Since 2004, the U.S. 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. There has been substantial growth in influenza surveillance capacities in the region over two decades that demonstrates commitment by national governments to strengthen national programs and contribute to global influenza surveillance. CDC ID remains committed to continuing support to the region and supporting partners to translate surveillance data into policies and programs effectively.

Few seroprevalence studies were performed on coronavirus disease (COVID-19) in Nepal. Here, we aimed to estimate seroprevalence and assess risk factors for infection in the general population of Nepal by conducting two rounds of sampling. The first round in October 2020 at the peak of the first generalized wave of COVID-19 and the second round in July-August 2021 following the peak of the wave caused by the delta variant of SARS-COV-2. We used cross-sectional probability-to-size (PPS)-based multistage cluster sampling to estimate the seroprevalence in the general population of Nepal at the national and provincial levels. We tested for the presence of anti-SARS-CoV-2 total antibody using the WANTAI SARS-CoV-2 Ab ELISA kit. In Round 1, the overall national seroprevalence was 14.4%, with provincial estimates ranging from 5.3% in Sudurpaschim to 27.3% in Madesh province. In Round 2, the estimated national seroprevalence was 70.7%, with the highest estimated seroprevalence in Madesh Province (84.8%) and the lowest in the Gandaki Province (62.9%). Seroprevalence was comparable between males and females (Round 1, 15.8% vs 12.2% and Round 2, 72.3% vs. 68.7%). The seroprevalence in the ecozones—terai, hills, and mountains—was 76.3%, 65.3%, and 60.5% in Round 2 and 17.7%, 11.7%, and 4.6% in Round 1, respectively. In Nepal, COVID-19 vaccination was introduced in January, 2021. At the peak of the first generalized wave of COVID-19, most of the population of Nepal remained unexposed to SARS-COV-2 and towards the end of the second generalized wave in April 2021, two-thirds of the population was exposed.

Background We used data from a prospective cohort to explore two-year trajectories of “long COVID” (persistent symptoms after SARS-CoV-2 infection) and their association with illness perception. Methods RECoVERED participants (adults; prospectively enrolled following laboratory-confirmed SARS-CoV-2 infection, May 2020-June 2021) completed symptom questionnaires at months 2-12, 18 and 24, and the Brief Illness Perception Questionnaire (B-IPQ) at months 1, 6, and 12. Using group-based trajectory models (GBTM), we modelled symptoms (mean total numbers and proportion with 4 specific complaints), including age, sex, BMI and timing of infection as covariates. In a multivariable linear mixed-effects model, we assessed the association between symptom trajectories and repeated B-IPQ scores. Results Among 292 participants (42% female; median age 51 [IQR=36-62]), four trajectories were identified, ranging from Trajectory 4 (8.9%; 6+ symptoms) to Trajectory 1 (24.8%; no symptoms). The occurrence of fatigue and myalgia increased among 23% and 12% of participants, respectively. Individuals in Trajectory 4 experienced more negative adjusted B-IPQ scores over time than those in Trajectories 1-3. Conclusions We observed little fluctuation in the total number of symptoms but individual symptoms may develop as others resolve. Reporting a greater number of symptoms was congruent with more negative illness perception over time.

Background: In Angola, COVID-19 cases have been reported in all provinces, resulting in >105,000 cases and >1,900 deaths. However, no detailed genomic surveillance into the introduction and spread of the SARS-CoV-2 virus has been conducted in Angola. We aimed to investigate the emergence, and epidemic progression during the peak of the COVID-19 pandemic in Angola. Methods: We generated 1,210 whole-genome SARS-CoV-2 sequences, contributing West African data to the global context, that were phylogenetically compared against global strains. Viral movement events were inferred using ancestral state reconstruction. Results: The epidemic in Angola was marked by four distinct waves of infection, dominated by 12 viral lineages, including VOCs, VOIs, and the VUM C.16, which was unique to Southwestern Africa and circulated for an extended period within the region. Viral exchanges occurred between Angola and its neighboring countries, and strong links with Brazil and Portugal reflected the historical and cultural ties shared between these countries. The first case likely originated from southern Africa. Conclusion: A lack of a robust genome surveillance network and strong dependence on out-of-country sequencing limit real-time data generation to achieve timely disease outbreak responses, which remains of the utmost importance to mitigate future disease outbreaks in Angola.

