UNASSIGNED: Influenza-like illness (ILI) caused by respiratory viruses results in various respiratory clinical manifestations. The ILI002 prospective observational cohort study aimed to describe viral agents, seasonality, and outcomes of patients with ILI during four seasons in the influenza H1N1-pandemic and post-pandemic years (2010-2014).
UNASSIGNED: Patients from six Mexican hospitals were enrolled from April 2010 to March 2014. Clinical data and nasopharyngeal swabs were obtained and tested for viral respiratory pathogens by real-time reverse-transcription polymerase chain reaction.
UNASSIGNED: Of the 5662 enrolled participants, 64.9% were adults and 35.1% were children. Among the 5629 participants with single-pathogen detection, rhinovirus (20.2%), influenza virus (11.2%), respiratory syncytial virus (RSV) (7.2%), and coronavirus (6.8%) were the most frequent pathogens. Co-infection occurred in 14.5% of cases; 49.3% of participants required hospitalization, particularly in RSV cases (42.9% adults, 89.6% children). The mortality rate was 2.8% higher among older adult participants and those with comorbidities. Influenza H1N1 had the highest mortality rate, yet almost half of the deceased had no pathogen. Rhinovirus persisted year-round, while influenza, coronavirus, and RSV peaked during cooler months.
UNASSIGNED: Analyses showed that some viruses causing ILI may lead to severe disease and hospitalization irrespective of comorbidities. These findings may help in decision-making about public health policies on prevention measures, vaccination, treatment, and administration of health care.

UNASSIGNED: This study investigated the lagged correlation between Baidu Index for influenza-related keywords and influenza-like illness percentage (ILI%) across regions in China. The aim is to establish a scientific foundation for utilizing Baidu Index as an early warning tool for influenza-like illness epidemics.
UNASSIGNED: In this study, data on ILI% and Baidu Index were collected from 30 provincial-level administrative divisions (PLADs) spanning April 2014 to March 2019. The Baidu Index was categorized into Overall Index, Ordinary Index, Prevention Index, Symptom Index, and Treatment Index based on search query themes. The lagged correlation between the Baidu Index and ILI% was examined through the cross-correlation function (CCF) method.
UNASSIGNED: Correlating the Baidu Overall Index of 30 PLADs with ILI% revealed CCF values ranging from 0.46 to 0.86, with a median lag of 0.5 days. Subcategory analysis indicated that the Prevention Index and Symptom Index exhibited quicker responses to ILI%, with median lags of -9 and -0.5 days, respectively, compared to 0 and 3 days for the Ordinary and Treatment Indexes. The median lag days between the Baidu Index and the ILI% were earlier in the northern PLADs compared to the southern PLADs.
UNASSIGNED: The Prevention and Symptom Indexes show promising predictive capabilities for influenza-like illness epidemics.

Respiratory viruses contribute to high morbidity and mortality in Africa. In 2020, the Ohio State University\'s Global One Health Initiative, in collaboration with the Ethiopian Public Health Institute and the US Centers for Disease Control and Prevention, took action to strengthen Ethiopia\'s existing respiratory virus surveillance system through decentralization of laboratory testing and scale-up of national and regional capacity for detecting respiratory viruses. In August 2022, four regional laboratories were established, thereby raising the number of reference laboratories conducting respiratory virus surveillance to five. This article highlights lessons learned during implementation and outlines processes undertaken for laboratory scale-up and decentralization.

In the last week of September 2023, a surge of influenza-like illness was observed among students of the Armed Forces of the Philippines (AFP) Health Service Education and Training Center, where 48 (27 males and 21 females; age in years: mean 33, range 27-41) of 247 military students at the Center presented with respiratory symptoms. Between September 25 and October 10, 2023, all 48 symptomatic students were evaluated with real-time reverse transcription polymerase chain reaction and sequencing for both influenza and SARS-CoV-2. Thirteen (27%) students were found positive for influenza A/H3 only, 6 (13%) for SARS-CoV-2 only, and 4 (8%) were co-infected with influenza A/H3 and SARS-CoV-2. Seventeen influenza A/ H3N2 viruses belonged to the same clade, 3C.2a1b.2a.2a.3a, and 4 SARSCoV-2 sequences belonged to the JE1.1 lineage, indicating a common source outbreak for both. The influenza A/H3N2 circulating virus belonged to a different clade than the vaccine strain for 2023 (3C.2a1b.2a.2a). Only 4 students had received the influenza vaccine for 2023. In response, the AFP Surgeon General issued a memorandum to all military health institutions on October 19, 2023 that mandated influenza vaccination as a prerequisite for enrollment of students at all education and training centers, along with implementation of non-pharmaceutical interventions and early notification and testing of students exhibiting influenza-like-illness.

