Risk of Severe Influenza Among Adults With Chronic Medical Conditions

BACKGROUND

Severe influenza illness is presumed more common in adults with chronic medical conditions (CMCs), but evidence is sparse and often combined into broad CMC categories.

METHODS

Residents (aged 18-80 years) of Central and South Auckland hospitalized for World Health Organization-defined severe acute respiratory illness (SARI) (2012-2015) underwent influenza virus polymerase chain reaction testing. The CMC statuses for Auckland residents were modeled using hospitalization International Classification of Diseases, Tenth Revision codes, pharmaceutical claims, and laboratory results. Population-level influenza rates in adults with congestive heart failure (CHF), coronary artery disease (CAD), cerebrovascular accidents (CVA), chronic obstructive pulmonary disease (COPD), asthma, diabetes mellitus (DM), and end-stage renal disease (ESRD) were calculated by Poisson regression stratified by age and adjusted for ethnicity.

RESULTS

Among 891 276 adults, 2435 influenza-associated SARI hospitalizations occurred. Rates were significantly higher in those with CMCs compared with those without the respective CMC, except for older adults with DM or those aged <65 years with CVA. The largest effects occurred with CHF (incidence rate ratio [IRR] range, 4.84-13.4 across age strata), ESRD (IRR range, 3.30-9.02), CAD (IRR range, 2.77-10.7), and COPD (IRR range, 5.89-8.78) and tapered with age.

CONCLUSIONS

Our findings support the increased risk of severe, laboratory-confirmed influenza disease among adults with specific CMCs compared with those without these conditions.

Risk of Severe Influenza Among Adults With Chronic Medical Conditions

BACKGROUND

Severe influenza illness is presumed more common in adults with chronic medical conditions (CMCs), but evidence is sparse and often combined into broad CMC categories.

METHODS

Residents (aged 18-80 years) of Central and South Auckland hospitalized for World Health Organization-defined severe acute respiratory illness (SARI) (2012-2015) underwent influenza virus polymerase chain reaction testing. The CMC statuses for Auckland residents were modeled using hospitalization International Classification of Diseases, Tenth Revision codes, pharmaceutical claims, and laboratory results. Population-level influenza rates in adults with congestive heart failure (CHF), coronary artery disease (CAD), cerebrovascular accidents (CVA), chronic obstructive pulmonary disease (COPD), asthma, diabetes mellitus (DM), and end-stage renal disease (ESRD) were calculated by Poisson regression stratified by age and adjusted for ethnicity.

RESULTS

Among 891 276 adults, 2435 influenza-associated SARI hospitalizations occurred. Rates were significantly higher in those with CMCs compared with those without the respective CMC, except for older adults with DM or those aged <65 years with CVA. The largest effects occurred with CHF (incidence rate ratio [IRR] range, 4.84-13.4 across age strata), ESRD (IRR range, 3.30-9.02), CAD (IRR range, 2.77-10.7), and COPD (IRR range, 5.89-8.78) and tapered with age.

CONCLUSIONS

Our findings support the increased risk of severe, laboratory-confirmed influenza disease among adults with specific CMCs compared with those without these conditions.

Risk Factors and Attack Rates of Seasonal Influenza Infection: Results of the Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS) Seroepidemiologic Cohort Study

Background

Understanding the attack rate of influenza infection and the proportion who become ill by risk group is key to implementing prevention measures. While population-based studies of antihemagglutinin antibody responses have been described previously, studies examining both antihemagglutinin and antineuraminidase antibodies are lacking.

Methods

In 2015, we conducted a seroepidemiologic cohort study of individuals randomly selected from a population in New Zealand. We tested paired sera for hemagglutination inhibition (HAI) or neuraminidase inhibition (NAI) titers for seroconversion. We followed participants weekly and performed influenza polymerase chain reaction (PCR) for those reporting influenza-like illness (ILI).

Results

Influenza infection (either HAI or NAI seroconversion) was found in 321 (35% [95% confidence interval, 32%-38%]) of 911 unvaccinated participants, of whom 100 (31%) seroconverted to NAI alone. Young children and Pacific peoples experienced the highest influenza infection attack rates, but overall only a quarter of all infected reported influenza PCR-confirmed ILI, and one-quarter of these sought medical attention. Seroconversion to NAI alone was higher among children aged <5 years vs those aged ≥5 years (14% vs 4%; P < .001) and among those with influenza B vs A(H3N2) virus infections (7% vs 0.3%; P < .001).

Conclusions

Measurement of antineuraminidase antibodies in addition to antihemagglutinin antibodies may be important in capturing the true influenza infection rates.

The MSM program: web-based statistics package for estimating usual dietary intake using the Multiple Source Method

BACKGROUND/OBJECTIVES

The Multiple Source Method (MSM) is a new statistical method for estimating usual dietary intake including episodically consumed foods on the basis of two or more short-term measurements such as 24-h dietary recalls. Optional information regarding habitual use or non-use of a food can be included as a covariate in the model estimating the intake, as well as a parameter for identifying consumers and non-consumers. The objective was to implement the MSM algorithms into an easy-to-use statistical program package.

SUBJECTS/METHODS

The implementation was realized as a web-based application using the Perl application framework Catalyst. As the engine for the statistical calculations, the R system was used. To allow simultaneous use of the program by different users, a multiuser system with a resource bag pattern design was implemented.

RESULTS

We established a software program that implements the algorithms of the MSM and allows interactive usage of the method, using standard web technologies. The program is hosted on a website established at the DIFE and can be accessed at https://nugo.dife.de/msm. The communication between users and the program web site is encrypted, securing transmitted data against unauthorized use. Users can interactively import several data sets, define the analysis model, review and export results and graphs. The use of the program is supported by online help and a user guide.

CONCLUSIONS

The MSM website provides a program package that allows nutritional scientists to calculate usual dietary intakes by combining short-term and long-term measurements (multiple sources). It promotes simple access to the MSM to estimate usual food intake for individuals and populations.

Estimating usual food intake distributions by using the multiple source method in the EPIC-Potsdam Calibration Study

Estimating usual food intake distributions from short-term quantitative measurements is critical when occasionally or rarely eaten food groups are considered. To overcome this challenge by statistical modeling, the Multiple Source Method (MSM) was developed in 2006. The MSM provides usual food intake distributions from individual short-term estimates by combining the probability and the amount of consumption with incorporation of covariates into the modeling part. Habitual consumption frequency information may be used in 2 ways: first, to distinguish true nonconsumers from occasional nonconsumers in short-term measurements and second, as a covariate in the statistical model. The MSM is therefore able to calculate estimates for occasional nonconsumers. External information on the proportion of nonconsumers of a food can also be handled by the MSM. As a proof-of-concept, we applied the MSM to a data set from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Calibration Study (2004) comprising 393 participants who completed two 24-h dietary recalls and one FFQ. Usual intake distributions were estimated for 38 food groups with a proportion of nonconsumers > 70% in the 24-h dietary recalls. The intake estimates derived by the MSM corresponded with the observed values such as the group mean. This study shows that the MSM is a useful and applicable statistical technique to estimate usual food intake distributions, if at least 2 repeated measurements per participant are available, even for food groups with a sizeable percentage of nonconsumers.