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. 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. 1271 patients of all ages presenting with influenza-like illness were recruited into the study. Nasopharyngeal swab specimens were screened using a multiplex RT–qPCR for SARS-CoV-2, Influenza A, Influenza B and RSV. Influenza A and RSV samples were subtyped, and all the SARS-CoV-2 positive samples were further screened for 12 viral and 7 bacterial respiratory pathogens. We had a prevalence of 13.93% SARS-CoV-2, Influenza A 5.7%, Influenza B 1.96% and 0.94%. 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 and Haemophilus influenzae, accounting for 16.4% and 10.7% of all the SARS-CoV-2 positive samples. Augmenting syndromic testing in ARI surveillance is crucial to inform evidence-based clinical and public health interventions.

Background: Within the ECDC-VEBIS project, we prospectively monitored vaccine effectiveness (VE) against COVID-19 hospitalisation and COVID-19-related death, using electronic health registries (EHR), between October 2021 and November 2022, in community-dwelling residents aged 65–79 and ≥80-years in six European countries. Methods: EHR linkage was used to construct population cohorts in Belgium, Denmark, Luxembourg, Navarre (Spain), Norway and Portugal. Using a common protocol, for each outcome (hospitalisation and death), VE was estimated monthly over eight-week follow-up periods, allowing one month-lag for data consolidation. Cox proportional-hazards regression models were used to estimate adjusted hazard ratios (aHR) and VE=(1 – aHR) x100. Site-specific estimates were pooled using random-effects meta-analysis. Results: For ≥80-years, VE against COVID-19 hospitalisation decreased from 66.9% (95%CI: 60.1; 72.6) to 36.1% (95%CI: -27.3; 67.9) for the primary vaccination and from 95.6% (95%CI: 88.0; 98.4) to 67.7% (95%CI: 45.9; 80.8) for the first booster. Similar trends were observed for 65-79-years. The second booster VE against hospitalisation ranged between 82.0% (95%CI: 75.9; 87.0) and 83.9% (95%CI: 77.7; 88.4) for the ≥80-years and between 39.3% (95%CI: -3.9; 64.5) and 80.6% (95%CI: 67.2; 88.5) for 65-79-years. The first booster VE against COVID-19-related death declined over time for both age groups, while the second booster VE against death remained above 80% for the ≥80-years. Conclusions: Successive vaccine boosters played a relevant role in maintaining protection against COVID-19 hospitalisation and death, in the context of decreasing VE over time. Multi-country data from EHR facilitate robust near-real-time monitoring of VE in the EU/EEA and supports public health decision-making.

Background: Several countries, including Bahrain, used Wastewater surveillance for disease activity monitoring. This study aimed to determine the presence of SARS-COV-2 in untreated wastewater and to correlate it with the disease spread. Methods: A retrospective review was conducted for all wastewater samples tested for SARS-CoV-2 in public health laboratories from October 2020 to October 2022. Samples were collected weekly between February and October 2022 from different areas across Bahrain. Real-time polymerase chain reaction (PCR) was used to test for the presence of SARS-CoV-2 in wastewater, and the results were correlated with the number of COVID-19 cases in the same area. Results: Of a total of 387 wastewater samples, 103 (26.6%) samples tested positive for SARS-CoV-2. In late 2020, of 42 samples collected initially, 4 (9.5%) samples tested positive for SARS-CoV-2 in the 4 locations that hosted COVID-19 isolation facilities. Between February and October 2022, 345 specimens of wastewater were tested, and 99 (28.7%) were positive. The highest detection rate was in February, June, and July (60%, 45%, and 43%, respectively), which corresponded to COVID-19 peaks during 2022, and the lowest detection rate was in August and September (11% and 0%, respectively), corresponding to the low number of COVID-19 cases. Conclusion: The detection rate of SARS-COV-2 in wastewater samples from Bahrain was high and was significantly correlated with the number of reported COVID-19 cases. Wastewater surveillance can aid the existing surveillance system in monitoring SARS-CoV-2 spread.

