Influenza-like Illness Attack Rates Research Articles

FluTracking: Weekly online community-based surveillance of influenza-like illness in Australia, 2019 Annual Report

FluTracking provided evidence for an early, long, but moderate influenza season in the Australian community compared to prior years. Influenza-like illness (ILI) activity in 2019 peaked earlier (week ending 16 June) than any season on record in FluTracking data. ILI attack rates were above average early in the 2019 season (peak of 2.2%), and the duration of peak activity was longer than most prior years. However, ILI attack rates were lower than the five-year average in the latter half of the season. FluTracking participants reported higher vaccination coverage in 2019 (73.3%) compared with 2018 (65.7%), with the most notable increase in children aged less than five years (69.3% in 2019, compared to 55.6% in 2018). The total 2019 count of laboratory notifications (312,945) was higher than prior years (2007 onwards), and the peak weekly count of 18,429 notifications in 2019 was also higher than all prior years, except 2017. FluTracking makes a comparison to another surveillance system each year. The peak weekly percentage of calls to HealthDirect that were influenza-related was higher in 2019 (12.8%) than for 2014-2018 (range of 8.2-11.4% for peak week of activity each year). FluTracking participants reported a 2.5 times increase in influenza testing from 2018 to 2019 and a 1.5 times increase from 2017. Although 2019 was of higher activity and severity than 2018, Flutracking data indicates that 2019 was a lower activity and severity season than 2017, and notifications and influenza-related calls were heightened by increased community concern and testing.

Flutracking weekly online community survey of influenza-like illness annual report, 2016

Flutracking is a national online community influenza-like illness (ILI) surveillance system that monitors weekly ILI attack rates and seriousness of disease in the Australian community. This article reports on the 2016 findings. From 2015 to 2016 there was an 11.4% increase in participants to 30,998 completing at least one survey with a peak weekly response of 27,094 participants and a minimum weekly response of 26,123. The 2016 Flutracking national weekly percentage of participants with fever and cough peaked in late August at 2.7%, one week earlier than the national counts of laboratory confirmed influenza peaked. A lower percentage of participants took 2 or more days off from work or normal duties and sought medical advice in 2016 (peak level 1.6% and 1.0% respectively) compared with 2015 (peak level 2.0% and 1.3% respectively). Flutracking fever and cough peaked in the same week as death rates for influenza and pneumonia recorded by the NSW Registry of Births, Deaths and Marriages. The percentage of participants aged 0 to 14 years with cough and fever was higher than all other age groups in 2016. Overall, Flutracking surveillance demonstrated that the attack rates and seriousness of disease for the 2016 season at the community level were lower than 2015 and 2014.

Influenza A(H1N1)pdm09 outbreak detected in inter-seasonal months during the surveillance of influenza-like illness in Pune, India, 2012-2015.

An outbreak of influenza A(H1N1)pdm09 was detected during the ongoing community-based surveillance of influenza-like illness (ILI). Among reported 119 influenza A(H1N1)pdm09 cases (59 cases in the year 2012 and 60 cases in 2015) in summer months, common clinical features were fever (100%), cough (90·7%), sore throat (85·7%), nasal discharge (48·7%), headache (55·5%), fatigue (18·5%), breathlessness (3·4%), and ear discharge (1·7%). Rise in ILI cases were negatively correlated with the seasonal factors such as relative humidity (Karl Pearson's correlation coefficient, i.e. r = -0·71 in the year 2012 and r = -0·44 in the year 2015), while rise in ILI cases were positively correlated with the temperature difference (r = 0·44 in the year 2012 and r = 0·77 in the year 2015). The effective reproduction number R, was estimated to be 1·30 in 2012 and 1·64 in 2015. The study highlights the rise in unusual influenza activity in summer month with high attack rate of ILI among children aged ⩽9 years. Children in this age group may need special attention for influenza vaccination. Influenza A(H1N1)pdm09 outbreak was confirmed in inter-seasonal months during the surveillance of ILI in Pune, India, 2012-2015.

