Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia

[EN] Seasonal fluctuations in the incidence of several respiratory infections are a feature of epidemiological surveys all around the world. This phenomenon is characteristic of influenza and respiratory syncytial virus pandemics. However, the explanation of the seasonal outbreaks of these diseases remains poorly understood. Many statistical studies have been carried out in order to provide a correlation of the outbreaks with climatic or social factors without achieving a definitive conclusion. Here we show that, in a random social network, self-sustained seasonal epidemics emerge as a process modulated by the infection probability and the immunity period after recovering from the infection. This is a purely endogenous phenomenon that does not require any exogenous forcing. Assuming that this is the dominant mechanism for seasonal epidemics, many implications for public health policies for infectious respiratory diseases could be drawn. (C) 2010 Elsevier Ltd. All rights reserved.Supported by a grant from the Universidad Politecnica de Valencia PAID-06-09 ref: 2588.Acedo Rodríguez, L.; Moraño Fernández, JA.; Villanueva Micó, RJ.; Villanueva Oller, FJ.; Díez Domingo, J. (2011). Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia. Mathematical and Computer Modelling. 54(7-8):1650-1654. https://doi.org/10.1016/j.mcm.2010.11.068S16501654547-

Cost analysis of a vaccination startegy for respiratory syncytial virus (RSV) in a network model

[EN] In this paper an age-structured mathematical model for respiratory syncytial virus (RSV) is proposed where children younger than one year old, who are the most affected by this illness, are specially considered. Real data of hospitalized children in the Spanish region of Valencia are used in order to determine some seasonal parameters of the model. Once the parameters are determined, we propose a complete stochastic network model to study the seasonal evolution of the respiratory syncytial virus (RSV) epidemics. In this model every susceptible individual can acquire the disease after a random encounter with any infected individual in the social network. The edges of a complete graph connecting every pair of individuals in the network simulate these encounters and a season dependent probability, beta(t), determines whether the healthy susceptible individual becomes infected or not. We show that the prediction of this model is compatible with the above mentioned age-structured model based upon differential equations, but sharper peaks are obtained in the case of the network. Then, on the network model, we propose the vaccination of children at 2 months, 4 months and 1 year old, and we study the cost of this vaccination strategy, which is emerging as the most plausible one to be applied when the vaccine hits the market. It is worth to note that this vaccination strategy is simulated in the network model because to implement it in the continuous model is very difficult and increases its complexity. (C) 2010 Elsevier Ltd. All rights reserved.Acedo Rodríguez, L.; Moraño Fernández, JA.; Diez-Domingo, J. (2010). Cost analysis of a vaccination startegy for respiratory syncytial virus (RSV) in a network model. Mathematical and Computer Modelling. 52(7):1016-1022. doi:10.1016/j.mcm.2010.02.041S1016102252

Positividad y acotamiento de soluciones de un modelo epidemiologico estacional estocástico para el virus respiratorio sincitial

In this paper we investigate the positivity and boundedness of the solution of a stochastic seasonal epidemic model for the respira tory syncytial virus (RSV). The stochasticity in the model is due to fluctuating physical and social environments and is introduced by perturbing the transmission parameter of the seasonal disease. We show the existence and uniqueness of the positive solution of the stochastic seasonal epidemic model which is required in the modeling of populations since all populations must be positive from a biological point of view. In addition, the positivity and boundedness of solutions is important to other nonlinear models that arise in sciences and engineering. Numerical simulations of the stochastic model are performed using the Milstein numerical scheme and are included to support our analytic results.En este trabajo se investiga la positividad y acotamineto de la solución de un modelo epidemiologico estacional estocástico para el virus respiratorio sincitial (RSV). La estocasticidad en el modelo se debe a entornos físicos y sociales fluctuantes y se introduce perturbando el parámetro de transmisión de la enfermedad. Se demuestra la existencia y unicidad de la solución positiva del modelo epidemiologico estacional estocástico, lo cual se requiere en el modelado de las poblaciones ya que todas las poblaciones deben ser positivos desde el punto de vista biológico. Adicionalmente, la positividad y la acotación de las soluciones es importante para otros modelos no lineales que se presentan en las ciencias y la ingeniería. Las simulaciones numéricas del modelo estocástico se realizan utilizando el esquema numérico de Milstein y se incluyen para apoyar los resultados analíticos

