Trends for Syndromic Surveillance of Norovirus in Emergency Department Data Based on Chief Complaints.

BACKGROUND: This study compared trends in norovirus cases to determine whether chief complaint-based emergency department (ED) visit data could reflect trends of norovirus in Korea. METHODS: The ED visits from the National Emergency Department Information System database and the weekly reported number of noroviruses from the sentinel surveillance system were collected between August 2017 and December 2020. The correlation between weekly norovirus cases and weekly ED visits considering the chief complaint and discharge diagnosis code was estimated using a 3-week moving average. RESULTS: In total, 6 399 774 patients with chief complaints related to digestive system disease visited an ED. A higher correlation between reported norovirus cases and ED visit with chief complaint of vomiting and discharge diagnosis code of gastroenteritis and colitis of unspecified origin or other and unspecified gastroenteritis and colitis of infectious origin was observed (R = 0.88, P < .0001). The correlation was highest for the age group 0-4 years (R = 0.89, P < .0001). However, no correlation was observed between the reported norovirus cases and the number of ED visits with norovirus identified as a discharge diagnosis code. CONCLUSIONS: ED visit data considering a combination of chief complaints and discharged diagnosis code would be useful for early detection of infectious disease trends.

Annual hepatitis C testing and positive tests among gay and bisexual men in Australia from 2016 to 2022: a serial cross-sectional analysis of sentinel surveillance data.

OBJECTIVE: Guidelines recommend annual hepatitis C virus (HCV) testing for gay and bisexual men (GBM) with HIV and GBM prescribed HIV pre-exposure prophylaxis (PrEP). However, there is a limited understanding of HCV testing among GBM. We aimed to examine trends in HCV testing and positivity from 2016 to 2022. METHODS: Using sentinel surveillance data, we examined the proportion of GBM with at least one test and the proportion with a positive test in each year for HCV antibody testing among GBM with no previous HCV positive test, HCV RNA testing among GBM with a positive antibody test but no previous positive RNA test (naïve RNA testing), and HCV RNA testing among people who had a previous RNA positive test and a subsequent negative test (RNA follow-up testing). Trends were examined using logistic regression from 2016 to 2019 and 2020 to 2022. RESULTS: Among GBM with HIV, from 2016 to 2019 antibody testing was stable averaging 55% tested annually. Declines were observed for both naïve HCV RNA testing (75.4%-41.4%: p<0.001) and follow-up HCV RNA testing (70.1%-44.5%: p<0.001). Test positivity declined for HCV antibody tests (2.0%-1.3%: p=0.001), HCV RNA naïve tests (75.4%-41.4%: p<0.001) and HCV RNA follow-up tests (11.3%-3.3%: p=0.001). There were minimal or no significant trends from 2020 to 2022.Among GBM prescribed PrEP, antibody testing declined from 2016 to 2019 (79.4%-69.4%: p<0.001) and was stable from 2020 to 2022. Naïve and follow-up HCV RNA testing was stable with an average of 55% and 60% tested each year, respectively. From 2016-2019, the proportion positive from HCV RNA naïve tests declined (44.1%-27.5%: p<0.046) with no significant change thereafter. Positive follow-up HCV RNA tests fluctuated with no or one new positive test among this group in most years. CONCLUSION: The proportion of GBM with positive HCV tests has declined, however a substantial proportion are not tested annually. A renewed focus on HCV testing, and treatment where required, is warranted to achieve HCV elimination among GBM in Australia.

An intervention to improve lumbar puncture rates for meningitis surveillance in children at four secondary health facilities in Malawi: A before/after analysis.

