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.

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.

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.

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.

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.

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.

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 ~5,000 sentinel sites are monitored weekly as part of influenza surveillance (as number of influenza cases/sentinel site). One limitation is that the number of influenza tests conducted is not reported. Separately, the National Hospital Organization (NHO), with ~140 hospitals, routinely publishes three indicators: number of influenza tests, influenza-positive case counts, and test positivity. We used NESID and NHO data from April 2011 to June 2022 to assess the usefulness of multiple indicators to monitor influenza activity. Temporal trends of the NHO and NESID indicators were similar, and NHO indicator levels well-correlated with those of the NESID indicator. Influenza positivity in the NHO data, however, showed an earlier rise and peak time compared to the NESID indicator. Importantly, through the non-epidemic summer periods and the coronavirus disease 2019 pandemic, a sizable number of influenza tests continued to be done 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.

Epidemiology of influenza in Nigeria: A secondary analysis of the sentinel surveillance data in Nigeria from 2010 - 2020.

BACKGROUND: Influenza is a leading cause of morbidity and mortality globally. Little is known of the true burden and epidemiology of influenza in Africa. Nigeria has a sentinel surveillance system for influenza virus (IFV). This study seeks to describe the epidemiological characteristics of influenza cases in Nigeria through secondary data analysis of the sentinel surveillance data from 2010 to 2020. METHODOLOGY: A retrospective secondary data analysis of data collected from patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) in the four Nigeria Influenza Sentinel Surveillance sites from January 2010 to December 2020. Data was cleaned and analyzed using Microsoft Excel and Epi info 7.2 for frequencies and proportions. The results of the analysis were summarized in tables and charts. RESULTS: A total of 13,828 suspected cases of influenza were recorded at the sentinel sites during the study period. About 10.3% (1421/13,828) of these tested positive for IFV of which 1243 (87.5%) were ILI patients, 175 (12.3%) SARI patients, and 3 (0.2%) novel H1N1 patients. Males accounted for 54.2% (770/1421) of the confirmed cases. The median age of confirmed cases was 3 years (range: <1month-97 years). Children 0-4 years accounted for 69.3% (985/1421) of all cases. The predominant subtypes were B lineage not determined (32.3%), A/H1N1 pdm09 (28.8%) and A/H3 (23.0%). There were periods of sustained transmission in most years with 2011 having the highest number of cases. Overall, there were more cases around January to March and August to November. Heart disease and chronic shortness of breath were the most common co-morbidities identified among confirmed cases. CONCLUSION: Influenza remains a significant cause of respiratory illness, especially among children aged less than 4 years. Influenza cases occur all year round with irregular seasonality in Nigeria. Children less than 4 years and those with co-morbidities should be prioritized for vaccination. Vaccine composition in the country should take cognizance of the prevailing strains which are type B (lineage not determined), A/H1N1 pdm09 and A/H3.

Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance.

BACKGROUND: The implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals. METHODS: We used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities. RESULTS: Weights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach. CONCLUSION: This novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.

Epidemiology of tuberculosis in Saudi Arabia following the implementation of end tuberculosis strategy: Analysis of the surveillance data 2015-2019.

OBJECTIVES: To analyze the evolution of tuberculosis (TB) epidemiology in Saudi Arabia in the 5 years following the implementation of the end-TB Strategy. METHODS: A retrospective analysis of surveillance data, reported by the national tuberculosis control program from 2015-2019, was carried out. The annual incidence and the percentage of yearly changes were calculated and compared to the World Health Organization (WHO) milestones, which anticipate a 4-5% annual decline. Additionally, various other epidemiological indicators of TB were examined. RESULTS: The national TB incidence declined from 10.55% per 100,000 in 2015 to 8.76% per 100,000 in 2019, aligning with the WHO's 2019 milestone estimated between 8.59-8.96% per 100,000. While Makkah Region (40.3%) and Riyadh (24.6%) accounted for the majority of cases, Jazan region consistently exhibited the highest incidence throughout the study period. Demographic features shifted towards a younger age category, male, and native dominance. There was a consistent decrease in resistance and intermediate sensitivity to all first-line anti-TB drugs, associated with a substantial decrease in both polydrug resistance (from 4.7-1.9%; p<0.001) and multidrug resistance (from 4.4-2.4%; p=0.008). CONCLUSION: The figures of TB incidence TB in Saudi Arabia between 2015-2019 has met the WHO end-TB milestones, predicting successful progress toward the 2035 goal.

