Modelled seasonal influenza mortality shows marked differences in risk by age, sex, ethnicity and socioeconomic position in New Zealand

J Infect. 2017 Sep;75(3):225-233. doi: 10.1016/j.jinf.2017.05.017. Epub 2017 Jun 1.

Abstract

Objectives: Influenza is responsible for a large number of deaths which can only be estimated using modelling methods. Such methods have rarely been applied to describe the major socio-demographic characteristics of this disease burden.

Methods: We used quasi Poisson regression models with weekly counts of deaths and isolates of influenza A, B and respiratory syncytial virus for the period 1994 to 2008.

Results: The estimated average mortality rate was 13.5 per 100,000 people which was 1.8% of all deaths in New Zealand. Influenza mortality differed markedly by age, sex, ethnicity and socioeconomic position. Relatively vulnerable groups were males aged 65-79 years (Rate ratio (RR) = 1.9, 95% CI: 1.9, 1.9 compared with females), Māori (RR = 3.6, 95% CI: 3.6, 3.7 compared with European/Others aged 65-79 years), Pacific (RR = 2.4, 95% CI: 2.4, 2.4 compared with European/Others aged 65-79 years) and those living in the most deprived areas (RR = 1.8, 95% CI: 1.3, 2.4) for New Zealand Deprivation (NZDep) 9&10 (the most deprived) compared with NZDep 1&2 (the least deprived).

Conclusions: These results support targeting influenza vaccination and other interventions to the most vulnerable groups, in particular Māori and Pacific people and men aged 65-79 years and those living in the most deprived areas.

Keywords: Influenza; Mortality; Regression model; Virus.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Female
  • Humans
  • Influenza A virus / isolation & purification
  • Influenza B virus / isolation & purification
  • Influenza, Human / ethnology
  • Influenza, Human / mortality*
  • Influenza, Human / virology
  • Male
  • Middle Aged
  • Models, Statistical
  • New Zealand / epidemiology
  • Regression Analysis
  • Risk Factors
  • Seasons
  • Sex Factors
  • Socioeconomic Factors
  • White People