Respiratory syncytial virus infection notification trends and interpretation of the reported case data, 2018-2021, Japan.

In Japan, as elsewhere, the COVID-19 pandemic affected the notification trends of respiratory syncytial virus (RSV) infection. Here, we describe the epidemiological trends of RSV cases among children reported during 2018-2021 in Japan, based on the national surveillance system. Compared to 2018 and 2019, 2020 saw an unprecedented decrease in RSV notifications per sentinel site. However, 2021 experienced an unseasonably early and high peak in week 28 (peak week in 2018 and 2019: week 37) with a large resurgence in notifications, nationwide and across regions. Regarding age, compared to 2018 and 2019, the number and proportion of cases aged 2, 3, and ≥4-years increased substantially in 2021 but the number of cases aged <1 year decreased slightly. Furthermore, in 2021, the ratio of notifications per site from outpatient clinics to hospitals increased, suggesting a proportionate increase in clinically milder case diagnoses. Notably, RSV-attributed deaths from vital statistics also dropped substantially in 2020 and rebounded in 2021, but were fewer than in 2018 or 2019. While RSV incidence likely declined in 2020 (possibly from COVID-19 countermeasures) and increased in 2021, notifications in 2021 appeared to be associated with milder presentations. Given unpredictable RSV epidemiology, continuous monitoring and pluralistic assessments are imperative.

From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England.

The purpose of syndromic surveillance is to provide early warning of public health incidents, real-time situational awareness during incidents and emergencies, and reassurance of the lack of impact on the population, particularly during mass gatherings. The United Kingdom Health Security Agency (UKHSA) currently coordinates a real-time syndromic surveillance service that encompasses 6 national syndromic surveillance systems reporting on daily health care usage across England. Each working day, UKHSA analyzes syndromic data from over 200,000 daily patient encounters with the National Health Service, monitoring over 140 unique syndromic indicators, risk assessing over 50 daily statistical exceedances, and taking and recommending public health action on these daily. This English syndromic surveillance service had its origins as a small exploratory pilot in a single region of England in 1999 involving a new pilot telehealth service, initially reporting only on "cold or flu" calls. This pilot showed the value of syndromic surveillance in England, providing advanced warning of the start of seasonal influenza activity over existing laboratory-based surveillance systems. Since this initial pilot, a program of real-time syndromic surveillance has evolved from the single-system, -region, -indicator pilot (using manual data transfer methods) to an all-hazard, multisystem, automated national service. The suite of systems now monitors a wide range of syndromes, from acute respiratory illness to diarrhea to cardiac conditions, and is widely used in routine public health surveillance and for monitoring seasonal respiratory disease and incidents such as the COVID-19 pandemic. Here, we describe the 25-year evolution of the English syndromic surveillance system, focusing on the expansion and improvements in data sources and data management, the technological and digital enablers, and novel methods of data analytics and visualization.

Estimation of vaccine effectiveness against SARS-CoV-2-associated hospitalization using sentinel surveillance in South Africa.

BACKGROUND: COVID-19 vaccine effectiveness (VE) studies leveraging systematic surveillance in sub-Saharan Africa are limited. We assessed the effectiveness of two vaccines (Pfizer BNT162b2 and Johnson & Johnson Ad26.COV2.S) against SARS-CoV-2-associated hospitalization in South African adults aged ≥18 years. METHODS: We conducted a test-negative case-control study using pneumonia surveillance data in South Africa. Inpatients with physician-diagnosed lower respiratory tract infection or suspected COVID-19, testing SARS-CoV-2 positive or negative from June 2021-March 2022, were cases or controls, respectively. Fully vaccinated individuals received one Ad26.COV2.S dose or two BNT162b2 doses ≥14-days before enrollment. VE was estimated using multivariable logistic regression for Delta- and Omicron BA.1/BA.2-predominant periods, stratified by age and HIV status. RESULTS: The study included 925 cases and 1890 controls; 38 (4%) cases and 186 (10%) controls were fully vaccinated with BNT162b2, and 30 (3%) cases and 94 (5%) controls with Ad26.COV2.S. The vaccine effectiveness of BNT162b2 against SARS-CoV-2-associated hospitalization over Delta and Omicron BA.1/BA.2 periods was 91% (95% CI: 52%, 98%) and 33% (-16%, 86%), respectively. The vaccine effectiveness of Ad26.COV2.S against hospitalization over Delta and Omicron BA.1/BA.2 periods was 72% (-36% ,94%), and -19% (-130%, 39%), respectively. The vaccine effectiveness of BNT162b2 against hospitalization over the Delta period was 94% (50%, 99%) and 89% (27%, 98%) among adults aged ≥60 years and HIV-uninfected, respectively. CONCLUSIONS: The BNT162b2 vaccine was effective against SARS-CoV-2-associated hospitalization during the Delta period for adults aged ≥18 years, ≥60 years and those HIV-uninfected. VE for Ad26.COV2.S was inconclusive, potentially due to limited sample size or residual confounding. These findings highlight the utility of sentinel surveillance for estimating VE.

