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This study presents enhanced surveillance data from 2004 – 2018 for all community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) specimens collected in Western Australia (WA), and describes the changing epidemiology over this period. A total of 57,557 cases were reviewed. Annual incidence rates increased from 86.2 cases per 100,000 population to 245.6 per 100,000 population (IRR = 2.9, CI95 2.7 – 3.0). The proportion of isolates carrying Panton-Valentine leukocidin (PVL)-associated genes increased from 3.4% to 59.8% (χ2 test for trend 7021.9, p<0.001). The emergence of PVL-positive, “Queensland CA-MRSA” (ST93- IV) and “WA 121” (ST5-IV) accounted for the majority of increases in CA-MRSA across the study period. It is unclear why some clones are more prolific in certain regions. In WA, CA-MRSA rates increase as indices of temperature and humidity increase after controlling for socioeconomic disadvantage. We suggest climatic conditions may contribute to transmission, along with other socio-behavioural factors. A better understanding of the ability for certain clones to form ecological niches and cause outbreaks is required.

Australia was previously believed to be free of enzootic swine influenza viruses due strict quarantine practices and use of biosecure breeding facilities. The first proven Australian outbreak of swine influenza occurred in Western Australian in 2012, revealing an unrecognized zoonotic risk, and a potential future pandemic threat. A public health investigation was undertaken to determine whether zoonotic infections had occurred and to reduce the risk of further transmission between humans and swine. A program of monitoring, testing, treatment, and vaccination was commenced, and a serosurvey of workers was also undertaken. No acute infections with the swine influenza viruses were detected. Serosurvey results were difficult to interpret due to previous influenza infections and past and current vaccinations. However, several workers had elevated haemagglutination inhibition (HI) antibody levels to the swine influenza viruses that could not be attributed to vaccination or infection with contemporaneous seasonal influenza A viruses. However, we lacked a suitable control population, so this was inconclusive. The experience was valuable in developing better protocols for managing outbreaks at the human-animal interface. Strict adherence to biosecurity practices, and ongoing monitoring of swine and their human contacts is important to mitigate pandemic risk. Strain specific serological assays would greatly assist in identifying zoonotic transmission.

Australia was previously believed to be free of enzootic swine influenza viruses due strict quarantine practices and use of biosecure breeding facilities. The first proven Australian outbreak of swine influenza occurred in Western Australian in 2012, revealing an unrecognized zoonotic risk, and a potential future pandemic threat. A public health investigation was undertaken to determine whether zoonotic infections had occurred and to reduce the risk of further transmission between humans and swine. A program of monitoring, testing, treatment, and vaccination was commenced, and a serosurvey of workers was also undertaken. No acute infections with the swine influenza viruses were detected. Serosurvey results were difficult to interpret due to previous influenza infections and past and current vaccinations. However, several workers had elevated haemagglutination inhibition (HI) antibody levels to the swine influenza viruses that could not be attributed to vaccination or infection with contemporaneous seasonal influenza A viruses. However, we lacked a suitable control population, so this was inconclusive. The experience was valuable in developing better protocols for managing outbreaks at the human–animal interface. Strict adherence to biosecurity practices, and ongoing monitoring of swine and their human contacts is important to mitigate pandemic risk. Strain specific serological assays would greatly assist in identifying zoonotic transmission.

Data were pooled from three Australian sentinel general practice influenza surveillance networks to estimate Australia-wide influenza vaccine coverage and effectiveness against community presentations for laboratory-confirmed influenza for the 2012, 2013 and 2014 seasons. Patients presenting with influenza-like illness at participating GP practices were swabbed and tested for influenza. The vaccination odds of patients testing positive were compared with patients testing negative to estimate influenza vaccine effectiveness (VE) by logistic regression, adjusting for age group, week of presentation and network. Pooling of data across Australia increased the sample size for estimation from a minimum of 684 to 3,683 in 2012, from 314 to 2,042 in 2013 and from 497 to 3,074 in 2014. Overall VE was 38% [95% confidence interval (CI) 24-49] in 2012, 60% (95% CI 45-70) in 2013 and 44% (95% CI 31-55) in 2014. For A(H1N1)pdm09 VE was 54% (95% CI-28 to 83) in 2012, 59% (95% CI 33-74) in 2013 and 55% (95% CI 39-67) in 2014. For A(H3N2), VE was 30% (95% CI 14-44) in 2012, 67% (95% CI 39-82) in 2013 and 26% (95% CI 1-45) in 2014. For influenza B, VE was stable across years at 56% (95% CI 37-70) in 2012, 57% (95% CI 30-73) in 2013 and 54% (95% CI 21-73) in 2014. Overall VE against influenza was low in 2012 and 2014 when A(H3N2) was the dominant strain and the vaccine was poorly matched. In contrast, overall VE was higher in 2013 when A(H1N1)pdm09 dominated and the vaccine was a better match. Pooling data can increase the sample available and enable more precise subtype- and age group-specific estimates, but limitations remain.

