Estimating the Disease Burden of Pandemic (H1N1) 2009 Virus Infection in Hunter New England, Northern New South Wales, Australia, 2009

Introduction: On May 26, 2009, the first confirmed case of Pandemic (H1N1) 2009 virus (pH1N1) infection in Hunter New England (HNE), New South Wales (NSW), Australia (population 866,000) was identified. We used local surveillance data to estimate pH1N1-associated disease burden during the first wave of pH1N1 circulation in HNE. Methods: Surveillance was established during June 1-August 30, 2009, for: 1) laboratory detection of pH1N1 at HNE and NSW laboratories, 2) pH1N1 community influenza-like illness (ILI) using an internet survey of HNE residents, and 3) pH1N1-associated hospitalizations and deaths using respiratory illness International Classification of Diseases 10 codes at 35 HNE hospitals and mandatory reporting of confirmed pH1N1-associated hospitalizations and deaths to the public health service. The proportion of pH1N1 positive specimens was applied to estimates of ILI, hospitalizations, and deaths to estimate disease burden. Results: Of 34,177 specimens tested at NSW laboratories, 4,094 (12%) were pH1N1 positive. Of 1,881 specimens from patients evaluated in emergency departments and/or hospitalized, 524 (26%) were pH1N1 positive. The estimated number of persons with pH1N1-associated ILI in the HNE region was 53,383 (range 37,828–70,597) suggesting a 6.2% attack rate (range 4.4–8.2%). An estimated 509 pH1N1-associated hospitalizations (range 388–630) occurred (reported: 184), and up to 10 pH1N1-associated deaths (range 8–13) occurred (reported: 5). The estimated case hospitalization ratio was 1% and case fatality ratio was 0.02%. Discussion: The first wave of pH1N1 activity in HNE resulted in symptomatic infection in a small proportion of the population, and the number of HNE pH1N1-associated hospitalizations and deaths is likely higher than officially reported

Who interacts with whom?:Social mixing insights from a rural population in India

Acute lower respiratory infections (ALRI) are a leading cause of morbidity and mortality globally, with most ALRI deaths occurring in children in developing countries. Computational models can be used to test the efficacy of respiratory infection prevention interventions, but require data on social mixing patterns, which are sparse in developing countries. We describe social mixing patterns among a rural community in northern India. During October 2015-February 2016, trained field workers conducted cross-sectional face-to-face standardized surveys in a convenience sample of 330 households in Faridabad District, Haryana State, India. Respondents were asked about the number, duration, and setting of social interactions during the previous 24 hours. Responses were compared by age and gender. Among the 3083 residents who were approached, 2943 (96%) participated, of whom 51% were male and the median age was 22 years (interquartile range (IQR) 9-37). Respondents reported contact (defined as having had a face-to-face conversation within 3 feet, which may or may not have included physical contact) with a median of 17 (IQR 12-25) people during the preceding 24 hours. Median total contact time per person was 36 person-hours (IQR 26-52). Female older children and adults had significantly fewer contacts than males of similar age (Kruskal-Wallis χ2 = 226.59, p<0.001), but spent a longer duration in contact with young children (Kruskal-Wallis χ2 = 27.26, p<0.001), suggesting a potentially complex pattern of differential risk of infection between genders. After controlling for household size and day of the week, respondent age was significantly associated with number and duration of contacts. These findings can be used to model the impact of interventions to reduce lower respiratory tract infections in India

Prevalence of 2009 Pandemic Influenza A (H1N1) Virus Antibodies, Tampa Bay Florida — November–December, 2009

BACKGROUND: In 2009, a novel influenza virus (2009 pandemic influenza A (H1N1) virus (pH1N1)) caused significant disease in the United States. Most states, including Florida, experienced a large fall wave of disease from September through November, after which disease activity decreased substantially. We determined the prevalence of antibodies due to the pH1N1 virus in Florida after influenza activity had peaked and estimated the proportion of the population infected with pH1N1 virus during the pandemic. METHODS: During November-December 2009, we collected leftover serum from a blood bank, a pediatric children's hospital and a pediatric outpatient clinic in Tampa Bay Florida. Serum was tested for pH1N1 virus antibodies using the hemagglutination-inhibition (HI) assay. HI titers ≥40 were considered seropositive. We adjusted seroprevalence results to account for previously established HI assay specificity and sensitivity and employed a simple statistical model to estimate the proportion of seropositivity due to pH1N1 virus infection and vaccination. RESULTS: During the study time period, the overall seroprevalence in Tampa Bay, Florida was 25%, increasing to 30% after adjusting for HI assay sensitivity and specificity. We estimated that 5.9% of the population had vaccine-induced seropositivity while 25% had seropositivity secondary to pH1N1 virus infection. The highest cumulative incidence of pH1N1 virus infection was among children aged 5-17 years (53%) and young adults aged 18-24 years (47%), while adults aged ≥50 years had the lowest cumulative incidence (11-13%) of pH1N1 virus infection. CONCLUSIONS: After the peak of the fall wave of the pandemic, an estimated one quarter of the Tampa Bay population had been infected with the pH1N1 virus. Consistent with epidemiologic trends observed during the pandemic, the highest burdens of disease were among school-aged children and young adults

Outbreak of Pneumonia in the Setting of Fatal Pneumococcal Meningitis among US Army Trainees: Potential Role of Chlamydia pneumoniae Infection

<p>Abstract</p> <p>Background</p> <p>Compared to the civilian population, military trainees are often at increased risk for respiratory infections. We investigated an outbreak of radiologically-confirmed pneumonia that was recognized after 2 fatal cases of serotype 7F pneumococcal meningitis were reported in a 303-person military trainee company (Alpha Company).</p> <p>Methods</p> <p>We reviewed surveillance data on pneumonia and febrile respiratory illness at the training facility; conducted chart reviews for cases of radiologically-confirmed pneumonia; and administered surveys and collected nasopharyngeal swabs from trainees in the outbreak battalion (Alpha and Hotel Companies), associated training staff, and trainees newly joining the battalion.</p> <p>Results</p> <p>Among Alpha and Hotel Company trainees, the average weekly attack rates of radiologically-confirmed pneumonia were 1.4% and 1.2% (most other companies at FLW: 0-0.4%). The pneumococcal carriage rate among all Alpha Company trainees was 15% with a predominance of serotypes 7F and 3. <it>Chlamydia pneumoniae </it>was identified from 31% of specimens collected from Alpha Company trainees with respiratory symptoms.</p> <p>Conclusion</p> <p>Although the etiology of the outbreak remains unclear, the identification of both <it>S. pneumoniae </it>and <it>C. pneumoniae </it>among trainees suggests that both pathogens may have contributed either independently or as cofactors to the observed increased incidence of pneumonia in the outbreak battalion and should be considered as possible etiologies in outbreaks of pneumonia in the military population.</p

Rates of hospitalisation for acute respiratory illness and the emergence of pandemic (H1N1) 2009 virus in the Hunter New England Area Health Service

Hospitalisation rates for seasonal influenza are highest among young children and people aged over 65 years. Calculation of laboratory-confirmed infection rates is difficult because influenza testing is not consistently performed. Using diagnostic codes to identify hospitalisations for acute respiratory illness provides one measure of the relative burden of pandemic (H1N1) 2009 (pH1N1) virus infection compared with influenza virus infections in previous influenza seasons