Evaluation of the influenza sentinel surveillance system in the Democratic Republic of Congo, 2012-2015

Estimating the incidence of COVID-19, influenza and respiratory syncytial virus infection in three regions of Queensland, Australia, winter 2022: findings from a novel longitudinal testing-based sentinel surveillance programme

OBJECTIVE

The 2022 Australian winter was the first time that COVID-19, influenza and respiratory syncytial virus (RSV) were circulating in the population together, after two winters of physical distancing, quarantine and borders closed to international travellers. We developed a novel surveillance system to estimate the incidence of COVID-19, influenza and RSV in three regions of Queensland, Australia.

DESIGN

We implemented a longitudinal testing-based sentinel surveillance programme. Participants were provided with self-collection nasal swabs to be dropped off at a safe location at their workplace each week. Swabs were tested for SARS-CoV-2 by PCR. Symptomatic participants attended COVID-19 respiratory clinics to be tested by multiplex PCR for SARS-CoV-2, influenza A and B and RSV. Rapid antigen test (RAT) results reported by participants were included in the analysis.

SETTING AND PARTICIPANTS

Between 4 April 2022 and 3 October 2022, 578 adults were recruited via their workplace. Due to rolling recruitment, withdrawals and completion due to positive COVID-19 results, the maximum number enrolled in any week was 423 people.

RESULTS

A total of 4290 tests were included. Participation rates varied across the period ranging from 25.9% to 72.1% of enrolled participants. The total positivity of COVID-19 was 3.3%, with few influenza or RSV cases detected. Widespread use of RAT may have resulted in few symptomatic participants attending respiratory clinics. The weekly positivity rate of SARS-CoV-2 detected during the programme correlated with the incidence of notified cases in the corresponding communities.

CONCLUSION

This testing-based surveillance programme could estimate disease trends and be a useful tool in settings where testing is less common or accessible. Difficulties with recruitment meant the study was underpowered. The frontline sentinel nature of workplaces meant participants were not representative of the general population but were high-risk groups providing early warning of disease.

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.

The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide

To reduce the consequences of infectious disease outbreaks, the timely implementation of public health measures is crucial. Currently used early-warning systems are highly context-dependent and require a long phase of model building. A proposed solution to anticipate the onset or termination of an outbreak is the use of so-called resilience indicators. These indicators are based on the generic theory of critical slowing down and require only incidence time series. Here we assess the potential for this approach to contribute to outbreak anticipation. We systematically reviewed studies that used resilience indicators to predict outbreaks or terminations of epidemics. We identified 37 studies meeting the inclusion criteria: 21 using simulated data and 16 real-world data. 36 out of 37 studies detected significant signs of critical slowing down before a critical transition (i.e., the onset or end of an outbreak), with a highly variable sensitivity (i.e., the proportion of true positive outbreak warnings) ranging from 0.03 to 1 and a lead time ranging from 10 days to 68 months. Challenges include low resolution and limited length of time series, a too rapid increase in cases, and strong seasonal patterns which may hamper the sensitivity of resilience indicators. Alternative types of data, such as Google searches or social media data, have the potential to improve predictions in some cases. Resilience indicators may be useful when the risk of disease outbreaks is changing gradually. This may happen, for instance, when pathogens become increasingly adapted to an environment or evolve gradually to escape immunity. High-resolution monitoring is needed to reach sufficient sensitivity. If those conditions are met, resilience indicators could help improve the current practice of prediction, facilitating timely outbreak response. We provide a step-by-step guide on the use of resilience indicators in infectious disease epidemiology, and guidance on the relevant situations to use this approach.