The WHO Unity Studies initiative engaged low- and middle-income countries in the implementation of standardized SARS-CoV-2 sero-epidemiological investigation protocols and timely sharing of comparable results for evidence-based action. To gain a deeper understanding of the methodological challenges faced when conducting seroprevalence studies in the Africa region, we conducted unstructured interviews with key study teams in five countries. We discuss the challenges identified: participant recruitment and retention, sample frame, sample and data management, data analysis and presentation to policy makers. Potential solutions to aid future implementation include preparedness actions such as the development of new tools, robust planning and practice.

Background: The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is complex and multifactorial. We aimed to identify the risk factors for infection among the household contacts of index patients and to determine the incubation period, serial interval, and estimates of secondary infection rate. Methods: We conducted a study in three districts of Kerala among the inhabitants of households of reverse transcriptase polymerase chain reaction (RT-PCR)-positive coronavirus disease (COVID-19) patients between January and July 2021. COVID-19-positive patients and corresponding contacts were enrolled and followed up for 28 days to determine RT-PCR positivity and the presence of total antibodies against SARS-CoV-2 on days 1, 7, 14, and 28 from the date of enrolment. Results: The mean incubation period, serial interval, and generation time were 1.6, 3, and 3.9 days, respectively. The secondary infection rate was 43.0%. Individuals who worked outside the home were protected, whereas those who had kissed the COVID-19-positive patients during illness were more than twice at risk of infection than those who had not kissed the COVID-19-positive patients. Similarly, the contacts who had shared a toilet with the COVID-19-positive patients were more at risk than those who had not shared a toilet. However, the contacts who reported using masks were at a higher risk of infection in household settings. Conclusions Assessment of SARS-CoV-2 transmission in household settings is important, considering its high secondary infection rate. Close physical contact and toilet sharing increase the risk of infection. This study demonstrates shorter incubation period and serial interval.

Backgroud Pregnant women are at high risk of developing febrile illness during the flu season. Early identification of a viral or bacterial infection is crucial in the management of febrile pregnant patients. Neutrophil CD64 (nCD64) has been shown to have more important diagnostic value in sepsis than traditional inflammatory indicators. Methods The pregnant women enrolled were divided into three groups according to disease: influenza A infection, bacterial infection and healthy controls. Peripheral blood CD64, leukocyte, C-reactive protein (CRP), procalcitonin (PCT) and human Th1/Th2-related cytokines levels were routinely measured. The correlation between and diagnostic value of the nCD64 index and other biomarkers were evaluated using Spearman’s correlation test and receiver operating characteristic (ROC) curve analysis. Results Pregnant women with bacterial infection had significantly elevated levels of leukocytes (8.4 vs. 5.95, 10^9/L; P=0.004), CRP (89.70 vs. 50.05, mg/ml; P=0.031), PCT (0.13 vs. 0.04, ng/ml; P=0.010), and TNF-α (0.46 vs. 0.38, pg/ml; P=0.012) and an elevated nCD64 index (12.16 vs. 0.81; P<0.001) compared to those with influenza A infection. The area under the curve (AUC) of the nCD64 index to discriminate bacterial infection among pregnant women (area = 0.9183, P < 0.0001) was the largest. The sensitivity and specificity of the nCD64 index at an optimal cut-off value of 3.16 were 84% and 100%, respectively, with a negative predictive value (NPV) of 94%. Conclusions Our study demonstrates the clinical value of the nCD64 index in distinguishing between bacterial infection and influenza A in pregnant women during the flu season.

Background We estimated the secondary attack rate of SARS-CoV-2 among household contacts of PCR-confirmed cases of COVID-19 in rural Kenya and analysed risk factors for transmission. Methods We enrolled incident PCR-confirmed cases and their household members. At baseline, a questionnaire, a blood sample, and naso-oropharyngeal swabs were collected. Household members were followed 4, 7, 10, 14, 21 and 28 days after the date of the first PCR-positive in the household; naso-oropharyngeal swabs were collected at each visit and used to define secondary cases. Blood samples were collected every 1-2 weeks. Symptoms were collected in a daily symptom diary. We used binomial regression to estimate secondary attack rates and survival analysis to analyze risk factors for transmission. Results A total of 119 households with at least one positive household member were enrolled between October 2020 and September 2022, comprising 503 household members; 226 remained in follow up at day-14 (45%). A total of 43 secondary cases arose within 14 days of identification of the primary case, 81 household members remained negative. The 7-day secondary attack rate was 4% (95%CI 1-10%), the 14-day secondary attack rate was 28% (95%CI 17-40%). Of 38 secondary cases with data, 8 reported symptoms (21%, 95%CI 8-34%). Antibody to SARS-CoV-2 spike protein at enrolment was not associated with risk of becoming a secondary case. Conclusion Households in our setting experienced a lower 7-day attack rate than a recent meta-analysis indicated as the global average (23-43% depending on variant), and infection is mostly asymptomatic in our setting.

