Search

Vaccination programs can provide an effective means to control infectious diseases at a population level. Evaluating the impact of these programs after implementation can be complicated by limitations of routine surveillance systems and lack of routine testing to confirm diagnosis, as well as natural fluctuations in disease rates over time. This thesis provides a structured explanation of statistical methods and how they can be used to address the epidemiological challenges in assessing changes in burden of disease as a result of vaccination programs. It explores statistical approaches to the evaluation of vaccination programs at a population level, using rotavirus vaccination in New South Wales (NSW), Australia, as a case study. A summary of the key features that need to be considered when trying to detect any changes in the burden of infectious diseases due to vaccination is given. An assessment of the impact of the Australian rotavirus vaccination program, introduced in 2007, on hospitalisations and emergency department (ED) presentations of children aged under five years for all-cause gastroenteritis in NSW from July 2001 to June 2013 was conducted. Previously published methods that separate these hospitalisations and ED presentations into those due to rotavirus and those that are not are compared. A simulation study is used to explore these methods in controlled scenarios to determine the most appropriate method for these data. The Australian rotavirus vaccination program had an almost immediate impact and led to a fifty and sixteen percent reduction in the rate of hospitalisations and ED presentations for acute gastroenteritis within the first 2.5 years. These declines were mostly attributed to a decline in the size of the seasonal peak. The methods to determine rotavirus cases from all-cause gastroenteritis cases had different strengths and limitations and the derived estimates varied. No robust method was identified from the simulation study for our data. Ea

The planning and delivery of care systems require knowledge on the ways in which individuals access available services that are funded by a range of health and community services. The aims of this study were to identify distinct groups of Home and Community Care (HACC) clients in New South Wales, Australia, based on patterns of actual service use, and to understand the health and social needs and resources of client groups that access different mixes of services. Multiple data sets linked at the individual level - including the 45 and Up Study community survey, the HACC Minimum Data Set and the Admitted Patient Data Collection for hospitals - provide an innovative basis to investigate the complexity of access to service use. Data were collected between 2006 and 2008. A cluster analysis based on clients' type and volume of community service use was conducted on the 4890 HACC clients in the linked dataset and nine distinct clusters of clients were identified. Three of these clusters were considered 'complex', in terms of the range of community and hospital assistance received, while the others comprised mainly of one or two dominant service types. The analytical approach and findings developed here provide a client-centred approach to monitor and evaluate access to local service systems that are being reformed to better integrate the delivery of health and community services currently funded and managed separately by national and state governments.

BACKGROUND There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%). METHODS Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights. RESULTS Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly. CONCLUSIONS These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items.