Comprehensive surveillance of acute respiratory infections during the COVID-19 pandemic: a methodological approach using sentinel networks, Castilla y León, Spain, January 2020 to May 2022

BackgroundSince 1996, epidemiological surveillance of acute respiratory infections (ARI) in Spain has been limited to seasonal influenza, respiratory syncytial virus (RSV) and potential pandemic viruses. The COVID-19 pandemic provides opportunities to adapt existing systems for extended surveillance to capture a broader range of ARI.AimTo describe how the Influenza Sentinel Surveillance System of Castilla y León, Spain was rapidly adapted in 2020 to comprehensive sentinel surveillance for ARI, including influenza and COVID-19.MethodsUsing principles and methods of the health sentinel network, we integrated electronic medical record data from 68 basic surveillance units, covering 2.6% of the regional population between January 2020 to May 2022. We tested sentinel and non-sentinel samples sent weekly to the laboratory network for SARS-CoV-2, influenza viruses and other respiratory pathogens. The moving epidemic method (MEM) was used to calculate epidemic thresholds.ResultsARI incidence was estimated at 18,942 cases per 100,000 in 2020/21 and 45,223 in 2021/22, with similar seasonal fold increases by type of respiratory disease. Incidence of influenza-like illness was negligible in 2020/21 but a 5-week epidemic was detected by MEM in 2021/22. Epidemic thresholds for ARI and COVID-19 were estimated at 459.4 and 191.3 cases per 100,000 population, respectively. More than 5,000 samples were tested against a panel of respiratory viruses in 2021/22.ConclusionExtracting data from electronic medical records reported by trained professionals, combined with a standardised microbiological information system, is a feasible and useful method to adapt influenza sentinel reports to comprehensive ARI surveillance in the post-COVID-19 era.

Etiologies of influenza-like illness and severe acute respiratory infections in Tanzania, 2017-2019

In 2016, Tanzania expanded sentinel surveillance for influenza-like illness (ILI) and severe acute respiratory infection (SARI) to include testing for non-influenza respiratory viruses (NIRVs) and additional respiratory pathogens at 9 sentinel sites. During 2017-2019, respiratory specimens from 2730 cases underwent expanded testing: 2475 specimens (90.7%) were tested using a U.S. Centers for Disease Control and Prevention (CDC)-developed assay covering 7 NIRVs (respiratory syncytial virus [RSV], rhinovirus, adenovirus, human metapneumovirus, parainfluenza virus 1, 2, and 3) and influenza A and B viruses. Additionally, 255 specimens (9.3%) were tested using the Fast-Track Diagnostics Respiratory Pathogens 33 (FTD-33) kit which covered the mentioned viruses and additional viral, bacterial, and fungal pathogens. Influenza viruses were identified in 7.5% of all specimens; however, use of the CDC assay and FTD-33 kit increased the number of specimens with a pathogen identified to 61.8% and 91.5%, respectively. Among the 9 common viruses between the CDC assay and FTD-33 kit, the most identified pathogens were RSV (22.9%), rhinovirus (21.8%), and adenovirus (14.0%); multi-pathogen co-detections were common. Odds of hospitalization (SARI vs. ILI) varied by sex, age, geographic zone, year of diagnosis, and pathogen identified; hospitalized illnesses were most common among children under the age of 5 years. The greatest number of specimens were submitted for testing during December-April, coinciding with rainy seasons in Tanzania, and several viral pathogens demonstrated seasonal variation (RSV, human metapneumovirus, influenza A and B, and parainfluenza viruses). This study demonstrates that expanding an existing influenza platform to include additional respiratory pathogens can provide valuable insight into the etiology, incidence, severity, and geographic/temporal patterns of respiratory illness. Continued respiratory surveillance in Tanzania, and globally, can provide valuable data, particularly in the context of emerging respiratory pathogens such as SARS-CoV-2, and guide public health interventions to reduce the burden of respiratory illnesses.

Evaluation of the influenza-like illness sentinel surveillance system: A national perspective in Tanzania from January to December 2019

BACKGROUND

The World Health Organization (WHO) recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data on the performance of established influenza surveillance systems are limited in Africa, including Tanzania. We aimed to assess the usefulness of the Influenza surveillance system in Tanzania and to ascertain if the system meets its objectives, including; estimating the burden of disease caused by the Influenza virus in Tanzania and identifying any circulating viral strains with pandemic potential.