OBJECTIVES: A lumbar puncture (LP) procedure plays a key role in meningitis diagnosis. In Malawi and other sub-Saharan African countries, LP completion rates are sometimes poor, making meningitis surveillance challenging. Our objective was to measure LP rates following an intervention to improve these during a sentinel hospital meningitis surveillance exercise in Malawi. METHODS: We conducted a before/after intervention analysis among under-five children admitted to paediatric wards at four secondary health facilities in Malawi. We used local and World Health Organization (WHO) guidelines to determine indications for LP, as these are widely used in low- and middle-income countries (LMIC). The intervention comprised of refresher trainings for facility staff on LP indications and procedure, use of automated reminders to perform LP in real time in the wards, with an electronic data management system, and addition of surveillance-specific clinical officers to support existing health facility staff with performing LPs. Due to the low numbers in the before/after analysis, we also performed a during/after analysis to supplement the findings. RESULTS: A total of 13,375 under-five children were hospitalised over the 21 months window for this analysis. The LP rate was 10.4% (12/115) and 60.4% (32/53) in the before/after analysis, respectively, and 43.8% (441/1006) and 72.5% (424/599) in the supplemental during/after analysis, respectively. In our intervention-specific analysis among the three individual components, there were improvements in the LP rate by 48% (p < 0.001) following the introduction of surveillance-specific clinical officers, 10% (p < 0.001) following the introduction of automated reminders to perform an LP and 13% following refresher training. CONCLUSIONS: This analysis demonstrated a rise in LP rates following our intervention. This intervention package may be considered for planning future facility-based meningitis surveillances in similar low-resource settings.

Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making.

More than 1.6 million Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests were administered daily in the United States at the peak of the epidemic, with a significant focus on individual treatment. Here, we show that objective-driven, strategic sampling designs and analyses can maximize information gain at the population level, which is necessary to increase situational awareness and predict, prepare for, and respond to a pandemic, while also continuing to inform individual treatment. By focusing on specific objectives such as individual treatment or disease prediction and control (e.g., via the collection of population-level statistics to inform lockdown measures or vaccine rollout) and drawing from the literature on capture-recapture methods to deal with nonrandom sampling and testing errors, we illustrate how public health objectives can be achieved even with limited test availability when testing programs are designed a priori to meet those objectives.

Evaluation of the sentinel yellow fever surveillance system in Uganda, 2017-2022: strengths and weaknesses.

BACKGROUND: Uganda has a sentinel surveillance system in seven high-risk sites to monitor yellow fever (YF) patterns and detect outbreaks. We evaluated the performance of this system from 2017 to 2022. METHODS: We evaluated selected attributes, including timeliness (lags between different critical time points), external completeness (proportion of expected sentinel sites reporting ≥ 1 suspect case in the system annually), and internal completeness (proportion of reports with the minimum required data elements filled), using secondary data in the YF surveillance database from January 2017-July 2022. We conducted key informant interviews with stakeholders at health facility and national level to assess usefulness, flexibility, simplicity, and acceptability of the surveillance system. RESULTS: In total, 3,073 suspected and 15 confirmed YF cases were reported. The median time lag from sample collection to laboratory shipment was 37 days (IQR:21-54). External completeness was 76%; internal completeness was 65%. Stakeholders felt that the surveillance system was simple and acceptable, but were uncertain about flexibility. Most (71%) YF cases in previous outbreaks were detected through the sentinel surveillance system; data were used to inform interventions such as intensified YF vaccination. CONCLUSION: The YF sentinel surveillance system was useful in detecting outbreaks and informing public health action. Delays in case confirmation and incomplete data compromised its overall effectiveness and efficiency.

Enhanced measures, including PCR-based screening and syndromic surveillance for nosocomial outbreaks of the COVID-19 Omicron variant, using descriptive epidemiology and whole-genome sequencing in a Japanese tertiary care hospital.

INTRODUCTION: In this study, we aimed to analyze the effectiveness of enhanced preventive measures against nosocomial COVID-19 Omicron outbreaks based on those encountered. METHODS: We introduced PCR-based screening and syndromic surveillance, in addition to standard and transmission-based precautions, during a COVID-19 outbreak in three wards of Kagoshima University Hospital, a Japanese tertiary care hospital, in February 2022, amid the Omicron variant endemic. Furthermore, we analyzed the descriptive epidemiology and whole-genome sequencing (WGS) of positive SARS-CoV-2 PCR samples from this outbreak. RESULTS: PCR-based screening tests were conducted following the identification of three cases through syndromic surveillance. As a result, 30 individuals tested positive for SARS-CoV-2, including 13 inpatients, five attendant family members, and 12 healthcare workers across the three wards. Notably, no new infections were observed within eight days following the implementation of preventive measures. Among the SARS-CoV-2 genomes analyzed (n = 16; 53.3%), all strains were identified as belonged to BA.1.1 variant. Detailed analysis of descriptive and molecular epidemiology, incorporating single-nucleotide polymorphism analysis of WGS and clarification of transmission links, considering two potential entry routes to the hospital. CONCLUSIONS: Introduction of additional preventive measures, including PCR-based screening and syndromic surveillance, in addition to WGS and descriptive epidemiology, is useful for the early intervention of nosocomial outbreaks and for revealing the transmission route of the COVID-19 Omicron variant.

Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model.

BACKGROUND: Influenza, an acute infectious respiratory disease, presents a significant global health challenge. Accurate prediction of influenza activity is crucial for reducing its impact. Therefore, this study seeks to develop a hybrid Convolution Neural Network-Long Short Term Memory neural network (CNN-LSTM) model to forecast the percentage of influenza-like-illness (ILI) rate in Hebei Province, China. The aim is to provide more precise guidance for influenza prevention and control measures. METHODS: Using ILI% data from 28 national sentinel hospitals in the Hebei Province, spanning from 2010 to 2022, we employed the Python deep learning framework PyTorch to develop the CNN-LSTM model. Additionally, we utilized R and Python to develop four other models commonly used for predicting infectious diseases. After constructing the models, we employed these models to make retrospective predictions, and compared each model's prediction performance using mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and other evaluation metrics. RESULTS: Based on historical ILI% data from 28 national sentinel hospitals in Hebei Province, the Seasonal Auto-Regressive Indagate Moving Average (SARIMA), Extreme Gradient Boosting (XGBoost), Convolution Neural Network (CNN), Long Short Term Memory neural network (LSTM) models were constructed. On the testing set, all models effectively predicted the ILI% trends. Subsequently, these models were used to forecast over different time spans. Across various forecasting periods, the CNN-LSTM model demonstrated the best predictive performance, followed by the XGBoost model, LSTM model, CNN model, and SARIMA model, which exhibited the least favorable performance. CONCLUSION: The hybrid CNN-LSTM model had better prediction performances than the SARIMA model, CNN model, LSTM model, and XGBoost model. This hybrid model could provide more accurate influenza activity projections in the Hebei Province.

A mixed methods study on poisoning and injury-related emergency department visits associated with opioids in Canada, 2011 to 2022: from the Canadian hospitals injury reporting and prevention program.

BACKGROUND: The opioid crisis is a serious public health issue in Canada. There have been many surveillance programs and research studies on opioid-related emergency department (ED) visits at a national, provincial, regional or municipal level. However, no published studies have investigated the in-depth contexts surrounding opioid-related ED visits. In addition, few studies have examined injuries other than poisonings in those visits. The objective of this study is to investigate the contextual factors and co-occurrence of poisonings and injuries among the opioid-related ED visits in a Canadian sentinel surveillance system on injuries and poisonings from 2011 to 2022. METHODS: This study used a mixed methods design. The data source was the Canadian Hospitals Injury Reporting and Prevention Program. We first selected all opioid-related ED visits during our study period and then identified the contextual factors through a content analysis of the combination of the narrative description and other variables in the patients' records. The contextual factors were organized into themes as opioid use context, social resource utilization, bystander involvement, and prior naloxone use. The opioid use context was used as a co-variable to examine the other themes and ED presentations (poisonings and other injuries). Quantitative descriptive approach was used to analyze all the contexts and ED presentations. RESULTS: The most common opioid use context was non-prescribed opioid use without intention to cause harm, followed by self-poisoning, children's exposure, and medication error. Various rare contexts occurred. Paramedics participated in 27.9% of visits. Police and security guards were involved in 5.1% and 2.3% of visits, respectively. Child welfare or social workers were involved in 0.4% of visits. Bystanders initiated 18.9% of the ED visits. Naloxone use before arriving at the ED occurred in 23.4% of the visits with a variety of administrators. The majority of patients presented with poisoning effects, either with poisoning effects only or with other injuries or conditions. CONCLUSIONS: Our study has provided an in-depth analysis of contextual factors and co-occurrence of poisonings and injuries among opioid-related ED visits in Canada. This information is important for ED programming and opioid-related poisoning and injury intervention and prevention.

