Are School Absences Correlated with Influenza Surveillance Data in England? Results from Decipher My Data—A Research Project Conducted through Scientific Engagement with Schools

Background

School aged children are a key link in the transmission of influenza. Most cases have little or no interaction with health services and are therefore missed by the majority of existing surveillance systems. As part of a public engagement with science project, this study aimed to establish a web-based system for the collection of routine school absence data and determine if school absence prevalence was correlated with established surveillance measures for circulating influenza.

Methods

We collected data for two influenza seasons (2011/12 and 2012/13). The primary outcome was daily school absence prevalence (weighted to make it nationally representative) for children aged 11 to 16. School absence prevalence was triangulated graphically and through univariable linear regression to Royal College of General Practitioners (RCGP) influenza like illness (ILI) episode incidence rate, national microbiological surveillance data on the proportion of samples positive for influenza (A+B) and with Rhinovirus, RSV and laboratory confirmed cases of Norovirus.

Results

27 schools submitted data over two respiratory seasons. During the first season, levels of influenza measured by school absence prevalence and established surveillance were low. In the 2012/13 season, a peak of school absence prevalence occurred in week 51, and week 1 in RCGP ILI surveillance data. Linear regression showed a strong association between the school absence prevalence and RCGP ILI (All ages, and 5–14 year olds), laboratory confirmed cases of influenza A & B, and weak evidence for a linear association with Rhinovirus and Norovirus.

Interpretation

This study provides initial evidence for using routine school illness absence prevalence as a novel tool for influenza surveillance. The network of web-based data collection platforms we established through active engagement provides an innovative model of conducting scientific research and could be used for a wide range of infectious disease studies in the future.     

The Burden of Influenza and RSV among Inpatients and Outpatients in Rural Western Kenya, 2009–2012

Background

In Kenya, detailed data on the age-specific burden of influenza and RSV are essential to inform use of limited vaccination and treatment resources.

Methods

We analyzed surveillance data from August 2009 to July 2012 for hospitalized severe acute respiratory illness (SARI) and outpatient influenza-like illness (ILI) at two health facilities in western Kenya to estimate the burden of influenza and respiratory syncytial virus (RSV). Incidence rates were estimated by dividing the number of cases with laboratory-confirmed virus infections by the mid-year population. Rates were adjusted for healthcare-seeking behavior, and to account for patients who met the SARI/ILI case definitions but were not tested.

Results

The average annual incidence of influenza-associated SARI hospitalization per 1,000 persons was 2.7 (95% CI 1.8–3.9) among children <5 years and 0.3 (95% CI 0.2–0.4) among persons ≥5 years; for RSV-associated SARI hospitalization, it was 5.2 (95% CI 4.0–6.8) among children <5 years and 0.1 (95% CI 0.0–0.2) among persons ≥5 years. The incidence of influenza-associated medically-attended ILI per 1,000 was 24.0 (95% CI 16.6–34.7) among children <5 years and 3.8 (95% CI 2.6–5.7) among persons ≥5 years. The incidence of RSV-associated medically-attended ILI was 24.6 (95% CI 17.0–35.4) among children <5 years and 0.8 (95% CI 0.3–1.9) among persons ≥5 years.

Conclusions

Influenza and RSV both exact an important burden in children. This highlights the possible value of influenza vaccines, and future RSV vaccines, for Kenyan children.     

Influenza surveillance among outpatients and inpatients in Morocco, 1996-2009

Background

There is limited information about the epidemiology of influenza in Africa. We describe the epidemiology and seasonality of influenza in Morocco from 1996 to 2009 with particular emphasis on the 2007–2008 and 2008–2009 influenza seasons. Successes and challenges of the enhanced surveillance system introduced in 2007 are also discussed.