METHODOLOGY

From March to April 2021, we collected retrospective data through a review of the Tanzania National Influenza Surveillance System electronic forms for 2019. Furthermore, we interviewed the surveillance personnel about the system's description and operating procedures. Case definition (ILI-Influenza Like Illness and SARI-Severe Acute Respiratory Illness), results, and demographic characteristics of each patient were obtained from the Laboratory Information System (Disa*Lab) at Tanzania National Influenza Center. The United States Centers for disease control and prevention updated guidelines for evaluating public health surveillance systems were used to evaluate the system's attributes. Additionally, the system's performance indicators (including turnaround time) were obtained by evaluating Surveillance system attributes, each being scored on a scale of 1 to 5 (very poor to excellent performance).

RESULTS

A total of 1731 nasopharyngeal and oropharyngeal samples were collected from each suspected influenza case in 2019 from fourteen (14/14) sentinel sites of the influenza surveillance system in Tanzania. Laboratory-confirmed cases were 21.5% (373/1731) with a predictive value positive of 21.7%. The majority of patients (76.1%) tested positive for Influenza A. Thirty-seven percent of patients' results met the required turnaround time, and 40% of case-based forms were incompletely filled. Although the accuracy of the data was good (100%), the consistency of the data was below (77%) the established target of ≥ 95%.

CONCLUSION

The overall system performance was satisfactory in conforming with its objectives and generating accurate data, with an average performance of 100%. The system's complexity contributed to the reduced consistency of data from sentinel sites to the National Public Health Laboratory of Tanzania. Improvement in the use of the available data could be made to inform and promote preventive measures, especially among the most vulnerable population. Increasing sentinel sites would increase population coverage and the level of system representativeness.

Protocol for a winter sentinel surveillance program of notifiable respiratory viruses in Queensland

BACKGROUND

With the reduction in access to polymerase chain reaction (PCR) testing and changes in testing guidelines in Australia, a reduced number of people are seeking testing for coronavirus disease (COVID-19), limiting the opportunity to monitor disease transmission. Knowledge of community transmission of COVID-19 and other respiratory viruses is essential to better predict subsequent surges in cases during the pandemic to alert health services, protect vulnerable populations and enhance public health measures. We describe a methodology for a testing-based sentinel surveillance program to monitor disease in the community for early signal detection of SARS-CoV-2 and other respiratory viruses.

METHODS/DESIGN

A longitudinal active testing-based sentinel surveillance program for respiratory viruses (including SARS-CoV-2, influenza A, influenza B and Respiratory Syncytial Virus) will be implemented in some regions of Queensland. Adults will be eligible for enrolment if they are part of specific community groups at increased risk of exposure and have not had a COVID-19 infection in the last 13 weeks. Recruitment via workplaces will occur in-person, via email and through online advertisement. Asymptomatic participants will be tested via PCR for SARS-CoV-2 infection by weekly self-collected nasal swabs. In addition, symptomatic participants will be asked to seek SARS-CoV-2 and additional respiratory virus PCR testing at nominated COVID-19 testing sites. SARS-CoV-2 and respiratory virus prevalence data will be analysed weekly and at the end of the study period.

DISCUSSION

Once implemented, this surveillance program will determine the weekly prevalence of COVID-19 and other respiratory viruses in the broader community by testing a representative sample of adults, with an aim to detect early changes in the baseline positivity rate. This information is essential to define the epidemiology of SARS-CoV-2 in the community in near-real time to inform public health control measures and prepare health services and other stakeholders for a rise in service demand.

Performance of COVID-19 case-based surveillance system in FCT, Nigeria, March 2020 –January 2021

Introduction

The emergence of novel SARS-CoV-2 has caused a pandemic of Coronavirus Disease 19 (COVID-19) which has spread exponentially worldwide. A robust surveillance system is essential for correct estimation of the disease burden and containment of the pandemic. We evaluated the performance of COVID-19 case-based surveillance system in FCT, Nigeria and assessed its key attributes.

Methods

We used a cross-sectional study design, comprising a survey, key informant interview, record review and secondary data analysis. A self-administered, semi-structured questionnaire was administered to key stakeholders to assess the attributes and process of operation of the surveillance system using CDC’s Updated Guidelines for Evaluation of Public Health Surveillance System 2001. Data collected alongside surveillance data from March 2020 to January 2021 were analyzed and summarized using descriptive statistics.

