Correction: Respiratory virus surveillance in the post-pandemic era: challenges and opportunities for dashboard-based public health action

Respiratory pathogen surveillance dashboards surged during the COVID-19 pandemic and have remained widely used tools for real-time data visualization in public health. While these dashboards offer timely, actionable insights for monitoring trends and decision-making, their rapid expansion has also highlighted persistent challenges related to governance, data accessibility, standardization, and sustainability. To explore these issues in depth, the Center of Excellence for Respiratory Pathogens (CERP) hosted a two-day workshop in Lyon, France. Experts representing a range of respiratory pathogen surveillance initiatives convened to share experiences, highlight successes, and discuss ongoing challenges. Key themes included the need for improved data quality, transparency, and standardization; sustainable IT infrastructure and staffing; greater access to underlying data; and alignment between dashboard objectives and user needs. Participants emphasized that broader governance and collaboration challenges strongly impact dashboard performance and interoperability. This report summarizes the valuable insights and subsequent actionable recommendations that emerged from the workshop, offering guidance to both developers and users of respiratory pathogen (or disease burden) dashboards. It aims to support the development of a more integrated, effective, and sustainable global respiratory surveillance ecosystem.

Human-dog interface poses a risk of transmission and spread of zoonotic viruses. The objective of the thesis entitled is to survey and genetic characterize zoonotic viruses in dogs and humans who have high-risk occupations and in close contact with dogs. This thesis contains 8 topics. The results of the first to third topics were the surveillance of respiratory viruses in dogs including Canine Parainfluenza type 5 (CPIV-5), Canine influenza virus (CIV) and Coronavirus (CoV). The nasal swab samples were collected from dogs with respiratory signs during 2015-2018. The results showed that the occurrence of CPIV-5, CIV and CoV were 5.6% (32 /571), 1.4% (8/571) and 13.1% (75/571), respectively. The genetic analysis of CPIV-5 showed that Thai CPIV-5 were closely related with CPIV-5 from China and South Korea but they were different from Human PIV-5. The genetic analysis of CIV showed that Thai CIV subtype was pandemic H1N1/2009. The Thai CIV was closely related to pandemic H1N1/2009 infected in swine and human. This result suggested that dogs can be infected with pandemic H1N1/2009, which is reverse zoonotic event. The genetic analysis of CoV showed that canine respiratory coronaviruses (CRCoVs) were grouped into betacoronavirus which closely related to human CoV (HCoV-OC43) and bovine CoV. Thai CRCoVs were different from canine enteric coronaviruses of the genus alphacoronavirus. The TMRCA analysis indicated that Thai CRCoV was estimated to separate from HCoV-OC43 and BCoV with the most recent common ancestor since 2004. The results of the fourth to seventh topic were the surveillance of gastroenteric viruses in dogs including Kobuvirus (KoV), Norovirus (NoV), Rotavirus (RoV) and Canine parvovirus type 2 (CPV-2). These viruses can cause gastroenteric disease. Since some viruses have been reported zoonotic transmission. The rectal swab samples were collected from dogs with gastroenteritis signs. The occurrence of KoV, NoV, CPV-2, and RoV in dogs were 17.6% (54/307), 11.1% (2/18), 29.9% (133/444) and 0.7% (5/710), respectively. The genetic analysis of KoV in dogs showed that Thai-KoVs were closely related to KoV from China. The genetic analysis of NoV showed that Thai-NoVs in dogs belonged to genotype GII.Pe-GII.4 Sydney which is the common genotype causing NoV outbreaks in humans in Thailand. In this study, canine NoVs were detected from dogs living on the same premises with the confirmed human NoV case suggesting human-to-canine transmission. The genetic analysis of CPV-2, this study is the first report of CPV-2c in dogs and cats in Thailand. The genetic analysis of RoV showed that the genotype G3P[3] was a predominant genotype of RoV in dogs in Thailand. The pattern of genetic constellation of Thai RoVs was G3-P[3]-I3-R3-C3-M3-A9-N2-T3-E3-H6, which never been reported in dogs. The TMRCA analysis showed that Thai-RoV was estimated to separate from bat, human, and dog RoVs and subsequently generating novel RoV G3P[3]. The result of the eighth topic was the surveillance of respiratory and enteric viruses in human. Nasal swab, stool samples and questionnaire interview were obtained from 100 participants who had high-risk occupations and in close contact with dogs. The nasal swab samples were tested for influenza virus, parainfluenza virus and coronavirus, while stool samples were tested for coronavirus and rotavirus. The result of this study showed that CoV could be detected from two participants, while none of the other viruses (IAV, PIV and RV) could be detected. The genetic analysis of CoV showed that the human CoV belonged to alphacoronavirus of HCoV- 229E. The questionnaire interview showed that 52% of workers reported that they concern about the risk of zoonotic infection from dogs. Only 8% of participants reported using of gloves when working/contracting with sick dogs. However, this study involved a relatively small population with on one time sample collection. Therefore, a large population shoulde be perfprmed. The conclusion of this thesis, there are potential zoonotic respiratory and enteric viruses circulating in dogs in Thailand. Moreover, the genetic analysis of the viruses indicated that the viruses are rapid evolving especially after introduction of novel virus in the population and/or interspecies transmission. The information will be useful for people who have high-risk occupations such as veterinarians, vet assistants and owners. Moreover, these results provide information of the status, distribution, genetic characteristics of the viruses for the effective prevention and control of respiratory and enteric zoonotic viruses in dogs in Thailand.