Methods

Virologic sentinel surveillance for influenza virus was initiated in Morocco in 1996 using a network of private practitioners that collected oro-pharyngeal and naso-pharyngeal swabs from outpatients presenting with influenza-like-illness (ILI). The surveillance network expanded over the years to include inpatients presenting with severe acute respiratory illness (SARI) at hospitals and syndromic surveillance for ILI and acute respiratory infection (ARI). Respiratory samples and structured questionnaires were collected from eligible patients, and samples were tested by immunofluorescence assays and by viral isolation for influenza viruses.

Results

We obtained a total of 6465 respiratory specimens during 1996 to 2009, of which, 3102 were collected during 2007–2009. Of those, 2249 (72%) were from patients with ILI, and 853 (27%) were from patients with SARI. Among the 3,102 patients, 98 (3%) had laboratory-confirmed influenza, of whom, 85 (87%) had ILI and 13 (13%) had SARI. Among ILI patients, the highest proportion of laboratory-confirmed influenza occurred in children less than 5 years of age (3/169; 2% during 2007–2008 and 23/271; 9% during 2008–2009) and patients 25–59 years of age (8/440; 2% during 2007–2009 and 21/483; 4% during 2008–2009). All SARI patients with influenza were less than 14 years of age. During all surveillance years, influenza virus circulation was seasonal with peak circulation during the winter months of October through April.

Conclusion

Influenza results in both mild and severe respiratory infections in Morocco, and accounted for a large proportion of all hospitalizations for severe respiratory illness among children 5 years of age and younger.     

Impact of Influenza on Outpatient Visits,Hospitalizations, and Deaths by Using a Time Series Poisson Generalized Additive Model

Background

The disease burden associated with influenza in developing tropical and subtropical countries is poorly understood owing to the lack of a comprehensive disease surveillance system and information-exchange mechanisms. The impact of influenza on outpatient visits, hospital admissions, and deaths has not been fully demonstrated to date in south China.

Methods

A time series Poisson generalized additive model was used to quantitatively assess influenza-like illness (ILI) and influenza disease burden by using influenza surveillance data in Zhuhai City from 2007 to 2009, combined with the outpatient, inpatient, and respiratory disease mortality data of the same period.

Results

The influenza activity in Zhuhai City demonstrated a typical subtropical seasonal pattern; however, each influenza virus subtype showed a specific transmission variation. The weekly ILI case number and virus isolation rate had a very close positive correlation (r = 0.774, P < 0.0001). The impact of ILI and influenza on weekly outpatient visits was statistically significant (P < 0.05). We determined that 10.7% of outpatient visits were associated with ILI and 1.88% were associated with influenza. ILI also had a significant influence on the hospitalization rates (P < 0.05), but mainly in populations <25 years of age. No statistically significant effect of influenza on hospital admissions was found (P > 0.05). The impact of ILI on chronic obstructive pulmonary disease (COPD) was most significant (P < 0.05), with 33.1% of COPD-related deaths being attributable to ILI. The impact of influenza on the mortality rate requires further evaluation.

Conclusions

ILI is a feasible indicator of influenza activity. Both ILI and influenza have a large impact on outpatient visits. Although ILI affects the number of hospital admissions and deaths, we found no consistent influence of influenza, which requires further assessment.     

Mortality amongst Patients with Influenza-Associated Severe Acute Respiratory Illness,South Africa, 2009-2013

Introduction

Data on the burden and risk groups for influenza-associated mortality from Africa are limited. We aimed to estimate the incidence and risk-factors for in-hospital influenza-associated severe acute respiratory illness (SARI) deaths.

Methods

Hospitalised patients with SARI were enrolled prospectively in four provinces of South Africa from 2009–2013. Using polymerase chain reaction, respiratory samples were tested for ten respiratory viruses and blood for pneumococcal DNA. The incidence of influenza-associated SARI deaths was estimated at one urban hospital with a defined catchment population.