Focus, vigilance, resilience: towards stronger infectious disease surveillance, threat detection and response in the EU/EEA.

This perspective summarises and explains the long-term surveillance framework 2021-2027 for infectious diseases in the European Union/European Economic Area (EU/EEA) published in April 2023. It shows how shortcomings in the areas of public health focus, vigilance and resilience will be addressed through specific strategies in the coming years and how these strategies will lead to stronger surveillance systems for early detection and monitoring of public health threats as well as informing their effective prevention and control. A sharper public health focus is expected from a more targeted list of notifiable diseases, strictly public-health-objective-driven surveillance standards, and consequently, leaner surveillance systems. Vigilance should improve through mandatory event reporting, more automated epidemic intelligence processing and increased use of genomic surveillance. Finally, EU/EEA surveillance systems should become more resilient by modernising the underlying information technology infrastructure, expanding the influenza sentinel surveillance system to other respiratory viruses for better pandemic preparedness, and increasingly exploiting potentially more robust alternative data sources, such as electronic health records and wastewater surveillance. Continued close collaboration across EU/EEA countries will be key to ensuring the full implementation of this surveillance framework and more effective disease prevention and control.

2023/24 mid-season influenza and Omicron XBB.1.5 vaccine effectiveness estimates from the Canadian Sentinel Practitioner Surveillance Network (SPSN).

The Canadian Sentinel Practitioner Surveillance Network reports mid-season 2023/24 influenza vaccine effectiveness (VE) of 63% (95% CI: 51-72) against influenza A(H1N1)pdm09, lower for clade 5a.2a.1 (56%; 95% CI: 33-71) than clade 5a.2a (67%; 95% CI: 48-80), and lowest against influenza A(H3N2) (40%; 95% CI: 5-61). The Omicron XBB.1.5 vaccine protected comparably well, with VE of 47% (95% CI: 21-65) against medically attended COVID-19, higher among people reporting a prior confirmed SARS-CoV-2 infection at 67% (95% CI: 28-85).

Validation of an acute respiratory infection phenotyping algorithm to support robust computerised medical record-based respiratory sentinel surveillance, England, 2023.

IntroductionRespiratory sentinel surveillance systems leveraging computerised medical records (CMR) use phenotyping algorithms to identify cases of interest, such as acute respiratory infection (ARI). The Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) is the English primary care-based sentinel surveillance network.AimThis study describes and validates the RSC's new ARI phenotyping algorithm.MethodsWe developed the phenotyping algorithm using a framework aligned with international interoperability standards. We validated our algorithm by comparing ARI events identified during the 2022/23 influenza season in England through use of both old and new algorithms. We compared clinical codes commonly used for recording ARI.ResultsThe new algorithm identified an additional 860,039 cases and excluded 52,258, resulting in a net increase of 807,781 cases (33.84%) of ARI compared to the old algorithm, with totals of 3,194,224 cases versus 2,386,443 cases. Of the 860,039 newly identified cases, the majority (63.7%) were due to identification of symptom codes suggestive of an ARI diagnosis not detected by the old algorithm. The 52,258 cases incorrectly identified by the old algorithm were due to inadvertent identification of chronic, recurrent, non-infectious and other non-ARI disease.ConclusionWe developed a new ARI phenotyping algorithm that more accurately identifies cases of ARI from the CMR. This will benefit public health by providing more accurate surveillance reports to public health authorities. This new algorithm can serve as a blueprint for other CMR-based surveillance systems wishing to develop similar phenotyping algorithms.

Hospital surveillance of respiratory viruses during the COVID-19 pandemic and beyond: contribution to the WHO mosaic framework, Israel, 2020 to 2023.

