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Travelers to developing regions are at risk for development of influenza-like illness (ILI). Little is known of traveler and trip characteristics associated with the development of ILI. TravMil is a prospective observational study, enrolling subjects presenting to six military travel clinics or predeployment-screening sites. We analyzed pre- and post-travel surveys from travelers visiting regions outside of the continental United States, Western or Northern Europe, Canada, Australia, or New Zealand between January 2010 and March 2016. Influenza-like illness was defined as a self-reported fever associated with either sore throat or cough. Trip and traveler characteristics were analyzed to determine risk factors for the development of ILI. Two thousand nine hundred and thirty-two trips were recorded (55% male, median age 45 years, 69% white, 51% on vacation, median travel duration 17 days). The 2,337 trips included the number of self-reported influenza vaccinations in the preceding 5 years (median 5). Eleven percent of the trips were complicated by an ILI lasting a median of 5 days; 70% and 17% of these reported upper and lower respiratory tract infection, respectively, and 12% reported both. On multivariate analysis, increased risk of ILI was associated with female gender (odds ratio [OR]: 1.60 [confidence interval (CI): 1.25–2.05], P < 0.01), age (years) (OR: 1.01 [CI: 1.01–1.02], P < 0.01); and duration of travel (days) (OR: 1.01 [CI: 1.00–1.01], P < 0.01). Influenza-like illness is common in travelers, regardless of traveler characteristics, purpose of travel, destination, or season of year. Female gender, older age, and longer duration of travel were associated with an increased risk of ILI. Additional tools and strategies are needed to prevent ILI in international travelers.

An outbreak of influenza-like disease caused illness among 48 per cent of 173 female military recruits, 35 per cent of whom smoked cigarettes. The risk of influenza-like illness was greater in smokers (60.0 per cent) than in nonsmokers (41.6 per cent), with a risk ratio of 1.44 (95 per cent CL 1.03-2.01). Among those ill, a significantly greater proportion of smokers visited the clinic than nonsmokers. This could have been due to more severe illness among smokers, or to a greater tendency to visit the physician. The proportion of influenza-like disease attributable to smoking in this population was 13 per cent.

The reasons for the unprecedented mortality during the 1918 influenza pandemic remain poorly understood. We examined morbidity records from three military cohorts from years prior to and during the 1918 pandemic period to assess the effects of previous respiratory illnesses on experiences during the pandemic. Clinical registers and morbidity lists were examined to identify all medical encounters for acute respiratory illnesses in students at two U.S. military officer training academies and Australian soldiers deployed in Europe. Influenza-like illness prior to the major pandemic wave of 1918 predisposed Australian soldiers [relative risk (RR) 1·37, 95% confidence interval (CI) 1·18–1·60, P < 0·0001] and US officer trainees at West Point (RR 3·10, 95% CI 2·13–4·52, P < 0·0001) and Annapolis (RR 2·03, 95% CI 1·65–2·50, P < 0·0001) to increased risks of medically treated illnesses in late 1918. The findings suggest that susceptibility to and/or clinical expressions of the 1918 pandemic influenza virus depended on previous experiences with respiratory infectious agents. The findings are consistent with observations during the 2009 pandemic in Canada and may reflect antibody-dependent enhancement of influenza infection.