Epidemic Random Network Simulations in a Distributed Computing Environment

We discuss a computational system following the paradigm of distributed computing, which will allow us to simulate the epidemic propagation in random networks with large number of nodes up to one million. This paradigm consists of a server that delivers tasks to be carried out by client computers. When the task is finished, the client sends the obtained results to the server to be stored until all tasks are finished and then ready to be analysed. Finally, we show that this technique allows us to disclose the emergence of seasonal patterns in the respiratory syncytial virus transmission dynamics which do not appear neither in smaller systems nor in continuous systems.This paper has been supported by the Grant from the Universitat Politecnica de Valencia PAID-06-11 ref: 2087 and the Grant FIS PI-10/01433. The authors would like to thank the staff of the Facultad de Administracion de Empresas of the Universidad Politecnica de Valencia, in particular Mara Angeles Herrera, Teresa Solaz, and Jose Luis Real, and the staff of the CES Felipe II of Aranjuez for their help and for letting them use free computer rooms to carry out the Sisifo computations described in this paper. They would also like to acknowledge the BOINC community for its support and the many anonymous volunteers who joined thier project and helped them obtain the results so fast.Villanueva-Oller, J.; Acedo Rodríguez, L.; Moraño Fernández, JA.; Sánchez Sánchez, A. (2013). Epidemic Random Network Simulations in a Distributed Computing Environment. Abstract and Applied Analysis. 2013:1-10. https://doi.org/10.1155/2013/462801S1102013PROULX, S., PROMISLOW, D., & PHILLIPS, P. (2005). Network thinking in ecology and evolution. Trends in Ecology & Evolution, 20(6), 345-353. doi:10.1016/j.tree.2005.04.004Traud, A. L., Mucha, P. J., & Porter, M. A. (2012). Social structure of Facebook networks. Physica A: Statistical Mechanics and its Applications, 391(16), 4165-4180. doi:10.1016/j.physa.2011.12.021Christakis, N. A., & Fowler, J. H. (2008). The Collective Dynamics of Smoking in a Large Social Network. New England Journal of Medicine, 358(21), 2249-2258. doi:10.1056/nejmsa0706154Christakis, N. A., & Fowler, J. H. (2007). The Spread of Obesity in a Large Social Network over 32 Years. New England Journal of Medicine, 357(4), 370-379. doi:10.1056/nejmsa066082Halloran, M. E. (2002). Containing Bioterrorist Smallpox. Science, 298(5597), 1428-1432. doi:10.1126/science.1074674Ahmed, E., & Agiza, H. N. (1998). On modeling epidemics Including latency, incubation and variable susceptibility. Physica A: Statistical Mechanics and its Applications, 253(1-4), 347-352. doi:10.1016/s0378-4371(97)00665-1Martins, M. L., Ceotto, G., Alves, S. G., Bufon, C. C. B., Silva, J. M., & Laranjeira, F. F. (2000). Cellular automata model for citrus variegated chlorosis. Physical Review E, 62(5), 7024-7030. doi:10.1103/physreve.62.7024Hershberg, U., Louzoun, Y., Atlan, H., & Solomon, S. (2001). HIV time hierarchy: winning the war while, loosing all the battles. Physica A: Statistical Mechanics and its Applications, 289(1-2), 178-190. doi:10.1016/s0378-4371(00)00466-0Witten, G., & Poulter, G. (2007). Simulations of infectious diseases on networks. Computers in Biology and Medicine, 37(2), 195-205. doi:10.1016/j.compbiomed.2005.12.002Acedo, L., Moraño, J.