Results

We enrolled 1376 patients with influenza-associated SARI and 3% (41 of 1358 with available outcome data) died. In patients with available HIV-status, the case-fatality proportion (CFP) was higher in HIV-infected (5%, 22/419) than HIV-uninfected individuals (2%, 13/620; p = 0.006). CFPs varied by age group, and generally increased with increasing age amongst individuals >5 years (p<0.001). On multivariable analysis, factors associated with death were age-group 45–64 years (odds ratio (OR) 4.0, 95% confidence interval (CI) 1.01–16.3) and ≥65 years (OR 6.5, 95%CI 1.2–34.3) compared to 1–4 year age-group who had the lowest CFP, HIV-infection (OR 2.9, 95%CI 1.1–7.8), underlying medical conditions other than HIV (OR 2.9, 95%CI 1.2–7.3) and pneumococcal co-infection (OR 4.1, 95%CI 1.5–11.2). The estimated incidence of influenza-associated SARI deaths per 100,000 population was highest in children <1 year (20.1, 95%CI 12.1–31.3) and adults aged 45–64 years (10.4, 95%CI 8.4–12.9). Adjusting for age, the rate of death was 20-fold (95%CI 15.0–27.8) higher in HIV-infected individuals than HIV-uninfected individuals.

Conclusion

Influenza causes substantial mortality in urban South Africa, particularly in infants aged <1 year and HIV-infected individuals. More widespread access to antiretroviral treatment and influenza vaccination may reduce this burden.     

Influenza Surveillance and Incidence in a Rural Area in China during the 2009/2010 Influenza Pandemic

Background

Most influenza surveillance is based on data from urban sentinel hospitals; little is known about influenza activity in rural communities. We conducted influenza surveillance in a rural region of China with the aim of detecting influenza activity in the 2009/2010 influenza season.

Methods

The study was conducted from October 2009 to March 2010. Real-time polymerase chain reaction was used to confirm influenza cases. Over-the-counter (OTC) drug sales were daily collected in drugstores and hospitals/clinics. Space-time scan statistics were used to identify clusters of ILI in community. The incidence rate of ILI/influenza was estimated on the basis of the number of ILI/influenza cases detected by the hospitals/clinics.

Results

A total of 434 ILI cases (3.88% of all consultations) were reported; 64.71% of these cases were influenza A (H1N1) pdm09. The estimated incidence rate of ILI and influenza were 5.19/100 and 0.40/100, respectively. The numbers of ILI cases and OTC drug purchases in the previous 7 days were strongly correlated (Spearman rank correlation coefficient [r] = 0.620, P = 0.001). Four ILI outbreaks were detected by space-time permutation analysis.

Conclusions

This rural community surveillance detected influenza A (H1N1) pdm09 activity and outbreaks in the 2009/2010 influenza season and enabled estimation of the incidence rate of influenza. It also provides a scientific data for public health measures.     

Estimation of the National Disease Burden of Influenza-Associated Severe Acute Respiratory Illness in Kenya and Guatemala: A Novel Methodology

Background

Knowing the national disease burden of severe influenza in low-income countries can inform policy decisions around influenza treatment and prevention. We present a novel methodology using locally generated data for estimating this burden.

Methods and Findings

This method begins with calculating the hospitalized severe acute respiratory illness (SARI) incidence for children <5 years old and persons ≥5 years old from population-based surveillance in one province. This base rate of SARI is then adjusted for each province based on the prevalence of risk factors and healthcare-seeking behavior. The percentage of SARI with influenza virus detected is determined from provincial-level sentinel surveillance and applied to the adjusted provincial rates of hospitalized SARI. Healthcare-seeking data from healthcare utilization surveys is used to estimate non-hospitalized influenza-associated SARI. Rates of hospitalized and non-hospitalized influenza-associated SARI are applied to census data to calculate the national number of cases. The method was field-tested in Kenya, and validated in Guatemala, using data from August 2009–July 2011. In Kenya (2009 population 38.6 million persons), the annual number of hospitalized influenza-associated SARI cases ranged from 17,129–27,659 for children <5 years old (2.9–4.7 per 1,000 persons) and 6,882–7,836 for persons ≥5 years old (0.21–0.24 per 1,000 persons), depending on year and base rate used. In Guatemala (2011 population 14.7 million persons), the annual number of hospitalized cases of influenza-associated pneumonia ranged from 1,065–2,259 (0.5–1.0 per 1,000 persons) among children <5 years old and 779–2,252 cases (0.1–0.2 per 1,000 persons) for persons ≥5 years old, depending on year and base rate used. In both countries, the number of non-hospitalized influenza-associated cases was several-fold higher than the hospitalized cases.

