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Background Influenza vaccination is the most effective way to prevent influenza and influenza-associated complications including those leading to hospitalization. Resources otherwise used for influenza could support caring for patients with coronavirus disease 2019 (COVID-19). The Health Resources and Services Administration (HRSA) Health Center Program serves 30 million people annually by providing comprehensive primary healthcare, including influenza vaccination, to demographically diverse and historically underserved communities. Because racial and ethnic minority groups have been disproportionately affected by COVID-19, the objective of this analysis was to assess disparities in influenza vaccination at HRSA-funded health centers during the COVID-19 pandemic. Methods The Centers for Disease Control and Prevention and HRSA analyzed cross-sectional data on influenza vaccinations from a weekly, voluntary health center COVID-19 survey after addition of an influenza-related question covering 7–11 November 2020. Results During the 3-week period, 1126 of 1385 health centers (81%) responded to the survey. Most of the 811 738 influenza vaccinations took place in urban areas and in the Western US region. There were disproportionately more health center influenza vaccinations among racial and ethnic minorities in comparison with county demographics, except among non-Hispanic blacks and American Indian/Alaska Natives. Conclusions HRSA-funded health centers were able to quickly vaccinate large numbers of mostly racial or ethnic minority populations, disproportionately more than county demographics. However, additional efforts might be needed to reach specific racial populations and persons in rural areas. Success in influenza vaccination efforts can support success in severe acute respiratory syndrome coronavirus 2 vaccination efforts.

This study described the utilisation of telemedicine during the COVID-19 pandemic in June to November 2020. In April 2020, the Centers for Disease Control and Prevention (CDC) and the Health Resources and Services Administration (HRSA) began administering a weekly survey to study the effects of COVID-19 on the testing capacity and operations of health centers. The survey was voluntary and available to 1,382 HRSA-funded centers. Urbanisation and region have been associated with higher rates of telehealth use. Health centers that responded to the COVID-19 surveys were more likely to report multiple visits than those that did not respond. The average percentage of weekly visits for all regions and urbanicity was calculated. The weekly changes were computed based on the number of visits during the first 10 weeks and the second 10 weeks. Week-to-week differences were calculated as the average number of telehealth visits during the first and second weeks of the study. The average percentage of weekly visits that were telehealth-related decreased 25% among the responding health centers during the study period. During the first 10 weeks of the study, the largest absolute change in the number of weekly telehealth visits was reported by health centers in the Northeast. Health centers in the Northeast maintained stable weekly telehealth visits during the second half of the study. Compared with the first 10 weeks, the second half of the study showed a significant change in the percentage of telehealth visits. The average percentage of weekly visits to a telehealth facility differed significantly among various regions. For instance, the South had the lowest percentage of visits. Urban health centers reported significantly higher average percentage of weekly visits for telehealth than rural health centers. The number of cases of COVID-19 in the Northeast also increased during the second quarter. The number of cases of COVID-19 increased in counties where urban health centers are located during the first 10 weeks of the study.

Background The International Health Regulations state that early detection and immediate reporting of unusual health events is important for early warning and response systems. Objective To describe a pilot surveillance program established in health facilities in Yaounde, Cameroon in 2017 which aimed to enable detection and reporting of public health events. Methods Cameroon's Ministry of Health, in partnership with the US Centers for Disease Control and Prevention, Cameroon Pasteur Center, and National Public Health Laboratory, implemented event-based surveillance (EBS) in nine Yaounde health facilities. Four signals were defined that could indicate possible public health events, and a reporting, triage, and verification system was established among partner organizations. A pre-defined laboratory algorithm was defined, and a series of workshops trained health facilities, laboratory, and public health staff for surveillance implementation. Results From May 2017 to January 2018, 30 signals were detected, corresponding to 15 unusual respiratory events. All health facilities reported a signal at least once, and more than three-quarters of health facilities reported ≥2 times. Among specimens tested, the pathogens detected included Klebsiella pneumoniae, Moraxella catarrhalis, Streptococcus pneumoniae, Haemophilus influenza, Staphylococcus aureus, Pneumocystis jiroveci, influenza A (H1N1) virus, rhinovirus, and adenovirus. Conclusions The events detected in this pilot were caused by routine respiratory bacteria and viruses, and no novel influenza viruses or other emerging respiratory threats were identified. The surveillance system, however, strengthened relationships and communication linkages between health facilities and public health authorities. Astute clinicians can play a critical role in early detection and EBS is one approach that may enable reporting of emerging outbreaks and public health events.