Age-related differences in the accuracy of web query-based predictions of influenza-like illness.

BackgroundWeb queries are now widely used for modeling, nowcasting and forecasting influenza-like illness (ILI). However, given that ILI attack rates vary significantly across ages, in terms of both magnitude and timing, little is known about whether the association between ILI morbidity and ILI-related queries is comparable across different age-groups. The present study aimed to investigate features of the association between ILI morbidity and ILI-related query volume from the perspective of age.MethodsSince Google Flu Trends is unavailable in Italy, Google Trends was used to identify entry terms that correlated highly with official ILI surveillance data. All-age and age-class-specific modeling was performed by means of linear models with generalized least-square estimation. Hold-out validation was used to quantify prediction accuracy. For purposes of comparison, predictions generated by exponential smoothing were computed.ResultsFive search terms showed high correlation coefficients of > .6. In comparison with exponential smoothing, the all-age query-based model correctly predicted the peak time and yielded a higher correlation coefficient with observed ILI morbidity (.978 vs. .929). However, query-based prediction of ILI morbidity was associated with a greater error. Age-class-specific query-based models varied significantly in terms of prediction accuracy. In the 0–4 and 25–44-year age-groups, these did well and outperformed exponential smoothing predictions; in the 15–24 and ≥ 65-year age-classes, however, the query-based models were inaccurate and highly overestimated peak height. In all but one age-class, peak timing predicted by the query-based models coincided with observed timing.ConclusionsThe accuracy of web query-based models in predicting ILI morbidity rates could differ among ages. Greater age-specific detail may be useful in flu query-based studies in order to account for age-specific features of the epidemiology of ILI.

Control of an H1N1 outbreak in a correctional facility in central Taiwan.

Controlling the outbreak of H1N1 in correctional facilities is difficult due to the inevitable close and prolonged contact between inmates. The current study reports an H1N1 outbreak in a correction facility and investigates the effectiveness of oseltamivir to control the spread of H1N1. All 2690 inmates at the prison received medical service from a single hospital. A list of patients with a diagnosis of influenza was compiled based on medical diagnoses with respiratory symptoms during the outbreak period. The outbreak was then investigated using both chart review and questionnaires. In the 4-week outbreak period, 24.6% (663/2690) of inmates experienced influenza-associated symptoms, 50.5% (335/663) fulfilled the criteria for influenza-like illness (ILI) with fever, and the overall attack rate of ILI was 12.8%. Twelve inmates were admitted for complicated influenza, and three of them experienced respiratory failure. Oseltamivir was provided at the end of the 2nd week, and the effectiveness of oseltamivir in the 1004 inmates from seven major sections in the prison was analyzed. The ILI incidence rate reduced from 12.6±4.1% between the 1st and 2nd weeks to 4.8±2.4% between the 3rd and 4th weeks (p=0.018) after the oseltamivir intervention. In the 878 uninfected inmates 47.0% (413/878) of inmates received prophylactic oseltamivir at the end of the 2nd week, the incidence of ILI was lower than those without prophylaxis (6.2% versus 2.4%; p=0.013). H1N1 influenza spread rapidly in the correctional facility. The use of oseltamivir may be a practical intervention to control an H1N1 outbreak an enclosed environment such as this.

