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The threat posed by highly pathogenic avian influenza A H5N1 viruses to humans remains significant, given the continued occurrence of sporadic human cases (499 human cases in 15 countries) with a high case fatality rate (approximately 60%), the endemicity in poultry populations in several countries, and the potential for reassortment with the newly emerging 2009 H1N1 pandemic strain. Therefore, we review risk factors for H5N1 infection in humans. Several epidemiologic studies have evaluated the risk factors associated with increased risk of H5N1 infection among humans who were exposed to H5N1 viruses. Our review shows that most H5N1 cases are attributed to exposure to sick poultry. Most cases are sporadic, while occasional limited human-to-human transmission occurs. The most commonly identified factors associated with H5N1 virus infection included exposure through contact with infected blood or bodily fluids of infected poultry via food preparation practices; touching and caring for infected poultry; [corrected] exposure to H5N1 via swimming or bathing in potentially virus laden ponds; and exposure to H5N1 at live bird markets. Research has demonstrated that despite frequent and widespread contact with poultry, transmission of the H5N1 virus from poultry to humans is rare. Available research has identified several risk factors that may be associated with infection including close direct contact with poultry and transmission via the environment. However, several important data gaps remain that limit our understanding of the epidemiology of H5N1 in humans. Although infection in humans with H5N1 remains rare, human cases continue to be reported and H5N1 is now considered endemic among poultry in parts of Asia and in Egypt, providing opportunities for additional human infections and for the acquisition of virus mutations that may lead to more efficient spread among humans and other mammalian species. Collaboration between human and animal health sectors for surveillance, case investigation, virus sharing, and risk assessment is essential to monitor for potential changes in circulating H5N1 viruses and in the epidemiology of H5N1 in order to provide the best possible chance for effective mitigation of the impact of H5N1 in both poultry and humans. The opinions expressed in this article are those of the authors and do not necessarily reflect those of the institutions or organizations with which they are affiliated.

Event-based surveillance (EBS) is the organised approach to the detection and reporting of 'signals,' defined as information that may represent events of public health importance, often through channels outside of routine surveillance systems. Signals can be designed to detect patterns of disease, such as clusters of similar illness in a community, or clusters of disease or death in animals. Signals can also include single cases of suspected high-priority events such a patient with viral haemorrhagic fever. EBS can be a key component of an effective early warning system, which enables countries to be better prepared for endemic and pandemic illness outbreaks. EBS uses an all-hazards approach that includes the principles of One Health. This review covers the concept and process of EBS, different sources for EBS data, and methods to obtain information from these sources. This overview will aid countries in implementing this important form of surveillance.

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 (WHO Mosaic Respiratory Surveillance 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.

Background. Although influenza is a vaccine-preventable disease that annually causes substantial disease burden, data on virus activity in tropical countries are limited. We analyzed publicly available influenza data to better understand the global circulation of influenza viruses. Method. We reviewed open-source, laboratory-confirmed influenza surveillance data. For each country, we abstracted data on the percentage of samples testing positive for influenza each epidemiologic week from the annual number of samples testing positive for influenza. The start of influenza season was defined as the first week when the proportion of samples that tested positive remained above the annual mean. We assessed the relationship between percentage of samples testing positive and mean monthly temperature with use of regression models. Findings. We identified data on laboratory-confirmed influenza virus infection from 85 countries. More than one influenza epidemic period per year was more common in tropical countries (41%) than in temperate countries (15%). Year-round activity (ie, influenza virus identified each week having ≥10 specimens submitted) occurred in 3 (7%) of 43 temperate, 1 (17%) of 6 subtropical, and 11 (37%) of 30 tropical countries with available data (P = .006). Percentage positivity was associated with low temperature (P = .001). Interpretation. Annual influenza epidemics occur in consistent temporal patterns depending on climate.

The formulation of accurate clinical case definitions is an integral part of an effective process of public health surveillance. Although such definitions should, ideally, be based on a standardized and fixed collection of defining criteria, they often require revision to reflect new knowledge of the condition involved and improvements in diagnostic testing. Optimal case definitions also need to have a balance of sensitivity and specificity that reflects their intended use. After the 2009-2010 H1N1 influenza pandemic, the World Health Organization (WHO) initiated a technical consultation on global influenza surveillance. This prompted improvements in the sensitivity and specificity of the case definition for influenza - i.e. a respiratory disease that lacks uniquely defining symptomology. The revision process not only modified the definition of influenza-like illness, to include a simplified list of the criteria shown to be most predictive of influenza infection, but also clarified the language used for the definition, to enhance interpretability. To capture severe cases of influenza that required hospitalization, a new case definition was also developed for severe acute respiratory infection in all age groups. The new definitions have been found to capture more cases without compromising specificity. Despite the challenge still posed in the clinical separation of influenza from other respiratory infections, the global use of the new WHO case definitions should help determine global trends in the characteristics and transmission of influenza viruses and the associated disease burden.