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.

What is the relevancy of a surveillance of mumps without a systematic laboratory confirmation in highly immunized populations? Epidemiology of suspected and biologically confirmed mumps cases seen in general practice in France between 2014 and 2020.

BACKGROUND: In France, mumps surveillance is conducted in primary care by the Sentinelles network, the National Reference Centre for Measles, Mumps and Rubella and Santé publique France. AIM: The objective of this study was to estimate the incidence of suspected mumps in general practice, the proportion of laboratory confirmed cases and the factors associated with a virological confirmation. METHODS: General practitioners (GPs) participating in the Sentinelles network should report all patients with suspected mumps according to a clinical definition in case of parotitis and a serological definition in case of clinical expression without parotitis. All suspected mumps cases reported between January 2014 and December 2020 were included. A sample of these cases were tested by real time reverse transcriptase polymerase chain reaction (RT-PCR) for mumps biological confirmation. RESULTS: A total of 252 individuals with suspected mumps were included in the study. The average annual incidence rate of suspected mumps in general practice in France between 2014 and 2020 was estimated at 11 cases per 100,000 population [CI95%: 6-17]. A mumps confirmation RT-PCR test was performed on 146 cases amongst which 17 (11.5 %) were positive. Age (between 20 and 29 years old), the presence of a clinical complication and an exposure to a suspected mumps case within the 21 days prior the current episode were associated with a mumps biological confirmation. CONCLUSION: If these results confirm the circulation of mumps virus in France, they highlight the limits of a surveillance without a systematic laboratory confirmation in highly immunized populations.

Quality over quantity in active tick surveillance: Sentinel surveillance outperforms risk-based surveillance for tracking tick-borne disease emergence in southern Canada.

Background: Lyme disease (LD) emerged in southern Québec at the start of the century, with many municipalities now endemic. A coordinated active surveillance programme has been in place in the province of Québec since 2014, including a limited number of sentinel field sites resampled each year and a larger set of accessory field sites that change yearly according to the LD surveillance signal. We aimed to evaluate whether a sentinel approach to active surveillance was more representative of LD risk to human populations, compared to risk-based surveillance. Methods: We compared enzootic hazard measures (average nymph densities) from sentinel and accessory sites with LD risk (number of human LD cases) across the study area between 2015 and 2019 using local bivariate Moran's I analysis. Results: Hazard measures from sentinel sites captured spatial risk significantly better than data from accessory sites (χ2=20.473, p<0.001). In addition, sentinel sites successfully tracked the interannual trend in LD case numbers, whereas accessory sites showed no association despite the larger sample size. Conclusion: Where surveillance aims to document changes in tick-borne disease risk over time and space, we suggest that repeated sampling of carefully selected field sites may be most effective, while risk-based surveillance may be more usefully applied to confirm the presence of emerging disease risk in a specific region of interest or to identify suitable sites for long-term monitoring as LD and other tick-borne diseases continue to emerge.

Strengthening influenza surveillance capacity in the Eastern Mediterranean Region: Nearly two decades of direct support from the United States Centers for Disease Control and Prevention.

Since 2004, the US Centers for Disease Control and Prevention (CDC) Influenza Division (ID) has supported seven countries in the Eastern Mediterranean region and the World Health Organization Regional Office for the Eastern Mediterranean to establish and strengthen influenza surveillance. The substantial growth of influenza surveillance capacities in the region demonstrates a commitment by governments to strengthen national programs and contribute to global surveillance. The full value of surveillance data is in its use to guide local public health decisions. CDC ID remains committed to supporting the region and supporting partners to translate surveillance data into policies and programs effectively.

