Google Flu Trends (GFT) uses anonymized, aggregated internet search activity to provide near-real time estimates of influenza activity. GFT estimates have shown a strong correlation with official ...influenza surveillance data. The 2009 influenza virus A (H1N1) pandemic pH1N1 provided the first opportunity to evaluate GFT during a non-seasonal influenza outbreak. In September 2009, an updated United States GFT model was developed using data from the beginning of pH1N1.
We evaluated the accuracy of each U.S. GFT model by comparing weekly estimates of ILI (influenza-like illness) activity with the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). For each GFT model we calculated the correlation and RMSE (root mean square error) between model estimates and ILINet for four time periods: pre-H1N1, Summer H1N1, Winter H1N1, and H1N1 overall (Mar 2009-Dec 2009). We also compared the number of queries, query volume, and types of queries (e.g., influenza symptoms, influenza complications) in each model. Both models' estimates were highly correlated with ILINet pre-H1N1 and over the entire surveillance period, although the original model underestimated the magnitude of ILI activity during pH1N1. The updated model was more correlated with ILINet than the original model during Summer H1N1 (r = 0.95 and 0.29, respectively). The updated model included more search query terms than the original model, with more queries directly related to influenza infection, whereas the original model contained more queries related to influenza complications.
Internet search behavior changed during pH1N1, particularly in the categories "influenza complications" and "term for influenza." The complications associated with pH1N1, the fact that pH1N1 began in the summer rather than winter, and changes in health-seeking behavior each may have played a part. Both GFT models performed well prior to and during pH1N1, although the updated model performed better during pH1N1, especially during the summer months.
Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.
Influenza ...activity data from 2003-04 through 2007-08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003-04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90).
This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003-04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior.
During December 14, 2020-April 10, 2021, data from the HEROES-RECOVER Cohorts,* a network of prospective cohorts among frontline workers, showed that the Pfizer-BioNTech and Moderna mRNA COVID-19 ...vaccines were approximately 90% effective in preventing symptomatic and asymptomatic infection with SARS-CoV-2, the virus that causes COVID-19, in real-world conditions (1,2). This report updates vaccine effectiveness (VE) estimates including all COVID-19 vaccines available through August 14, 2021, and examines whether VE differs for adults with increasing time since completion of all recommended vaccine doses. VE before and during SARS-CoV-2 B.1.617.2 (Delta) variant predominance, which coincided with an increase in reported COVID-19 vaccine breakthrough infections, were compared (3,4).
In a multi-center prospective cohort of essential workers, we assessed knowledge, attitudes, and practices (KAP) by vaccine intention, prior SARS-CoV-2 positivity, and occupation, and their impact on ...vaccine uptake over time.
Initiated in July 2020, the HEROES-RECOVER cohort provided socio-demographics and COVID-19 vaccination data. Using two follow-up surveys approximately three months apart, COVID-19 vaccine KAP, intention, and receipt was collected; the first survey categorized participants as reluctant, reachable, or endorser.
A total of 4,803 participants were included in the analysis. Most (70%) were vaccine endorsers, 16% were reachable, and 14% were reluctant. By May 2021, 77% had received at least one vaccine dose. KAP responses strongly predicted vaccine uptake, particularly positive attitudes about safety (aOR = 5.46, 95% CI: 1.4–20.8) and effectiveness (aOR = 5.0, 95% CI: 1.3–19.1). Participants’ with prior SARS-CoV-2 infection were 22% less likely to believe the COVID-19 vaccine was effective compared with uninfected participants (aOR 0.78, 95% CI: 0.64–0.96). This was even more pronounced in first responders compared with other occupations, with first responders 42% less likely to believe in COVID-19 vaccine effectiveness (aOR = 0.58, 95% CI 0.40–0.84). Between administrations of the two surveys, 25% of reluctant, 56% reachable, and 83% of endorser groups received the COVID-19 vaccine. The reachable group had large increases in positive responses for questions about vaccine safety (10% of vaccinated, 34% of unvaccinated), and vaccine effectiveness (12% of vaccinated, 27% of unvaccinated).
