.cfm) was accessed on 13 March 2016. The variables in the dataset included: notification date, influenza type, age, sex, and Indigenous status. The dataset was analysed using IBM SPSS v22. Results: A total of 236,241 cases of influenza were collected over six years, with Influenza A the most common sub-type. Considering all influenza types, males had a marginally higher number of notifications at ages 0 to 19 years. However, the number of female notifications overtook from ages 20 to 39 years, and the sex disparity became less pronounced from age 45 years onwards. Similar trends were observed regardless of influenza sub-type. There were 180,475 cases (76.4%) without identification of Indigeneity, which rendered the variable inappropriate for analysis. Conclusions: This study on a large dataset revealed that the number of notifications of influenza infection was associated with sex and age. Notifications are influenced by utilisation of healthcare, and healthcare use is generally higher in females. We confirmed known, age-dependent sex disparity in influenza patterns independent of influenza subtype. Females aged 20 to 39 years had higher age-adjusted notification rates per 100,000 population, which is presumably related to being of child-bearing age, i.e. pregnancy-related reduced immunity against influenza. It is recommended that the surveillance authority should request information on pregnancy status. Other variables such as Indigenous status may shed light on susceptibility to influenza infection. These data are not universally recorded across Australia but are important to inform targeted preventive strategies.