-A., & Díez-Domingo, J. (2010). Cost analysis of a vaccination strategy for respiratory syncytial virus (RSV) in a network model. Mathematical and Computer Modelling, 52(7-8), 1016-1022. doi:10.1016/j.mcm.2010.02.041Hethcote, H. W. (2000). The Mathematics of Infectious Diseases. SIAM Review, 42(4), 599-653. doi:10.1137/s0036144500371907Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509Villanueva-Oller, J., Villanueva, R. J., & Díez, S. (2007). CASANDRA: A prototype implementation of a system of network progressive transmission of medical digital images. Computer Methods and Programs in Biomedicine, 85(2), 152-164. doi:10.1016/j.cmpb.2006.10.002Korpela, E., Werthimer, D., Anderson, D., Cobb, J., & Leboisky, M. (2001). SETI@home-massively distributed computing for SETI. Computing in Science & Engineering, 3(1), 78-83. doi:10.1109/5992.895191Hall, C. B., Powell, K. R., MacDonald, N. E., Gala, C. L., Menegus, M. E., Suffin, S. C., & Cohen, H. J. (1986). Respiratory Syncytial Viral Infection in Children with Compromised Immune Function. New England Journal of Medicine, 315(2), 77-81. doi:10.1056/nejm198607103150201Falsey, A. R., & Walsh, E. E. (2000). Respiratory Syncytial Virus Infection in Adults. Clinical Microbiology Reviews, 13(3), 371-384. doi:10.1128/cmr.13.3.371-384.2000Díez Domingo, J., Ridao López, M., Úbeda Sansano, I., & Ballester Sanz, A. (2006). Incidencia y costes de la hospitalización por bronquiolitis y de las infecciones por virus respiratorio sincitial en la Comunidad Valenciana. Años 2001 y 2002. Anales de Pediatría, 65(4), 325-330. doi:10.1157/13093515ACEDO, L., DÍEZ-DOMINGO, J., MORAÑO, J.-A., & VILLANUEVA, R.-J. (2009). Mathematical modelling of respiratory syncytial virus (RSV): vaccination strategies and budget applications. Epidemiology and Infection, 138(6), 853-860. doi:10.1017/s0950268809991373Weber, A., Weber, M., & Milligan, P. (2001). Modeling epidemics caused by respiratory syncytial virus (RSV). Mathematical Biosciences, 172(2), 95-113. doi:10.1016/s0025-5564(01)00066-9White, L. J., Mandl, J. N., Gomes, M. G. M., Bodley-Tickell, A. T., Cane, P. A., Perez-Brena, P., … Medley, G. F. (2007). Understanding the transmission dynamics of respiratory syncytial virus using multiple time series and nested models. Mathematical Biosciences, 209(1), 222-239. doi:10.1016/j.mbs.2006.08.018Acedo, L., Moraño, J.-A., Villanueva, R.-J., Villanueva-Oller, J., & Díez-Domingo, J. (2011). Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia. Mathematical and Computer Modelling, 54(7-8), 1650-1654. doi:10.1016/j.mcm.2010.11.068SCHNEEBERGER, A., MERCER, C. H., GREGSON, S. A. J., FERGUSON, N. M., NYAMUKAPA, C. A., ANDERSON, R. M., … GARNETT, G. P. (2004). Scale-Free Networks and Sexually Transmitted Diseases. Sexually Transmitted Diseases, 31(6), 380-387. doi:10.1097/00007435-200406000-00012Lou, J., & Ruggeri, T. (2010). The dynamics of spreading and immune strategies of sexually transmitted diseases on scale-free network. Journal of Mathematical Analysis and Applications, 365(1), 210-219. doi:10.1016/j.jmaa.2009.10.044Fleming, D. M. (2005). Mortality in children from influenza and respiratory syncytial virus. Journal of Epidemiology & Community Health, 59(7), 586-590. doi:10.1136/jech.2004.026450Meerhoff, T. J., Paget, J. W., Kimpen, J. L., & Schellevis, F. (2009). Variation of Respiratory Syncytial Virus and the Relation With Meteorological Factors in Different Winter Seasons. The Pediatric Infectious Disease Journal, 28(10), 860-866. doi:10.1097/inf.0b013e3181a3e949Welliver, R. C. (2007). Temperature, Humidity, and Ultraviolet B Radiation Predict Community Respiratory Syncytial Virus Activity. The Pediatric Infectious Disease Journal, 26(Supplement), S29-S35. doi:10.1097/inf.0b013e318157da59Dushoff, J., Plotkin, J. B., Levin, S. A., & Earn, D. J. D. (2004). Dynamical resonance can account for seasonality of influenza epidemics. Proceedings of the National Academy of Sciences, 101(48), 16915-16916. doi:10.1073/pnas.0407293101Arino, J., Davis, J. R., Hartley, D., Jordan, R., Miller, J. M., & van den Driessche, P. (2005). A multi-species epidemic model with spatial dynamics. Mathematical Medicine and Biology: A Journal of the IMA, 22(2), 129-142. doi:10.1093/imammb/dqi00