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.

Reconstructing the age-structured case count of COVID-19 from sentinel surveillance data in Japan: A modeling study.

OBJECTIVES: To reconstruct age-structured case counts of COVID-19 using sentinel reporting, which replaced universal reporting of COVID-19 from May 2023 in Japan. METHODS: Using COVID-19 sentinel data stratified by discrete age groups in selected prefectures and referring to universal case count data up to May 8, 2023, we fitted a statistical model to handle weekly growth rates as a function of age and time so as to convert sentinel data to case counts after cessation of universal reporting. RESULTS: The age distribution of cases in sentinel reporting was significantly biased toward younger age groups compared to universal reporting. When comparing the epidemic size of the 9th wave (May 8 to September 18, 2023) to the 8th wave (October 3, 2022 to April 10, 2023), using the wave-on-wave ratio of total cumulative sentinel cases led to a significant underestimation of the wave-on-wave in Tokyo (0.975, vs 1.461 by universal reporting) and Okinawa (1.299, vs 1.472). The estimates of growth rates, scaling factors between universal and sentinel cases, and expected universal case count showed robustness to changes in the ending week of the data period. CONCLUSION: Our model quantified COVID-19 dynamics, comparably to universal reporting that ended in May 2023, enabling detailed and up-to-date health burden analysis using sentinel reports. The cumulative incidence was greater than that suggested from sentinel data in Tokyo, Nara, and Okinawa. Per-population burdens among children were particularly high in Osaka and Nara, indicating a strong bias in sentinel reporting toward pediatric cases.

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.

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.

Epidemiologic and Virologic Characteristics of Influenza in Lao PDR, 2016-2023.

BACKGROUND: Influenza sentinel surveillance in Lao PDR is used to inform seasonal vaccination programs. This analysis reviews epidemiologic and virologic characteristics of influenza virus infection over 8 years, before and after emergence of SARS-CoV-2. METHODS: Data collected for ILI and SARI surveillance during January 2016 through December 2023 were analyzed from nine hospitals. Respiratory specimens from ILI and SARI cases were tested by reverse transcriptase polymerase chain reaction to determine influenza positivity and subtype and lineage. Aggregate counts of outpatient visits and hospitalizations were collected from hospital logbooks. Epidemiologic trends of influenza activity were described, and the proportional contribution of influenza-associated ILI and SARI to outpatient and inpatient loads was estimated. RESULTS: Influenza was detected year-round with positivity peaking during September through January and occurring in most years approximately 1 month earlier in the south than the north. After decreasing in 2 years following the emergence of SARS-CoV-2, influenza positivity increased in 2022 and resumed its typical temporal trend. Influenza-associated ILI contribution to outpatient visits was highest among children ages 5-14 years (3.0% of all outpatient visits in 2023), and influenza-associated SARI contribution to inpatient hospitalizations was highest among children ages 2-4 years (2.2% of all hospitalizations in 2023). CONCLUSIONS: Influenza surveillance in Lao PDR provides clinicians and public health authorities with information on geographic and temporal patterns of influenza transmission. Influenza surveillance data support current vaccination timing and recommendations to vaccinate certain populations, especially young children.

SARS-CoV-2 infection in synanthropic rats from Guayaquil city (Ecuador) during COVID-19 pandemic: A proxy to prevent wild reservoirs in the tropics.