Conclusions

Influenza virus was associated with a substantial amount of severe disease in Kenya and Guatemala. This method can be performed in most low and lower-middle income countries.     

The Clinical and Etiological Characteristics of Influenza-Like Illness (ILI) in Outpatients in Shanghai,China, 2011 to 2013

Introduction

Clinical and etiological characteristics of influenza-like illness (ILI) in outpatients is poorly understood in the southern temperate region of China. We conducted laboratory-based surveillance of viral etiology for ILI outpatients in Shanghai from January 2011 to December 2013.

Materials and Methods

Clinical and epidemiological data from ILI outpatients, both children and adults, were collected. A total of 1970 nasopharyngeal swabs were collected and tested for 12 respiratory viruses using multiplex RT-PCR, and the data were analyzed anonymously.

Results

All 12 respiratory viruses were detected in the specimens. At least one virus was detected in 32.4% of 1970 specimens analyzed, with 1.1% showing co-infections. The most frequently detected agents were influenza A (11.7%), influenza B (9.6%), and rhinoviruses (3.1%).Other viruses were present at a frequency less than 3.0%. We observed a winter peak in the detection rate in ILI patients during 3 years of surveillance and a summer peak in 2012. HCoV, HADV, and HMPV were detected more frequently in children than in adults. Patients infected with influenza virus experienced higher temperatures, more coughs, running noses, headaches and fatigue than patients infected with other viruses and virus-free patients (p<0.001).

Conclusions

The spectrum, seasonality, age distribution and clinical associations of respiratory virus infections in children and adults with influenza-like illness were analyzed in this study for the first time. To a certain extent, the findings can provide baseline data for evaluating the burden of respiratory virus infection in children and adults in Shanghai. It will also provide clinicians with helpful information about the etiological patterns of outpatients presenting with complaints of acute respiratory syndrome, but further studies should be conducted, and longer-term laboratory-based surveillance would give a better picture of the etiology of ILI.     

Influenza Virus Surveillance in Pakistan during 2008-2011

Background

There is little information about influenza among the Pakistani population. In order to assess the trends of Influenza-like-Illness (ILI) and to monitor the predominant circulating strains of influenza viruses, a country-wide lab-based surveillance system for ILI and Severe Acute Respiratory Illness (SARI) with weekly sampling and reporting was established in 2008. This system was necessary for early detection of emerging novel influenza subtypes and timely response for influenza prevention and control.

Methods

Five sentinel sites at tertiary care hospitals across Pakistan collected epidemiological data and respiratory samples from Influenza-like illness (ILI) and severe acute respiratory illness (SARI) cases from January 2008 to December 2011. Samples were typed and sub-typed by Real-Time RT-PCR assay.

Results

A total of 6258 specimens were analyzed; influenza virus was detected in 1489 (24%) samples, including 1066 (72%) Influenza type A and 423 (28%) influenza type B viruses. Amongst influenza A viruses, 25 (2%) were seasonal A/H1N1, 169 (16%) were A/H3N2 and 872 (82 %) were A(H1N1)pdm09. Influenza B virus circulation was detected throughout the year along with few cases of seasonal A/H1N1 virus during late winter and spring. Influenza A/H3N2 virus circulation was mainly observed during summer months (August-October).

Conclusions

The findings of this study emphasize the need for continuous and comprehensive influenza surveillance. Prospective data from multiple years is needed to predict seasonal trends for vaccine development and to further fortify pandemic preparedness.     