Evaluation of the Effectiveness of Pandemic Influenza A(H1N1) 2009 Vaccine Based on an Outbreak Investigation During the 2010–2011 Season in Korean Military Camps

ObjectivesIn December 2010, there was an outbreak of acute febrile respiratory disease in many Korean military camps that were not geographically related. A laboratory analysis confirmed a number of these cases to be infected by the pandemic influenza A(H1N1) 2009 (H1N1pdm09) virus. Because mass vaccination against H1N1pdm09 was implemented at the infected military camps eleven months ago, the outbreak areas in which both vaccinated and nonvaccinated individuals were well mixed, gave us an opportunity to evaluate the effectiveness of H1N1pdm09 vaccine through a retrospective cohort study design. MethodsA self-administered questionnaire was distributed to the three military camps in which the outbreak occurred for case detection, determination of vaccination status, and characterization of other risk factors. The overall response rate was 86.8% (395/455). Case was defined as fever (≥38 °C) with cough or sore throat, influenza-like illness (ILI), and vaccination status verified by vaccination registry. Crude vaccine effectiveness (VE) was calculated as “1 − attack rate in vaccinated individuals/attack rate in nonvaccinated individuals”, and adjusted VE was calculated as “1 – odds ratio” using logistic regression adjusted for potential confounding factor. A number of ILI definitions were used to test the robustness of the result. ResultsThe attack rate of ILI was 12.8% in register-verified vaccinated individuals and 24.0% in nonvaccinated individuals. The crude VE was thus calculated to be 46.8% [95% confidence interval (CI): 14.5–66.9]. The adjusted VE rate was 46.8% (95% CI: –9.4 to 74.1). Various combinations of ILI symptoms also showed similar VE rates. ConclusionWe evaluated the effectiveness of H1N1pdm09 vaccine in the 2010–2011 season in an outbreak setting. Although the result was not sensitive to any analytical method used and ILI case definition, the magnitude of effectiveness was lower than estimated in the 2009–2010 season.

Outbreaks of influenza‐like illness in long‐term care facilities in Winnipeg, Canada

Outbreaks of influenza-like illness (ILI) are common in long-term care facilities (LTCFs) and result in significant morbidity and mortality among residents. We describe patterns of reported ILI outbreaks in LTCFs in Winnipeg, Canada, and examine LTCF and outbreak characteristics that influence the clinical outcomes of these outbreaks. We analyzed the electronic records of all ILI outbreaks reported by LTCFs in Winnipeg from 2003 to 2011. Outbreak duration, ILI attack rates among staff and residents, and residents' death rates were calculated by presumed viral etiology, staff vaccination rates, type of influenza chemoprophylaxis used, and time to notification to public health. Of a total of 154 reported outbreaks, most (N=80) were attributed to influenza, and these outbreaks tended to have higher attack and death rates among LTCF residents compared with outbreaks caused by other respiratory viruses (12) or those of unknown etiology (62). About 92% of residents and 38% of staff of the average LTCFs were vaccinated. Chemoprophylaxis was used in 57·5% of influenza outbreaks. Regardless of presumed viral etiology, outbreaks reported within 3 days of onset ended sooner and had lower attack and mortality rates among residents. Influenza-like illness outbreaks still occur among highly immunized LTCF residents, so in addition to vaccination of staff and residents, it is important to maintain competent infection control practices. Early identification and notification to public health authorities and possibly early initiation of control measures could improve clinical outcomes of ILI outbreaks.

HIV and AIDS Data Hub forAsia Pacific: a regional tool to support strategic information needs.

This report describes a 2011 seasonal influenza B outbreak in a metropolitan primary school in Australia with 179 students.Epidemiological, microbiological and environmental investigations were undertaken. A retrospective cohort study was conducted using a questionnaire that included demographic data, details of illness, chronic health conditions and vaccination status. Influenza-like illness (ILI) was defined as fever plus cough and/or sore throat. Analysis of ILI was undertaken with the χ(2) test and Fisher's exact test.Seventy-two questionnaire respondents (75%) reported illness during the outbreak - 43 with ILI, giving an attack rate of 45%. There was no association between ILI and age or chronic lung disease. Six (6%) students were vaccinated against influenza before the outbreak; although four became ill, none satisfied the ILI case definition. Seven students were positive for influenza B including two confirmed as B/Brisbane/60/2008-like; one student was positive for rhinovirus and another for metapneumovirus. The recommended influenza vaccine matched the circulating influenza strains.This cohort study estimated a high ILI attack rate and demonstrated low influenza vaccine coverage within the setting of a primary school. Gastrointestinal symptoms, in addition to constitutional and respiratory symptoms, were common.