Background First Few “X” (FFX) studies provide evidence to guide public health decision making and resource allocation. The adapted WHO Unity FFX protocol for COVID-19 was implemented to gain an understanding of the clinical, epidemiological, virological, and household transmission dynamics of the first cases of COVID-19 infection detected in Juba, South Sudan. Methods Laboratory-confirmed COVID-19 cases were identified through the national surveillance system, and an initial visit was conducted with eligible cases to identify all close contacts. Consenting cases and close contacts were enrolled between June 2020 and December 2020. Demographic, clinical information and biological samples were taken at enrolment and 14–21 days post-enrolment for all participants. Results Twenty-nine primary cases and 82 contacts were included in analyses. Most primary cases (n=23/29, 79.3%) and contacts (n=61/82, 74.4%) were male. Many primary cases (n=18/29, 62.1%) and contacts (n=51/82, 62.2%) were seropositive for SARS-CoV-2 at baseline. The secondary attack rate among susceptible contacts was 12.9% (4/31; 95% CI: 4.9%–29.7%). All secondary cases and most (72%) primary cases were asymptomatic. Reported symptoms included coughing (n=6/29, 20.7%), fever or history of fever (n=4/29, 13.8%), headache (n=3/29, 10.3%) and shortness of breath (n=3/29, 10.3%). Of 38 cases, two were hospitalised (5.3%) and one died (2.6%). Conclusions These findings were used to develop the South Sudanese Ministry of Health surveillance and contract tracing protocols, informing local COVID-19 case definitions, follow-up protocols and data management systems. This investigation demonstrates that rapid FFX implementation is critical in understanding the emerging disease and informing response priorities.

Widespread school closures and other non-pharmaceutical interventions (NPIs), used to limit the spread of SARS-CoV-2, significantly disrupted transmission patterns of seasonal respiratory viruses. As NPIs were relaxed, populations were vulnerable to resurgence. This study within a small community assessed acute respiratory illness among kindergarten through grade 12 students as they returned to public schools from September through December 2022 without masking and distancing requirements. The 277 specimens collected demonstrated a shift from rhinovirus to influenza. With continued circulation of SARS-CoV-2 and return of seasonal respiratory viruses, understanding evolving transmission patterns will play an important role in reducing disease burden.

We examined associations between mild or asymptomatic prenatal SARS-CoV-2 infection and preterm live birth in a prospective cohort study. During August 2020–October 2021, pregnant persons were followed with systematic surveillance for RT-PCR or serologically-confirmed SARS-CoV-2 infection until pregnancy end. The association between prenatal SARS-CoV-2 infection and preterm birth was assessed using Cox proportional-hazards regression. Among 954 pregnant persons with a live birth, 185 (19%) had prenatal SARS-CoV-2 infection and 123 (13%) had preterm birth. The adjusted hazard ratio for the association between SARS-CoV-2 infection and preterm birth was 1.28 (95% confidence interval 0.82-1.99, p=0.28), although results did not reach statistical significance.