Clinical Characteristics Are Similar across Type A and B Influenza Virus Infections

Background

Studies that aimed at comparing the clinical presentation of influenza patients across virus types and subtypes/lineages found divergent results, but this was never investigated using data collected over several years in a countrywide, primary care practitioners-based influenza surveillance system.

Methods

The IBVD (Influenza B in Vircases Database) study collected information on signs and symptoms at disease onset from laboratory-confirmed influenza patients of any age who consulted a sentinel practitioner in France. We compared the clinical presentation of influenza patients across age groups (0–4, 5–14, 15–64 and 65+ years), virus types (A, B) and subtypes/lineages (A(H3N2), pandemic A(H1N1), B Victoria, B Yamagata).

Results

Overall, 14,423 influenza cases (23.9% of which were influenza B) were included between 2003–2004 and 2012–2013. Influenza A and B accounted for over 50% of total influenza cases during eight and two seasons, respectively. There were minor differences in the distribution of signs and symptoms across influenza virus types and subtypes/lineages. Compared to patients aged 0–4 years, those aged 5–14 years were more likely to have been infected with type B viruses (OR 2.15, 95% CI 1.87–2.47) while those aged 15–64 years were less likely (OR 0.83, 95% CI 0.73–0.96). Males and influenza patients diagnosed during the epidemic period were less likely to be infected with type B viruses.

Conclusions

Despite differences in age distribution, the clinical illness produced by the different influenza virus types and subtypes is indistinguishable among patients that consult a general practitioner for acute respiratory infections.     

Recording of Influenza-Like Illness in UK Primary Care 1995-2013: Cohort Study

Background

There is a lack of recent studies examining recording of influenza-like illness (ILI) in primary care in the UK over time and according to population characteristics. Our aim was to determine time trends and socio-demographic patterns of ILI recorded consultations in primary care.

Methods

We used The Health Improvement Network (THIN) UK primary care database and extracted data on all ILI consultations between 1995 and 2013. We estimated ILI recorded consultation rates per 100,000 person-weeks (pw) by age, gender, deprivation and winter season. Negative binomial regression models were used to examine time trends and the effect of socio-demographic characteristics. Trends in ILI recorded consultations were compared to trends in consultations with less specific symptoms (cough or fever) recorded.

Results

The study involved 7,682,908 individuals in 542 general practices. The ILI consultation rate decreased from 32.5/100,000 pw (95% confidence interval (CI) 32.1, 32.9) in 1995–98 to 15.5/100,000 pw (95% CI 15.4, 15.7) by 2010–13. The decrease occurred prior to 2002/3, and rates have remained largely stable since then. Declines were evident in all age groups. In comparison, cough or fever consultation rates increased from 169.4/100,000 pw (95% CI 168.6, 170.3) in 1995–98 to 237.7/100,000 pw (95% CI 237.2, 238.2) in 2010–13. ILI consultation rates were highest among individuals aged 15–44 years, higher in women than men, and in individuals from deprived areas.

Conclusion

There is substantial variation in ILI recorded consultations over time and by population socio-demographic characteristics, most likely reflecting changing recording behaviour by GPs. These results highlight the difficulties in using coded information from electronic primary care records to measure the severity of influenza epidemics across time and assess the relative burden of ILI in different population subgroups.     

Demonstrating the Use of High-Volume Electronic Medical Claims Data to Monitor Local and Regional Influenza Activity in the US

Introduction

Fine-grained influenza surveillance data are lacking in the US, hampering our ability to monitor disease spread at a local scale. Here we evaluate the performances of high-volume electronic medical claims data to assess local and regional influenza activity.

Material and Methods

We used electronic medical claims data compiled by IMS Health in 480 US locations to create weekly regional influenza-like-illness (ILI) time series during 2003–2010. IMS Health captured 62% of US outpatient visits in 2009. We studied the performances of IMS-ILI indicators against reference influenza surveillance datasets, including CDC-ILI outpatient and laboratory-confirmed influenza data. We estimated correlation in weekly incidences, peak timing and seasonal intensity across datasets, stratified by 10 regions and four age groups (<5, 5–29, 30–59, and 60+ years). To test IMS-Health performances at the city level, we compared IMS-ILI indicators to syndromic surveillance data for New York City. We also used control data on laboratory-confirmed Respiratory Syncytial Virus (RSV) activity to test the specificity of IMS-ILI for influenza surveillance.

