Applied epidemiology of influenza and other respiratory infections in Australia, Bangladesh and Cambodia
Creators: name: Tolosa Alvarez, Ximena
Publisher: name: The Australian National University
Year: 2019

description: This thesis documents the work I completed to fulfil the core requirements of the Master of Philosophy in Applied Epidemiology (MAE) while based at the World Health Organization Collaborating Centre for Reference and Research on Influenza in Melbourne. In May 2017 I travelled to Cambodia to conduct an influenza burden of disease study. I worked in collaboration with Cambodian public health officials and WHO Country Office staff to assist in the estimation of a national hospitalisation rate due to influenza-associated severe acute respiratory infection (SARI). The numerator used in the calculation of rates relied on existing surveillance data. Substantial field work was required to estimate the denominator. Field work entailed conducting two hospital admission surveys in two geographical regions in Cambodia. The results of this study showed that annual rates of influenza-associated hospitalisations were highest in infants and young children (&lt;1 year and 1-4 years). This work represented the epidemiology study component of the MAE (Chapter 2). For my data analysis project I used the Australian influenza-like illness (ILI) surveillance system to estimate influenza vaccine effectiveness in Australia for the period of 2012 to 2017 and compare interim and final estimates. Vaccine effectiveness (VE) against influenza viruses was estimated using the case test-negative design and at two time points: mid-season (i.e., interim VE) and at the end of the influenza season (i.e., final VE). VE pairs were also estimated for influenza A and B combined, by subtype/lineage, by age group and by target group of vaccination. We assessed the association between sample size (i.e., the number of ILI specimens tested) and precision of VE pair estimates. This work demonstrated the need for a larger number of specimens to be collected, particularly from children and elderly patients (Chapter 3). A second data analysis project involved the assessment of a virus isolation external quality assurance program implemented by the Influenza Centre in 2017-2018. This program tested virus isolation and identification performance in 25 National Influenza Centres (NIC) in countries in the WHO regions of the Americas, Africa and Easter Mediterranean. Results of this analysis was used to identify laboratories that required support in meeting their core NIC responsibilities (Chapter 3). In January 2018, I supported the Bangladesh Ministry of Health and Family Welfare and WHO in responding to a diphtheria outbreak among Rohingya refugees. I worked in Cox's Bazar for four weeks as a laboratory technical officer and was one of three members of the WHO's case management team. My main responsibility was to facilitate the urgent establishment of a basic public health laboratory in close proximity to the refugee camps to ensure timely testing of diphtheria specimens as well as rapid confirmation of alert signals emanating from the Early Warning and Alert System. Challenges encountered in establishing laboratory capacity in the context of an acute large scale public health crisis in one of Bangladesh poorest districts were described. This work represents my participation in a response to an acute public health problem (Chapter 4). In my final project I assessed the feasibility of establishing systematic, ongoing epidemiological surveillance of people occupationally exposed to animals for emergent zoonotic influenza viruses. We focused on workers in intensive pig and poultry industries including abattoir workers. Through stakeholder engagement we examined drivers and barriers of conducting this type of surveillance. Furthermore, I developed a framework for conducting surveillance of zoonotic respiratory viruses targeting people working in the intensive pig and poultry production and processing industries in Australia. This work is presented in Chapter 5.