BackgroundA new respiratory virus surveillance platform, based on nationwide hospital laboratory data, was established in Israel during the COVID-19 pandemic.AimWe aimed to evaluate the performance of this platform with respect to the detection of influenza and respiratory syncytial virus (RSV) from week 36 in 2020 to week 15 in 2023, and how it fits with the World Health Organization (WHO) mosaic surveillance framework.MethodsData of respiratory samples from hospitalised patients sent for laboratory confirmation of influenza virus or RSV from 25 general hospital laboratories nationwide were collected. We analysed the weekly number and percentage of samples positive for influenza virus or RSV vis-à-vis SARS-CoV-2 activity and compared data from the new surveillance platform with existing surveillance platforms. Using data in the new surveillance platform, we analysed early stages of a 2021 out-of-season RSV outbreak and evaluated the capabilities of the new surveillance system with respect to objectives and domains of the WHO mosaic framework.ResultsThe new hospital-laboratory surveillance platform captured the activity of influenza virus and RSV, provided crucial data when outpatient sentinel surveillance was not operational and supported an out-of-season RSV outbreak investigation. The new surveillance platform fulfilled important objectives in all three domains of the mosaic framework and could serve for gathering additional information to fulfil more domain objectives.ConclusionThe new hospital laboratory surveillance platform provided essential data during the COVID-19 pandemic and beyond, fulfilled important domain objectives of the mosaic framework and could be adapted for the surveillance of other viruses.

Twenty-five years of sentinel laboratory-based surveillance of shigellosis in a high-income country endemic for the disease, Israel, 1998 to 2022.

BackgroundShigella is a leading cause of moderate-to-severe diarrhoea worldwide and diarrhoeal deaths in children in low- and-middle-income countries.AimWe investigated trends and characteristics of shigellosis and antimicrobial resistance of Shigella sonnei in Israel.MethodsWe analysed data generated by the Sentinel Laboratory-Based Surveillance Network for Enteric Pathogens that systematically collects data on detection of Shigella at sentinel laboratories, along with the characterisation of the isolates at the Shigella National Reference Laboratory. Trends in the shigellosis incidence were assessed using Joinpoint regression and interrupted time-series analyses.ResultsThe average incidence of culture-confirmed shigellosis in Israel declined from 114 per 100,000 population (95% confidence interval (CI): 112-115) 1998-2004 to 80 per 100,000 population (95% CI: 79-82) 2005-2011. This rate remained stable 2012-2019, being 18-32 times higher than that reported from the United States or European high-income countries. After decreasing to its lowest values during the COVID-19 pandemic years (19/100,000 in 2020 and 5/100,000 in 2021), the incidence of culture-confirmed shigellosis increased to 39 per 100,000 population in 2022. Shigella sonnei is the most common serogroup, responsible for a cyclic occurrence of propagated epidemics, and the proportion of Shigella flexneri has decreased. Simultaneous resistance of S. sonnei to ceftriaxone, ampicillin and sulphamethoxazole-trimethoprim increased from 8.5% (34/402) in 2020 to 92.0% (801/876) in 2022.ConclusionsThese findings reinforce the need for continuous laboratory-based surveillance and inform the primary and secondary prevention strategies for shigellosis in Israel and other endemic high-income countries or communities.

Chlamydia retesting remains low among young women in Australia: an observational study using sentinel surveillance data, 2018-2022.

BACKGROUND: Chlamydia remains the most notified bacterial sexually transmissible infection in Australia with guidelines recommending testing for re-infection at 3months post treatment. This paper aimed to determine chlamydia retesting and repeat positivity rates within 2-4months among young women in Australia, and to evaluate what factors increase or decrease the likelihood of retesting. METHODS: Chlamydia retesting rates among 16-29-year-old women were analysed from Australian Collaboration for Coordinated Enhanced Sentinel Surveillance of sexually transmissible infection and bloodborne virus (ACCESS) sentinel surveillance data (n =62 sites). Among women with at least one positive test between 1 January 2018 and 31 August 2022, retesting counts and proportions within 2-4months were calculated. Logistic regression was performed to assess factors associated with retesting within 2-4months. RESULTS: Among 8758 women who were positive before 31 August 2022 to allow time for follow up, 1423 (16.2%) were retested within 2-4months, of whom 179 (12.6%) tested positive. The odds of retesting within 2-4months were 25% lower if tested in a coronavirus disease 2019 (COVID-9) pandemic year (2020-2022) (aOR=0.75; 95% CI 0.59-0.95). Among 9140 women with a positive test before 30 November 2022, 397 (4.3%) were retested too early (within 7days to 1month) and 81 (20.4%) of those were positive. CONCLUSIONS: Chlamydia retesting rates remain low with around a sixth of women retested within 2-4months in line with guidelines. Re-infection is common with around one in eight retesting positive. An increase in retesting is required to reduce the risk of reproductive complications and onward transmission.