Human-to-animal reverse transmission of SARS-CoV-2 is a risk for new reservoirs' emergence and new variants' evolution. SARS-CoV-2 infection of synanthropic rodents in urban settings has been reported during COVID-19 in New York and Mexico cities. In this study, we addressed the potential transmission of SARS-CoV-2 to synanthropic rats in the city of Guayaquil (Ecuador) during the COVID-19 pandemic. A total number of 234 rats were collected and analyzed for SARS-CoV-2 detection by RT-qPCR. A positivity rate of 6 % (14 rats) was found, and SARS-CoV-2 infection was confirmed by Sanger sequencing of the viral genome. Our results confirm the potential risk of synanthropic rats as reservoirs for SARS-CoV-2 infection. This is worrisome for low and middle income countries like Ecuador, where pest and waste control in urban settings is challenging. Moreover, the risk of spillover to wild fauna is a concern in Guayaquil, where synanthropic fauna includes raccoons or coatis and forest patches with a wild population of felids or primates existing within the city limits. In this context, SARS-CoV-2 sentinel surveillance of synanthropic rodents could serve as a proxy for a One Health approach to prevent the emergence of new wild reservoirs.

Influenza virus circulation and vaccine effectiveness during June 2021-May 2023 in Thailand.

Thai Ministry of Public Health recommends influenza vaccination for certain risk groups. We evaluated 2023 Southern Hemisphere influenza vaccine effectiveness against medically attended influenza using surveillance data from nine Thai hospitals and a test-negative design. During June 2022-May 2023, influenza vaccine provided moderate protection against seeking care for influenza illness (adjusted vaccine effectiveness 51%; 95% confidence interval 28-67). Understanding vaccine effectiveness can help guide future antigen selection and support clinicians to make a strong influenza vaccine recommendation to patients.

Laboratory capacity expansion: lessons from establishing molecular testing in regional referral laboratories in Ethiopia.

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.

Model-based disease mapping using primary care registry data.

BACKGROUND: Spatial modeling of disease risk using primary care registry data is promising for public health surveillance. However, it remains unclear to which extent challenges such as spatially disproportionate sampling and practice-specific reporting variation affect statistical inference. METHODS: Using lower respiratory tract infection data from the INTEGO registry, modeled with a logistic model incorporating patient characteristics, a spatially structured random effect at municipality level, and an unstructured random effect at practice level, we conducted a case and simulation study to assess the impact of these challenges on spatial trend estimation. RESULTS: Even with spatial imbalance and practice-specific reporting variation, the model performed well. Performance improved with increasing spatial sample balance and decreasing practice-specific variation. CONCLUSION: Our findings indicate that, with correction for reporting efforts, primary care registries are valuable for spatial trend estimation. The diversity of patient locations within practice populations plays an important role.

Cooperative Sentinel Surveillance of Malaria in Laiza and Nearby Areas of Myanmar and Importation Threat Monitoring - China, 2019-2023.

Introduction: Laiza and nearby areas (LNA) in Myanmar are identified as the primary malaria hotspots in the bordering regions of Yunnan Province, China. Methods: Six sentinel surveillance sites were established at the China-Myanmar border in LNA to monitor malaria. Data from 2019 was used as a baseline to analyze malaria incidence and trends in LNA and Myanmar, as well as the importation of malaria cases into China from 2019 to 2023. Results: Plasmodium vivax was the predominant species, representing 99.95% (14,060/14,066) of confirmed malaria cases in LNA. A total of 8,356 malaria cases were identified in 2023, with an annual parasite incidence (API) of 19.78 per 100 person-years. Compared to 2019, the incidence rate ratio was 21.47 (95% confidence interval: 18.84, 24.48), indicating that the API in 2023 was 21.47 times higher than that in 2019. In Yunnan, out of 1,016 reported cases, 545 imported cases (53.64%) originated from LNA and spread to 18 (13.95%) out of 129 counties. Ten provinces in China, including Yunnan, reported imported malaria cases from LNA in Myanmar. Conclusions: The increase in population, particularly among internally displaced persons, along with inadequate healthcare services, has led to a notable resurgence of malaria in LNA. This resurgence poses a risk to preventing the re-emergence of malaria transmission in China. There is an urgent need for novel collaborative policies, as well as financial and technical assistance, to enhance malaria control efforts in LNA, Myanmar.

A Profile of Influenza Vaccine Coverage for 2019-2020: Database Study of the English Primary Care Sentinel Cohort.