IntroductionThe COVID-19 pandemic has significantly affected healthcare systems worldwide, impacting the occurrence and management of respiratory illnesses. This has also influenced respiratory infections’ role in childhood mortality. Surveillance of common respiratory viruses in Ghana is limited, making it crucial to assess the prevalence of respiratory viral infections, particularly in children, in the post-pandemic era. This study provides data on the prevalence of respiratory viruses and the associated risk factors in symptomatic children aged 5 or younger in an urban paediatric hospital setting.MethodsThe study was a cross-sectional study with a convenience sampling method, conducted in four health facilities: Asokwa Children’s Hospital, HopeXchange Medical Centre, University Health Services-KNUST, and Kumasi South Hospital in Kumasi, Ghana, between August 2022 and June 2023. Recruitment was not done in parallel in each hospital. Oropharyngeal swabs were collected from 303 children ≤ 5 years old and screened by RT-qPCR for common respiratory viruses.ResultsOut of the 303 patients enrolled in the study, 165 (54.4%) were male, and 122 (40.3%) were aged from 13 to 36 months. The median age of the patients was 19 months. The most common symptoms reported were cough (87.0%), runny nose (87.0%), and fever (72.0%). Respiratory viruses were detected in 100 (33.0%) of the samples, with 36 (12.0%) testing positive for Human metapneumovirus (HMPV), 27 (8.9%) for Respiratory syncytial virus (RSV), and 20 (6.6%) for Human Adenovirus (HAdV). In 8.0% of the cases, multiple viruses were detected, with HAdV being the most common (75.0%). Children under 6 months (AOR: 4.81, 95% CI: 1.20–24.60) had a higher risk of RSV detection compared to children aged 37 to 60 months. Furthermore, it was found that caregivers with tertiary education had higher odds of HMPV detection (AOR: 6.91, 95% CI: 1.71–47.3).ConclusionThe detection of multiple viruses with a higher prevalence of HMPV and RSV in our study emphasises the need for a scaled-up and sustained surveillance of respiratory viruses in Ghana in the post-pandemic era. Such an establishment in respiratory virus surveillance systems in Ghana would help in the timely detection and education on viral seasonal patterns, which will inform public health responses.

The development of effective methods for the surveillance of seasonal respiratory viruses is required for the timely management of outbreaks. We aimed to survey Influenza-A, Influenza-B, RSV-A, Rhinovirus and SARS-CoV-2 surveillance in a tertiary hospital and a campus over 5 months. The effectiveness of air screening as an early warning system for respiratory viruses was evaluated in correlation with respiratory tract panel test results. The overall viral positivity was higher on the campus than in the hospital (55.0% vs. 38.0%). Influenza A was the most prevalent pathogen in both locations. There were two influenza peaks (42nd and 49th weeks) in the hospital air, and a delayed peak was detected on campus in the 1st-week of January. Panel tests indicated a high rate of Influenza A in late December. RSV-A-positivity was higher on the campus than the hospital (21.6% vs. 7.4%). Moreover, we detected two RSV-A peaks in the campus air (48th and 51st weeks) but only one peak in the hospital and panel tests (week 49). Although rhinovirus was the most common pathogen in panel tests, rhinovirus positivity was low in air samples. The air screening for Influenza-B and SARS-Cov-2 revealed comparable positivity rates with panel tests. Air screening can be integrated into surveillance programs to support infection control programs for potential epidemics of respiratory virus infections except for rhinoviruses.