Background: Existing scores to identify children at risk of hospitalized pneumonia-related mortality lack broad external validation. Our objective was to externally validate three such risk scores. Methods: We applied the Respiratory Index of Severity in Children (RISC) for HIV-negative children, the RISC-Malawi, and the Pneumonia Etiology Research for Child Health (PERCH) scores to hospitalized children in the Pneumonia REsearch Partnerships to Assess WHO REcommendations (PREPARE) data set. The PREPARE data set includes pooled data from 41 studies on pediatric pneumonia from across the world. We calculated test characteristics and the area under the curve (AUC) for each of these clinical prediction rules. Results: The RISC score for HIV-negative children was applied to 3574 children 0-24 months and demonstrated poor discriminatory ability (AUC = 0.66, 95% confidence interval (CI) = 0.58-0.73) in the identification of children at risk of hospitalized pneumonia-related mortality. The RISC-Malawi score had fair discriminatory value (AUC = 0.75, 95% CI = 0.74-0.77) among 17 864 children 2-59 months. The PERCH score was applied to 732 children 1-59 months and also demonstrated poor discriminatory value (AUC = 0.55, 95% CI = 0.37-0.73). Conclusions: In a large external application of the RISC, RISC-Malawi, and PERCH scores, a substantial number of children were misclassified for their risk of hospitalized pneumonia-related mortality. Although pneumonia risk scores have performed well among the cohorts in which they were derived, their performance diminished when externally applied. A generalizable risk assessment tool with higher sensitivity and specificity to identify children at risk of hospitalized pneumonia-related mortality may be needed. Such a generalizable risk assessment tool would need context-specific validation prior to implementation in that setting. publishedVersion

Background Simulation exercises can functionally validate World Health Organization (WHO) International Health Regulations (IHR 2005) core capacities. In 2018, the Vietnam Ministry of Health (MOH) conducted a full-scale exercise (FSX) in response to cases of severe viral pneumonia with subsequent laboratory confirmation for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) to evaluate the country’s early warning and response capabilities for high-risk events. Methods An exercise planning team designed a complex fictitious scenario beginning with one case of severe viral pneumonia presenting at the hospital level and developed all the materials required for the exercise. Actors, controllers and evaluators were trained. In August 2018, a 3-day exercise was conducted in Quang Ninh province and Hanoi city, with participation of public health partners at the community, district, province, regional and national levels. Immediate debriefings and an after-action review were conducted after all exercise activities. Participants assessed overall exercise design, conduction and usefulness. Results FSX findings demonstrated that the event-based surveillance component of the MOH surveillance system worked optimally at different administrative levels. Detection and reporting of signals at the community and health facility levels were appropriate. Triage, verification and risk assessment were successfully implemented to identify a high-risk event and trigger timely response. The FSX identified infection control, coordination with internal and external response partners and process documentation as response challenges. Participants positively evaluated the exercise training and design. Conclusions This exercise documents the value of exercising surveillance capabilities as part of a real-time operational scenario before facing a true emergency. The timing of this exercise and choice of disease scenario was particularly fortuitous given the subsequent appearance of COVID-19. As a result of this exercise and subsequent improvements made by the MOH, the country may have been better able to deal with the emergence of SARS-CoV-2 and contain it.