BACKGROUND: Innovation in seasonal influenza vaccine development has resulted in a wider range of formulations becoming available. Understanding vaccine coverage across populations including the timing of administration is important when evaluating vaccine benefits and risks. OBJECTIVE: This study aims to report the representativeness, uptake of influenza vaccines, different formulations of influenza vaccines, and timing of administration within the English Primary Care Sentinel Cohort (PCSC). METHODS: We used the PCSC of the Oxford-Royal College of General Practitioners Research and Surveillance Centre. We included patients of all ages registered with PCSC member general practices, reporting influenza vaccine coverage between September 1, 2019, and January 29, 2020. We identified influenza vaccination recipients and characterized them by age, clinical risk groups, and vaccine type. We reported the date of influenza vaccination within the PCSC by International Standard Organization (ISO) week. The representativeness of the PCSC population was compared with population data provided by the Office for National Statistics. PCSC influenza vaccine coverage was compared with published UK Health Security Agency's national data. We used paired t tests to compare populations, reported with 95% CI. RESULTS: The PCSC comprised 7,010,627 people from 693 general practices. The study population included a greater proportion of people aged 18-49 years (2,982,390/7,010,627, 42.5%; 95% CI 42.5%-42.6%) compared with the Office for National Statistics 2019 midyear population estimates (23,219,730/56,286,961, 41.3%; 95% CI 4.12%-41.3%; P<.001). People who are more deprived were underrepresented and those in the least deprived quintile were overrepresented. Within the study population, 24.7% (1,731,062/7,010,627; 95% CI 24.7%-24.7%) of people of all ages received an influenza vaccine compared with 24.2% (14,468,665/59,764,928; 95% CI 24.2%-24.2%; P<.001) in national data. The highest coverage was in people aged ≥65 years (913,695/1,264,700, 72.3%; 95% CI 72.2%-72.3%). The proportion of people in risk groups who received an influenza vaccine was also higher; for example, 69.8% (284,280/407,228; 95% CI 69.7%-70%) of people with diabetes in the PCSC received an influenza vaccine compared with 61.2% (983,727/1,607,996; 95% CI 61.1%-61.3%; P<.001) in national data. In the PCSC, vaccine type and brand information were available for 71.8% (358,365/498,923; 95% CI 71.7%-72%) of people aged 16-64 years and 81.9% (748,312/913,695; 95% CI 81.8%-82%) of people aged ≥65 years, compared with 23.6% (696,880/2,900,000) and 17.8% (1,385,888/7,700,000), respectively, of the same age groups in national data. Vaccination commenced during ISO week 35, continued until ISO week 3, and peaked during ISO week 41. The in-week peak in vaccination administration was on Saturdays. CONCLUSIONS: The PCSC's sociodemographic profile was similar to the national population and captured more data about risk groups, vaccine brands, and batches. This may reflect higher data quality. Its capabilities included reporting precise dates of administration. The PCSC is suitable for undertaking studies of influenza vaccine coverage.

Predicting influenza-like illness trends based on sentinel surveillance data in China from 2011 to 2019: A modelling and comparative study1.

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

Characterising the changes in RSV epidemiology in Beijing, China during 2015-2023: results from a prospective, multi-centre, hospital-based surveillance and serology study.

