Epidemiology of repeat influenza infection in Queensland, Australia, 2005-2017.

Natural infection with the influenza virus is believed to generate cross-protective immunity across both types and subtypes. However, less is known about the persistence of this immunity and thus the susceptibility of individuals to repeat infection. We used 13 years (2005-2017) of surveillance data from Queensland, Australia, to describe the incidence and distribution of repeat influenza infections. Consecutive infections that occurred within 14 days of prior infection were considered a mixed infection; those that occurred more than 14 days later were considered separate (repeat) infections. Kaplan-Meier plots were used to investigate the probability of reinfection over time and the Prentice, Williams and Peterson extension of the Cox proportional hazards model was used to assess the association of age and gender with reinfection. Among the 188 392 notifications received during 2005-2017, 6165 were consecutively notified for the same individual (3.3% of notifications), and 2958 were mixed infections (1.6%). Overall, the probability of reinfection was low: the cumulative incidence was <1% after one year, 4.6% after five years, and 9.6% after ten years. The majority of consecutive infections were the result of two type A infections (43%) and were most common among females (adjusted hazard ratio (aHR): 1.15, 95% confidence interval (CI) 1.09-1.21), children aged less than 5 years (relative to adults aged 18-64 years aHR: 1.58, 95% CI 1.47-1.70) and older adults aged at least 65 years (aHR: 1.35; 95% CI 1.24-1.47). Our study suggests consecutive infections are possible but rare. These findings have implications for our understanding of population immunity to influenza.

Impact of COVID-19 Mitigation Measures on Mosquito-Borne Diseases in 2020 in Queensland, Australia.

We describe the impact of COVID-19 mitigation measures on mosquito-borne diseases in Queensland, Australia, during the first half of 2020. Implementation of restrictions coincided with an atypical late season outbreak of Ross River virus (RRV) characterized by a peak in notifications in April (1173) and May (955) which were greater than 3-fold the mean observed for the previous four years. We propose that limitations on human movement likely resulted in the majority of RRV infections being acquired at or near the place of residence, and that an increase in outdoor activities, such as gardening and bushwalking in the local household vicinity, increased risk of exposure to RRV-infected mosquitoes. In contrast, the precipitous decline in international passenger flights led to a reduction in the number of imported dengue and malaria cases of over 70% and 60%, respectively, compared with the previous five years. This substantial reduction in flights also reduced a risk pathway for importation of exotic mosquitoes, but the risk posed by importation via sea cargo was not affected. Overall, the emergence of COVID-19 has had a varied impact on mosquito-borne disease epidemiology in Queensland, but the need for mosquito surveillance and control, together with encouragement of personal protective measures, remains unchanged.

Anatomy of a seasonal influenza epidemic forecast

Bayesian methods have been used to predict the timing of infectious disease epidemics in various settings and for many infectious diseases, including seasonal influenza. But integrating these techniques into public health practice remains an ongoing challenge, and requires close collaboration between modellers, epidemiologists, and public health staff. During the 2016 and 2017 Australian influenza seasons, weekly seasonal influenza forecasts were produced for cities in the three states with the largest populations: Victoria, New South Wales, and Queensland. Forecast results were presented to Health Department disease surveillance units in these jurisdictions, who provided feedback about the plausibility and public health utility of these predictions. In earlier studies we found that delays in reporting and processing of surveillance data substantially limited forecast performance, and that incorporating climatic effects on transmission improved forecast performance. In this study of the 2016 and 2017 seasons, we sought to refine the forecasting method to account for delays in receiving the data, and used meteorological data from past years to modulate the force of infection. We demonstrate how these refinements improved the forecast's predictive capacity, and use the 2017 influenza season to highlight challenges in accounting for population and clinician behaviour changes in response to a severe season.

Did socio-ecological factors drive the spatiotemporal patterns of pandemic influenza A (H1N1)?

BACKGROUND: Pandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia. METHODOLOGY: We obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns. RESULTS: Our results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63-47.43%) and 23.20% (95% CrI: 16.10-32.67%), for a 1 °C decrease in average weekly maximum temperature at a lag of one week and a 10mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48-0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39-3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level. CONCLUSIONS: Our results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.

Surveillance of hospitalizations with pandemic A(H1N1) 2009 influenza infection in Queensland, Australia.