Results

Out of 69,338 suspected cases, 12,595 tested positive with RT-PCR with a positive predictive value (PPV) of 18%. Healthcare workers were identified as high-risk group with a prevalence of 23.5%. About 82% respondents perceived the system to be simple, 85.5% posited that the system was flexible and easily accommodates changes, 71.4% reported that the system was acceptable and expressed willingness to continue participation. Representativeness of the system was 93%, stability 40%, data quality 56.2% and timeliness 45.5%, estimated result turnaround time (TAT) was suboptimal.

Conclusion

The system was found to be useful, simple, flexible, sensitive, acceptable, with good representativeness but the stability, data quality and timeliness was poor. The system meets initial surveillance objectives but rapid expansion of sample collection and testing sites, improvement of TAT, sustainable funding, improvement of electronic database, continuous provision of logistics, supplies and additional trainings are needed to address identified weaknesses, optimize the system performance and meet increasing need of case detection in the wake of rapidly spreading pandemic. More risk-group persons should be tested to improve surveillance effectiveness.

Influenza Virus: Tracking, Predicting, and Forecasting

Influenza is a common respiratory infection that causes considerable morbidity and mortality worldwide each year. In recent years, along with the improvement in computational resources, there have been a number of important developments in the science of influenza surveillance and forecasting. Influenza surveillance systems have been improved by synthesizing multiple sources of information. Influenza forecasting has developed into an active field, with annual challenges in the United States that have stimulated improved methodologies. Work continues on the optimal approaches to assimilating surveillance data and information on relevant driving factors to improve estimates of the current situation (nowcasting) and to forecast future dynamics.

Implementing sequencing-based surveillance in developing countries: findings from a pilot rollout for hepatitis A in China

Background

The emergence of SARS-Cov2 variants has highlighted the need to implement sequencing-based surveillance in developing countries for early response to mutant viruses of concern. However, limited information on how to implement sequencing-based surveillance is available, and the feasibility and performance of this new type of surveillance are still in question.

Methods

To understand the challenges with the implementation and to promote sequencing-based surveillance, we reported findings from a pilot for hepatitis A (HepA) in five sentinel provinces in China as an example of sequencing-based surveillance implementation. The performance of the surveillance system was evaluated by indicators related to acceptability, data quality, simplicity, utility, and timeliness. We use a scale from 1 to 3 was used to provide a score for each aspect.

Results

During the pilot, 306 cases of HepA were reported, and 49.79% of samples were available for sequencing. Eleven genomic clusters were found, of which seven clusters were potentially related to a foodborne outbreak oyster based on identical viral sequence and epidemiologic investigations. The greatest strength of the system was its simplicity (Score: 2.63). The acceptability (Score: 2.0) and utility (Score: 2.33) were modest, but data quality (Score: 1.75) and timeliness (Score: 1.75) were the main challenges.

Conclusions

Overall, the system performed satisfactorily and proved to be useful for virological characterization of cases and early outbreak detection, with a great potential for scale-up. Further efforts are required to address financial and human resource constraints and inadequate support among physicians. Education should be given to health care professionals to improve the data quality. The establishment of decentralized surveillance networks can be an approach to improve timeliness for emerging infections.

Performance of the Severe Acute Respiratory Illness Sentinel Surveillance System in Yemen: Mixed Methods Evaluation Study

Background

The national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks.

Objective

To ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen.

Methods

The updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%).

Results

As rated by the evaluators, the SARI surveillance system achieved its objectives. The system’s flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as “excellent,” and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as “good.” The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support.

Conclusions

The SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities’ (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.

The epidemiology of seasonal influenza after the 2009 influenza pandemic in Africa: a systematic review

Background

Influenza infection is a serious public health problem that causes an estimated 3 to 5 million cases and 250,000 deaths worldwide every year. The epidemiology of influenza is well-documented in high- and middle-income countries, however minimal effort had been made to understand the epidemiology, burden and seasonality of influenza in Africa. This study aims to assess the state of knowledge of seasonal influenza epidemiology in Africa and identify potential data gaps for policy formulation following the 2009 pandemic.

