Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for ‘nowcasting’ (integrated detection and prediction) of influenza activity are warranted.

Non-steroidal anti-inflammatory drugs (NSAIDs) may inhibit antibody production by peripheral blood mononuclear cells; one consequence of this could be decreased effectiveness of vaccines in NSAID users. Because many older adults use low-dose aspirin for primary or secondary prevention of coronary events, any inhibitory effect of aspirin on vaccine immune response could reduce the benefits of vaccination programmes in older adults. We tested whether immune response to vaccination differed between users vs. non-users of low-dose aspirin, using data from four randomized trials of monovalent 2009 pandemic influenza A(H1N1) vaccine. Geometric mean haemagglutination inhibition antibody titres were not significantly lower in low-dose aspirin users compared to non-users. Our results provide reassurance that influenza vaccination effectiveness is probably not reduced in older adults taking chronic low-dose aspirin.

Objectives: Vaccinating healthy children is proposed as a strategy to produce a herd effect and protect vulnerable groups. The Hutterite Influenza Prevention Study investigated this strategy, comparing communities with or without childhood influenza immunization programs. There are costs associated with vaccination therefore there may be a trade-off between these costs and the benefits of avoiding influenza cases. This evaluation estimates the cost-effectiveness of immunizing only healthy children in preventing cases of influenza within entire communities.

Methods: Effect data and resource utilization were collected during the trial. Cost data were collected from payer, literature and Internet sources. A two-stage bootstrap (TSB) with shrinkage correction was used to estimate average costs and effects. The incremental cost effectiveness ratio (ICER) and sample uncertainty around this estimate were calculated from the TSB results.

Results: Mean costs per patient for the treatment and control arms were $69.07 and $32.66 (difference $36.41). Mean number of influenza cases for the treatment and control arms were 0.04 and 0.27 (difference 0.23). ICER was $164.12 ($28.38, $2767.75) per case of influenza averted.

Conclusions: Immunizing healthy children for influenza is more costly, yet more effective than no immunization in preventing cases in the sample. At a cost of $164.12 to prevent a case of influenza, immunizing healthy children to protect all community members may be considered costeffective. Estimated results are conservative as the influenza season was mild and the sample population was healthy. In a more severe season with a less healthy population the ICER is expected to decrease.

Continued monitoring of the seriousness of influenza viruses is a public health priority. We applied time-series regression models to data on cardio-respiratory mortality rates in Hong Kong from 2001 to 2011. We used surveillance data on outpatient consultations for influenza-like illness, and laboratory detections of influenza types/subtypes to construct proxy measures of influenza activity. In the model we allowed the regression coefficients for influenza to drift over time, and adjusted for temperature and humidity. The regression coefficient for influenza A(H3N2) increased significantly in 2005. The regression coefficients for influenza A(H1N1) and B were relatively stable over the period. Our model suggested an increase in seriousness of A(H3N2) in 2005, the year after the appearance of the A/Fujian/411/2002(H3N2)-like virus when the drifted A/California/7/2004(H3N2)-like virus appeared. Ongoing monitoring of mortality and influenza activity could permit identification of future changes in seriousness of influenza virus infections.

Objective: The novel H1N1 influenza pandemic renewed the concern that during a severe pandemic illness, critical care and mechanical ventilation resources will be inadequate to meet the needs of patients. Several published protocols address the need to triage patients for access to ventilator resources. However, to our knowledge, none of these has addressed the pediatric populations.

Methods: We used a systematic review of the pediatric critical care literature to evaluate pediatric critical care prognosis and multisystem organ failure scoring systems. We used multiple search engines, including MEDLINE and EMBASE, using a search for terms and key words including including multiple organ failure, multiple organ dysfunction, PELOD, PRISM III, pediatric risk of mortality score, pediatric logistic organ dysfunction, pediatric index of mortality pediatric multiple organ dysfunction score, “child+multiple organ failure + scoring system. ” Searches were conducted in the period January 2010-February 2010.

Results: Of the 69 papers reviewed, 22 were used. Five independently derived scoring systems were evaluated for use in a respiratory pandemic ventilator triage protocol. The Pediatric Logistic Organ Dysfunction (PELOD) scoring system was the most appropriate for use in such a triage protocol.

Conclusions: We present a pediatric-specific ventilator triage protocol using the PELOD scoring system to complement the NY State adult triage protocol. Further evaluation of pediatric scoring systems is imperative to ensure appropriate triage of pediatric patients.

(Disaster Med Public Health Preparedness. 2012;6:131–137)

We analysed long-term epidemiological trends in influenza-like illness (ILI) in The Netherlands and used an ecological analysis to estimate its relationship with age, influenza vaccination, and virological aspects. This study used data from weekly ILI consultation reports from sentinel general practitioners (1986/1987 to 2006/2007), virological data from sentinel ILI patients (1992/1993 to 2006/2007), and data for influenza vaccine uptake (1991–2005). The incidence of ILI consultations, although varying during the study period, was estimated to decrease in the total population by 12·2/10 000 persons each season (95% CI 8·6–15·9). Uptake of influenza vaccination in people aged ⩾65 years (elderly) increased from 28% in 1991 to >70% since 1997. ILI incidence in the elderly declined by 1·7/10 000 persons (P=0·05) per percentage vaccine uptake per season. The decline in ILI incidence over the last 20 years could be related to the increased vaccine uptake. However, insufficient data were present to assess the impact of other potential contributing factors, such as diminished fitness of influenza viruses and changes in consulting behaviour.