Background In 2016–2017, Vietnam’s Ministry of Health (MoH) implemented an event-based surveillance (EBS) pilot project in six provinces as part of Global Health Security Agenda (GHSA) efforts. This manuscript describes development and design of tools for monitoring and evaluation (M&E) of EBS in Vietnam. Methods A strategic EBS framework was developed based on the EBS implementation pilot project’s goals and objectives. The main process and outcome components were identified and included input, activities, outputs, and outcome indicators. M&E tools were developed to collect quantitative and qualitative data. The tools included a supervisory checklist, a desk review tool, a key informant interview guide, a focus group discussion guide, a timeliness form, and an online acceptability survey. An evaluation team conducted field visits for assessment of EBS 5–9 months after implementation. Results The quantitative data collected provided evidence on the number and type of events that were being reported, the timeliness of the system, and the event-to-signal ratio. The qualitative and subjective data collected helped to increase understanding of the system’s field utility and acceptance by field staff, reasons for non-compliance with established guidelines, and other factors influencing implementation. Conclusions The use of M&E tools for the EBS pilot project in Vietnam provided data on signals and events reported, timeliness of reporting and response, perceptions and opinions of implementers, and fidelity of EBS implementation. These data were valuable for Vietnam’s MoH to understand the function of the EBS program, and the success and challenges of implementing this project in Vietnam.

Surveillance and outbreak reporting systems in Vietnam required improvements to function effectively as early warning and response systems. Accordingly, the Ministry of Health of Vietnam, in collaboration with the US Centers for Disease Control and Prevention, launched a pilot project in 2016 focusing on community and hospital event–based surveillance. The pilot was implemented in 4 of Vietnam’s 63 provinces. The pilot demonstrated that event-based surveillance resulted in early detection and reporting of outbreaks, improved collaboration between the healthcare facilities and preventive sectors of the ministry, and increased community participation in surveillance and reporting.

The database of the Global Influenza B Study was created by collecting surveillance datasets from each of the participating countries. These national datasets are owned by the participating countries, and thus cannot be shared publicly. Researchers interested in obtaining the country-specific datasets may contact the individuals listed below for further details regarding data access.Argentina (Santa Fe Province): Gabriela Kusznierz (labconi@yahoo.com.ar)Australia: Kate Pennington (kate.pennington@health.gov.au)Bhutan: Sonam Wangchuk (swangchuk@health.gov.bt)Brazil: Cláudio Maierovitch Pessanha Henriques (claudio.henriques@saude.gov.br)Cameroon: Guy Vernet (vernet@pasteur-yaounde.org)Chile: Rodrigo Fasce (rfasce@ispch.cl)China: Feng Luzhao (fenglz@chinacdc.cn)Costa Rica: Alexey W. Clara (wclara@cdc.gov)Ecuador: Alfredo Bruno (alfredobruno@yahoo.es)El Salvador: Alexey W. Clara (wclara@cdc.gov)England: Maria Zambon (maria.zambon@phe.gov.uk)Guatemala: Alexey W. Clara (wclara@cdc.gov)Honduras: Alexey W. Clara (wclara@cdc.gov)Indonesia: Herman Kosasih (hermaninarespond@gmail.com)Italy: Caterina Rizzo (caterina.rizzo@iss.it)Ivory Coast: Herve A. Kadjo (hervekadjo@pasteur.ci)Kazakhstan: Gulzhan Muratbayeva (hnv2@cdc.gov)Kenya: Joshua Mott (zud9@cdc.gov)Madagascar: Jean-Michel Heraud (jmheraud@pasteur.mg)Morocco: Amal Barakat (amal.barakat@yahoo.fr)New Zealand: Sue Huang (sue.huang@esr.cri.nz)Nicaragua: Alexey W. Clara (wclara@cdc.gov)Panama: Alexey W. Clara (wclara@cdc.gov)Portugal: Ana Paula Rodrigues (ana.rodrigues@insa.min-saude.pt)Singapore: Vernon Lee (vernonljm@hotmail.com)South Africa: Cheryl Cohen (cherylc@nicd.ac.za)Turkey: Meral Akcay Ciblak (ciblakm@yahoo.com)Ukraine: Alla Mironenko (miralla@ukr.net)Viet Nam: Le Thi Quinh Mai (lom9@hotmail.com); International audience; BACKGROUND:Influenza disease burden varies by age and this has important public health implications. We compared the proportional distribution of different influenza virus types within age strata using surveillance data from twenty-nine countries during 1999-2014 (N=358,796 influenza cases).METHODS:For each virus, we calculated a Relative Illness Ratio (defined as the ratio of the percentage of cases in an age group to the percentage of the country population in the same age group) for young children (0-4 years), older children (5-17 years), young adults (18-39 years), older adults (40-64 years), and the elderly (65+ years). We used random-effects meta-analysis models to obtain summary relative illness ratios (sRIRs), and conducted meta-regression and sub-group analyses to explore causes of between-estimates heterogeneity.RESULTS:The influenza virus with highest sRIR was A(H1N1) for young children, B for older children, A(H1N1)pdm2009 for adults, and (A(H3N2) for the elderly. As expected, considering the diverse nature of the national surveillance datasets included in our analysis, between-estimates heterogeneity was high (I2>90%) for most sRIRs. The variations of countries' geographic, demographic and economic characteristics and the proportion of outpatients among reported influenza cases explained only part of the heterogeneity, suggesting that multiple factors were at play.CONCLUSIONS:These results highlight the importance of presenting burden of disease estimates by age group and virus (sub)type.

