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Objective: We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021. Materials and methods: The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator-including the vaccination model-is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million. Results: The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation. Conclusion: The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities. This work has been partially funded by the agreement between the Community of Madrid and the Carlos III University of Madrid for the funding of research projects on SARS-CoV-2 and COVID-19 disease, project name 'Multi-source and multi-method prediction to support COVID-19 policy decision making', which was supported with REACT-EU funds from the European regional development fund 'a way of making Europe' (2020/00692/003) and the European High-Performance Computing Joint Undertaking (JU) under the ADMIRE project (grant agreement No 956748). We have also used the Spanish Supercomputing Network (RES) under the grant BCV-2021-1-0011. The role of all study sponsors was limited to financial support. Sí

European region influenza surveillance Network author lisT - Portugal: Raquel Guiomar, Pedro Pechirra, Paula Cristóvão, Inês Costa, Patricia Conde (National Influenza and Other Respiratory Virus Reference Laboratory, Infectious Diseases Department, National Institute of Health Dr. Ricardo Jorge, Lisbon) and Ana Paula Rodrigues (Department of Epidemiology, National Instituteof Health Dr. Ricardo Jorge, Lisbon) Erratum in: Erratum to "Predominance of influenza A(H3N2) virus genetic subclade 3C.2a1 during an early 2016/17 influenza season in Europe - Contribution of surveillance data from World Health Organization (WHO) European region to the WHO vaccine composition consultation for northern hemisphere 2017/18" [Vaccine 35 (2017) 4828-4835]. [Vaccine. 2018 May 3;36(19):2740-2741. doi: 10.1016/j.vaccine.2017.12.039. Epub 2017 Dec 20]. Disponível em: https://doi.org/10.1016/j.vaccine.2017.12.039 During the European 2016/17 influenza season, A(H3N2) viruses have predominated and the majority clustered in genetic subclade 3C.2a1. Genetic analyses showed that circulating viruses have undergone considerable genetic diversification of the haemagglutinin gene from the current vaccine virus A/Hong Kong/4801/2014 (clade 3C.2a), but the antigenic data that is limited by the challenges with the antigenic characterisation of currently circulating A(H3N2) viruses, showed no clear evidence of antigenic change. The recommended A(H3N2) vaccine component for the northern hemisphere 2017/18 influenza season remained unchanged. However, early and mid-season vaccine effectiveness (VE) estimates were suggestive of reduced VE against A(H3N2) viruses. info:eu-repo/semantics/publishedVersion

Respiratory syncytial virus (RSV) is considered the major pathogen causing severe lower respiratory tract infections among infants and young children [1]. RSV is the most common cause of hospitalisation for acute lower respiratory tract infection in children younger than 5 years and is estimated to cause between 66,000 and 199,000 deaths worldwide every year [2]. Its significance in causing substantial morbidity and hospitalisation in the first year of life has been affirmed in a recent study and a meta-analysis [3,4]. In England, average annual hospital admission rates are 35.1 per 1,000 children younger than 1 year and 5.31 per 1,000 children aged 1–4 years [5]. In addition to children, RSV causes a substantial disease burden in elderly people and patients with chronic obstructive pulmonary disease [6,7]. RSV causes seasonal epidemics worldwide [8], with one to two epidemics each year [9] following latitudinal gradients in timing, duration, seasonal amplitude and between-year variability [8,9]. In some studies, the seasonal periodicity has been connected to climatic factors [9-11], but a common factor that explains all observed periodicity has not been established. Meteorological conditions such as temperature and high relative humidity have been reported as important predictors of RSV epidemics [9,12]. In the United States (US) and Japan, annual national and regional variation of RSV season onset and end has been reported [13-15]. In the Nordic countries, a major outbreak often alternates with a minor one, with the minor peak in the spring and a major one the following winter [16-19], a phenomenon reported also in Croatia [20], Denmark [21] and Germany [22]. RSV antigenic groups A and B alternate in two-year cycles in Finland, with dominance of the group A viruses in years 1981–82, 1985–86 and 1989–90 and the group B viruses 1983–84 and 1987–88 [17,19], and different genotypes dominate the circulation in consecutive epidemics in Korea [23]. In Spain, no biennial rhythm has been detected but rather a stable annual epidemic with a peak between week 52 and week 1 and circulation 2–8 weeks earlier than influenza viruses [24]. Similarly, in the United Kingdom (UK), one stable epidemic per year is observed [5]. Immunoprophylaxis to prevent RSV infection with a neutralising monoclonal antibody, palivizumab, has been developed for administration to target groups on a monthly basis during the RSV season [25]. However, this drug is limited to high-risk infants, the cost prohibits its use in low- and middle-income countries and the data on effectiveness of the drug in children at high risk other than infants born at gestational age

