Influenza transmission in a cohort of households with children: 2010-2011

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Workshop 1: Surveillance issues of pandemic influenza

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Can We “Hedge” against the Development of Antiviral Resistance among Pandemic Influenza Viruses?

David K. Shay and Benjamin Ridenhour discuss a modeling study predicting that stockpiling a secondary antiviral for use early in a flu pandemic can forestall resistance to the primary stockpiled drug

Efficacy and Safety of Oseltamivir in Children: Systematic Review and Individual Patient Data Meta-analysis of Randomized Controlled Trials

AbstractBackground: Oseltamivir has been used to treat children with influenza for nearly two decades, with treatment currently approved for infants 2 weeks of age or older, but efficacy and safety remain controversial. Newer randomized placebo controlled trials (RCT), not included in previous meta-analyses, can add to the evidence base.Methods: We conducted a systematic review to identify RCTs of oseltamivir therapy in children. We obtained individual patient data and examined protocol-defined outcomes. We then conducted a two-stage, random effects meta-analysis to determine the efficacy of treatment in reducing the duration of illness, estimated using differences in restricted mean survival time (RSMT) by treatment group. We also examined complications and safety.Results: We identified 5 trials including 2561 patients in the intent to treat (ITT) and 1598 in the intent to treat infected (ITTI) population. Overall, oseltamivir treatment significantly reduced the duration of illness in the ITTI population (RMST difference -17.6 hours 95% CI: -34.7 to -0.62 hours). In trials that enrolled patients without asthma, the difference was larger (-29.9 hours 95% CI -53.9 to -5.8 hours). Risk of otitis media was 34% lower in the ITTI population. Vomiting was the only adverse event with a significantly higher risk in the treatment group.Conclusion: Despite substantial heterogeneity in pediatric trials, we found that treatment with oseltamivir significantly reduced the duration of illness in those with influenza and lowered the risk of developing otitis media. Alternative endpoints may be required to evaluate the efficacy of oseltamivir in pediatric patients with asthma.</div

Estimation of Influenza Vaccine Effectiveness from Routine Surveillance Data

BACKGROUND: Influenza vaccines are reviewed each year, and often changed, in an effort to maintain their effectiveness against drifted influenza viruses. There is however no regular review of influenza vaccine effectiveness during, or at the end of, Australian influenza seasons. It is possible to use a case control method to estimate vaccine effectiveness from surveillance data when all patients in a surveillance system are tested for influenza and their vaccination status is known. METHODOLOGY/PRINCIPAL FINDINGS: Influenza-like illness (ILI) surveillance is conducted during the influenza season in sentinel general practices scattered throughout Victoria, Australia. Over five seasons 2003-7, data on age, sex and vaccination status were collected and nose and throat swabs were offered to patients presenting within three days of the onset of their symptoms. Swabs were tested using a reverse transcriptase polymerase chain reaction (RT-PCR) test. Those positive for influenza were sent to the World Health Organization (WHO) Collaborating Centre for Reference and Research on Influenza where influenza virus culture and strain identification was attempted. We used a retrospective case control design in five consecutive influenza seasons, and estimated influenza vaccine effectiveness (VE) for patients of all ages to be 53% (95% CI 38-64), but 41% (95% CI 19-57) adjusted for age group and year. The adjusted VE for all adults aged at least 20 years, the age groups for whom a benefit of vaccination could be shown, was 51% (95% CI 34-63). Comparison of VE estimates with vaccine and circulating strain matches across the years did not reveal any significant differences. CONCLUSIONS/SIGNIFICANCE: These estimates support other field studies of influenza vaccine effectiveness, given that theoretical considerations suggest that these values may underestimate true effectiveness, depending on test specificity and the ratio of the influenza ILI attack rate to the non-influenza ILI attack rate. Incomplete recording of vaccination status and under-representation of children in patients from whom a swab was collected limit the data. Improvements have been implemented for prospective studies

Evaluation of school absenteeism data for early outbreak detection, New York City

BACKGROUND: School absenteeism data may have utility as an early indicator of disease outbreaks, however their value should be critically examined. This paper describes an evaluation of the utility of school absenteeism data for early outbreak detection in New York City (NYC). METHODS: To assess citywide temporal trends in absenteeism, we downloaded three years (2001–02, 2002–03, 2003–04) of daily school attendance data from the NYC Department of Education (DOE) website. We applied the CuSum method to identify aberrations in the adjusted daily percent absent. A spatial scan statistic was used to assess geographic clustering in absenteeism for the 2001–02 academic year. RESULTS: Moderate increases in absenteeism were observed among children during peak influenza season. Spatial analysis detected 790 significant clusters of absenteeism among elementary school children (p < 0.01), two of which occurred during a previously reported outbreak. CONCLUSION: Monitoring school absenteeism may be moderately useful for detecting large citywide epidemics, however, school-level data were noisy and we were unable to demonstrate any practical value in using cluster analysis to detect localized outbreaks. Based on these results, we will not implement prospective monitoring of school absenteeism data, but are evaluating the utility of more specific school-based data for outbreak detection