OBJECTIVE: To describe the demographic and clinical characteristics of patients hospitalized with pandemic A(H1N1) 2009 infection in Queensland, Australia between 25 May and 3 October 2009 and to examine the relationship between timing of antiviral treatment and severity of illness. METHOD: Using data from the Queensland Health EpiLog information system, descriptive analysis and logistic regression modelling were used to describe and model factors which influence patient outcomes (death, admission to intensive care unit and/or special care unit). Data on patients admitted to hospital in Queensland with confirmed pandemic A(H1N1) 2009 infection were included in this analysis. RESULTS: 1236 patients with pandemic A(H1N1) 2009 infection were admitted to hospitals in Queensland during the study period. Of the total group: 15% were admitted to an intensive care unit or special care unit; 3% died; 34% were under the age of 18 years and 8% were 65 years of age or older; and 55% had at least one underlying medical condition. Among the 842 patients for whom data were available regarding the use of antiviral drugs, antiviral treatment was initiated in 737 (87.5%) patients, treatment commenced at a median of one day (range 1-33 days) after onset of illness. Admission to an intensive care unit or special care unit (ICU/SCU) or death was significantly associated with increased age, lack of timeliness of antiviral treatment, chronic renal disease and morbid obesity. DISCUSSION: Early antiviral treatment was significantly associated with lower likelihood of ICU/SCU admission or death. Early antiviral treatment for influenza cases may therefore have important public health implications.

Pilot of non-invasive (oral fluid) testing for HIV within a community setting.

BACKGROUND: The present study sought to determine the level of undiagnosed HIV infection within a community setting of men who have sex with men (MSM) and identify any associated sexual risk behaviours. METHODS: A total of 427 MSM were recruited in sex-on-premises venues (SOPV) and gay bars within the inner city of Brisbane. An additional 37 MSM were recruited in a smaller, regional centre (Toowoomba). Oral fluid testing for HIV antibodies was undertaken using the Orasure collection system and assay. Each participant was invited to complete a brief behaviour questionnaire and submit an oral fluid specimen. Confirmed serology results were linked to reported sexual behaviours, testing patterns and HIV status. RESULTS: Of the 464 men surveyed, 33 identified as HIV-positive, and all of these were reactive by the Orasure assay. A further eight people who identified as negative or unknown serostatus, had confirmed Orasure reactive results, resulting in 1.9% of the 'non-HIV positive' MSM sample unaware of their positive HIV status. Therefore, 19.5% of the total confirmed HIV-positive individuals were not aware of their true serostatus. CONCLUSIONS: A significant minority of HIV-positive MSM are currently unaware of their positive serostatus. However, an analysis of their risk behaviour does not seem to indicate any significant difference to those who are HIV-negative. Interestingly, 86% of those who were unaware they were HIV-positive identified that they had been tested in the previous 6 months and all of them claimed to have been tested in the previous 2 years.

The changing phases of pandemic (H1N1) 2009 in Queensland: an overview of public health actions and epidemiology.

A graded public health response was implemented to control the pandemic (H1N1) 2009 outbreak in Queensland. Public health measures to contain the outbreak included border control, enhanced surveillance, management of cases and contacts with isolation or quarantine and antivirals, school closures and public education messages. The first confirmed case in Australia was notified on 8 May 2009, in a traveller returning to Queensland from the United States. In Queensland, 593 laboratory-confirmed cases were notified with a date of onset between 26 April and 22 June 2009, when the Protect phase of the Australian Health Management Plan for Pandemic Influenza was implemented; 16 hospitalisations and no deaths were reported during this time. The largest number of confirmed cases was reported in the 10-19-years age group (167, 28% of cases), followed by the 20-29-years age group (153, 26% of cases). With ongoing community transmission, the focus has shifted from public health to the clinical domain, with an emphasis on protecting vulnerable groups. Considerable resources have been invested to prevent and control the spread of disease in Indigenous communities in Far North Queensland. The capacity of clinical services to cope with increased admissions, the potential for widespread antiviral resistance, and rollout of mass vaccination campaigns remain future challenges.

Early evidence for direct and indirect effects of the infant rotavirus vaccine program in Queensland.