The lockdown enforced amid the COVID-19 pandemic has affected the occurrence and trends of various respiratory virus infections, with a particular focus on influenza. Our study seeks to analyze the repercussions of the COVID-19 pandemic on the positivity of the influenza virus throughout a 4-year span, encompassing both the pre-COVID-19 era (2018 and 2019) and the COVID-19 period (2020 and 2021). Data collected from patients clinically diagnosed with Influenza-like Illness and Severe Acute Respiratory Illness (SARI) from January 2018 to December 2021 for influenza virus detection were acquired and analyzed through multiplex RT-qPCR. The statistical analysis was conducted using SPSS (Statistical Package for Social Sciences) Version 21.0 Software. A total of 4464 samples were tested over 4 years (2018-2021), with 3201 samples from the pre-COVID era and 1263 samples from the COVID era. Influenza A positivity dropped from 17.7 to 9.57% and Influenza B positivity decreased from 3.74 to 2.61%. Subtyping revealed changes in prevalence for both viruses. Seasonal variations showed more pronounced peaks in the pre-COVID-19 era with reduced activity during lockdown. Influenza A saw a resurgence in August 2021. Throughout the COVID-19 pandemic (2020-2021) SARI cases did not decrease. The positivity rate for Influenza A slightly rose to 7.79% from 4.23% in the COVID period (2020-2021). This increase correlates with heightened hospitalization rates during the pandemic, sparking concerns of potential coinfection with coronavirus and Influenza A. The notable drop in influenza cases in 2020-2021 is likely due to stringent precautions, lockdowns, drug repurposing, and prioritized testing, indicating no reduction in influenza transmission. Increased influenza positivity in SARI patients during COVID-19 highlights a heightened risk of coinfection. Emphasizing solely on COVID-19 may lead to underreporting of other respiratory pathogens, including influenza viruses.

Viral respiratory illness surveillance has traditionally focused on single pathogens (e.g., influenza) and required fever to identify influenza-like illness (ILI). We developed an automated system applying both laboratory test and syndrome criteria to electronic health records from 3 practice groups in Massachusetts, USA, to monitor trends in respiratory viral-like illness (RAVIOLI) across multiple pathogens. We identified RAVIOLI syndrome using diagnosis codes associated with respiratory viral testing or positive respiratory viral assays or fever. After retrospectively applying RAVIOLI criteria to electronic health records, we observed annual winter peaks during 2015-2019, predominantly caused by influenza, followed by cyclic peaks corresponding to SARS-CoV-2 surges during 2020-2024, spikes in RSV in mid-2021 and late 2022, and recrudescent influenza in late 2022 and 2023. RAVIOLI rates were higher and fluctuations more pronounced compared with traditional ILI surveillance. RAVIOLI broadens the scope, granularity, sensitivity, and specificity of respiratory viral illness surveillance compared with traditional ILI surveillance.

During the initial half-year of their existence, infants cannot receive the influenza vaccine, yet they face the greatest susceptibility to severe influenza complications. In this study, we seek to determine whether influenza vaccination of maternal and household contacts is associated with a reduced risk of influenza-like illness (ILI) and severe acute respiratory infection (SARI) in infants. This work was prospectively conducted during the influenza season. A total of 206 infants were included in this study. The percentage of infants with only the mother vaccinated is 12.6% (n:26), and the percent of infants with all household contacts vaccinated is 16% (n:33). Among the infants with only the mother vaccinated, the effectiveness of influenza vaccine is estimated as 35.3% for ILI and 41.3% for SARI. Among infants with all household contacts vaccinated, the effectiveness is estimated as 48.9% for ILI and 76.9% for SARI. Based on the results of multivariate logistic regression analysis, all-household vaccination is a protective factor against SARI (OR: 0.07 95% CI [0.01-0.56]), household size (OR: 1.75, 95% CI [1.24-2.48]) and presence of secondhand smoke (OR: 2.2, 95% CI [1.12-4.45]) significant risk factors for SARI in infants. The mother alone being vaccinated is not a statistically significant protective factor against ILI (OR: 0.46, 95% CI [0.19-1.18]) or SARI (OR: 0.3, 95% CI [0.11-1.21]). Along with the obtained results and analysis, this study provides clear evidence that influenza vaccination of all household contacts of infants aged 0-6 months is significantly associated with protecting infants from both ILI and SARI.