Our study demonstrates attitudes associated with COVID-19 vaccine uptake and a positive shift in attitudes over time. First responders, despite potential high exposure to SARS-CoV-2, and participants with a history of SARS-CoV-2 infection were more vaccine reluctant.
Perceptions of the COVID-19 vaccine can shift over time. Targeting messages about the vaccine’s safety and effectiveness in reducing SARS-CoV-2 virus infection and illness severity may increase vaccine uptake for reluctant and reachable participants.
BACKGROUND:The observational test-negative study design is used to estimate vaccine effectiveness against influenza virus infection. An important assumption of the test-negative design is that ...vaccination does not affect the risk of infection with another virus. If such virus interference occurred, detection of other respiratory viruses would be more common among influenza vaccine recipients and vaccine effectiveness estimates could differ. We evaluated the potential for virus interference using data from the Influenza Incidence Surveillance Project.
METHODS:From 2010 to 2013, outpatients presenting to clinics in 13 US jurisdictions with acute respiratory infections were tested for influenza and other respiratory viruses. We investigated whether virus interference might affect vaccine effectiveness estimates by first evaluating the sensitivity of estimates using alternative control groups that include or exclude patients with other respiratory virus detections by age group and early/middle/late stage of influenza seasons. Second, we evaluated the association between influenza vaccination receipt and other respiratory virus detection among influenza test negative patients.
RESULTS:Influenza was detected in 3,743/10,650 patients (35%), and overall vaccine effectiveness was 47% (95% CI42%, 52%). Estimates using each control group were consistent overall or when stratified by age groups, and there were no differences among early, middle, or late phase during influenza season. We found no associations between detection of other respiratory viruses and receipt of influenza vaccination.
CONCLUSIONS:In this 3-year test-negative design study in an outpatient setting in the United States, we found no evidence of virus interference or impact on influenza vaccine effectiveness estimation.
Human metapneumovirus (HMPV) infection causes respiratory illness, including bronchiolitis and pneumonia. However, national HMPV seasonality, as it compares with respiratory syncytial virus (RSV) and ...influenza seasonality patterns, has not been well described.
Hospital and clinical laboratories reported weekly aggregates of specimens tested and positive detections for HMPV, RSV, and influenza to the National Respiratory and Enteric Virus Surveillance System from 2008 to 2014. A season was defined as consecutive weeks with ≥3% positivity for HMPV and ≥10% positivity for RSV and influenza during a surveillance year (June through July). For each virus, the season, onset, offset, duration, peak, and 6-season medians were calculated.
Among consistently reporting laboratories, 33 583 (3.6%) specimens were positive for HMPV, 281 581 (15.3%) for RSV, and 401 342 (18.2%) for influenza. Annually, 6 distinct HMPV seasons occurred from 2008 to 2014, with onsets ranging from November to February and offsets from April to July. Based on the 6-season medians, RSV, influenza, and HMPV onsets occurred sequentially and season durations were similar at 21 to 22 weeks. HMPV demonstrated a unique biennial pattern of early and late seasonal onsets. RSV seasons (onset, offset, peak) were most consistent and occurred before HMPV seasons. There were no consistent patterns between HMPV and influenza circulations.
HMPV circulation begins in winter and lasts until spring and demonstrates distinct seasons each year, with the onset beginning after that of RSV. HMPV, RSV, and influenza can circulate simultaneously during the respiratory season.