Results

Regional IMS-ILI indicators were highly synchronous with CDC''s reference influenza surveillance data (Pearson correlation coefficients rho≥0.89; range across regions, 0.80–0.97, P<0.001). Seasonal intensity estimates were weakly correlated across datasets in all age data (rho≤0.52), moderately correlated among adults (rho≥0.64) and uncorrelated among school-age children. IMS-ILI indicators were more correlated with reference influenza data than control RSV indicators (rho = 0.93 with influenza v. rho = 0.33 with RSV, P<0.05). City-level IMS-ILI indicators were highly consistent with reference syndromic data (rho≥0.86).

Conclusion

Medical claims-based ILI indicators accurately capture weekly fluctuations in influenza activity in all US regions during inter-pandemic and pandemic seasons, and can be broken down by age groups and fine geographical areas. Medical claims data provide more reliable and fine-grained indicators of influenza activity than other high-volume electronic algorithms and should be used to augment existing influenza surveillance systems.     

Impact of Intensive Handwashing Promotion on Secondary Household Influenza-Like Illness in Rural Bangladesh: Findings from a Randomized Controlled Trial

Rationale

There is little evidence for the efficacy of handwashing for prevention of influenza transmission in resource-poor settings. We tested the impact of intensive handwashing promotion on household transmission of influenza-like illness and influenza in rural Bangladesh.

Methods

In 2009–10, we identified index case-patients with influenza-like illness (fever with cough or sore throat) who were the only symptomatic person in their household. Household compounds of index case-patients were randomized to control or intervention (soap and daily handwashing promotion). We conducted daily surveillance and collected oropharyngeal specimens. Secondary attack ratios (SAR) were calculated for influenza and ILI in each arm. Among controls, we investigated individual risk factors for ILI among household contacts of index case-patients.

Results

Among 377 index case-patients, the mean number of days between fever onset and study enrollment was 2.1 (SD 1.7) among the 184 controls and 2.6 (SD 2.9) among 193 intervention case-patients. Influenza infection was confirmed in 20% of controls and 12% of intervention index case-patients. The SAR for influenza-like illness among household contacts was 9.5% among intervention (158/1661) and 7.7% among control households (115/1498) (SAR ratio 1.24, 95% CI 0.92–1.65). The SAR ratio for influenza was 2.40 (95% CI 0.68–8.47). In the control arm, susceptible contacts <2 years old (RR_adj 5.51, 95% CI 3.43–8.85), those living with an index case-patient enrolled ≤24 hours after symptom onset (RR_adj 1.91, 95% CI 1.18–3.10), and those who reported multiple daily interactions with the index case-patient (RR_adj 1.94, 95% CI 1.71–3.26) were at increased risk of influenza-like illness.

Discussion

Handwashing promotion initiated after illness onset in a household member did not protect against influenza-like illness or influenza. Behavior may not have changed rapidly enough to curb transmission between household members. A reactive approach to reduce household influenza transmission through handwashing promotion may be ineffective in the context of rural Bangladesh.

Trial Registration

ClinicalTrials.gov NCT00880659     

Burden of Influenza and Respiratory Syncytial Virus Infection in Pregnant Women and Infants Under 6 Months in Mongolia: A Prospective Cohort Study

Background

Pregnant women and infants under 6 months are at risk of influenza-related complications. Limited information exists on their community burden of respiratory viruses.