Ghana Health Service (GHS) has strengthened community-based surveillance (CBS) to facilitate early detection and rapid reporting of health events of all origins. Since June 2017, GHS has employed an event-based surveillance approach at the community level in a phased manner. CBS coverage has broadened from 2 to 30 districts across Ghana. Through this effort, capacity was built across all administrative levels in these districts to detect, report, triage, and verify signals, and to perform risk assessment and investigate events. Data were collected and analyzed during an evaluation of initial 2-district implementation in March 2018 and during expanded 30-district implementation in March 2019. Between September 2018 and March 2019, 317 health events were detected through CBS. These events included vaccine-preventable disease cases, acute hemorrhagic conjunctivitis outbreaks, clusters of unexpected animal deaths, and foodborne illness clusters. Eighty-nine percent of the 317 events were reported to district-level public health staff within 24 hours of detection at the community level, and 87% of all detected events were responded to within 48 hours of detection. CBS detected 26% of all suspected vaccine-preventable disease cases that were reported from implementing districts through routine disease surveillance. GHS strengthened CBS in Ghana to function as an early warning system for health events of all origins, advancing the Global Health Security Agenda.

Data needed to guide influenza vaccine policies are lacking in tropical countries. We multiplied the number of severe acute respiratory infections by the proportion testing positive for influenza. There were ≈6,699 influenza hospitalizations and 803 deaths in Costa Rica during 2009–2012, supporting continuation of a national influenza vaccine program.

Community event-based surveillance aims to enhance the early detection of emerging public health threats and thus build health security. The Ministry of Health of Vietnam launched a community event-based surveillance pilot program in 6 provinces to improve the early warning functions of the existing surveillance system. An evaluation of the pilot program took place in 2017 and 2018. Data from this evaluation were analyzed to determine which factors were associated with increased detection and reporting. Results show that a number of small, local events were detected and reported through community event-based surveillance, supporting the notion that it would also facilitate the rapid detection and reporting of potentially larger events or outbreaks. The study showed the value of supportive supervision and monitoring to sustain community health worker reporting and the importance of conducting evaluations for community event-based surveillance programs to identify barriers to effective implementation.