BACKGROUND: Estimating the national burden of influenza disease is challenging. We aimed to estimate the disease burden of seasonal influenza in Spain, at the primary care and hospital level, over the 6 influenza seasons after 2009 pandemic. METHODS: We used data from the Spanish Influenza Sentinel Surveillance System to estimate weekly influenza rates and the number of influenza-like illness (ILI) and mild confirmed influenza cases (MCIC). From the surveillance of severe hospitalized confirmed influenza cases (SHCIC), we obtained hospitalization rates and total number of SHCIC, intensive care unit (ICU) admissions and deaths in influenza hospitalized patients. We estimated both mild and severe influenza cases, overall, and by age-group (

Background We used data provided by the Spanish influenza surveillance system to measure seasonal influenza vaccine effectiveness (VE) against medically attended cases, laboratory confirmed with the predominately circulating influenza virus over eight seasons (2003–2011). Methods Using the test-negative case-control design, we compared the vaccination status of swabbed influenza-like illnesses (ILI) patients who were laboratory confirmed with predominantly circulating influenza strain in the season (cases) to that of ILI patients testing negative for any influenza (controls). Data on age, sex, vaccination status and laboratory results were available for all seasons. We used logistic regression to calculate adjusted influenza VE for age, week of swabbing, Spanish region and season. We calculated the influenza VE by each season and pooling the seasons with the same predominant type/subtype. Results Overall influenza VE against infection with A(H3N2) subtype (four seasons) was 31 (95% confidence interval (CI):10; 48). For seasonal influenza A(H1N1) (two seasons), the effectiveness was 86% (95% CI: 65; 94). Against B infection (three seasons), influenza VE was 47% (95% CI: 27; 62). Conclusions The Spanish influenza surveillance system allowed estimating influenza VE in the studied seasons for the predominant strain. Strengthening the influenza surveillance will result in more precise VE estimates for decision making.

SUMMARYThe aim of this study was to monitor the spatio-temporal spread of influenza incidence in Spain during the 2009 pandemic and the following two influenza seasons 2010–2011 and 2011–2012 using a Bayesian Poisson mixed regression model; and implement this model of geographical analysis in the Spanish Influenza Surveillance System to obtain maps of influenza incidence for every week. In the pandemic wave the maps showed influenza activity spreading from west to east. The 2010–2011 influenza epidemic wave plotted a north-west/south-east pattern of spread. During the 2011–2012 season the spread of influenza was geographically heterogeneous. The most important source of variability in the model is the temporal term. The model of spatio-temporal spread of influenza incidence is a supplementary tool of influenza surveillance in Spain.

Contains fulltext : 109779.pdf (Publisher’s version ) (Open Access) BACKGROUND: The world has recently experienced the first influenza pandemic of the 21st century that lasted 14 months from June 2009 to August 2010. This study aimed to compare the timing, geographic spread and community impact during the winter wave of influenza pandemic A (H1N1) 2009 to historical influenza seasons in countries of the WHO European region. METHODS: We assessed the timing of pandemic by comparing the median peak of influenza activity in countries of the region during the last seven influenza seasons. The peaks of influenza activity were selected by two independent researchers using predefined rules. The geographic spread was assessed by correlating the peak week of influenza activity in included countries against the longitude and latitude of the central point in each country. To assess the community impact of pandemic influenza, we constructed linear regression models to compare the total and age-specific influenza-like-illness (ILI) or acute respiratory infection (ARI) rates reported by the countries in the pandemic season to those observed in the previous six influenza seasons. RESULTS: We found that the influenza activity reached its peak during the pandemic, on average, 10.5 weeks (95% CI 6.4-14.2) earlier than during the previous 6 seasons in the Region, and there was a west to east spread of pandemic A(H1N1) influenza virus in the western part of the Region. A regression analysis showed that the total ILI or ARI rates were not higher than historical rates in 19 of the 28 countries. However, in countries with age-specific data, there were significantly higher consultation rates in the 0-4 and/or 5-14 age groups in 11 of the 20 countries. CONCLUSIONS: Using routine influenza surveillance data, we found that pandemic influenza had several differential features compared to historical seasons in the region. It arrived earlier, caused significantly higher number of outpatient consultations in children in most countries and followed west to east spread that was previously observed during some influenza seasons with dominant A (H3N2) ifluenza viruses. The results of this study help to understand the epidemiology of 2009 influenza pandemic and can be used for pandemic preparedness planning.