Traditional surveillance for respiratory viruses relies on symptom detection and laboratory detection during medically attended encounters for acute respiratory infection/influenza‐like illness (ARI/ILI). Ecological momentary reporting using text messages is a novel method for surveillance. This study compares respiratory viral activity detected through longitudinal community‐based surveillance using text message responses for sample acquisition and testing to respiratory viral activity obtained from hospital laboratory data from the same community. We demonstrate a significant correlation between community‐ and hospital laboratory‐based surveillance for most respiratory viruses, although the relative proportions of viruses detected in the community and hospital differed significantly.

On May 5, 2023, the World Health Organization removed the public health emergency of international concern (PHEIC) designation for the COVID-19 pandemic, noting reduced global risk of severe COVID-19 due to widespread infection and vaccine-induced immunity. Several months prior, the Philippine Department of Health (DOH) requested technical assistance from the U.S. Centers for Disease Control and Prevention (CDC) to evaluate its COVID-19 surveillance ecosystem and inform decision-making for sustainable respiratory virus monitoring. This manuscript describes the evaluation methodology, findings, and recommendations to inform these surveillance transitions. In April 2023, an evaluation team from DOH, CDC, and Task Force for Global Health conducted a cross-sectional evaluation of six surveillance systems (COVID-19 case-based, traveler screening, and genomic surveillance; influenza-like illness surveillance, severe acute respiratory infection surveillance, and the Respiratory Syncytial Virus surveillance pilot) at 26 sites across three Philippine regions. Using tailored data collection tools, we analyzed systems’ structure, processes, attributes, and key performance indicators. Findings were categorized into three areas: surveillance system scope and design, system performance, and laboratory capacity. Although the DOH expanded and upgraded systems for COVID-19 surveillance, including universal case surveillance, contact tracing, and molecular testing and genomic sequencing, rapid development of multiple, isolated systems during the pandemic created inefficiencies and data discrepancies. Prioritizing COVID-19 surveillance strained staff capacity, impacting other surveillance efforts. Key findings included variable reporting completeness and timeliness and underutilization of sentinel sites. Challenges included fragmented data systems, heavy workloads, and resource limitations. Staff adaptability and dedication demonstrated their commitment to surveillance compliance. Progress in molecular testing and genomic sequencing was notable. Pandemic-era surveillance of respiratory viruses requires adaptation to the interpandemic period. Recommendations focus on right-sizing COVID-19 surveillance while strengthening other surveillance systems, integrating respiratory virus surveillance systems, enhancing staff capacity, and improving stakeholder coordination. These findings offer valuable insights for transitioning to sustainable respiratory virus surveillance post-pandemic.

Background: Endemic and seasonally recurring respiratory viruses are a major cause of disease and death globally. The burden is particularly severe in developing countries. Improved understanding of the source of infection, pathways of spread and persistence in communities would be of benefit in devising intervention strategies. Methods: We report epidemiological data obtained through surveillance of respiratory viruses at nine outpatient health facilities within the Kilifi Health and Demographic Surveillance System, Kilifi County, coastal Kenya, between January and December 2016. Nasopharyngeal swabs were collected from individuals of all ages presenting with acute respiratory infection (ARI) symptoms (up to 15 swabs per week per facility) and screened for 15 respiratory viruses using real-time PCR. Paediatric inpatient surveillance at Kilifi County Hospital for respiratory viruses provided comparative data. Results: Over the year, 5,647 participants were sampled, of which 3,029 (53.7%) were aged <5 years. At least one target respiratory virus was detected in 2,380 (42.2%) of the samples; the most common being rhinovirus 18.6% (1,050), influenza virus 6.9% (390), coronavirus 6.8% (387), parainfluenza virus 6.6% (371), respiratory syncytial virus (RSV) 3.9% (219) and adenovirus 2.7% (155). Virus detections were higher among <5-year-olds compared to older children and adults (50.3% vs 32.7%, respectively; χ 2(1) =177.3, P=0.0001). Frequency of viruses did not differ significantly by facility (χ 2(8) =13.38, P=0.072). However, prevalence was significantly higher among inpatients than outpatients in <5-year-olds for RSV (22.1% vs 6.0%; χ 2(1) = 159.4, P=0.0001), and adenovirus (12.4% vs 4.4%, χ 2(1) =56.6, P=0.0001). Conclusions: Respiratory virus infections are common amongst ARI outpatients in this coastal Kenya setting, particularly in young children. Rhinovirus predominance warrants further studies on the health and socio-economic implications. RSV and adenovirus were more commonly associated with severe disease. Further analysis will explore epidemiological transmission patterns with the addition of virus sequence data.