BACKGROUND: Viral respiratory infections are a common cause of hospitalization for younger, otherwise-healthy populations. In this study, we describe the epidemiology of influenza-like illness in non-elderly adults within the U.S. Military Health System (MHS) by pathogen and hospitalization status. METHODS: The Acute Respiratory Infection Consortium (ARIC) is a prospective cohort of patients with influenza-like illness within the MHS. Participants between 18 and 65 years of age were identified in outpatient settings between 2012 and 2017, and were excluded if pregnant, if reporting chronic cardiac, respiratory, renal, or neurologic disease, or if on long-term aspirin therapy. Demographics, nasopharyngeal swabs and symptom data were collected; swabs were tested for viral pathogens using a target-enriched multiplex PCR panel (TEM-PCR(TM), Diatherix LLC). Data were analyzed to compare clinical features and risks for hospitalization. RESULTS: 397 participants met inclusion criteria. 34 participants required hospitalization; 363 were outpatients. Median length of hospitalization was 2 days. A virus was identified in 58.4% of outpatients (OP) and 55.9% of inpatients (IP); coronaviruses (63/363), enteroviruses (50/363), and influenza A (73/363) predominated in OP, whereas influenza A predominated among IP (35.3%, 12/34). There were no significant differences between OP and IP in terms of age, gender, ethnicity, or tobacco use. IP were more likely to be obese (BMI ≥30, 43.3% vs. 20.5%, P = 0.004) and less likely to have received influenza vaccination (45.5% vs. 16.9%, P > 0.001). IP with influenza did not report more severe symptoms (chills, cough, sore throat, diarrhea, myalgia, or headache) on enrollment but were more likely to have fever (temperature ≥38.0⁰ C) than OP (92.9 vs. 57.1%, P = 0.014). CONCLUSION: Influenza A is the most frequently identified cause of hospitalization among healthy, non-elderly adults with viral respiratory infection. Although age and tobacco use may be risks for viral acquisition, they ...

BACKGROUND: Influenza-like illnesses (ILI) are common in military populations due to close living and working conditions, physical exertion, and exposure to novel viruses. The PAIVED trial aims to compare the effectiveness of 3 FDA approved influenza vaccines in active-duty military, retiree, and dependent populations, and will also provide information about the burden, impact, and severity of ILI. METHODS: Participants were enrolled in the 2018–2019 influenza season at 5 geographically diverse military facilities. Active duty, non-recruit military personnel, retirees, and dependents were randomized to receive influenza vaccine (egg-based, recombinant, or cell-culture derived) and then completed weekly electronic surveys throughout the influenza season. If a participant reported ILI symptoms during surveillance, 2 in-person visits with study personnel were scheduled for confirmed ILI. Nasal swabs and blood samples were collected for diagnostic and immunologic testing. RESULTS: Among the 852 non-recruit participants enrolled in PAIVED, 25% were active military, 36% retired military, and 39% dependents. Almost half (48%) were female, and 72% were white, 15% African American, 6% Asian, 4% multiple races, and 3% unknown or other race. 788 participants (92%) responded to at least one surveillance questionnaire. Participants reported 407 ILIs (Figure 1), of which 160 met the study case definition. Between 12 and 28% of the participants experienced an ILI during the surveillance period, and 12 people experienced 2 ILIs. Most sites reported a median 2–3 days of fever/feverishness or chills and 3–4 days of reduced activity associated with an ILI episode. No viruses were detected in 58% of nasal swabs, 1 virus in 40%, and 2 viruses in 1% of swabs (Figure 2 for pathogen data). CONCLUSION: During the period under study, ILIs were common with 1 in 6 participants experiencing a confirmed ILI, many of which were 6–8 days in duration. ILIs resulted in reduced activity, although few individuals reported missing work or school, a ...

International audience ; BackgroundThe Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.MethodsIn 2011/2012 Influenzanet launched a standardized common framework for data collection applied to seven European countries. Influenzanet participants were compared to the general population of the participating countries to assess the representativeness of the sample in terms of a set of demographic, geographic, socio-economic and health indicators.ResultsMore than 30,000 European residents registered to the system in the 2011/2012 season, and a subset of 25,481 participants were selected for this study. All age classes (10 years brackets) were represented in the cohort, including under 10 and over 70 years old. The Influenzanet population was not representative of the general population in terms of age distribution, underrepresenting the youngest and oldest age classes. The gender imbalance differed between countries. A counterbalance between gender-specific information-seeking behavior (more prominent in women) and Internet usage (with higher rates in male populations) may be at the origin of this difference. Once adjusted by demographic indicators, a similar propensity to commute was observed for each country, and the same top three transportation modes were used for six countries out of seven. Smokers were underrepresented in the majority of countries, as were individuals with diabetes; the representativeness of asthma prevalence and vaccination coverage for 65+ individuals in two successive seasons (2010/2011 and 2011/2012) varied between countries.ConclusionsExisting demographic and national datasets allowed the quantification of the participation biases of a large cohort for influenza-like-illness surveillance in the general population. Significant differences were found between Influenzanet participants and the general population. The quantified biases need to be taken into account in the analysis of Influenzanet epidemiological studies and provide indications on populations groups that should be targeted in recruitment efforts.