Transmission dynamics and risk factors for pandemic H1N1‐related illness: outbreak investigation in a rural community of British Columbia, Canada

Please cite this paper as: Janjua et al. (2012) Transmission dynamics and risk factors for pandemic H1N1‐related illness: outbreak investigation in a rural community of British Columbia, Canada. Influenza and Other Respiratory Viruses 6(3), e54–e62. Objective To characterize the first‐wave epidemiologic features of influenza‐like illness (ILI) associated with the novel pandemic A/H1N1 [A(H1N1)pdm09] virus. Methods We used generalized linear mixed models (GLMM) to assess risk factors and non‐parametric and/or parametric distributions to estimate attack rates, secondary attack rates (SAR), duration of illness, and serial interval during a laboratory‐confirmed community outbreak of A(H1N1)pdm09 clustered around on‐reserve residents and households of an elementary school in rural British Columbia, Canada, in late April/early May 2009. ILI details were collected as part of outbreak investigation by community telephone survey in early June 2009. Results Overall, 92/408 (23%) of participants developed ILI and 36/408 (9%) experienced medically attended ILI (MAILI). The overall SAR in households was 22%: highest among participants 1–4 years of age (yoa) (50%) followed by <1 yoa (38%), 5–8 yoa (20%), 10–19 yoa (13%), 20–49 yoa (20%), and 50–64 yoa (0%). The median serial interval was estimated at 3·5 days (95% CI: 2·1–5·1). In multivariable GLMM analysis, having a chronic condition (OR: 2·58; 95% CI: 1·1–6·04), younger age [1–8 yoa: OR: 4·63; 95% CI: 2·25–9·52; 9–19 yoa: OR: 1·95; 95% CI: 0·97–3·9 (referent: ≥20 yoa)] and receipt of 2008–2009 influenza vaccine (OR: 2·68; 95% CI: 1·37–5·25) were associated with increased risk of ILI. Median duration of illness was 9 days, longer among those with chronic conditions (21 days). Median time to seeking care after developing illness was 4·5 days. On‐reserve participants had higher chronic conditions, household density, ILI, MAILI, and SAR. Conclusions During a community outbreak of A(H1N1)pdm09‐related illness, we identified substantial clinical ILI attack rates exceeding 20% with secondary household attack rates as high as 50% in young children. The serial interval was short suggesting a narrow period to prevent transmission.

Pandemic Influenza A(H1N1) Outbreak Among a Group of Medical Students Who Traveled to the Dominican Republic

From the beginning of the influenza pandemic until the time the outbreak described here was detected, 77,201 cases of pandemic influenza A(H1N1) with 332 deaths had been reported worldwide, mostly in the United States and Mexico. All of the cases reported in Spain until then had a recent history of travel to Mexico, the Dominican Republic, or Chile. We describe an outbreak of influenza among medical students who traveled from Spain to the Dominican Republic in June 2009. We collected diagnostic samples and clinical histories from consenting medical students who had traveled to the Dominican Republic and from their household contacts after their return to Spain. Of 113 students on the trip, 62 (55%) developed symptoms; 39 (45%) of 86 students tested had laboratory evidence of influenza A(H1N1) infection. Most students developed symptoms either just before departure from the Dominican Republic or within days of returning to Spain. The estimated secondary attack rate of influenza-like illness among residential contacts of ill students after return to Spain was 2.1%. The attack rate of influenza A(H1N1) can vary widely depending on the circumstances of exposure. We report a high attack rate among a group of traveling medical students but a much lower secondary attack rate among their contacts after return from the trip. These findings may aid the development of recommendations to prevent influenza.

