A norovirus oyster-related outbreak in a nursing home in France, January 2012.

The presence of norovirus in shellfish is a public health concern in Europe. Here, we report the results of an investigation into a norovirus gastroenteritis outbreak following a festive lunch which affected 84 (57%) residents and staff members of a nursing home in January 2012 in France. Individuals who had eaten oysters had a significantly higher risk of developing symptoms in the following 2·5 days than those who had not, the risk increasing with the amount eaten [relative risk 2·2 (1·0-4·6) and 3·3 (1·6-6·6) for 3-4 and 5-12 oysters, respectively]. In healthy individuals during those days, 29 (32%) subsequently became ill, most of whom were staff members performing activities in close contact with residents. Genogroup II noroviruses were detected in faecal samples, in a sample of uneaten oysters and in oysters from the production area. Identifying a norovirus's infectious dose may facilitate the health-related management of contaminated shellfish.

Forecasts of health care utilization related to pandemic A(H1N1)2009 influenza in the Nord-Pas-de-Calais region, France.

OBJECTIVES: To describe and evaluate the forecasts of the load that pandemic A(H1N1)2009 influenza would have on the general practitioners (GP) and hospital care systems, especially during its peak, in the Nord-Pas-de-Calais (NPDC) region, France. STUDY DESIGN: Modelling study. METHODS: The epidemic curve was modelled using an assumption of normal distribution of cases. The values for the forecast parameters were estimated from a literature review of observed data from the Southern hemisphere and French Overseas Territories, where the pandemic had already occurred. Two scenarios were considered, one realistic, the other pessimistic, enabling the authors to evaluate the 'reasonable worst case'. Forecasts were then assessed by comparing them with observed data in the NPDC region--of 4 million people. RESULTS: The realistic scenarios forecasts estimated 300,000 cases, 1500 hospitalizations, 225 intensive care units (ICU) admissions for the pandemic wave; 115 hospital beds and 45 ICU beds would be required per day during the peak. The pessimistic scenario's forecasts were 2-3 times higher than the realistic scenario's forecasts. Observed data were: 235,000 cases, 1585 hospitalizations, 58 ICU admissions; and a maximum of 11.6 ICU beds per day. CONCLUSIONS: The realistic scenario correctly estimated the temporal distribution of GP and hospitalized cases but overestimated the number of cases admitted to ICU. Obtaining more robust data for parameters estimation--particularly the rate of ICU admission among the population that the authors recommend to use--may provide better forecasts.

A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

PURPOSE: High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. METHODS: The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. RESULTS: The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. CONCLUSIONS: Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. TRANSLATIONAL RELEVANCE: Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.