UNASSIGNED: Influenza is an acute respiratory infectious disease with a significant global disease burden. Additionally, the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions (NPIs) have introduced uncertainty to the spread of influenza. However, comparative studies on the performance of innovative models and approaches used for influenza prediction are limited. Therefore, this study aimed to predict the trend of influenza-like illness (ILI) in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance.
UNASSIGNED: The generalized additive model (GAM), deep learning hybrid model based on Gate Recurrent Unit (GRU), and autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model were established to predict the trends of ILI 1-, 2-, 3-, and 4-week-ahead in Beijing, Tianjin, Shanxi, Hubei, Chongqing, Guangdong, Hainan, and the Hong Kong Special Administrative Region in China, based on sentinel surveillance data from 2011 to 2019. Three relevant metrics, namely, Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and R squared, were calculated to evaluate and compare the goodness of fit and robustness of the three models.
UNASSIGNED: Considering the MAPE, RMSE, and R squared values, the ARMA-GARCH model performed best, while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China. Additionally, the models\' predictive performance declined as the weeks ahead increased. Furthermore, blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting.
UNASSIGNED: Our study suggested that the ARMA-GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model. Therefore, in the future, the ARMA-GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones, thereby contributing to influenza control and prevention efforts.

UNASSIGNED: Influenza is the first infectious disease that implements global monitoring and is one of the major public health issues in the world. Air pollutants have become an important global public health issue, in recent years, and much epidemiological and clinical evidence has shown that air pollutants are associated with respiratory diseases.
UNASSIGNED: We comprehensively searched articles published up to 15 November 2022 in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Database of Chinese sci-tech periodicals, and Wanfang Database. The search strategies were based on keyword combinations related to influenza and air pollutants. The air pollutants included particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Meta-analysis was performed using the R programming language (R4.2.1).
UNASSIGNED: A total of 2926 records were identified and 1220 duplicates were excluded. Finally, 19 studies were included in the meta-analysis according to inclusion and exclusion criteria. We observed a significant association between partial air pollutants (PM2.5, NO2, PM10 and SO2) and the incidence risk of influenza. The RRs were 1.0221 (95% CI: 1.0093~1.0352), 1.0395 (95% CI: 1.0131~1.0666), 1.007 (95% CI: 1.0009~1.0132), and 1.0352 (95% CI. 1.0076~1.0635), respectively. However, there was no significant relationship between CO and O3 exposure and influenza, and the RRs were 1.2272 (95% CI: 0.9253~1.6275) and 1.0045 (95% CI: 0.9930~1.0160), respectively.
UNASSIGNED: Exposure to PM2.5, NO2, PM10, and SO2 was significantly associated with influenza, which may be risk factors for influenza. The association of CO and O3 with influenza needs further investigation.

Respiratory viral infections (RVIs) are common reasons for healthcare consultations. The inpatient management of RVIs consumes significant resources. From 2009 to 2014, we assessed the costs of RVI management in 4776 hospitalized children aged 0-18 years participating in a quality improvement program, where all ILI patients underwent virologic testing at the National Reference Centre followed by detailed recording of their clinical course. The direct (medical or non-medical) and indirect costs of inpatient management outside the ICU (\'non-ICU\') versus management requiring ICU care (\'ICU\') added up to EUR 2767.14 (non-ICU) vs. EUR 29,941.71 (ICU) for influenza, EUR 2713.14 (non-ICU) vs. EUR 16,951.06 (ICU) for RSV infections, and EUR 2767.33 (non-ICU) vs. EUR 14,394.02 (ICU) for human rhinovirus (hRV) infections, respectively. Non-ICU inpatient costs were similar for all eight RVIs studied: influenza, RSV, hRV, adenovirus (hAdV), metapneumovirus (hMPV), parainfluenza virus (hPIV), bocavirus (hBoV), and seasonal coronavirus (hCoV) infections. ICU costs for influenza, however, exceeded all other RVIs. At the time of the study, influenza was the only RVI with antiviral treatment options available for children, but only 9.8% of influenza patients (non-ICU) and 1.5% of ICU patients with influenza received antivirals; only 2.9% were vaccinated. Future studies should investigate the economic impact of treatment and prevention of influenza, COVID-19, and RSV post vaccine introduction.