Using a novel 'difference-in-differences' method and syndromic surveillance to estimate the change in local healthcare utilisation during periods of media reporting in the early stages of the COVID-19 pandemic in England.

OBJECTIVES: Syndromic surveillance supplements traditional laboratory reporting for infectious diseases monitoring. Prior to widespread COVID-19 community surveillance, syndromic surveillance was one of several systems providing real-time information on changes in healthcare-seeking behaviour. The study objective was to identify changes in healthcare utilisation during periods of high local media reporting in England using 'difference-in-differences' (DiD). STUDY DESIGN: A retrospective observational study was conducted using five media events in January-February 2020 in England on four routinely monitored syndromic surveillance indicators. METHODS: Dates 'exposed' to a media event were estimated using Google Trends internet search intensity data (terms = 'coronavirus' and local authority [LA]). We constructed a negative-binomial regression model for each indicator and event time period to estimate a direct effect. RESULTS: We estimated a four-fold increase in telehealth 'cough' calls and a 1.4-fold increase in emergency department (ED) attendances for acute respiratory illness in Brighton and Hove, when a so-called 'superspreading event' in this location was reported in local and national media. Significant decreases were observed in the Buxton (telehealth and ED attendance) and Wirral (ED attendance) areas during media reports of a returnee from an outbreak abroad and a quarantine site opening in the area respectively. CONCLUSIONS: We used a novel approach to directly estimate changes in syndromic surveillance reporting during the early phase of the COVID-19 pandemic in England, providing contextual information on the interpretation of changes in health indicators. With careful consideration of event timings, DiD is useful in producing real-time estimates on specific indicators for informing public health action.

Utilizing Wearable Device Data for Syndromic Surveillance: A Fever Detection Approach.

Commercially available wearable devices (wearables) show promise for continuous physiological monitoring. Previous works have demonstrated that wearables can be used to detect the onset of acute infectious diseases, particularly those characterized by fever. We aimed to evaluate whether these devices could be used for the more general task of syndromic surveillance. We obtained wearable device data (Oura Ring) from 63,153 participants. We constructed a dataset using participants' wearable device data and participants' responses to daily online questionnaires. We included days from the participants if they (1) completed the questionnaire, (2) reported not experiencing fever and reported a self-collected body temperature below 38 °C (negative class), or reported experiencing fever and reported a self-collected body temperature at or above 38 °C (positive class), and (3) wore the wearable device the nights before and after that day. We used wearable device data (i.e., skin temperature, heart rate, and sleep) from the nights before and after participants' fever day to train a tree-based classifier to detect self-reported fevers. We evaluated the performance of our model using a five-fold cross-validation scheme. Sixteen thousand, seven hundred, and ninety-four participants provided at least one valid ground truth day; there were a total of 724 fever days (positive class examples) from 463 participants and 342,430 non-fever days (negative class examples) from 16,687 participants. Our model exhibited an area under the receiver operating characteristic curve (AUROC) of 0.85 and an average precision (AP) of 0.25. At a sensitivity of 0.50, our calibrated model had a false positive rate of 0.8%. Our results suggest that it might be possible to leverage data from these devices at a public health level for live fever surveillance. Implementing these models could increase our ability to detect disease prevalence and spread in real-time during infectious disease outbreaks.

[Results of PCR Pool Testing In Primary and Special Needs Schools In Bavaria For The School Year 2021/2022: Sentinel Surveillance In Face-To-Face Teaching During The Sars-CoV-2 Pandemic]. / Ergebnisse von PCR-Pooltestungen an bayerischen Grund- und Förderschulen im Schuljahr 2021/2022 zur Surveillance im Präsenzunterricht während der SARS-CoV-2-Pandemie.

