Nicola Turner

The effectiveness of seasonal trivalent inactivated influenza vaccine in preventing laboratory confirmed influenza hospitalisations in Auckland, New Zealand in 2012.

BACKGROUND Few studies report the effectiveness of trivalent inactivated influenza vaccine (TIV) in preventing hospitalisation for influenza-confirmed respiratory infections. Using a prospective surveillance platform, this study reports the first such estimate from a well-defined ethnically diverse population in New Zealand (NZ). METHODS A case test-negative design was used to estimate propensity adjusted vaccine effectiveness. Patients with a severe acute respiratory infection (SARI), defined as a patient of any age requiring hospitalisation with a history of a fever or a measured temperature ≥38°C and cough and onset within the past 7 days, admitted to public hospitals in South and Central Auckland were eligible for inclusion in the study. Cases were SARI patients who tested positive for influenza, while non-cases (controls) were SARI patients who tested negative. Results were adjusted for the propensity to be vaccinated and the timing of the influenza season. RESULTS The propensity and season adjusted vaccine effectiveness (VE) was estimated as 39% (95% CI 16;56). The VE point estimate against influenza A (H1N1) was lower than for influenza B or influenza A (H3N2) but confidence intervals were wide and overlapping. Estimated VE was 59% (95% CI 26;77) in patients aged 45-64 years but only 8% (-78;53) in those aged 65 years and above. CONCLUSION Prospective surveillance for SARI has been successfully established in NZ. This study for the first year, the 2012 influenza season, has shown low to moderate protection by TIV against influenza positive hospitalisation.

Effectiveness of seasonal trivalent inactivated influenza vaccine in preventing influenza hospitalisations and primary care visits in Auckland, New Zealand, in 2013

This study reports the first vaccine effectiveness (VE) estimates for the prevention of general practice visits and hospitalisations for laboratory-confirmed influenza from an urban population in Auckland, New Zealand, in the same influenza season (2013). A case test-negative design was used to estimate propensity-adjusted VE in both hospital and community settings. Patients with a severe acute respiratory infection (SARI) or influenza-like illness (ILI) were defined as requiring hospitalisation (SARI) or attending a general practice (ILI) with a history of fever or measured temperature ≥38 °C, cough and onset within the past 10 days. Those who tested positive for influenza virus were cases while those who tested negative were controls. Results were analysed to 7 days post symptom onset and adjusted for the propensity to be vaccinated and the timing during the influenza season. Influenza vaccination provided 52% (95% CI: 32 to 66) protection against laboratory-confirmed influenza hospitalisation and 56% (95% CI: 34 to 70) against presenting to general practice with influenza. VE estimates were similar for all types and subtypes. This study found moderate effectiveness of influenza vaccine against medically attended and hospitalised influenza in New Zealand, a temperate, southern hemisphere country during the 2013 winter season.

Effectiveness of seasonal influenza vaccine in preventing influenza primary care visits and hospitalisation in Auckland, New Zealand in 2015: interim estimates.

Preliminary results for influenza vaccine effectiveness (VE) against acute respiratory illness with circulating laboratory-confirmed influenza viruses in New Zealand from 27 April to 26 September 2015, using a case test-negative design were 36% (95% confidence interval (CI): 11-54) for general practice encounters and 50% (95% CI: 20-68) for hospitalisations. VE against hospitalised influenza A(H3N2) illnesses was moderate at 53% (95% CI: 6-76) but improved compared with previous seasons.

Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance

The 2009 influenza A(H1N1)pdm09 pandemic highlighted the need for improved scientific knowledge to support better pandemic preparedness and seasonal influenza control. The Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS) project, a 5‐year (2012–2016) multiagency and multidisciplinary collaboration, aimed to measure disease burden, epidemiology, aetiology, risk factors, immunology, effectiveness of vaccination and other prevention strategies for influenza and other respiratory infectious diseases of public health importance. Two active, prospective, population‐based surveillance systems were established for monitoring influenza and other respiratory pathogens among those hospitalized patients with acute respiratory illness and those enrolled patients seeking consultations at sentinel general practices. In 2015, a sero‐epidemiological study will use a sample of patients from the same practices. These data will provide a full picture of the disease burden and risk factors from asymptomatic infections to severe hospitalized disease and deaths and related economic burden. The results during the first 2 years (2012–2013) provided scientific evidence to (a) support a change to NZs vaccination policy for young children due to high influenza hospitalizations in these children; (b) contribute to the revision of the World Health Organizations case definition for severe acute respiratory illness for global influenza surveillance; and (c) contribute in part to vaccine strain selection using vaccine effectiveness assessment in the prevention of influenza‐related consultations and hospitalizations. In summary, SHIVERS provides valuable international platforms for supporting seasonal influenza control and pandemic preparedness, and responding to other emerging/endemic respiratory‐related infections.

Accessing primary care Big Data: the development of a software algorithm to explore the rich content of consultation records

Objective To develop a natural language processing software inference algorithm to classify the content of primary care consultations using electronic health record Big Data and subsequently test the algorithms ability to estimate the prevalence and burden of childhood respiratory illness in primary care. Design Algorithm development and validation study. To classify consultations, the algorithm is designed to interrogate clinical narrative entered as free text, diagnostic (Read) codes created and medications prescribed on the day of the consultation. Setting Thirty-six consenting primary care practices from a mixed urban and semirural region of New Zealand. Three independent sets of 1200 child consultation records were randomly extracted from a data set of all general practitioner consultations in participating practices between 1 January 2008–31 December 2013 for children under 18 years of age (n=754 242). Each consultation record within these sets was independently classified by two expert clinicians as respiratory or non-respiratory, and subclassified according to respiratory diagnostic categories to create three ‘gold standard’ sets of classified records. These three gold standard record sets were used to train, test and validate the algorithm. Outcome measures Sensitivity, specificity, positive predictive value and F-measure were calculated to illustrate the algorithms ability to replicate judgements of expert clinicians within the 1200 record gold standard validation set. Results The algorithm was able to identify respiratory consultations in the 1200 record validation set with a sensitivity of 0.72 (95% CI 0.67 to 0.78) and a specificity of 0.95 (95% CI 0.93 to 0.98). The positive predictive value of algorithm respiratory classification was 0.93 (95% CI 0.89 to 0.97). The positive predictive value of the algorithm classifying consultations as being related to specific respiratory diagnostic categories ranged from 0.68 (95% CI 0.40 to 1.00; other respiratory conditions) to 0.91 (95% CI 0.79 to 1.00; throat infections). Conclusions A software inference algorithm that uses primary care Big Data can accurately classify the content of clinical consultations. This algorithm will enable accurate estimation of the prevalence of childhood respiratory illness in primary care and resultant service utilisation. The methodology can also be applied to other areas of clinical care.

Immunization champions: Characteristics of general practitioners associated with better immunization delivery

Our aim was to describe characteristics of general practitioners (GPs) working in practices that achieve higher immunisation coverage and more timely delivery. We conducted computer-assisted telephone interviews with randomly selected GPs from randomly selected practices. Most GPs believed immunisation to be important and were confident about their knowledge of immunisation although assessment revealed their knowledge to be incomplete. A minority considered six weeks is too young to immunise. Greater GP knowledge and confidence in their knowledge was associated with higher practice immunisation coverage, whereas immunisation delivery was more timely at practices where GPs perceived parental access difficulties a barrier.