Erratum in - Correction: Temporal Patterns of Influenza A and B in Tropical and Temperate Countries: What Are the Lessons for Influenza Vaccination? PLoS One. 2016 May 2;11(5):e0155089. doi: 10.1371/journal.pone.0155089. Introduction: Determining the optimal time to vaccinate is important for influenza vaccination programmes. Here, we assessed the temporal characteristics of influenza epidemics in the Northern and Southern hemispheres and in the tropics, and discuss their implications for vaccination programmes. Methods: This was a retrospective analysis of surveillance data between 2000 and 2014 from the Global Influenza B Study database. The seasonal peak of influenza was defined as the week with the most reported cases (overall, A, and B) in the season. The duration of seasonal activity was assessed using the maximum proportion of influenza cases during three consecutive months and the minimum number of months with 80% of cases in the season. We also assessed whether co-circulation of A and B virus types affected the duration of influenza epidemics. Results: 212 influenza seasons and 571,907 cases were included from 30 countries. In tropical countries, the seasonal influenza activity lasted longer and the peaks of influenza A and B coincided less frequently than in temperate countries. Temporal characteristics of influenza epidemics were heterogeneous in the tropics, with distinct seasonal epidemics observed only in some countries. Seasons with co-circulation of influenza A and B were longer than influenza A seasons, especially in the tropics. Discussion: Our findings show that influenza seasonality is less well defined in the tropics than in temperate regions. This has important implications for vaccination programmes in these countries. High-quality influenza surveillance systems are needed in the tropics to enable decisions about when to vaccinate. The Global Influenza B Study is supported by an unrestricted research grant from Sanofi Pasteur. info:eu-repo/semantics/publishedVersion

Summary Background The annual number of hospital admissions and in-hospital deaths due to severe acute lower respiratory infections (ALRI) in young children worldwide is unknown. We aimed to estimate the incidence of admissions and deaths for such infections in children younger than 5 years in 2010. Methods We estimated the incidence of admissions for severe and very severe ALRI in children younger than 5 years, stratified by age and region, with data from a systematic review of studies published between Jan 1, 1990, and March 31, 2012, and from 28 unpublished population-based studies. We applied these incidence estimates to population estimates for 2010, to calculate the global and regional burden in children admitted with severe ALRI in that year. We estimated in-hospital mortality due to severe and very severe ALRI by combining incidence estimates with case fatality ratios from hospital-based studies. Findings We identified 89 eligible studies and estimated that in 2010, 11·9 million (95% CI 10·3–13·9 million) episodes of severe and 3·0 million (2·1–4·2 million) episodes of very severe ALRI resulted in hospital admissions in young children worldwide. Incidence was higher in boys than in girls, the sex disparity being greatest in South Asian studies. On the basis of data from 37 hospital studies reporting case fatality ratios for severe ALRI, we estimated that roughly 265 000 (95% CI 160 000–450 000) in-hospital deaths took place in young children, with 99% of these deaths in developing countries. Therefore, the data suggest that although 62% of children with severe ALRI are treated in hospitals, 81% of deaths happen outside hospitals. Interpretation Severe ALRI is a substantial burden on health services worldwide and a major cause of hospital referral and admission in young children. Improved hospital access and reduced inequities, such as those related to sex and rural status, could substantially decrease mortality related to such infection. Community-based management of severe disease could be an important complementary strategy to reduce pneumonia mortality and health inequities. Funding WHO.

We estimate the proportion of patients hospitalized for suspected dengue that tested positive for influenza virus in El Salvador during the 2012 influenza season. We tested specimens from 321 hospitalized patients: 198 patients with SARI and 123 patients with suspected dengue. Among 121 hospitalized suspected dengue (two co-infected excluded) patients, 28% tested positive for dengue and 19% positive for influenza; among 35 with suspected dengue and respiratory symptoms, 14% were positive for dengue and 39% positive for influenza. One percent presented co-infection between influenza and dengue. Clinicians should consider the diagnosis of influenza among patients with suspected dengue during the influenza season.