In the school years 2019/20 and 2020/21, children were physically, psychologically, and socially stressed by school closures caused by the SARS-CoV-2 pandemic. To ensure attendance with optimal infection protection, PCR pool testing was conducted during the 2021/22 school year at Bavarian elementary schools and schools for pupils with special needs for timely detection of SARS-CoV-2 infection. This study analyzes the results of PCR pool testing over time stratified by region, school type, and age of children. The data were obtained from classes in elementary and special needs schools, involving pupils aged 6 to 11 years, who participated in the Bavaria-wide PCR pool testing from 09/20/21 to 04/08/22. Samples were collected twice weekly, consisting of PCR pool samples and individual PCR samples, which were only evaluated in case of a positive pool test. A class was considered positive if at least one individual sample from that class was positive within a calendar week (CW). A school (class) was considered to be infection-prone if three or more classes in that school (students in that class) were positive within a CW. The data included 2,430 elementary schools (339 special needs schools) with 23,021 (2,711) classes and 456,478 (29,200) children. A total of 1,157,617 pools (of which 3.37% were positive) and 724,438 individual samples (6.76% positive) were analyzed. Larger schools exhibited higher PR compared to smaller schools. From January 2022, the Omicron variant led to a massive increase in PR across Bavaria. The incidence rates per 100,000 person-weeks within the individual school samples were significantly lower than the concurrently reported age-specific and general infection incidences in the overall Bavarian population. PCR pool testing revealed relatively few positive pools, with an average of four children per one hundred pools testing positive. Schools and classes were rarely considered infection-prone, even during periods of high incidences outside of schools. The combination of PCR pool testing and hygiene measures allowed for a largely safe in-person education for pupils in primary and special needs schools in the school year 2021/22.

[Epidemiological characteristics of human respiratory syncytial virus in Hubei Province from 2016 to 2023].

Objective: To analyze the epidemiological characteristics of human respiratory syncytial virus (HRSV) in patients with acute respiratory infection (ARIs) in sentinel hospitals of the Hubei influenza surveillance network from 2016 to 2023. Methods: ARIs samples [including influenza-like cases (ILI) and severe acute respiratory infection (SARI)] were collected from influenza surveillance sentinel hospitals in Hubei Province from 2016 to 2023, and case information was collected. HRSV virus nucleic acid typing was performed by fluorescence quantitative PCR method, and the data were collated, plotted and analyzed. Results: From 2016 to 2023, 12 779 cases of ILI and 9 166 cases of SARI were collected. The positive rate of HRSV was the highest in<5 years of age group [15.77% (168/1 065)], among which the positive rate was the highest in 2 to 5 years of age group of ILI cases [13.60% (31/228)], and the positive rate was the highest in 0 to 2 years of age group of SARI cases [25.97% (60/231)] (all P values<0.001). The positive rate of HRSV in SARI cases was 2.31%-25.97%, higher than that in ILI cases (0-13.60%) (P=0.016). HRSV was prevalent in autumn and winter from 2016 to 2020 and in spring in 2023. Alternating epidemics of HRSV virus type A and B in Hubei Province from 2016 to 2023 (dominant epidemics of type B in 2016 and 2020; dominant epidemics of type A in 2017-2019 and 2023). Conclusion: SARI and ILI patients under five years old are the main infection groups of HRSV. The seasonal prevalence characteristics of HRSV in Hubei Province from 2016 to 2023 shift from autumn and winter to spring.

Sentinel Surveillance System Implementation and Evaluation for SARS-CoV-2 Genomic Data, Washington, USA, 2020-2021.

Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.

Increased cases of influenza C virus in children and adults in Austria, 2022.

Sentinel surveillance of influenza-like illnesses revealed an increase in the cases of influenza C virus in children and adults in Austria, 2022, compared to previous years, following one season (2020/2021), wherein no influenza C virus was detected. Whole-genome sequencing revealed no obvious genetic basis for the increase. We propose that the reemergence is explained by waning immunity from lack of community exposure due to restrictions intended to limit severe acute respiratory syndrome coronavirus 2 spread in prior seasons, pending further investigation.