Influenza Outbreaks during World Youth Day 2008 Mass Gathering

Novel viruses were introduced and seasonal viruses were amplified

Representativeness of CO and O3 Along ATom Transects Derived from GEOS-5 and GMI-CTM Simulations

One major goal for the NASA Atmospheric Tomography Mission (ATom) is producing an observation-based chemical climatology to represent the atmospheric heterogeneity. In this study, we use CO and O3 observations and global atmospheric model simulations to examine the spatial representativeness of the ATom-1 and -2 transects within a 4D framework provided by the NASA GEOS-5 and GMI-CTM models. Based on the probability density functions, we find that the variability of CO and O3 along the flight tracks is well hindcast by the model when sampled per ATom flights. The CO variations along the ATom-transect are likely representative of the typical CO variations over the whole Pacific basin during both the ATom-1 and -2 periods, the northern Atlantic during the ATom-1 period, and the tropical Atlantic in the ATom-2 period. Over southern Atlantic, CO along the ATom-1 transects is likely less well mixed than that of the broader region, but is still representative of the median CO concentration. CO along the ATom-2 transect is likely higher than the median CO concentration over this region. For O3, the agreements between PDFs of O3 sampled along the ATom transects and over the broader regions are fair to good over all six regions (Scores > 0.65) with notable discrepancies over some regions. For example, in ATom-1 over the northern Pacific and Atlantic, the transect samples air masses with higher O3 levels. During ATom-2, the transect over-represents the occurrence of O3 plumes over tropical Pacific. Over the southern Pacific and Atlantic for both ATom-1 and -2, the transects have a less uniform distribution compared to the surrounding basins, but still represent the median O3 abundance. Overall, we conclude in most cases that ATom measurements represent the statistical variations of these two species over the ocean basins at the time of measurement. Higher-order statistics, including covariance of species, has not been tested in this study

Men who have sex with men, infectious syphilis and HIV coinfection in inner Sydney: results of enhanced surveillance

Background: The resurgence of infectious syphilis in men who have sex with men (MSM) has been documented worldwide; however, HIV coinfection and syphilis reinfections in MSM in inner Sydney have not been published. Methods: For all laboratory syphilis notifications assessed as a newly notified case or reinfection, a questionnaire was sent to the requesting physician seeking demographic data and disease classification. Sex of partner and HIV status were collected for all infectious syphilis notifications in men received from 1 April 2006 to March 2011. Results: From April 2001 to March 2011, 3664 new notifications were received, 2278 (62%) were classified as infectious syphilis. Infectious syphilis notifications increased 12-fold from 25 to 303 in the first and last year respectively, and almost all notifications were in men (2220, 97.5%). During April 2006 to March 2011, 1562 infectious syphilis notifications in males were received and 765 (49%) of these men were HIV-positive and 1351 (86%) reported a male sex partner. Reinfections increased over time from 17 (9%) to 56 (19%) in the last year of the study and were significantly more likely to be in HIV-positive individuals (χ2 = 140.92, degrees of freedom= 1, P = \u3c0.001). Conclusion: Inner Sydney is experiencing an epidemic of infectious syphilis in MSM and about half of these cases are in HIV-positive patients. Reinfections are increasing and occur predominantly in HIV-positive men. Accurate surveillance information is needed to inform effective prevention programs, and community and clinician education needs to continue until a sustained reduction is achieved

Developing a climate change inequality health impact assessment for health services

Objectives: To develop a Climate Change Inequality Health Impact Assessment (CCIHIA) framework for health services; to provide a systematic process for assessing potential unequal health impacts of climate change on vulnerable and marginalised populations and places; to support effective planning to address these impacts; and to develop contextually appropriate local strategies. Type of program: A collaborative interdisciplinary scoping research project involving two universities and two local health districts (LHDs) in New South Wales (NSW) to develop a CCIHIA framework. This work builds upon the health impact assessment (HIA) approach, which systematically assesses proposals’ potential health and equity impacts by involving stakeholders in developing responses. Methods: The project involved four main activities: understanding stakeholder requirements; conceptualising climate change vulnerability; considering the role of health services; and integrating findings into a conceptual framework. Results: Stakeholders identified key functions that should be addressed across the framing, process and utility of the CCIHIA framework. The resulting conceptual framework outlines contexts and social stratification, the differential impacts of climate change (including factors influencing unequal impacts) and the health system’s position, and also identifies key potential points of intervention. Lessons learnt: The challenge of addressing the complexity of factors and resulting health impacts is reflected within the CCIHIA framework. While there are many intervention points within this framework for health services to address, many factors influencing unequal impacts are created outside the health sector’s direct control. The framework’s development process reflected the focus on collaboration and the interdisciplinary nature of climate change response. Ultimately, the CCIHIA framework is an assessment tool and an approach for prioritising inclusive, cross-cutting, multisector working, and problem-solving

Influenza A testing and detection in patients admitted through emergency departments in Sydney during winter 2009 : implications for rational testing

Aim: To examine factors associated with testing and detection of influenza A in patients admitted to hospital for acute care during the winter 2009 pandemic influenza outbreak. Design, setting and participants: Retrospective observational study of patients who were tested for influenza A after being admitted to hospital through emergency departments of the Sydney South West Area Health Service from 15 June to 30 August 2009. Main outcome measures: The association of factors such as age, diagnosis at admission, hospital and week of admission with rates of testing and detection of influenza A. Results: 17 681 patients were admitted through nine emergency departments; 1344 (7.6%) were tested for influenza A, of whom 356 (26.5%) tested positive for pandemic influenza. Testing rates were highest in 0–4-year-old children, in the peak period of the outbreak, and in patients presenting with a febrile or respiratory illness. Positive influenza test results were common across a range of diagnoses, but occurred most frequently in children aged 10–14 years (64.3%) and in patients with a diagnosis at admission of influenza-like illness (59.1%). Using multivariate logistic regression, patients with a diagnosis at admission of fever or a respiratory illness at admission were most likely to be tested (odds ratios [ORs], 15 [95% CI, 11–21] and 17 [95% CI, 15–19], respectively). These diagnoses were stronger predictors of influenza testing than the peak testing week (Week 4; OR, 7.0 [95% CI, 3.8–13]) or any age group. However, diagnosis at admission and age were significant but weak predictors of a positive test result, and the strongest predictor of a positive test result was the peak epidemic week (Week 3; OR, 120 [95% CI, 27–490]). Conclusion: The strongest predictor of a clinician’s decision to test for influenza was the diagnosis at admission, but the strongest predictor of a positive test was the week of admission. A rational approach to influenza testing for patients who are admitted to hospital for acute care could include active tracking of influenza testing and detection rates, testing patients with a strong indication for antiviral treatment, and admitting only MJA 2010; 193: 455–459 those who test negative to “clean” wards during the peak of an outbreak