Self-sampling for community respiratory illness: a new tool for national virological surveillance.

This report aims to evaluate the usefulness of self-sampling as an approach for future national surveillance of emerging respiratory infections by comparing virological data from two parallel surveillance schemes in England. Nasal swabs were obtained via self-administered sampling from consenting adults (≥ 16 years-old) with influenza symptoms who had contacted the National Pandemic Flu Service (NPFS) health line during the 2009 influenza pandemic. Equivalent samples submitted by sentinel general practitioners participating in the national influenza surveillance scheme run jointly by the Royal College of General Practitioners (RCGP) and Health Protection Agency were also obtained. When comparable samples were analysed there was no significant difference in results obtained from self-sampling and clinician-led sampling schemes. These results demonstrate that self-sampling can be applied in a responsive and flexible manner, to supplement sentinel clinician-based sampling, to achieve a wide spread and geographically representative way of assessing community transmission of a known organism.

A new laboratory-based surveillance system (Respiratory DataMart System) for influenza and other respiratory viruses in England: results and experience from 2009 to 2012.

During the 2009 influenza A(H1N1) pandemic, a new laboratory-based virological sentinel surveillance system, the Respiratory DataMart System (RDMS), was established in a network of 14 Health Protection Agency (now Public Health England (PHE)) and National Health Service (NHS) laboratories in England. Laboratory results (both positive and negative) were systematically collected from all routinely tested clinical respiratory samples for a range of respiratory viruses including influenza, respiratory syncytial virus (RSV), rhinovirus, parainfluenza virus, adenovirus and human metapneumovirus (hMPV). The RDMS also monitored the occurrence of antiviral resistance of influenza viruses. Data from the RDMS for the 2009­2012 period showed that the 2009 pandemic influenza virus caused three waves of activity with different intensities during the pandemic and post pandemic periods. Peaks in influenza A(H1N1)pdm09 positivity (defined as number of positive samples per total number of samples tested) were seen in summer and autumn in 2009, with slightly higher peak positivity observed in the first post-pandemic season in 2010/2011. The influenza A(H1N1)pdm09 virus strain almost completely disappeared in the second postpandemic season in 2011/2012. The RDMS findings are consistent with other existing community-based virological and clinical surveillance systems. With a large sample size, this new system provides a robust supplementary mechanism, through the collection of routinely available laboratory data at minimum extra cost, to monitor influenza as well as other respiratory virus activity. A near real-time, daily reporting mechanism in the RDMS was established during the London 2012 Olympic and Paralympic Games. Furthermore, this system can be quickly adapted and used to monitor future influenza pandemics and other major outbreaks of respiratory infectious disease, including novel pathogens.

Effectiveness of seasonal 2010/11 and pandemic influenza A(H1N1)2009 vaccines in preventing influenza infection in the United Kingdom: mid-season analysis 2010/11.

This study provides mid-season estimates of the effectiveness of 2010/11 trivalent influenza vaccine and previous vaccination with monovalent influenza A(H1N1)2009 vaccine in preventing confirmed influenza A(H1N1)2009 infection in the United Kingdom in the 2010/11 season. The adjusted vaccine effectiveness was 34% (95% CI: -10 - 60%) if vaccinated only with monovalent vaccine in the 2009/10 season; 46% (95% CI: 7 - 69%) if vaccinated only with trivalent influenza vaccine in the 2010/11 season and 63% (95% CI: 37 - 78%) if vaccinated in both seasons.

Effectiveness of pandemic and seasonal influenza vaccine in preventing pandemic influenza A(H1N1)2009 infection in England and Scotland 2009-2010.

Following the global spread of pandemic influenza A(H1N1)2009, several pandemic vaccines have been rapidly developed. The United Kingdom and many other countries in the northern hemisphere implemented seasonal and pandemic influenza vaccine programmes in October 2009. We present the results of a case­control study to estimate effectiveness of such vaccines in preventing confirmed pandemic influenza infection. Some 5,982 individuals with influenza-like illness seen in general practices between November 2009 and January 2010 were enrolled. Those testing positive on PCR for pandemic influenza were assigned as cases and those testing negative as controls. Vaccine effectiveness was estimated as the relative reduction in odds of confirmed infection between vaccinated and unvaccinated individuals. Fourteen or more days after immunisation with the pandemic vaccine, adjusted vaccine effectiveness (VE) was 72% (95% confidence interval (CI): 21% to 90%). If protection was assumed to start after seven or more days, the adjusted VE was 71% (95% CI: 37% to 87%). Pandemic influenza vaccine was highly effective in preventing confirmed infection with pandemic influenza A(H1N1)2009 from one week after vaccination. No evidence of effectiveness against pandemic influenza A(H1N1)2009 was found for the 2009/10 trivalent seasonal influenza vaccine (adjusted VE of -30% (95% CI: -89% to 11%)).

Estimating influenza vaccine effectiveness using routinely collected laboratory data.

BACKGROUND: Estimation of influenza vaccine effectiveness (V/E) is needed early during influenza outbreaks in order to optimise management of influenza--a need which will be even greater in a pandemic situation. OBJECTIVE: Examine the potential of routinely collected virological surveillance data to generate estimates of V/E in real-time during winter seasons. METHODS: Integrated clinical and virological community influenza surveillance data collected over three winters 2004/5-2006/7 were used. We calculated the odds of vaccination in persons that were influenza-virus-positive and the odds in those that were negative and provided a crude estimate of V/E. Logistic regression was used to obtain V/E estimates adjusted for confounding variables such as age. RESULTS: Multivariable analysis suggested that adjustments to the crude V/E estimate were necessary for patient age and month of sampling. The annual adjusted V/E was 2005/6, 67% (95% CI 41% to 82%); 2006/7 55% (26% to 73%) and 2007/8 67% (41% to 82%). The adjusted V/E in persons <65 years was 70% (57% to 78%) and 65 years and over 46% (-17% to 75%). Estimates differed by small insignificant amounts when calculated separately for influenza A and B; by interval between illness onset and swab sample; by analysis for the period November to January in each year compared with February to April and according to viral load. CONCLUSION: We have demonstrated the potential of using routine virological and clinical surveillance data to provide estimates of V/E early in season and conclude that it is feasible to introduce this approach to V/E measurement into evaluation of national influenza vaccination programs.