Method

We reviewed articles from Africa published into four databases namely: MEDLINE (PubMed), Google Scholar, Cochrane Library and Scientific Research Publishing from 2010 to 2019.

Results

We screened titles and abstracts of 2070 studies of which 311 were selected for full content evaluation and 199 studies were considered. Selected articles varied substantially on the basis of the topics they addressed covering the field of influenza surveillance (n=80); influenza risk factors and co-morbidities (n=15); influenza burden (n=37); influenza vaccination (n=40); influenza and other respiratory pathogens (n=22) and influenza diagnosis (n=5).

Conclusion

Significant progress has been made since the last pandemic in understanding the influenza epidemiology in Africa. However, efforts still remain for most countries to have sufficient data to allow countries to prioritize strategies for influenza prevention and control.

Evaluation of a mobile health approach to improve the Early Warning System of influenza surveillance in Cameroon

Background

Rapid reporting of surveillance data is essential to better inform national prevention and control strategies.

Objectives

We compare the newly implemented smartphone‐based system to the former paper‐based and short message service (SMS) for collecting influenza epidemiological data in Cameroon.

Methods

Of the 13 sites which collect data from persons with influenza‐like illness (ILI), six sites send data through the EWS, while seven sites make use of the paper‐based system and SMS. We used four criteria for the comparison of the data collection tools: completeness, timeliness, conformity and cost.

Results

Regarding the different collection tools, data sent by the EWS were significantly more complete (97.6% vs 81.6% vs 44.8%), prompt (74.4% vs n/a vs 60.7%) and of better quality (93.7% vs 76.1% vs 84.0%) than data sent by the paper‐based system and SMS, respectively. The average cost of sending a datum by a sentinel site per week was higher for the forms (5.0 USD) than for the EWS (0.9 USD) and SMS (0.1 USD). The number of outpatient visits and subsequently all surveillance data decreased across the years 2017‐2019 together with the influenza positivity rate from 30.7% to 28.3%. Contrarily, the proportion of influenza‐associated ILI to outpatient load was highest in the year 2019 (0.37 per 100 persons vs 0.28 and 0.26 in the other 2 years).

Conclusion

All sentinel sites and even other disease surveillance systems are expected to use this tool in the near term future due to its satisfactory performance and cost.

An evaluation of the Zambia influenza sentinel surveillance system, 2011-2017

Background

Over the past decade, influenza surveillance has been established in several African countries including Zambia. However, information on the on data quality and reliability of established influenza surveillance systems in Africa are limited. Such information would enable countries to assess the performance of their surveillance systems, identify shortfalls for improvement and provide evidence of data reliability for policy making and public health interventions.

Methods

We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza surveillance system (ISS) in Zambia during 2011–2017 using 9 attributes: (i) data quality and completeness, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability, (viii) utility, and (ix) sustainability. Each attribute was evaluated using pre-defined indicators. For each indicator we obtained the proportion (expressed as percentage) of the outcome of interest over the total. A scale from 1 to 3 was used to provide a score for each attribute as follows: < 60% (as obtained in the calculation above) scored 1 (weak performance); 60–79% scored 2 (moderate performance); ≥80% scored 3 (good performance). An overall score for each attribute and the ISS was obtained by averaging the scores of all evaluated attributes.

Results

The overall mean score for the ISS in Zambia was 2.6. Key strengths of the system were the quality of data generated (score: 2.9), its flexibility (score: 3.0) especially to monitor viral pathogens other than influenza viruses, its simplicity (score: 2.8), acceptability (score: 3.0) and stability (score: 2.6) over the review period and its relatively low cost ($310,000 per annum). Identified weaknesses related mainly to geographic representativeness (score: 2.0), timeliness (score: 2.5), especially in shipment of samples from remote sites, and sustainability (score: 1.0) in the absence of external funds.

Conclusions

The system performed moderately well in our evaluation. Key improvements would include improvements in the timeliness of samples shipments and geographical coverage. However, these improvements would result in increased cost and logistical complexity. The ISSS in Zambia is largely reliant on external funds and the acceptability of maintaining the surveillance system through national funds would require evaluation.