Lone Simonsen and colleagues use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries. Please see later in the article for the Editors' Summary, Background Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries. Methods and Findings We obtained weekly virology and underlying cause-of-death mortality time series for 2005–2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%–85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons, Editors' Summary Background Every winter, millions of people catch influenza—a viral infection of the airways—and hundreds of thousands of people (mainly elderly individuals) die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Influenza viruses also occasionally emerge that are very different. Human populations have virtually no immunity to these new viruses, which can start global epidemics (pandemics) that kill millions of people. The most recent influenza pandemic, which was first recognized in Mexico in March 2009, was caused by the 2009 influenza A H1N1 pandemic (H1N1pdm09) virus. This virus spread rapidly, and on 11 June 2009, the World Health Organization (WHO) declared that an influenza pandemic was underway. H1N1pdm09 caused a mild disease in most people it infected, but by the time WHO announced that the pandemic was over (10 August 2010), there had been 18,632 laboratory-confirmed deaths from H1N1pdm09. Why Was This Study Done? The modest number of laboratory-confirmed H1N1pdm09 deaths has caused commentators to wonder whether the public health response to H1N1pdm09 was excessive. However, as is the case with all influenza epidemics, the true mortality (death) burden from H1N1pdm09 is substantially higher than these figures indicate because only a minority of influenza-related deaths are definitively diagnosed by being confirmed in laboratory. Many influenza-related deaths result from secondary bacterial infections or from exacerbation of preexisting chronic conditions, and are not recorded as related to influenza infection. A more complete assessment of the impact of H1N1pdm09 on mortality is essential for the optimization of public health responses to future pandemics. In this modeling study (the Global Pandemic Mortality [GLaMOR] project), researchers use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries. What Did the Researchers Do and Find? The researchers obtained weekly virology data from the World Health Organization FluNet database and national influenza centers to identify influenza active periods, and obtained weekly national underlying cause-of-death time series for 2005–2009 from collaborators in more than 20 countries (35% of the world's population). They used a multivariate linear regression model to measure the numbers and rates of pandemic influenza respiratory deaths in each of these countries. Then, in the second stage of their analysis, they used a multiple imputation model that took into account country-specific geographical, economic, and health indicators to project the single-country estimates to all world countries. The researchers estimated that between 123,000 and 203,000 pandemic influenza respiratory deaths occurred globally from 1 April through 31 December 2009. Most of these deaths (62%–85%) occurred in people younger than 65 years old. There was a striking regional heterogeneity in deaths, with up to 20-fold higher mortality in Central and South American countries than in European countries. Finally, the model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season. Notably, only 19% of these deaths occurred in people younger than 65 years old. What Do These Findings Mean? These findings suggest that respiratory mortality from the 2009 influenza pandemic was about 10-fold higher than laboratory-confirmed mortality. The true total mortality burden is likely to be even higher because deaths that occurred late in the winter of 2009–2010 and in later pandemic waves were missed in this analysis, and only pandemic influenza deaths that were recorded as respiratory deaths were included. The lack of single-country estimates from low-income countries may also limit the accuracy of these findings. Importantly, although the researchers' estimates of mortality from H1N1pdm09 and from seasonal influenza were of similar magnitude, the shift towards mortality among younger people means that more life-years were lost during the 2009 influenza pandemic than during an average pre-pandemic influenza season. Although the methods developed by the GLaMOR project can be used to make robust and comparable mortality estimates in future influenza pandemics, the lack of timeliness of such estimates needs to be remedied. One potential remedy, suggest the researchers, would be to establish a collaborative network that analyzes timely hospitalization and/or mortality data provided by sentinel countries. Such a network should be able to provide the rapid and reliable data about the severity of pandemic threats that is needed to guide public health policy decisions. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001558. The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including archived information on H1N1pdm09 Flu.gov, a US government website, provides access to information on seasonal and pandemic influenza H1N1pdm09 The World Health Organization provides information on influenza and on the global response to H1N1pdm09, including a publication on the evolution of H1N1pdm09 (some information in several languages). Information on FluNet, a global tool for influenza surveillance, is also available Public Health England provides information on pandemic influenza and archived information on H1N1pdm09 More information for patients about H1N1pdm09 is available through Choices, an information resource provided by the UK National Health Service More information about the GLaMOR project is available