Economic evaluations of interventions against influenza at workplaces: systematic review.

BACKGROUND: The burden of influenza is mostly felt by employees and employers because of increased absenteeism rates, loss of productivity and associated direct costs. Even though interventions against influenza among working adults are effective, patronage and compliance to these measures especially vaccination are low compared to other risk groups. AIMS: This study was aimed to assess evidence of economic evaluations of interventions against influenza virus infection among workers or in the workplace setting. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guideline for systematic reviews was followed. Three databases, PubMed, Web of Science and EconLit, were searched using keywords to identify relevant articles from inception till 25 October 2020. Original peer-reviewed papers that conducted economic evaluations of influenza interventions using cost-benefit, cost-effectiveness or cost-utility analysis methods focused on working-age adults or work settings were eligible for inclusion. Two independent teams of co-authors extracted and synthesized data from identified studies. RESULTS: Twenty-four articles were included: 21 were cost-benefit analyses and 3 examined cost-effectiveness analyses. Two papers also presented additional cost-utility analysis. Most of the studies were pharmaceutical interventions (n = 23) primarily focused on vaccination programs while one study was a non-pharmaceutical intervention examining the benefit of paid sick leave. All but two studies reported that interventions against influenza virus infection at the workplace were cost-saving and cost-effective regardless of the analytic approach. CONCLUSIONS: Further cost-effectiveness research in non-pharmaceutical interventions against influenza in workplace settings is warranted. There is a need to develop standardized methods for reporting economic evaluation methods to ensure comparability and applicability of future research findings.

Ecologic association between influenza and COVID-19 mortality rates in European countries.

Ecologic studies investigating COVID-19 mortality determinants, used to make predictions and design public health control measures, generally focused on population-based variable counterparts of individual-based risk factors. Influenza is not causally associated with COVID-19, but shares population-based determinants, such as similar incidence/mortality trends, transmission patterns, efficacy of non-pharmaceutical interventions, comorbidities and underdiagnosis. We investigated the ecologic association between influenza mortality rates and COVID-19 mortality rates in the European context. We considered the 3-year average influenza (2014-2016) and COVID-19 (31 May 2020) crude mortality rates in 34 countries using EUROSTAT and ECDC databases and performed correlation and regression analyses. The two variables - log transformed, showed significant Spearman's correlation ρ = 0.439 (P = 0.01), and regression coefficients, b = 0.743 (95% confidence interval, 0.272-1.214; R2 = 0.244; P = 0.003), b = 0.472 (95% confidence interval, 0.067-0.878; R2 = 0.549; P = 0.02), unadjusted and adjusted for confounders (population size and cardiovascular disease mortality), respectively. Common significant determinants of both COVID-19 and influenza mortality rates were life expectancy, influenza vaccination in the elderly (direct associations), number of hospital beds per population unit and crude cardiovascular disease mortality rate (inverse associations). This analysis suggests that influenza mortality rates were independently associated with COVID-19 mortality rates in Europe, with implications for public health preparedness, and implies preliminary undetected SARS-CoV-2 spread in Europe.

Parental perspectives on hand, foot, and mouth disease among children in Hong Kong: a longitudinal study.

Hand, foot, and mouth disease (HFMD), usually a self-limiting illness for young children, could cause a significant burden for parents because it can take up to 1-2 weeks for a sick child to recover. We conducted a two-wave longitudinal study over one summer peak season (May-July 2014) of HFMD to examine parents' HFMD-related risk perceptions and protective responses. In total, 618 parents with at least one child aged ⩽12 years, recruited using randomly-dialled household telephone calls completed the baseline survey interview, 452 of whom subsequently completed the follow-up survey. Around two-thirds of participants perceived the chance of their child being infected by HFMD was 'zero/very small/small' but the likelihood of being hospitalized once infected was 'somewhat likely/likely/very likely'. At follow-up, 82% reported washing child's hands frequently (Hygiene), 16% would keep their child away from school if HFMD cases were identified in school (Distancing) and 23% were 'very likely/certainly' to take the child for HFMD vaccination if available (Vaccination). Anticipated regret was consistently the strongest predictor for Hygiene (OR 3.34), and intention of Distancing (OR 2.58) and Vaccination (OR 3.16). Interventions focusing on anticipated regret may be effective to promote protective behaviour against HFMD among parents for their children.

The role of symptomatic presentation in influenza A transmission risk.

Computer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods. It was found that the presence of particular respiratory symptoms in an index case does not influence transmission probabilities, with the exception of child-to-child transmission where the donor has phlegm or a phlegmy cough.

Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

Quantifying homologous and heterologous antibody titre rises after influenza virus infection.