Background: Endemic and seasonally recurring respiratory viruses are a major cause of disease and death globally. The burden is particularly severe in developing countries. Improved understanding of the source of infection, pathways of spread and persistence in communities would be of benefit in devising intervention strategies. Methods: We report epidemiological data obtained through surveillance of respiratory viruses at nine outpatient health facilities within the Kilifi Health and Demographic Surveillance System, Kilifi County, coastal Kenya, between January and December 2016. Nasopharyngeal swabs were collected from individuals of all ages presenting with acute respiratory infection (ARI) symptoms (up to 15 swabs per week per facility) and screened for 15 respiratory viruses using real-time PCR. Paediatric inpatient surveillance at Kilifi County Hospital for respiratory viruses provided comparative data. Results: Over the year, 5,647 participants were sampled, of which 3,029 (53.7%) were aged <5 years. At least one target respiratory virus was detected in 2,380 (42.2%) of the samples; the most common being rhinovirus 18.6% (1,050), influenza virus 6.9% (390), coronavirus 6.8% (387), parainfluenza virus 6.6% (371), respiratory syncytial virus (RSV) 3.9% (219) and adenovirus 2.7% (155). Virus detections were higher among <5-year-olds compared to older children and adults (50.3% vs 32.7%, respectively; χ 2(1) =177.3, P=0.0001). Frequency of viruses did not differ significantly by facility (χ 2(8) =13.38, P=0.072). However, prevalence was significantly higher among inpatients than outpatients in <5-year-olds for RSV (22.1% vs 6.0%; χ 2(1) = 159.4, P=0.0001), and adenovirus (12.4% vs 4.4%, χ 2(1) =56.6, P=0.0001). Conclusions: Respiratory virus infections are common amongst ARI outpatients in this coastal Kenya setting, particularly in young children. Rhinovirus predominance warrants further studies on the health and socio-economic implications. RSV and adenovirus were more commonly associated with severe disease. Further analysis will explore epidemiological transmission patterns with the addition of virus sequence data.

Background: Respiratory viruses are primary agents of respiratory tract diseases. Knowledge on the types and frequency of respiratory viruses affecting school-children is important in determining the role of schools in transmission in the community and identifying targets for interventions. Methods: We conducted a one-year (term-time) surveillance of respiratory viruses in a rural primary school in Kilifi County, coastal Kenya between May 2017 and April 2018. A sample of 60 students with symptoms of ARI were targeted for nasopharyngeal swab (NPS) collection weekly. Swabs were screened for 15 respiratory virus targets using real time PCR diagnostics. Data from respiratory virus surveillance at the local primary healthcare facility was used for comparison. Results: Overall, 469 students aged 2-19 years were followed up for 220 days. A total of 1726 samples were collected from 325 symptomatic students; median age of 7 years (IQR 5-11). At least one virus target was detected in 384 (22%) of the samples with a frequency of 288 (16.7%) for rhinovirus, 47 (2.7%) parainfluenza virus, 35 (2.0%) coronavirus, 15 (0.9%) adenovirus, 11 (0.6%) respiratory syncytial virus (RSV) and 5 (0.3%) influenza virus. The proportion of virus positive samples was higher among lower grades compared to upper grades (25.9% vs 17.5% respectively; χ 2 = 17.2, P -value <0.001). Individual virus target frequencies did not differ by age, sex, grade, school term or class size. Rhinovirus was predominant in both the school and outpatient setting. Conclusion: Multiple respiratory viruses circulated in this rural school population. Rhinovirus was dominant in both the school and outpatient setting and RSV was of notably low frequency in the school. The role of school children in transmitting viruses to the household setting is still unclear and further studies linking molecular data to contact patterns between the school children and their households are required.