Optimal Design of Intervention Studies to Prevent Influenza in Healthy Cohorts

Background: Influenza cohort studies, in which participants are monitored for infection over an epidemic period, are invaluable in assessing the effectiveness of control measures such as vaccination, antiviral prophylaxis and nonpharmaceutical interventions (NPIs). Influenza infections and illnesses can be identified through a number of approaches with different costs and logistical requirements. Methodology and Principal Findings: In the context of a randomized controlled trial of an NPI with a constrained budget, we used a simulation approach to examine which approaches to measuring outcomes could provide greater statistical power to identify an effective intervention against confirmed influenza. We found that for a short epidemic season, the optimal design was to collect respiratory specimens at biweekly intervals, as well as following report of acute respiratory illness (ARI), for virologic testing by reverse transcription polymerase chain reaction (RT-PCR). Collection of respiratory specimens only from individuals reporting ARI was also an efficient design particularly for studies in settings with longer periods of influenza activity. Collection of specimens only from individuals reporting a febrile ARI was less efficient. Collection and testing of sera before and after influenza activity appeared to be inferior to collection of respiratory specimens for RT-PCR confirmation of acute infections. The performance of RT-PCR was robust to uncertainty in the costs and diagnostic performance of RT-PCR and serological tests

Risk factors for acute respiratory tract infections in general practitioner patients in The Netherlands: a case-control study

<p>Abstract</p> <p>Background</p> <p>Acute respiratory tract infections (ARTI) are an important public health problem. Improved identification of risk factors might enable targeted intervention. Therefore we carried out a case-control study with the aim of identifying environmental risk factors for ARTI consultations in the Dutch general population.</p> <p>Methods</p> <p>A subset of patients visiting their GP in the period of 2000–2003 with an ARTI (cases) and age-matched controls (visiting for other complaints) were included in a case-control study. They were asked to complete a questionnaire about potential risk factors. Conditional logistic regression was used to calculate odds ratio's (OR) and 95% confidence intervals (CI) to estimate the independent effect of potential risk factors.</p> <p>Results</p> <p>A total of 493 matched pairs of case and control subjects were enrolled. Exposure to persons with respiratory complaints, both inside and outside the household, was found to be an independent risk factor for visiting a GP with an ARTI (respectively OR_adj= 1.9 and OR_adj= 3.7). Participants exposed to dampness or mould at home (OR_adj=0.5) were significantly less likely to visit their GP. In accordance with the general risk of consultations for ARTI, participants with a laboratory-confirmed ARTI who were exposed to persons with respiratory complaints outside the household were also significantly more likely to visit their GP (OR_adj=2.5).</p> <p>Conclusion</p> <p>This study confirmed that heterogeneity in the general population as well as in pathogens causing ARTI makes it complicated to detect associations between potential risk factors and respiratory infections. Whereas it may be difficult to intervene on the risk posed by exposure to persons with respiratory complaints, transmission of ARTI in the general population might be reduced by improved hygienic conditions.</p

Rapid detection of pandemic influenza in the presence of seasonal influenza

Background: Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland. Methods: We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data. Results: We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland. Conclusions: While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical

Incidence of Influenza in Healthy Adults and Healthcare Workers: A Systematic Review and Meta-Analysis

BACKGROUND: Working in healthcare is often considered a risk factor for influenza; however, this risk has not been quantified. We aimed to systematically review evidence describing the annual incidence of influenza among healthy adults and healthcare workers (HCWs). METHODS AND FINDINGS: We searched OVID MEDLINE (1950 to 2010), EMBASE (1947 to 2010) and reference lists of identified articles. Observational studies or randomized trials reporting full season or annual influenza infection rates for healthy, working age adult subjects and HCWs were included. Influenza infection was defined as a four-fold rise in antibody titer, or positive viral culture or polymerase chain reaction. From 24,707 citations, 29 studies covering 97 influenza seasons with 58,245 study participants were included. Pooled influenza incidence rates (IR) (95% confidence intervals (CI)) per 100 HCWs per season and corresponding incidence rate ratios (IRR) (95% CI) as compared to healthy adults were as follows. All infections: IR 18.7 (95% CI, 15.8 to 22.1), IRR 3.4 (95% CI, 1.2 to 5.7) in unvaccinated HCWs; IR 6.5 (95% CI, 4.6 to 9.1), IRR 5.4 (95% CI, 2.8 to 8.0) in vaccinated HCWs. Symptomatic infections: IR 7.5 (95% CI, 4.9 to 11.7), IRR 1.5 (95% CI, 0.4 to 2.5) in unvaccinated HCWs, IR 4.8 (95% CI, 3.2 to 7.2), IRR 1.6 (95% CI, 0.5 to 2.7) in vaccinated HCWs. CONCLUSIONS: Compared to adults working in non-healthcare settings, HCWs are at significantly higher risk of influenza