Methods and Findings

This prospective, observational open cohort study was conducted in Baganuur district, Ulaanbaatar, Mongolia during 2013/14 and 2014/15 influenza seasons. Influenza-like illness (ILI) and severe acute respiratory infection (sARI) were identified by follow-up calls twice a week. For those identified, influenza and respiratory syncytical virus (RSV) were tested by point-of-care test kits. We calculated overall and stratified (by trimester or age group) incidence rates (IR) and used Cox proportional hazard regression for risk factor analyses. Among 1260 unvaccinated pregnant women enrolled, overall IRs for ILI, sARI and influenza A were 11.8 (95% confidence interval (C.I):11.2–12.4), 0.1 (95%C.I:0.0–0.4), and 1.7 (95%C.I:1.5–1.9) per 1,000person-days, respectively. One sARI case was influenza A positive. IRs and adjusted hazard ratios (Adj.HR) for ILI and influenza A were lowest in the third trimester. Those with co-morbidity were 1.4 times more likely to develop ILI [Adj.HR:1.4 (95%C.I:1.1–1.9)]. Among 1304 infants enrolled, overall ILI and sARI IRs were 15.2 (95%C.I:14.5–15.8) and 20.5 (95%C.I:19.7–21.3) per 1,000person-days, respectively. From the tested ILI (77.6%) and sARI (30.6%) cases, the overall positivity rates were 6.3% (influenza A), 1.1% (influenza B) and 9.3% (RSV). Positivity rates of influenza A and RSV tend to increase with age. sARI cases were 1.4 times more likely to be male [Adj.HR:1.4 (95%C.I:1.1–1.8)]. Among all influenza A and RSV positive infants, 11.8% and 68.0% were respectively identified among sARI hospitalized cases.

Conclusion

We observed low overall influenza A burden in both groups, though underestimation was likely due to point-of-care tests used. For infants, RSV burden was more significant than influenza A. These findings would be useful for establishing control strategies for both viruses in Mongolia.     

Case Fatality Rates Based on Population Estimates of Influenza-Like Illness Due to Novel H1N1 Influenza: New York City,May–June 2009

Background

The public health response to pandemic influenza is contingent on the pandemic strain''s severity. In late April 2009, a potentially pandemic novel H1N1 influenza strain (nH1N1) was recognized. New York City (NYC) experienced an intensive initial outbreak that peaked in late May, providing the need and opportunity to rapidly quantify the severity of nH1N1.

Methods and Findings

Telephone surveys using rapid polling methods of approximately 1,000 households each were conducted May 20–27 and June 15–19, 2009. Respondents were asked about the occurrence of influenza-like illness (ILI, fever with either cough or sore throat) for each household member from May 1–27 (survey 1) or the preceding 30 days (survey 2). For the overlap period, prevalence data were combined by weighting the survey-specific contribution based on a Serfling model using data from the NYC syndromic surveillance system. Total and age-specific prevalence of ILI attributed to nH1N1 were estimated using two approaches to adjust for background ILI: discounting by ILI prevalence in less affected NYC boroughs and by ILI measured in syndromic surveillance data from 2004–2008. Deaths, hospitalizations and intensive care unit (ICU) admissions were determined from enhanced surveillance including nH1N1-specific testing. Combined ILI prevalence for the 50-day period was 15.8% (95% CI:13.2%–19.0%). The two methods of adjustment yielded point estimates of nH1N1-associated ILI of 7.8% and 12.2%. Overall case-fatality (CFR) estimates ranged from 0.054–0.086 per 1000 persons with nH1N1-associated ILI and were highest for persons ≥65 years (0.094–0.147 per 1000) and lowest for those 0–17 (0.008–0.012). Hospitalization rates ranged from 0.84–1.34 and ICU admission rates from 0.21–0.34 per 1000, with little variation in either by age-group.

Conclusions

ILI prevalence can be quickly estimated using rapid telephone surveys, using syndromic surveillance data to determine expected “background” ILI proportion. Risk of severe illness due to nH1N1 was similar to seasonal influenza, enabling NYC to emphasize preventing severe morbidity rather than employing aggressive community mitigation measures.     

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

Background

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea.

Methods

Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson''s correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons.

Results

The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05).

Conclusions

In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.