International audience ; BackgroundThe Internet is becoming more commonly used as a tool for disease surveillance. Similarly to other surveillance systems and to studies using online data collection, Internet-based surveillance will have biases in participation, affecting the generalizability of the results. Here we quantify the participation biases of Influenzanet, an ongoing European-wide network of Internet-based participatory surveillance systems for influenza-like-illness.MethodsIn 2011/2012 Influenzanet launched a standardized common framework for data collection applied to seven European countries. Influenzanet participants were compared to the general population of the participating countries to assess the representativeness of the sample in terms of a set of demographic, geographic, socio-economic and health indicators.ResultsMore than 30,000 European residents registered to the system in the 2011/2012 season, and a subset of 25,481 participants were selected for this study. All age classes (10 years brackets) were represented in the cohort, including under 10 and over 70 years old. The Influenzanet population was not representative of the general population in terms of age distribution, underrepresenting the youngest and oldest age classes. The gender imbalance differed between countries. A counterbalance between gender-specific information-seeking behavior (more prominent in women) and Internet usage (with higher rates in male populations) may be at the origin of this difference. Once adjusted by demographic indicators, a similar propensity to commute was observed for each country, and the same top three transportation modes were used for six countries out of seven. Smokers were underrepresented in the majority of countries, as were individuals with diabetes; the representativeness of asthma prevalence and vaccination coverage for 65+ individuals in two successive seasons (2010/2011 and 2011/2012) varied between countries.ConclusionsExisting demographic and national datasets allowed the quantification ...

Dynamic transmission models are essential to design and evaluate control strategies for airborne infections. Our objective was to develop a dynamic transmission model for seasonal influenza allowing to evaluate the impact of vaccinating specific age groups on the incidence of infection, disease and mortality. Projections based on such models heavily rely on assumed 'input' parameter values. In previous seasonal influenza models, these parameter values were commonly chosen ad hoc, ignoring between-season variability and without formal model validation or sensitivity analyses. We propose to directly estimate the parameters by fitting the model to age-specific influenza-like illness (ILI) incidence data over multiple influenza seasons. We used a weighted least squares (WLS) criterion to assess model fit and applied our method to Belgian ILI data over six influenza seasons. After exploring parameter importance using symbolic regression, we evaluated a set of candidate models of differing complexity according to the number of season-specific parameters. The transmission parameters (average R0, seasonal amplitude and timing of the seasonal peak), waning rates and the scale factor used for WLS optimization, influenced the fit to the observed ILI incidence the most. Our results demonstrate the importance of between-season variability in influenza transmission and our estimates are in line with the classification of influenza seasons according to intensity and vaccine matching. ; NG is beneficiary of a postdoctoral grant from the AXA Research Fund. LW acknowledges support from an interdisciplinary doctoral grant of the University of Antwerp (Bijzonder Onderzoeksfonds, BOF). YV acknowledges support from a doctoral grant of Hasselt University (BOF11D04FAEC). NH acknowledges support from the Antwerp University Scientific Chair in Evidence-Based Vaccinology, financed in 2009-2014 by an unrestricted gift from Pfizer. Support from the IAP Research Network P7/06 of the Belgian State (Belgian Science Policy) is gratefully acknowledged. This study was co-financed by the Health Care Knowledge Centre (KCE) of the Belgian Federal government and benefited from discussions held as part of the KCE's expert committee and with Joke Bilcke, Adriaan Blommaert and Pieter Neels. We thank Francoise Wuillaume, Viviane van Casteren and Isabelle Thomas (Scientific Institute for Public Health) for collecting and providing sentinel data on ILI and influenza, and Nancy Thiry for useful discussions. The computational resources and services used in this work were provided by the Hercules Foundation and the Flemish Government - Department EWI. We thank Geert Jan Bex for support with using the VSC cluster.