Background: Respiratory syncytial virus (RSV) has posed substantial morbidity and mortality burden to young children and older adults globally. The coronavirus disease 2019 (COVID-19) pandemic was reported to have altered RSV epidemiology and could have important implications for RSV prevention and control strategies. We aimed to compare RSV epidemiology in different phases of the COVID-19 pandemic with the pre-pandemic period by leveraging epidemiological, molecular, and serological data collected from a prospective respiratory pathogen surveillance and serology study. Methods: This study was based on the data during July 1, 2015 to November 30, 2023 from the Respiratory Pathogen Surveillance System (RPSS), a sentinel-hospital based surveillance system of acute respiratory infections consisting of 35 hospitals that represent residents of all ages from all 16 districts in Beijing, China. RSV infection status was tested by RT-PCR and gene sequencing and phylogenetic analysis was conducted among the identified RSV strains. We further supplemented RPSS data with three serology surveys conducted during 2017-2023 that tested RSV IgG levels from serum specimens. RSV detection rate was calculated by calendar month and compared across RSV seasons (defined as the July 1 through June 30 of the following year). RSV IgG positivity proportion was calculated by quarter of the year and was correlated with quarterly aggregated RSV detection rate for understanding the relationship between infection and immunity at the population level. Findings: Overall, a total of 52,931 respiratory specimens were collected and tested over the study period. RSV detection rates ranged from 1.24% (94/7594) in the 2017-2018 season to 2.80% (219/7824) in the 2018-2019 season, and from 1.06% (55/5165) in the 2022-2023 season to 2.98% (147/4938) in the 2021-2022 season during the pre-pandemic and pandemic period, respectively. ON1 and BA9 remained the predominant genotypes during the pandemic period; no novel RSV strains were identified. RSV circulation followed a winter-months seasonal pattern in most seasons. One exception was the 2020-2021 season when an extensive year-round circulation was observed, possibly associated with partial relaxation of non-pharmaceutical interventions (NPIs). The other exception was the 2022-2023 season when very low RSV activity was observed during the usual winter months (possibly due to the concurrent local COVID-19 epidemic), and followed by an out-of-season resurgence in the spring, with RSV detection persisting to the end of the study period (November 2023). During the two seasons above, we noted an age-group related asynchrony in the RSV detection rate; the RSV detection rate in young children remained similar (or even increased with borderline significance; 43/594, 7.24%, and 42/556, 7.55% vs 292/5293, 5.52%; P = 0.10 and P = 0.06, respectively) compared with the pre-pandemic seasons whereas the detection rate in older adults decreased significantly (8/1779, 0.45%, and 3/2021, 0.15% vs 160/10,348, 1.55%; P < 0.001 in two comparisons). Results from serology surveys showed significantly declined RSV IgG positivity in the 2022-2023 season compared to the pre-pandemic seasons (9.32%, 29/311 vs 20.16%, 100/496; P < 0.001); older adults had significantly higher RSV IgG positivity than young children in both pre-pandemic and pandemic periods (P values < 0.001). Interpretation: Our study documented the trajectory of RSV detection along with the changes in the stringency of NPIs, measured IgG positivity, and local COVID-19 epidemics. The findings suggest the interplay between contact patterns, immunity dynamics, and SARS-CoV-2 infection in shaping the RSV epidemics of population of different ages. These findings provide novel insights into the potential drivers of RSV circulating patterns and have important implications for RSV prevention and control strategies. Funding: The High-qualified Public Health Professionals Development Project, Capital's Funds for Health Improvement and Research, and the Public Health Personnel Training Support Program.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024.

BACKGROUND: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE: We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS: The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

Usefulness of a Pluralistic Approach in Sentinel Surveillance: Seasonal Influenza Activity Based on Case Counts per Sentinel Site in the National Epidemiological Surveillance of Infectious Diseases Program and Test Counts, Case Counts, and Test Positivity from the National Hospital Organization.

In Japan, based on the National Epidemiological Surveillance of Infectious Diseases (NESID) Program, influenza cases from approximately 5,000 sentinel sites are monitored weekly as part of influenza surveillance (as the number of influenza cases per sentinel site). One limitation is that the number of influenza tests conducted is not reported. However, the National Hospital Organization (NHO), with approximately 140 hospitals, routinely publishes three indicators: the number of influenza tests, the number of influenza-positive cases, and test positivity. We used the NESID and NHO data from April 2011 to June 2022 to assess the usefulness of multiple indicators for monitoring influenza activity. The temporal trends of the NHO and NESID indicator were similar, and the NHO indicator levels correlated well with those of the NESID indicators. However, influenza positivity in the NHO data showed an earlier rise and peak time than that in the NESID indicator. Importantly, during the non-epidemic summer periods and the coronavirus disease 2019 pandemic, a sizable number of influenza tests were still performed at NHO hospitals, with results showing considerably low case counts and test positivity. These data show that a relatively small number of sentinel sites is sufficient to monitor influenza activity nationally and that utilizing multiple indicators can increase our confidence in situational awareness and data interpretations.

Use of Sentinel Surveillance Platforms for Monitoring SARS-CoV-2 Activity: Evidence From Analysis of Kenya Influenza Sentinel Surveillance Data.