Background: Respiratory viruses are primary agents of respiratory tract diseases. Knowledge on the types and frequency of respiratory viruses affecting school-children is important in determining the role of schools in transmission in the community and identifying targets for interventions. Methods: We conducted a one-year (term-time) surveillance of respiratory viruses in a rural primary school in Kilifi County, coastal Kenya between May 2017 and April 2018. A sample of 60 students with symptoms of ARI were targeted for nasopharyngeal swab (NPS) collection weekly. Swabs were screened for 15 respiratory virus targets using real time PCR diagnostics. Data from respiratory virus surveillance at the local primary healthcare facility was used for comparison. Results: Overall, 469 students aged 2-19 years were followed up for 220 days. A total of 1726 samples were collected from 325 symptomatic students; median age of 7 years (IQR 5-11). At least one virus target was detected in 384 (22%) of the samples with a frequency of 288 (16.7%) for rhinovirus, 47 (2.7%) parainfluenza virus, 35 (2.0%) coronavirus, 15 (0.9%) adenovirus, 11 (0.6%) respiratory syncytial virus (RSV) and 5 (0.3%) influenza virus. The proportion of virus positive samples was higher among lower grades compared to upper grades (25.9% vs 17.5% respectively; χ 2 = 17.2, P -value <0.001). Individual virus target frequencies did not differ by age, sex, grade, school term or class size. Rhinovirus was predominant in both the school and outpatient setting. Conclusion: Multiple respiratory viruses circulated in this rural school population. Rhinovirus was dominant in both the school and outpatient setting and RSV was of notably low frequency in the school. The role of school children in transmitting viruses to the household setting is still unclear and further studies linking molecular data to contact patterns between the school children and their households are required.

Background: Respiratory viruses are primary agents of respiratory tract diseases. Knowledge on the types and frequency of respiratory viruses affecting school-children is important in determining the role of schools in transmission in the community and identifying targets for interventions. Methods: We conducted a one-year (term-time) surveillance of respiratory viruses in a rural primary school in Kilifi County, coastal Kenya between May 2017 and April 2018. A sample of 60 students with symptoms of ARI were targeted for nasopharyngeal swab (NPS) collection weekly. Swabs were screened for 15 respiratory virus targets using real time PCR diagnostics. Data from respiratory virus surveillance at the local primary healthcare facility was used for comparison. Results: Overall, 469 students aged 2-19 years were followed up for 220 days. A total of 1726 samples were collected from 325 symptomatic students; median age of 7 years (IQR 5-11). At least one virus target was detected in 384 (22%) of the samples with a frequency of 288 (16.7%) for rhinovirus, 47 (2.7%) parainfluenza virus, 35 (2.0%) coronavirus, 15 (0.9%) adenovirus, 11 (0.6%) respiratory syncytial virus (RSV) and 5 (0.3%) influenza virus. The proportion of virus positive samples was higher among lower grades compared to upper grades (25.9% vs 17.5% respectively; χ 2 = 17.2, P -value <0.001). Individual virus target frequencies did not differ by age, sex, grade, school term or class size. Rhinovirus was predominant in both the school and outpatient setting. Conclusion: Multiple respiratory viruses circulated in this rural school population. Rhinovirus was dominant in both the school and outpatient setting and RSV was of notably low frequency in the school. The role of school children in transmitting viruses to the household setting is still unclear and further studies linking molecular data to contact patterns between the school children and their households are required.