Data were pooled from three Australian sentinel general practice influenza surveillance networks to estimate Australia-wide influenza vaccine coverage and effectiveness against community presentations for laboratory-confirmed influenza for the 2012, 2013 and 2014 seasons. Patients presenting with influenza-like illness at participating GP practices were swabbed and tested for influenza. The vaccination odds of patients testing positive were compared with patients testing negative to estimate influenza vaccine effectiveness (VE) by logistic regression, adjusting for age group, week of presentation and network. Pooling of data across Australia increased the sample size for estimation from a minimum of 684 to 3,683 in 2012, from 314 to 2,042 in 2013 and from 497 to 3,074 in 2014. Overall VE was 38% [95% confidence interval (CI) 24-49] in 2012, 60% (95% CI 45-70) in 2013 and 44% (95% CI 31-55) in 2014. For A(H1N1)pdm09 VE was 54% (95% CI-28 to 83) in 2012, 59% (95% CI 33-74) in 2013 and 55% (95% CI 39-67) in 2014. For A(H3N2), VE was 30% (95% CI 14-44) in 2012, 67% (95% CI 39-82) in 2013 and 26% (95% CI 1-45) in 2014. For influenza B, VE was stable across years at 56% (95% CI 37-70) in 2012, 57% (95% CI 30-73) in 2013 and 54% (95% CI 21-73) in 2014. Overall VE against influenza was low in 2012 and 2014 when A(H3N2) was the dominant strain and the vaccine was poorly matched. In contrast, overall VE was higher in 2013 when A(H1N1)pdm09 dominated and the vaccine was a better match. Pooling data can increase the sample available and enable more precise subtype- and age group-specific estimates, but limitations remain.

During 2010–2012 the strain composition of the influenza vaccine in the Southern Hemisphere did not change, but the circulating virus type/subtype did. We pooled data for these years from the Western Australian sentinel medical practice surveillance system for influenza to estimate vaccine effectiveness (VE) by influenza virus type and subtype. A case test-negative design was used with VE estimated as (1-odds ratio) × 100%. There were 2182 patients included in the analysis across the 3 years studied. The predominant subtype was A/H1pdm09 in 2010 and 2011, and A/H3 in 2012. The overall adjusted VE estimate against all influenza for 2010–2012 was 51% (95% CI: 36, 63). Estimates were highest against A/H1pdm09 at 74% (95% CI: 47, 87), followed by 56% (95% CI: 33, 71) for influenza B and lowest against A/H3 at 39% (95% CI: 13, 57). When analyses were restricted to compare influenza-positive patients with patients who tested positive for a non-influenza virus, overall adjusted VE was 59% (95% CI: 39, 72). These results suggest moderate protection against influenza by vaccination in Western Australia over the period 2010–2012, and are consistent with findings from other settings.

Bloomfield, L. E., Coombs, G. W., Tempone, S., & Armstrong, P. K. (2020). Marked increase in community-associated methicillin-resistant Staphylococcus aureus infections, Western Australia, 2004–2018. Epidemiology & Infection, 148, Article e153. https://doi.org/10.1017/S0950268820000849

Alfayyadh, M., Collins, D. A., Tempone, S., McCann, R., Armstrong, P. K., Riley, T. V., & Cook, A. (2019). Recurrence of Clostridium difficile infection in the Western Australian population. Epidemiology and Infection, 147, Article e153. Available here