BACKGROUND: Little is known about the cocirculation of influenza and SARS-CoV-2 viruses during the COVID-19 pandemic and the use of respiratory disease sentinel surveillance platforms for monitoring SARS-CoV-2 activity in sub-Saharan Africa. OBJECTIVE: We aimed to describe influenza and SARS-CoV-2 cocirculation in Kenya and how the SARS-CoV-2 data from influenza sentinel surveillance correlated with that of universal national surveillance. METHODS: From April 2020 to March 2022, we enrolled 7349 patients with severe acute respiratory illness or influenza-like illness at 8 sentinel influenza surveillance sites in Kenya and collected demographic, clinical, underlying medical condition, vaccination, and exposure information, as well as respiratory specimens, from them. Respiratory specimens were tested for influenza and SARS-CoV-2 by real-time reverse transcription polymerase chain reaction. The universal national-level SARS-CoV-2 data were also obtained from the Kenya Ministry of Health. The universal national-level SARS-CoV-2 data were collected from all health facilities nationally, border entry points, and contact tracing in Kenya. Epidemic curves and Pearson r were used to describe the correlation between SARS-CoV-2 positivity in data from the 8 influenza sentinel sites in Kenya and that of the universal national SARS-CoV-2 surveillance data. A logistic regression model was used to assess the association between influenza and SARS-CoV-2 coinfection with severe clinical illness. We defined severe clinical illness as any of oxygen saturation <90%, in-hospital death, admission to intensive care unit or high dependence unit, mechanical ventilation, or a report of any danger sign (ie, inability to drink or eat, severe vomiting, grunting, stridor, or unconsciousness in children younger than 5 years) among patients with severe acute respiratory illness. RESULTS: Of the 7349 patients from the influenza sentinel surveillance sites, 76.3% (n=5606) were younger than 5 years. We detected any influenza (A or B) in 8.7% (629/7224), SARS-CoV-2 in 10.7% (768/7199), and coinfection in 0.9% (63/7165) of samples tested. Although the number of samples tested for SARS-CoV-2 from the sentinel surveillance was only 0.2% (60 per week vs 36,000 per week) of the number tested in the universal national surveillance, SARS-CoV-2 positivity in the sentinel surveillance data significantly correlated with that of the universal national surveillance (Pearson r=0.58; P<.001). The adjusted odds ratios (aOR) of clinical severe illness among participants with coinfection were similar to those of patients with influenza only (aOR 0.91, 95% CI 0.47-1.79) and SARS-CoV-2 only (aOR 0.92, 95% CI 0.47-1.82). CONCLUSIONS: Influenza substantially cocirculated with SARS-CoV-2 in Kenya. We found a significant correlation of SARS-CoV-2 positivity in the data from 8 influenza sentinel surveillance sites with that of the universal national SARS-CoV-2 surveillance data. Our findings indicate that the influenza sentinel surveillance system can be used as a sustainable platform for monitoring respiratory pathogens of pandemic potential or public health importance.

Systematic Genomic Surveillance of SARS-CoV-2 at Xiamen International Airport and the Port of Xiamen Reveals the Importance of Incoming Travelers in Lineage Diversity.

Sever Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is still a threat to human health globally despite the World Health Organization (WHO) announcing the end of the COVID-19 pandemic. Continued surveillance of SARS-CoV-2 at national borders would be helpful in understanding the epidemics of novel imported variants and updating local strategies for disease prevention and treatment. This study focuses on the surveillance of imported SARS-CoV-2 variants among travelers entering Xiamen International Airport and the Port of Xiamen from February to August 2023. A total of 97 imported SARS-CoV-2 sequences among travelers from 223 cases collected from 12 different countries and regions were identified by real-time RT-PCR. Next-generation sequencing was used to generate high-quality complete sequences for phylogenetic and population dynamic analysis. The study revealed a dominant shift in variant distribution, in which the XBB subvariant (XBB.1.5, XBB.1.16, XBB.1.9, XBB.2.3, and EG.5.1) accounted for approximately 88.8% of the sequenced samples. In detail, clades 23D and 23E accounted for 26.2% and 21.4% of the sequenced samples, respectively, while clades 23B (13.6%) and 23F (10.7%) took the third and fourth spots in the order of imported sequences, respectively. Additionally, the XBB.2.3 variants were first identified in imported cases from the mainland of Xiamen, China on 27 February 2023. The spatiotemporal analyses of recent viral genome sequences from a limited number of travelers into Xiamen provide valuable insights into the situation surrounding SARS-CoV-2 and highlight the importance of sentinel surveillance of SARS-CoV-2 variants in the national border screening of incoming travelers, which serves as an early warning system for the presence of highly transmissible circulating SARS-CoV-2 lineages.