Nosocomial Influenza: What Have We Missed?

Contagion, October 2016, Volume 1, Issue 1

Many concurrent interventions are needed to control nosocomial influenza (NI). The determinants facilitating its spread and constraint have been reported.


However, certain issues in NI “natural history” were raised recently at the ASM 2016 Microbe Conference (June 16-20, 2016: in Boston, MA). We have summarized some of them here, based on our experience. Exposure to the influenza virus can occur before and during hospitalization. However, the determinants of community exposure differ from those of hospital ex­posure. In addition, some patients might be exposed outside shortly before hospitalization and diagnosed with influenza shortly after hospital admission. It is im­portant to identify sources of exposure because control measures and transmission investigations will diverge. Unfortunately, criteria defining NI have not yet been standardized.

The time interval between hospital admission and on­set ranges from 24 to 72 hours, but can be less than 24 hours in some situations. The 48-hour period between admission and diagnosis, often cited as an epidemiolog­ical definition of bacterial nosocomial infections, cannot be applied to NI.

A standardized definition is needed because attack rates may be impacted by it, sources of exposure may vary in relation to this time interval, and patient char­acteristics may change by time periods adopted for diagnosis. In addition, hospital-attributable risk can be questioned, in terms of legalities, depending on the definition accepted.

A recent survey, conducted in 55 of the 218 centers of the Society for Healthcare Epidemiology of America Research Network, determined that 76% of the centers adopted a standardized definition of NI based on clini­cal (24%), virological (31%) and clinical-virological (45%) features.


The mean time threshold between admission and onset considered in the definition of NI was 57.1 hours (median 48.0 hours, range 24-96 hours).

The NI definition may be adapted according to objec­tives targeted: early hospital warning, surveillance net­works, collaborative studies, intervention assessment, site comparisons, and preventive measures (clinical tri­als), including vaccination. However, the NI definition is based on clinical features, and is therefore not suitable for asymptomatic cases, which might contribute to the spread of influenza.

Asymptomatic fraction is the proportion of asymp­tomatic influenza virus infections. This disease stage is important to estimate influenza incidence, taking symptomatic and asymptomatic cases into account. Knowledge of infectiousness—to optimize control strategies—may be driven by the presence or absence of symptomatic cases. The asymptomatic fraction is es­timated to include 20% to 50% of patients.


In outbreak investigations, point estimates of the asymptomatic fraction have ranged from 4% to 28%, with a pooled mean of 16% (95% CI, 13%-19%). In surveillance situ­ations, point estimates of the asymptomatic fraction ranged from 65% to 85%. Estimation of the asymptom­atic fraction is affected by study design (outbreak inves­tigation or planned surveillance system).

Asymptomatic or symptomatic patients are sources of influenza infection for others through individual contact. The frequency and duration of contacts between individ­uals are major elements in the transmission process. We have reported some results with radio-frequency iden­tification devices complemented by repeat virological sampling. We observed nosocomial transmission mostly when contact duration and frequency increased.


Some supercontactors were found, but around 40% of contacts involved only 6 out of a total 47 healthcare professionals (HCPs). If HCP supercontactors are infected by influen­za, they might become “superspreaders.


The issues cited above underscore the need of multiple interventions and adapted preventive policies required at various levels for NI control.


Determinants at the community level include


outbreak intensity; influenza incidence among specific populations most likely to be hospitalized; vaccine promotion, coverage, and effective­ness; circulating viral strains; and general population ed­ucation (hand hygiene, etc).

At the hospital level,


the following determinants need to be considered: vaccine promotion, training, and ed­ucation (hand hygiene, droplet precautions, etc); patient flow management; bed and care organization; NI surveil­lance and early warning; and respiratory hygiene/cough etiquette. At the unit or ward level,


the following deter­minants will impact NI: information on NI given to HCPs, patients, and visitors; HCP and patient vaccination rates; hand hygiene practices; droplet precautions; antiviral prophylaxis; encouraging ill HCPs to stay home; limiting admissions and visits; cohorting of patients, if any; and influenza diagnosis policies. Finally, at the individual lev­el, vaccination, vaccine promotion, antiviral treatment, limited patient circulation, droplet precautions, antiviral use, and HCPs not working because of illness are import­ant determinants—but the list is not exhaustive.


In conclusion, NI control can be improved with ample epidemiological data for a better understanding of NI spread. Hygiene measures need to include controlling cross-transmission and droplet precautions. HCP immu­nization is a key determinant because HCPs can be both recipients and sources of NI for patients. Therefore, NI control will be also improved with a better knowledge of epidemiological links between community and hospitals for better warning and anticipation.

Philippe Vanhems, MD, PhD, is the head of the Department of Infection Control, Epidemiol­ogy and Prevention of Hôpital Edouard Herriot at Lyon Univer­sity hospitals. He is also profes­sor of epidemiology and public health at Lyon Medical school (Université Claude Bernard). His main research topics are the epidemiology of infectious diseases and methodology for clinical studies.Thomas Bénet, MD, MPH, is a public health physician and epidemiologist. He works in the Department of Infection Control, Epidemiology and Prevention of Hôpital Edouard Herriot at Lyon University hospitals. Dr Bénet’s research interests focus on the epidemiology of infectious diseases and particularly on hospital epidemiology.


1. Maltezou HC. Nosocomial influenza: new concepts and prac­tice. Curr Opin Infect Dis. 2008;21(4):337-343. doi: 10.1097/ QCO.0b013e3283013945.

2. Vanhems P, Bénet T, Munier-Marion E. Nosocomial influenza: encouraging insights and future challenges. Curr Opin Infect Dis. 2016;29(4):366-372. doi: 10.1097/QCO.0000000000000287.

3. Munier-Marion ET, Vanhems P. Definition of healthcare-associated influenza: criteria considered by SHEA Research Network participants. Presented at: Society for Healthcare Epidemiology of America Confer­ence; May 2016; Atlanta, GA. Abstract No. P633.

4. Leung NH, Xu C, Ip DK, Cowling BJ. Review article: the fraction of influenza virus infections that are asymptomatic: a systematic review and meta-analysis. Epidemiology. 2015;26(6):862-872. doi: 10.1097/ EDE.0000000000000340.

5. Vanhems P, Barrat A, Cattuto C, et al. Estimating potential infec­tion transmission routes in hospital wards using wearable proximi­ty sensors published correction appears in PLoS One. 2013;8(9). doi: 10.1371/annotation/b20d3cec-62b7-44ec-9150-8a06a9b30a9b. PLoS One. 2013;8(9):e73970. doi: 10.1371/journal.pone.0073970. eCollec­tion 2013.

6. Voirin N, Payet C, Barrat A, et al. Combining high-resolution contact data with virological data to investigate influenza transmission in a tertiary care hospital. Infect Control Hosp Epidemiol. 2015;36(3):254- 260. doi: 10.1017/ice.2014.53.

7. Oussaid N, Voirin N, Régis C, et al. Contacts between health care workers and patients in a short-stay geriatric unit during the peak of a seasonal influenza epidemic compared with a nonepidem­ic period. Am J Infect Control. 2016;44(8):905-909. doi: 10.1016/j. ajic.2016.02.002.