Most influenza virus infections are associated with mild disease. One approach to estimate the occurrence of influenza virus infections in individuals is via repeated measurement of humoral antibody titres. We used baseline and convalescent antibody titres measured by haemagglutination inhibition (HI) and viral neutralization (VN) assays against influenza A(H1N1), A(H3N2) and B viruses to investigate the characteristics of antibody rises following virologically confirmed influenza virus infections in participants in a community-based study. Multivariate models were fitted in a Bayesian framework to characterize the distribution of changes in antibody titres following influenza A virus infections. In 122 participants with PCR-confirmed influenza A virus infection, homologous antibody titres rose by geometric means of 1·2- to 10·2-fold after infection with A(H1N1), A(H3N2) and A(H1N1)pdm09. Significant cross-reactions were observed between A(H1N1)pdm09 and seasonal A(H1N1). Antibody titre rises for some subtypes and assays varied by age, receipt of oseltamivir treatment, and recent receipt of influenza vaccination. In conclusion, we provided a quantitative description of the mean and variation in rises in influenza virus antibody titres following influenza virus infection. The multivariate patterns in boosting of antibody titres following influenza virus infection could be taken into account to improve estimates of cumulative incidence of infection in seroepidemiological studies.

Real-time estimation of the hospitalization fatality risk of influenza A(H1N1)pdm09 in Hong Kong.

During the early stage of an epidemic, timely and reliable estimation of the severity of infections are important for predicting the impact that the influenza viruses will have in the population. We obtained age-specific deaths and hospitalizations for patients with laboratory-confirmed H1N1pdm09 infections from June 2009 to December 2009 in Hong Kong. We retrospectively obtained the real-time estimates of the hospitalization fatality risk (HFR), using crude estimation or allowing for right-censoring for final status in some patients. Models accounting for right-censoring performed better than models without adjustments. The risk of deaths in hospitalized patients with confirmed H1N1pdm09 increased with age. Reliable estimates of the HFR could be obtained before the peak of the first wave of H1N1pdm09 in young and middle-aged adults but after the peak in the elderly. In the next influenza pandemic, timely estimation of the HFR will contribute to risk assessment and disease control.

Assessment of the severity of Ebola virus disease in Sierra Leone in 2014-2015.

The current Ebola virus disease (EVD) epidemic in West Africa is unprecedented in scale, and Sierra Leone is the most severely affected country. The case fatality risk (CFR) and hospitalization fatality risk (HFR) were used to characterize the severity of infections in confirmed and probable EVD cases in Sierra Leone. Proportional hazards regression models were used to investigate factors associated with the risk of death in EVD cases. In total, there were 17 318 EVD cases reported in Sierra Leone from 23 May 2014 to 31 January 2015. Of the probable and confirmed EVD cases with a reported final outcome, a total of 2536 deaths and 886 recoveries were reported. CFR and HFR estimates were 74·2% [95% credibility interval (CrI) 72·6-75·5] and 68·9% (95% CrI 66·2-71·6), respectively. Risks of death were higher in the youngest (0-4 years) and oldest (⩾60 years) age groups, and in the calendar month of October 2014. Sex and occupational status did not significantly affect the mortality of EVD. The CFR and HFR estimates of EVD were very high in Sierra Leone.

Breast cancer incidence and mortality in a transitioning Chinese population: current and future trends.

BACKGROUND: Projections of future trends in cancer incidence and mortality are important for public health planning. METHODS: By using 1976-2010 data in Hong Kong, we fitted Poisson age-period-cohort models and made projections for future breast cancer incidence and mortality to 2025. RESULTS: Age-standardised breast cancer incidence (/mortality) is projected to increase (/decline) from 56.7 (/9.3) in 2011-2015 to 62.5 (/8.6) per 100,000 women in 2021-2025. CONCLUSIONS: The incidence pattern may relate to Hong Kong's socio-economic developmental history, while falling mortality trends are, most likely, due to improvements in survival from treatment advancement and improved health service delivery.

Analysis of potential changes in seriousness of influenza A and B viruses in Hong Kong from 2001 to 2011.

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.

Multivariate analysis of factors affecting the immunogenicity of trivalent inactivated influenza vaccine in school-age children.

We examined factors affecting the immunogenicity of trivalent inactivated influenza vaccination (TIV) in children using the antibody titres of children participating in a Hong Kong community-based study. Antibody titres of strains included in the 2009-2010 northern hemisphere TIV [seasonal A(H1N1), seasonal A(H3N2) and B (Victoria lineage)] and those not included in the TIV [2009 pandemic A(H1N1) and B (Yamagata lineage)] were measured by haemagglutination inhibition immediately before and 1 month after vaccination. Multivariate regression models were fitted in a Bayesian framework to characterize the distribution of changes in antibody titres following vaccination. Statistically significant rises in geometric mean antibody titres were observed against all strains, with a wide variety of standard deviations and correlations in rises observed, with the influenza type B antibodies showing more variability than the type A antibodies. The dynamics of antibody titres after vaccination can be used in more complex models of antibody dynamics in populations.