Tracking severe acute respiratory syndrome coronavirus 2 transmission and co-infection with other acute respiratory pathogens using a sentinel surveillance system in Rift Valley, Kenya.

BACKGROUND: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been the most significant public health challenge in over a century. SARS-CoV-2 has infected over 765 million people worldwide, resulting in over 6.9 million deaths. This study aimed to detect community transmission of SARS-CoV-2 and monitor the co-circulation of SARS-CoV-2 with other acute respiratory pathogens in Rift Valley, Kenya. METHODS: We conducted a cross-sectional active sentinel surveillance for the SARS-CoV-2 virus among patients with acute respiratory infections at four sites in Rift Valley from January 2022 to December 2022. One thousand two hundred seventy-one patients aged between 3 years and 98 years presenting with influenza-like illness (ILI) were recruited into the study. Nasopharyngeal swab specimens from all study participants were screened using a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for SARS-CoV-2, influenza A, influenza B and respiratory syncytial virus (RSV). RESULTS: The samples that tested positive for influenza A (n = 73) and RSV (n = 12) were subtyped, while SARS-CoV-2 (n = 177) positive samples were further screened for 12 viral and seven bacterial respiratory pathogens. We had a prevalence of 13.9% for SARS-CoV-2, 5.7% for influenza A, 2% for influenza B and 1% for RSV. Influenza A-H1pdm09 and RSV B were the most dominant circulating subtypes of influenza A and RSV, respectively. The most common co-infecting pathogens were Streptococcus pneumoniae (n = 29) and Haemophilus influenzae (n = 19), accounting for 16.4% and 10.7% of all the SARS-CoV-2 positive samples. CONCLUSIONS: Augmenting syndromic testing in acute respiratory infections (ARIs) surveillance is crucial to inform evidence-based clinical and public health interventions.

First identification of the SARS-COV-2/XBB.1.5 sublineage among indigenous COVID-19 cases through the influenza sentinel surveillance system in Niger.

The emergence of the Omicron variant in November 2021, has caused panic worldwide due to the rapid evolution and the ability of the virus to escape the immune system. Since, several Omicron sublineages (BA.1 to BA.5) and their descendent recombinant lineages have been circulating worldwide. Furthermore, in December 2022, a new Omicron subvariant XBB.1.5 characterized by an unusual mutation in the spike protein evolved in the United States and rapidly spread to the other continents. Our study reports on the first cases of XBB.1.5 sublineage among indigenous Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2) positive cases detected through the influenza sentinel surveillance system in Niger. All influenza suspected cases were tested for both influenza and SARS-COV-2 using the Centre for Disease Control and prevention (CDC) Influenza SARS-COV-2 Multiplex quantitative Reverse-Transcription Polymerase Chain Reaction (qRT-PCR) Assay. SARS-COV-2 positive samples with cycle threshold ≤28 were selected for whole genome sequencing subsequently using the Oxford Nanopore Midnight protocol with rapid barcoding on a MinIon MK1B device. A total of 51 SARS-COV-2 positive samples were confirmed between December 2022 and March 2023. We successfully obtained 19 sequences with a predominance of the XBB.1/XBB.1.5 sublineages (73.7 %). In addition, a recombinant XBD sequence was also first-ever identified in early March 2023. Our findings support the need to strengthen the influenza sentinel surveillance for routine Coronavirus Disease 2019 (COVID-19) surveillance and SARS-COV-2 variants monitoring in Niger.

Development, implementation, and evaluation of a local community-based ophthalmology sentinel surveillance system in a remote rural area in Japan.