Respiratory infections are common, and the most common causative agent is a virus. Therefore, routine surveillance of respiratory viruses is useful in the case of novel viral diseases such as coronavirus disease 2019 (COVID-19). In this study, to clarify the kind of virus involved in suspected cases of COVID-19 in the early stages of the pandemic, we attempted to detect various respiratory viruses in 613 specimens that tested negative for severe acute respiratory syndrome coronavirus 2 using reverse transcription polymerase chain reaction. As a result, viruses were detected in 59 (9.6%) patients. In addition, human rhinovirus (HRV), human metapneumovirus (HMPV), human respiratory syncytial virus, and human parechovirus were detected in 29, 25, 3, and 2 patients, respectively. Although this study was conducted over a short period of time and not all specimens were tested, these results indicate that various respiratory viruses, especially HRV and HMPV, can be detected even during the early stages of the COVID-19 pandemic. Because various respiratory viruses maintain a constant effect during the outbreak of the newly emerged pandemic, systematic surveillance of respiratory viruses is needed during the normal period to make good use for clinical and public health.

A community-based, time-matched, case-control study of respiratory viruses and exacerbations of COPD

There is limited surveillance and laboratory capacity for non-influenza respiratory viruses in India. We leveraged the influenza sentinel surveillance of India to detect other respiratory viruses among patients with acute respiratory infection. Six centers representing different geographic areas of India weekly enrolled a convenience sample of 5-10 patients with acute respiratory infection (ARI) and severe acute respiratory infection (SARI) between September 2016-December 2018. Staff collected nasal and throat specimens in viral transport medium and tested for influenza virus, respiratory syncytial virus (RSV), parainfluenza virus (PIV), human meta-pneumovirus (HMPV), adenovirus (AdV) and human rhinovirus (HRV) by reverse transcription polymerase chain reaction (RT-PCR). Phylogenetic analysis of influenza and RSV was done. We enrolled 16,338 including 8,947 ARI and 7,391 SARI cases during the study period. Median age was 14.6 years (IQR:4-32) in ARI cases and 13 years (IQR:1.3-55) in SARI cases. We detected respiratory viruses in 33.3% (2,981) of ARI and 33.4% (2,468) of SARI cases. Multiple viruses were co-detected in 2.8% (458/16,338) specimens. Among ARI cases influenza (15.4%) were the most frequently detected viruses followed by HRV (6.2%), RSV (5%), HMPV (3.4%), PIV (3.3%) and AdV (3.1%),. Similarly among SARI cases, influenza (12.7%) were most frequently detected followed by RSV (8.2%), HRV (6.1%), PIV (4%), HMPV (2.6%) and AdV (2.1%). Our study demonstrated the feasibility of expanding influenza surveillance systems for surveillance of other respiratory viruses in India. Influenza was the most detected virus among ARI and SARI cases.

There is limited surveillance and laboratory capacity for non-influenza respiratory viruses in India. We leveraged the influenza sentinel surveillance of India to detect other respiratory viruses among patients with acute respiratory infection. Six centers representing different geographic areas of India weekly enrolled a convenience sample of 5–10 patients with acute respiratory infection (ARI) and severe acute respiratory infection (SARI) between September 2016-December 2018. Staff collected nasal and throat specimens in viral transport medium and tested for influenza virus, respiratory syncytial virus (RSV), parainfluenza virus (PIV), human meta-pneumovirus (HMPV), adenovirus (AdV) and human rhinovirus (HRV) by reverse transcription polymerase chain reaction (RT-PCR). Phylogenetic analysis of influenza and RSV was done. We enrolled 16,338 including 8,947 ARI and 7,391 SARI cases during the study period. Median age was 14.6 years (IQR:4–32) in ARI cases and 13 years (IQR:1.3–55) in SARI cases. We detected respiratory viruses in 33.3% (2,981) of ARI and 33.4% (2,468) of SARI cases. Multiple viruses were co-detected in 2.8% (458/16,338) specimens. Among ARI cases influenza (15.4%) were the most frequently detected viruses followed by HRV (6.2%), RSV (5%), HMPV (3.4%), PIV (3.3%) and AdV (3.1%),. Similarly among SARI cases, influenza (12.7%) were most frequently detected followed by RSV (8.2%), HRV (6.1%), PIV (4%), HMPV (2.6%) and AdV (2.1%). Our study demonstrated the feasibility of expanding influenza surveillance systems for surveillance of other respiratory viruses in India. Influenza was the most detected virus among ARI and SARI cases.