Seasonal Influenza Vaccination of Healthy Working-Age Adults

The recent impact of influenza on the working-age population of the US has led to changes in the recommendations for vaccination against seasonal influenza; however, the implications of vaccinating such a population have been debated. A review of cost-effectiveness analyses of vaccinating the working-age population of the US against seasonal influenza was conducted using articles published between January 1990 and January 2010. Studies considered for inclusion were identified using MEDLINE, EMBASE and Econlit. Reviewers worked in pairs, and each team member independently extracted relevant data using a standard abstraction form. The source and appropriateness of parameters (epidemiological data, probabilities and costs), the designs employed and the sufficiency of sensitivity analysis were considered during review. Key inputs extracted from the selected studies included influenza or influenza-like illness attack rates, outpatient visits averted, total vaccination days and lost workdays. Seven studies were identified as appropriate for this review. All studies were conducted in the US and from the societal perspective; three were randomized controlled trials and the remaining four were economic simulation models comparing vaccination and influenza antiviral drugs or no intervention; analyses focused on healthy working-age adults aged 18-49 years. Results ranged from net savings of $US68.96 to net costs of $US85.92 per person vaccinated (four studies) and net costs of $US104-1005 per episode of influenza averted (one study). Only two studies reported cost-effectiveness ratios; these ranged from $US26,565 to $US50,512 per quality-adjusted life-year gained. Nearly all of the studies conducted sensitivity analysis; results were most sensitive to variation in wage rates, levels of worker productivity, the costs and effectiveness of vaccination, and the rate of influenza illness. Review of the included studies suggests that seasonal influenza vaccination of healthy, working-age adults is generally not cost saving, requiring an investment to generate health benefits. The decision to vaccinate such a group will depend upon the societal and payer valuation of those benefits.

Estimate of 2009 H1N1 influenza cases in Shenzhen – the biggest migratory city in China

The 2009 novel H1N1 influenza pandemic had a significant impact on Shenzhen's population with 2063 laboratory-confirmed human H1N1 cases and five deaths being reported. We used parameters from two population-based surveys and the Shenzhen Influenza Surveillance System to estimate the total number of H1N1 influenza infections in Shenzhen in the 2009 pandemic. The attack rate of influenza-like illness (ILI) in family households was 11·2% (95% CI 9·4-13·0), with 80·2% (95% CI 77·8-82·5) seeking medical care. The ILI attack rate in workers was 38·1% (95% CI 34·3-41·7) with 72·5% (95% CI 66·9-78·0) seeking medical care. The average H1N1 positive rate in individuals reporting ILI and testing by polymerase chain reaction was 22·7%. A total of 611 000-768 000 people, or 4·7-5·9% of the Shenzhen population, are estimated to have experienced H1N1 influenza. The estimated total number of cases of H1N1 is likely to be 330 times greater than the number of laboratory-confirmed cases.

Secondary attack rate of pandemic influenza A(H1N1)2009 in Western Australian households, 29 May–7 August 2009

Understanding household transmission of the pandemic influenza A(H1N1)2009 virus, including risk factors for transmission, is important for refining public health strategies to reduce the burden of the disease. During the influenza season of 2009 we investigated transmission of the emerging virus in 595 households in which the index case was the first symptomatic case of influenza A(H1N1)2009. Secondary cases were defined as household contacts with influenza-like illness (ILI) or laboratory-confirmed influenza A(H1N1)2009, occurring at least one day after but within seven days following symptom onset in the index case. ILI developed in 231 of the 1,589 household contacts, a secondary attack rate of 14.5% (95% confidence interval (CI): 12.9–16.4). At least one secondary case occurred in 166 of the 595 households (a household transmission rate of 27.9%; 95% CI: 24.5–31.6).Of these, 127 (76.5%) households reported one secondary case and 39 (23.5%) households reported two or more secondary cases. Secondary attack rates were highest in children younger than five years (p=0.001), and young children were also more efficient transmitters (p=0.01). Individual risk was not associated with household size. Prophylactic antiviral therapy was associated with reduced transmission (p=0.03). The secondary attack rate of ILI in households with a confirmed pandemic influenza A(H1N1)2009 index case was comparable to that described previously for seasonal influenza.