OBJECTIVE: To assess the impact of introducing a publicly funded infant rotavirus vaccination program on disease notifications and on laboratory testing and results. DESIGN AND SETTING: Retrospective analysis of routinely collected data (rotavirus notifications [2006-2008] and laboratory rotavirus testing data from Queensland Health laboratories [2000-2008]) to monitor rotavirus trends before and after the introduction of a publicly funded infant rotavirus vaccination program in Queensland in July 2007. MAIN OUTCOME MEASURES: Age group-specific rotavirus notification trends; number of rotavirus tests performed and the proportion positive. RESULTS: In the less than 2 years age group, rotavirus notifications declined by 53% (2007) and 65% (2008); the number of laboratory tests performed declined by 3% (2007) and 15% (2008); and the proportion of tests positive declined by 45% (2007) and 43% (2008) compared with data collected before introduction of the vaccination program. An indirect effect of infant vaccination was seen: notifications and the proportion of tests positive for rotavirus declined in older age groups as well. CONCLUSIONS: The publicly funded rotavirus vaccination program in Queensland is having an early impact, direct and indirect, on rotavirus disease as assessed using routinely collected data. Further observational studies are required to assess vaccine effectiveness. Parents and immunisation providers should ensure that all Australian children receive the recommended rotavirus vaccine doses in the required timeframe.

Effect of healthcare-acquired infection on length of hospital stay and cost.

OBJECTIVE: To estimate the independent effect of a single lower respiratory tract infection, urinary tract infection, or other healthcare-acquired infection on length-of-stay and variable costs and to demonstrate the bias from omitted variables that is present in previous estimates. DESIGN: Prospective cohort study.Setting. A tertiary care referral hospital and regional district hospital in southeast Queensland, Australia. PATIENTS: Adults aged 18 years or older with a minimum inpatient stay of 1 night who were admitted to selected clinical specialities. RESULTS: Urinary tract infection was not associated with an increase in length of hospital stay or variable costs. Lower respiratory tract infection was associated with an increase of 2.58 days in the hospital and variable costs of AU $24, whereas other types of infection were associated with an increased length of stay of 2.61 days but not with variable costs. Many other factors were found to be associated with increased length of stay and variable costs alongside healthcare-acquired infection. The exclusion of these variables caused a positive bias in the estimates of the costs of healthcare-acquired infection. CONCLUSIONS: The existing literature may overstate the costs of healthcare-acquired infection because of bias, and the existing estimates of excess costs may not make intuitive sense to clinicians and policy makers. Accurate estimates of the costs of healthcare-acquired infection should be made and used in appropriately designed decision-analytic economic models (ie, cost-effectiveness models) that will make valid and believable predictions of the economic value of increased infection control.

Modeling the economic losses from pressure ulcers among hospitalized patients in Australia.

The objective of this study was to predict the number of cases of pressure ulcer, the bed days lost, and the economic value of these losses at Australian public hospitals. All adults (>or= 18 years of age) with a minimum stay of 1 night and discharged from selected clinical units from all Australian public hospitals in 2001-02 were included in the study. The main outcome measures were the number of cases of pressure ulcer, bed days lost to pressure ulcer, and economic value of these losses. We predict a median of 95,695 cases of pressure ulcer with a median of 398,432 bed days lost, incurring median opportunity costs of AU$285 M. The number of cases, and so costs, were greatest in New South Wales and lowest in Australian Capitol Territory. We conclude that pressure ulcers represent a serious clinical and economic problem for a resource-constrained public hospital system. The most cost-effective, risk-reducing interventions should be pursued up to a point where the marginal benefit of prevention is equalized with marginal cost. By preventing pressure ulcers, public hospitals can improve efficiency and the quality of the patient's experience and health outcome.

Effect of pressure ulcers on length of hospital stay.

OBJECTIVE: To identify the independent effect of pressure ulcers on excess length of stay and control for all observable factors that may also contribute to excess length of stay. Hospitalized patients who develop a pressure ulcer during their hospital stay are at a greater risk for increased length of stay as compared with patients who do not. DESIGN: Cross-sectional, observational study. SETTING: Tertiary-care referral and teaching hospital in Australia. PATIENTS: Two thousand hospitalized patients 18 years and older who had a minimum stay in the hospital of 1 night and admission to selected clinical units. METHODS: Two thousand participants were randomly selected from 4,500 patients enrolled in a prospective survey conducted between October 2002 and January 2003. Quantile median robust regression was used to assess risk factors for excess length of hospital stay. RESULTS: Having a pressure ulcer resulted in a median excess length of stay of 4.31 days. Twenty other variables were statistically significant at the 5% level in the final model. CONCLUSIONS: Pressure ulcers make a significant independent contribution to excess length of hospitalization beyond what might be expected based on admission diagnosis. However, our estimates were substantially lower than those currently used to make predictions of the economic costs of pressure ulcers; existing estimates may overstate the true economic cost.