Population-based estimates of the effectiveness of pneumococcal vaccination in Australia IJPDS (2017) Issue 1, Vol 1:201 Proceedings of the IPDLN Conference (August 2016)

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Heather Gidding
Hannah Moore
Lisa McCallum
Parveen Fathima
Thomas Snelling
Nicholas de Klerk
Peter McIntyre
Published online: Apr 18, 2017


ABSTRACT

Objectives
Australia’s Childhood Immunisation Register (ACIR) is one of only a handful of national immunisation registers world-wide. We have, for the first time, linked the ACIR to other health datasets to measure the real-world impact of Australia’s immunisation program. In this study, we aimed to assess the population-based effectiveness of the 3-dose infant pneumococcal vaccination program (due at 2, 4, and 6 months) against invasive pneumococcal disease caused by the 7 vaccine specific serotypes. The 7-valent pneumococcal conjugate vaccine (PCV7) has been available since 2001 and a funded universal program started in 2005 (with a switch to 13-valent PCV in 2011).

Approach
Vaccination records from ACIR, death records, and invasive pneumococcal disease notifications for 2001-2013 were individually linked for 1.37 million children born in 2001-2012 in two Australian states (Western Australia and New South Wales). A Cox proportional hazards model (adjusting for sex, Indigenous status and year of birth) was used to estimate the hazard ratio for invasive pneumococcal disease in vaccinated compared to unvaccinated children less than 2 years old. The per cent of disease prevented by vaccination, or vaccine effectiveness, was calculated as (1-adjusted hazard ratio) x 100%.

Results
From 2005, vaccination coverage with dose 3 of the pneumococcal vaccine was steady at ~91% in eligible cohorts. Between 2001 and 2013, there were 468 notifications of invasive pneumococcal disease caused by the 7 vaccine specific serotypes during 2.66 million person years of observation; only 39 (8.3%) of these cases occurred after the universal program was implemented. Vaccine effectiveness against invasive pneumococcal disease caused by the 7 vaccine specific serotypes for 1, 2 and 3 doses of the pneumococcal vaccine was 68% (95%CI: 44-89%), 93% (81-97%), and 92% (95%CI: 86-93%), respectively.

Conclusion
This is the first study to link Australia’s national immunisation register and measure population-based vaccine effectiveness. The study provides robust evidence of the effectiveness of at least 2 doses of pneumococcal vaccine against vaccine serotype specific infection using a 3 dose infant schedule.


Objectives

Statistics New Zealand's Integrated Data Infrastructure (IDI) combines information from a range of government agencies (such as tax, health and education data) in order to provide the insights government needs to improve social and economic outcomes for New Zealanders. New Zealand has no national population register or unique identifier used in common across these multiple data sources, and probabilistic linkages are a feature of the IDI. A challenge for researchers is to understand the impact of linkage errors and coverage issues present in the linked data, and to develop the rules necessary to define their target population. We outline the statistical infrastructure Statistics New Zealand is developing to help researchers navigate these issues.

Approach

A method has been developed to identify NZ residents at a given time from the much larger number of individuals present in the IDI. Census data linked to the IDI offers insight into the coverage of key population groups and the quality of the attribute information held in the IDI (e.g. location and ethnicity). We are assessing ways that Statistics New Zealand could use these findings to assist researchers in forming their population of interest and assess the potential for bias.

Results

The derived administrative resident population is compared with the official population figures and patterns of under- and over-coverage are identified at an aggregate, and individual level. Some coverage discrepancies may be improved through reducing linkage errors. Comparison with census data reveals some significant quality issues with location and ethnicity variables in administrative collections. Work is underway to improve methods for combining information from multiple sources of varying quality.

Conclusion

Identifying NZ residents at a given time, and quantifying errors in administrative data sources will assist researchers ability to recognise and adjust for these errors in their analysis. Simply quantifying (often for the first time) the limitations of administrative sources also provides impetus to improving the collection of these variables at source.

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