Intimate Partner Violence (IPV) is a major public health issue, including during pregnancy where it poses a serious risk to the woman's health. Influenza-Like Illness (ILI) also causes significant morbidity for women during pregnancy. It may be possible that ILI in pregnancy is associated with IPV, and that depression and trauma history play a role in the connection. 524 Australia-born women and 578 refugee-background women participated in the study. Baseline participants were randomly recruited and interviewed from antenatal clinics between January 2015 and March 2016, and they were reinterviewed six months post-partum. Bivariate and path analysis were used to assess links between IPV, depression and ILI. One in 10 women (10%; 111 out of 1102) reported ILI during their pregnancy period and this rate was significantly (p < 0.001) higher for women born in conflict-affected countries (13%; 76 out of 578) as compared to Australian-born women (7%; 35 out of 524). In both groups, Time 1 traumatic events, IPV and depression symptoms were significantly associated with ILI at Time 2. A significant association between IPV at Time 1 and ILI at Time 2 was fully mediated by depression symptoms at Time 1 (Beta = 0.36 p < 0.001). A significant direct path was shown from depression symptoms to ILI (Beta = 0.26, p < 0.001). Regardless of migration history, pregnant women who have experienced IPV and depression are more likely to report influenza-like symptoms in pregnancy. This may suggest that trauma and depression negatively affect immunity, although it could also indicate a connection between depressive symptoms and physical experiences of ILI.

Rapidly characterizing the amplitude and variability in transmissibility of novel human influenza strains as they emerge is a key public health priority. However, comparison of early estimates of the basic reproduction number during the 2009 pandemic were challenging because of inconsistent data sources and methods. Here, we define and analyze influenza-like-illness (ILI) case data from 2009–2010 for the 50 largest spatially distinct US military installations (military population defined by zip code, MPZ). We used publicly available data from non-military sources to show that patterns of ILI incidence in many of these MPZs closely followed the pattern of their enclosing civilian population. After characterizing the broad patterns of incidence (e.g. single-peak, double-peak), we defined a parsimonious SIR-like model with two possible values for intrinsic transmissibility across three epochs. We fitted the parameters of this model to data from all 50 MPZs, finding them to be reasonably well clustered with a median (mean) value of 1.39 (1.57) and standard deviation of 0.41. An increasing temporal trend in transmissibility (, p-value: 0.013) during the period of our study was robust to the removal of high transmissibility outliers and to the removal of the smaller 20 MPZs. Our results demonstrate the utility of rapidly available – and consistent – data from multiple populations.

The impact of HIV on influenza-like illness (ILI) has been incompletely described in the era of combination antiretroviral therapy, particularly in the post-H1N1 pandemic period. This analysis informs on ILI in an otherwise healthy, predominantly outpatient cohort of adults with HIV in the USA. From September 2010 to March 2015, this multisite observational cohort study enrolled otherwise healthy adults presenting to a participating US military medical center with ILI, a subset of whom were HIV positive. Demographics, clinical data, and self-reported symptom severity were ascertained, and enrollees completed a daily symptom diary for up to 10 days. 510 men were included in the analysis; 50 (9.8%) were HIV positive. Subjects with HIV were older and less likely to be on active duty. Rhinovirus and influenza A were the most commonly identified pathogens. Moderate–severe diarrhea (p<0.001) and fatigue (p=0.01) were more frequently reported by HIV-positive men. HIV positivity was associated with higher gastrointestinal scores, but not other measures of ILI symptom severity, after controlling for age, race, military status, and influenza season. Few were hospitalized. HIV-positive subjects had more influenza B (p=0.04) and were more likely to receive antivirals (32% vs 6%, p<0.01). Antiviral use was not significantly associated with symptom scores when accounting for potential confounders. In this predominantly outpatient cohort of adult men, HIV had minimal impact on ILI symptom severity. Despite similar illness severity, a higher percentage of subjects with HIV reported undergoing antiviral treatment for ILI, likely reflecting differences in prescribing practices.Trial registration number: NCT01021098.