Health authorities find thresholds useful to gauge the start and severity of influenza seasons. We explored a method for deriving thresholds proposed in an influenza surveillance manual published by the World Health Organization (WHO). For 2002-2011, we analysed two routine influenza-like-illness (ILI) datasets, general practice sentinel surveillance and a locum medical service sentinel surveillance, plus laboratory data and hospital admissions for influenza. For each sentinel dataset, we created two composite variables from the product of weekly ILI data and the relevant laboratory data, indicating the proportion of tested specimens that were positive. For all datasets, including the composite datasets, we aligned data on the median week of peak influenza or ILI activity and assigned three threshold levels: seasonal threshold, determined by inspection; and two intensity thresholds termed average and alert thresholds, determined by calculations of means, medians, confidence intervals (CI) and percentiles. From the thresholds, we compared the seasonal onset, end and intensity across all datasets from 2002-2011. Correlation between datasets was assessed using the mean correlation coefficient. The median week of peak activity was week 34 for all datasets, except hospital data (week 35). Means and medians were comparable and the 90% upper CIs were similar to the 95(th) percentiles. Comparison of thresholds revealed variations in defining the start of a season but good agreement in describing the end and intensity of influenza seasons, except in hospital admissions data after the pandemic year of 2009. The composite variables improved the agreements between the ILI and other datasets. Datasets were well correlated, with mean correlation coefficients of >0.75 for a range of combinations. Thresholds for influenza surveillance are easily derived from historical surveillance and laboratory data using the approach proposed by WHO. Use of composite variables is helpful for describing influenza season characteristics.

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.

IntroductionAs of 26 March 2021, the Africa Centres for Disease Control and Prevention had reported 4 159 055 cases of COVID-19 and 111 357 deaths among the 55 African Union member states; however, no country has published a nationally representative serosurvey as of October 2021. Such data are vital for understanding the pandemic’s progression on the continent, evaluating containment measures, and policy planning.MethodsWe conducted a cross-sectional, nationally representative, age-stratified serosurvey in Sierra Leone in March 2021 by randomly selecting 120 Enumeration Areas throughout the country and 10 randomly selected households in each of these. One to two persons per selected household were interviewed to collect information on sociodemographics, symptoms suggestive of COVID-19, exposure history to laboratory-confirmed COVID-19 cases, and history of COVID-19 illness. Capillary blood was collected by fingerstick, and blood samples were tested using the Hangzhou Biotest Biotech RightSign COVID-19 IgG/IgM Rapid Test Cassette. Total seroprevalence was estimated after applying sampling weights.ResultsThe overall weighted seroprevalence was 2.6% (95% CI 1.9% to 3.4%). This was 43 times higher than the reported number of cases. Rural seropositivity was 1.8% (95% CI 1.0% to 2.5%), and urban seropositivity was 4.2% (95% CI 2.6% to 5.7%).DiscussionOverall seroprevalence was low compared with countries in Europe and the Americas (suggesting relatively successful containment in Sierra Leone). This has ramifications for the country’s third wave (which started in June 2021), during which the average number of daily reported cases was 87 by the end of the month:this could potentially be on the order of 3700 actual infections per day, calling for stronger containment measures in a country with only 0.2% of people fully vaccinated. It may also reflect significant under-reporting of incidence and mortality across the continent.

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.

The influenza A (H1N1) pandemic swept across the globe from April 2009 to August 2010 affecting millions. Many WHO Member States relied on antiviral drugs, specifically neuraminidase inhibitors (NAIs) oseltamivir and zanamivir, to treat influenza patients in critical condition. Such drugs have been found to be effective in reducing severity and duration of influenza illness, and likely reduced morbidity during the pandemic. However, it is less clear whether NAIs used during the pandemic reduced H1N1 mortality. Country-level data on supply of oseltamivir and zanamivir were used to predict H1N1 mortality (per 100,000 people) from July 2009 to August 2010 in forty-two WHO Member States. Poisson regression was used to model the association between NAI supply and H1N1 mortality, with adjustment for economic, demographic, and health-related confounders. After adjustment for potential confounders, each 10% increase in kilograms of oseltamivir, per 100,000 people, was associated with a 1.6% reduction in H1N1 mortality over the pandemic period (relative rate (RR) = 0.84 per log increase in oseltamivir supply). While the supply of zanamivir was considerably less than that of oseltamivir in each Member State, each 10% increase in kilogram of active zanamivir, per 100,000, was associated with a 0.3% reduction in H1N1 mortality (RR = 0.97 per log increase). While there are limitations to the ecologic nature of these data, this analysis offers evidence of a protective relationship between antiviral drug supply and influenza mortality and supports a role for influenza antiviral use in future pandemics.