INTRODUCTION: Solid and sensitive infectious disease surveillance systems need to be developed and implemented to prevent and control epidemics. Although statutory national infectious disease surveillance systems have been developed in many countries, some challenges remain, such as their limited timeliness, representativeness, and sensitivity, as well as the fact that they cannot capture all local outbreaks that occur in small communities. To overcome these limitations, local community-based infectious disease surveillance systems that meet local needs and can operate with constrained resources need to be developed, especially in remote and rural low-resource areas. This study aimed to develop, implement, and evaluate a voluntary and unique local community-based ophthalmology sentinel surveillance system in Isa city (OSSS-Isa), a remote rural area in Japan. METHODS: For the development of OSSS-Isa, one hospital in Isa city assumed a leading role and developed a network with all medical institutions - 20 hospitals and clinics in the local community, including two ophthalmology clinics - as sentinel reporting sites. Surveillance was conducted on a weekly basis from Monday to Sunday. The collection, aggregation, and reporting of the surveillance data were implemented promptly on the same day, Monday, using a paper-based form and fax. For the evaluation of OSSS-Isa, the study followed the updated guidelines for evaluating public health surveillance systems proposed by the Centers for Disease Control and Prevention to select the evaluation criteria and develop a questionnaire. The questionnaires were then distributed to 20 hospitals and clinics, with the responses evaluated on a five-point Likert scale. RESULTS: For the implementation of OSSS-Isa, the system issued alerts twice to the networked hospitals and clinics when signs of an increase in the prevalence of a target infectious eye disease appeared in Isa city. After the alerts, the number of cases decreased in the community. Regarding the evaluation survey, physicians from 18 hospitals and clinics responded to the questionnaire (response rate 90%). In contrast to flexibility, more than 75% of the respondents gave high ratings to simplicity, data quality, acceptability, timeliness, and stability in evaluating OSSS-Isa, with the mean score for these evaluation criteria higher than 3.67. CONCLUSION: The present results indicate that OSSS-Isa has high simplicity, data quality, acceptability, timeliness, and stability, which is highly embedded with the local healthcare providers in Isa city. OSSS-Isa contributed to the early and accurate detection of signs of infectious eye disease outbreaks emerging in a small remote rural local community. The success factors seem to include its simple well-designed implementation methods, good external factors, and active human factors suited to the characteristics of the small remote rural community. The OSSS-Isa initiative appears to be a meaningful practical example of successful health advocacy by healthcare providers by developing a system at the local social level while going beyond the boundaries of routine medical practice. If voluntary small-scale surveillance systems can complement statutory large-scale ones and work together locally, nationally, and internationally, it might be possible to detect small, unusual happenings that occur in the community, such as emerging infectious diseases, and thereby help avert global outbreaks.

Infections with long latency in international refugees, immigrants, and migrants seen at GeoSentinel sites, 2016-2018.

BACKGROUND: The continued increase in global migration compels clinicians to be aware of specific health problems faced by refugees, immigrants, and migrants (RIM). This analysis aimed to characterize RIM evaluated at GeoSentinel sites, their migration history, and infectious diseases detected through screening and diagnostic workups. METHODS: A case report form was used to collect data on demographics, migration route, infectious diseases screened, test results, and primary infectious disease diagnosis for RIM patients seen at GeoSentinel sites. Descriptive statistics were performed. RESULTS: Between October 2016 and November 2018, 5,319 RIM patients were evaluated at GeoSentinel sites in 19 countries. Africa was the region of birth for 2,436 patients (46 %), followed by the Americas (1,644, 31 %), and Asia (1,098, 21 %). Tuberculosis (TB) was the most common infection screened and reported as positive (853/2,273, 38 % positive by any method). TB, strongyloidiasis, and hepatitis B surface antigen positivity were observed across all migration administrative categories and regions of birth. Chagas disease was reported only among RIM patients from the Americas (393/394, 100 %) and schistosomiasis predominantly in those from Africa (480/510, 94 %). TB infection (694/5,319, 13 %) and Chagas disease (524/5,319, 10 %) were the leading primary infectious disease diagnoses. CONCLUSIONS: Several infections of long latency (e.g. TB, hepatitis B, and strongyloidiasis) with potential for long-term sequelae were seen among RIM patients across all migration administrative categories and regions of origin. Obtaining detailed epidemiologic information from RIM patients is critical to optimize detection of diseases of individual and public health importance, particularly those with long latency periods.