Background. Encephalitis is a relatively rare presentation of enterovirus (EV) infections. Clinical and epidemiologic characteristics of EV encephalitis (EVE) have not been well characterized. ...Methods. Patients with encephalitis enrolled in the California Encephalitis Project from 1998 to 2005 were tested for a range of pathogens, including EV, using a standardized diagnostic algorithm. EVE was categorized as “confirmed” (EV detected in cerebrospinal fluid CSF or brain tissue) or “possible” (EV found in respiratory or fecal specimens or serum EV immunoglobulin Ig M detected). We compared clinical and epidemiologic characteristics of EVE with those of other infectious encephalitis cases. Results. EVE was diagnosed in 73 (4.6%) of 1571 patients (45 confirmed cases, 28 possible cases); 11.1% of cases had other infectious causes. Patients with confirmed EVE were younger, although 27% were adults, who presented with significantly less severe symptoms. Serotypes identified in EVE cases correlated with the predominant serotype for the given year reported to the National Enterovirus Surveillance System at the Centers for Disease Control and Prevention. Two of 4 fatal EVE cases were associated with EV71. Conclusion. EVs are an important cause of encephalitis cases requiring hospitalization, in both children and adults. Our data suggest that EVE severity varies by serotype, confirm the importance of CSF/brain tissue polymerase chain reaction, and demonstrate that serum IgM findings are of little value in diagnosing EVE.
Researchers in observational studies of vaccine effectiveness (VE) in which they compared quadrivalent live attenuated vaccine (LAIV4) and inactivated influenza vaccine (IIV) among children and ...adolescents have shown inconsistent results, and the studies have been limited by small samples.
We combined data from 5 US studies from 2013-2014 through 2015-2016 to compare the VE of LAIV4 and IIV against medically attended, laboratory-confirmed influenza among patients aged 2 to 17 years by influenza season, subtype, age group, and prior vaccination status. The VE of IIV or LAIV4 was calculated as 100% × (1 - odds ratio), comparing the odds of vaccination among patients who were influenza-positive to patients who were influenza-negative from adjusted logistic regression models. Relative effectiveness was defined as the odds of influenza comparingLAIV4 and IIV recipients.
Of 17 173 patients aged 2 to 17 years, 4579 received IIV, 1979 received LAIV4, and 10 615 were unvaccinated. Against influenza A/H1N1pdm09, VE was 67% (95% confidence interval CI: 62% to 72%) for IIV and 20% (95% CI: -6% to 39%) for LAIV4. Results were similar when stratified by vaccination in the previous season. LAIV4 recipients had significantly higher odds of influenza A/H1N1pdm09 compared with IIV recipients (odds ratio 2.66; 95% CI: 2.06 to 3.44). LAIV4 and IIV had similar effectiveness against influenza A/H3N2 and B. Our overall findings were consistent when stratified by influenza season and age group.
From this pooled individual patient-level data analysis, we found reduced effectiveness of LAIV4 against influenza A/H1N1pdm09 compared with IIV, which is consistent with published results from the individual studies included.
Existing literature suggests that influenza C typically causes mild respiratory tract disease. However, clinical and epidemiological data are limited.
Four outpatient clinics and 3 hospitals ...submitted clinical data and respiratory specimens through a surveillance network for acute respiratory infection (ARI) from May 2013 through December 2016. Specimens were tested using multitarget nucleic acid amplification for 19-22 respiratory pathogens, including influenza C.
Influenza C virus was detected among 59 of 10 202 (0.58%) hospitalized severe ARI cases and 11 of 2282 (0.48%) outpatients. Most detections occurred from December to March, 73% during the 2014-2015 season. Influenza C detections occurred among patients of all ages, with rates being similar between inpatients and outpatients. The highest rate of detection occurred among children aged 6-24 months (1.2%). Among hospitalized cases, 7 required intensive care. Medical comorbidities were reported in 58% of hospitalized cases and all who required intensive care. At least 1 other respiratory pathogen was detected in 40 (66%) cases, most commonly rhinovirus/enterovirus (25%) and respiratory syncytial virus (20%). The hemagglutinin-esterase-fusion gene was sequenced in 37 specimens, and both C/Kanagawa and C/Sao Paulo lineages were detected in inpatients and outpatients.
We found seasonal circulation of influenza C with year-to-year variability. Detection was most frequent among young children but occurred in all ages. Some cases that were positive for influenza C, particularly those with comorbid conditions, had severe disease, suggesting a need for further study of the role of influenza C virus in the pathogenesis of respiratory disease.
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