Background: Knowledge of the specific dynamics of influenza introduction and spread in university settings is limited. Methods: Persons with acute respiratory illness symptoms received influenza testing by molecular assay during October 6–November 23, 2022. Viral sequencing and phylogenetic analysis were conducted on nasal swab samples from case-patients. Case-control analysis of a voluntary survey of persons tested was used to identify factors associated with influenza; logistic regression was conducted to calculate odds ratios and 95% CIs. A subset of case-patients tested during the first month of the outbreak was interviewed to identify sources of introduction and early spread. Results: Among 3,268 persons tested, 788 (24.1%) tested positive for influenza; 744 (22.8%) were included in the survey analysis. All 380 sequenced specimens were influenza A (H3N2) virus clade 3C.2a1b.2a.2, suggesting rapid transmission. Influenza (OR [95% CI]) was associated with indoor congregate dining (1.43 [1.002–2.03]), attending large gatherings indoors (1.83 [1.26–2.66]) or outdoors (2.33 [1.64–3.31]), and varied by residence type (apartment with ≥1 roommate: 2.93 [1.21–7.11], residence hall room alone: 4.18 [1.31–13.31], or with roommate: 6.09 [2.46–15.06], or fraternity/sorority house: 15.13 [4.30–53.21], all compared with single-dwelling apartment). Odds of influenza were lower among persons who left campus for ≥1 day during the week before their influenza test (0.49 [0.32–0.75]). Almost all early cases reported attending large events. Conclusions: Congregate living and activity settings on university campuses can lead to rapid spread of influenza following introduction. Isolating following a positive influenza test or administering antiviral medications to exposed persons may help mitigate outbreaks.

Pregnant women with their infants are considered at higher risk for influenza-associated complications, and the WHO recommends influenza vaccination during pregnancy to protect them, including their infants (0-6 months). There are limited data on the influenza burden among pregnant women and their infants (0-6 months), and there is no routine influenza vaccination in Bangladesh. Five annual cohorts (2013-2017) of pregnant women were enrolled from 8 sub-districts of Bangladesh before the influenza season (May-September); contacted weekly to identify new onset of influenza-like illness (ILI) (subjective or measured fever and cough) and acute respiratory illness (ARI) (at least two of: cough, rhinorrhea, or difficulty breathing) among their infants from birth to 6 months of age. We collected nasopharyngeal swabs from ILI and ARI cases, tested by rRT-PCR for influenza virus (including types and subtypes) and estimated influenza incidence (95% CI) /10,000 pregnancy-months or infant-months, respectively. We enrolled 9,020 pregnant women, followed for 26,709 pregnancy-months and detected 1,241 ILI episodes. We also followed 8,963 infants for 51,518 infant-months and identified 5,116 ARI episodes. Influenza positivity was 23% for ILI and 3% for ARI cases. The overall incidence (2013-2017) of influenza among pregnant women was 158.5/10,000 pregnancy-months (95% CI: 141.4-177.6), and that among infants was 21.9/10,000 infant-months (95% CI: 18.2-26.5). Although the data was collected more than five years ago, as the only baseline data, our findings illustrate evidence of influenza burden among pregnant women and infants (0-6 months) which may support preventive policy decisions in Bangladesh.

Objectives: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in young children. We aimed to analyze the factors affecting the estimation of RSV-related disease burden, and furthermore, to provide evidence to help establish a surveillance system. Methods: We searched for literature published in English or Chinese between 1 January, 2010 and 2 June, 2022. The quality of the included articles was assessed using the Agency for Healthcare Research and Quality scale. Random-effects models were used for data synthesis and subgroup analyses. This review was registered in the Prospective Register of Systematic Reviews (PROSPERO: CRD42022372972). Results: We included 44 studies (149,321,171 participants), all of which were of medium or high quality. The pooled RSV-associated disease incidence, hospitalization rate, in-hospital mortality, and overall mortality rates in children aged 5 years and younger were 9.0% (95% confidence interval [CI]: 7.0–11.0%), 1.68% (95% CI: 1.30–2.05%), 0.45% (95% CI: 0.38–0.52%), and 0.05% (95% CI: 0.04–0.06%), respectively. Age, economics, surveillance types, case definition, and data source were all influencing factors. Conclusions: A standardized and unified RSV surveillance system is required. Case definition and surveillance types should be fully considered for surveillance of different age groups.

It is impossible to address the many complex needs of respiratory virus surveillance with a single system. Therefore, multiple surveillance systems and complementary studies must fit together as tiles in a “mosaic” to provide a complete picture of the risk, transmission, severity, and impact of respiratory viruses of epidemic and pandemic potential. Below we present a framework to assist national authorities to identify priority respiratory virus surveillance objectives and the best approaches to meet them; to develop implementation plans according to national context and resources; and to prioritize and target technical assistance and financial investments to meet most pressing needs.