Investigating 2009 Pandemic Influenza A (H1N1) in US Schools: What Have We Learned?

US investigations of school-based outbreaks of 2009 pandemic influenza A (H1N1) virus infection characterized influenza-like illness (ILI) attack rates, transmission risk factors, and adherence to nonpharmaceutical interventions. We summarize seven school-based investigations conducted during April-June 2009 to determine what questions might be answered by future investigations. Surveys were administered 5-28 days after identification of the outbreaks, and participation rates varied among households (39-86%) and individuals (24-49%). Compared with adults (4%-10%) and children aged <4 years (2%-7%), elementary through university students had higher ILI attack rates (4%-32%). Large gatherings or close contact with sick persons were identified as transmission risk factors. More participants reported adherence to hygiene measures, but fewer reported adherence to isolation measures. Challenges included low participation and delays in survey initiation that potentially introduced bias. Although school-based investigations can increase our understanding of epidemiology and prevention strategy effectiveness, investigators should decide which objectives are most feasible, given timing and design constraints.

Influenza-Like Illness in a Community Surrounding a School-Based Outbreak of 2009 Pandemic Influenza A (H1N1) Virus-Chicago, Illinois, 2009

In April 2009, following the first school closure due to 2009 pandemic influenza A (H1N1) (pH1N1) in Chicago, Illinois, area hospitals were inundated with patients presenting with influenza-like illness (ILI). The extent of disease spread into the surrounding community was unclear. We performed a household survey to estimate the ILI attack rate among community residents and compared reported ILI with confirmed pH1N1 cases and ILI surveillance data (ie, hospital ILI visits, influenza testing, and school absenteeism). The estimated ILI attack rate was 4.6% (95% confidence interval, 2.8%-7.4%), with cases distributed throughout the 5-week study period. In contrast, 36 (84%) of 43 confirmed pH1N1 cases were identified the week of the school closure. Trends in surveillance data peaked during the same week and rapidly decreased to near baseline. Public awareness and health care practices impact standard ILI surveillance data. Community-based surveys are a valuable tool to help assess the burden of ILI in a community.

Gripenet: an internet-based system to monitor influenza-like illness uniformly across Europe

Gripenet has been monitoring the activity of influenza-like-illness (ILI) with the aid of volunteers via the internet in the Netherlands and Belgium since 2003 and in Portugal since 2005. In contrast with the traditional system of sentinel networks of mainly primary care physicians coordinated by the European Influenza Surveillance Scheme (EISS), Gripenet obtains its data directly from the population. Any resident of the three countries can participate in Gripenet by completing an application form on the appropriate websites (http://www.griepmeting.nl for the Netherlands and Belgium, http://www.gripenet.pt for Portugal), which contains various medical, geographic and behavioural questions. Participants report weekly on the website any symptoms they have experienced since their last visit. ILI incidence is determined on the basis of a uniform case definition. In the 2006/2007 season, 19,623 persons participated in Gripenet in the Netherlands, 7,025 in Belgium and 3,118 in Portugal. The rise, peak and decline of ILI activity occurred at similar times according to Gripenet and EISS. However, ILI attack rates in the Netherlands (6.6%), Belgium (6.1%) and Portugal (5.6%) were remarkably more similar in Gripenet than in EISS (0.8%, 3.9%, and 0.6% respectively). Monitoring ILI activity with the direct participation of volunteers provides similar incidence curves compared to the traditional system coordinated by EISS. Whereas EISS provides an established system whose data is validated by virology tests, Gripenet is a fast and flexible monitoring system whose uniformity allows for direct comparison of ILI rates between countries. A current objective of Gripenet is to engage more European countries.