A deterministic model for highly contagious diseases: The case of varicella

[EN] The classic nonlinear Kermack-McKendrick model based upon a system of differential equations has been widely applied to model the rise and fall of global pandemic and also seasonal epidemic by introducing a forced harmonic infectivity which would change throughout the year. These methods work well in their respective domains of applicability, and for certain diseases, but they fail when both seasonality and high infectivity are combined. In this paper we consider a Susceptible-Infected-Recovered, or SIR, model with two latent states to model the propagation and evolutionary history of varicella in humans. We show that infectivity can be calculated from real data and we find a nonstandard seasonal variation that cannot be fitted with a single harmonic. Moreover, we show that infectivity for the present strains of the virus has raised following a sigmoid function in a period of several centuries. This could allow the design of vaccination strategies and the study of the epidemiology of varicella and herpes zoster. (C) 2016 Elsevier B.V. All rights reserved.Acedo Rodríguez, L.; Moraño Fernández, JA.; Santonja, F.; Villanueva Micó, RJ. (2016). A deterministic model for highly contagious diseases: The case of varicella. Physica A: Statistical Mechanics and its Applications. 450:278-286. doi:10.1016/j.physa.2015.12.153S27828645

Random Network Models to Predict the Long-Term Impact of HPV Vaccination on Genital Warts

[EN] The Human papillomaviruses (HPV) vaccine induces a herd immunity effect in genital warts when a large number of the population is vaccinated. This aspect should be taken into account when devising new vaccine strategies, like vaccination at older ages or male vaccination. Therefore, it is important to develop mathematical models with good predictive capacities. We devised a sexual contact network that was calibrated to simulate the Spanish epidemiology of different HPV genotypes. Through this model, we simulated the scenario that occurred in Australia in 2007, where 12¿13 year-old girls were vaccinated with a three-dose schedule of a vaccine containing genotypes 6 and 11, which protect against genital warts, and also a catch-up program in women up to 26 years of age. Vaccine coverage were 73% in girls with three doses and with coverage rates decreasing with age until 52% for 20¿26 year-olds. A fast 59% reduction in the genital warts diagnoses occurred in the model in the first years after the start of the program, similar to what was described in the literature.We are grateful for the support from Sanofi Pasteur. The authors would also like to thank M. Diaz-Sanchis from the Institut Catala d'Oncologia (ICO) for her useful comments and the data provided on HPV prevalence. We would also like to thank the ICO for the HPV information centre at http://hpvcentre.net.Diez-Domingo, J.; Sánchez-Alonso, V.; Villanueva Micó, RJ.; Acedo Rodríguez, L.; Moraño Fernández, JA.; Villanueva-Oller, J. (2017). Random Network Models to Predict the Long-Term Impact of HPV Vaccination on Genital Warts. Viruses. 9(10). doi:10.3390/v9100300S91

Modelling the transmission dynamics of RSV and the impact of routine vaccination

Introduction: Respiratory Syncytial Virus is the major viral cause of lower respiratory tract disease in young children worldwide, with the greatest burden of disease in infants aged 1-3 months. Consequently, vaccine development has centered on a vaccine to directly protect the infants in this age group. The fundamental problem is that these young infants are poor responders to candidate RSV vaccines. This thesis focuses on the use of mathematical models to explore the merits of vaccination. Methods: Following development and analysis of a simple non-age-structured ODE model, we elaborate this to a Realistic Age Structured model (RAS) capturing the key epidemiological characteristics of RSV and incorporating age-specific vaccination options. The compartmental ODE model was calibrated using agespecific and time series hospitalization data from a rural coastal Kenyan population. The determination of Who Acquires Infection From Whom (WAIFW) matrix was done using social contact data from 1) a synthetic mixing matrix generated from primarily household occupancy data and 2) a diary study that we conducted in the Kilifi Health and Demographic Surveillance System (KHDSS). The vaccine was assumed to elicit partial immunity equivalent to wild type infection and its impact was measured by the ratio of hospitalized RSV cases after to before introduction. of vaccination. Uncertainty and sensitivity analysis were undertaken using Latin Hypercube Sampling (LHS) and partial rank correlation respectively. Given the importance of households in the transmission of respiratory infections, an exploratory household model was developed to capture the transmission dynamics of RSV A and B in a population of households. Results: From the analytical work of the simple ODE model, we have demonstrated that the model has the potential to exhibit a backward bifurcation curve within realistic parameter ranges. Both the diary and the synthetic mixing matrices had similar characteristics i.e. strong assortative mixing in individuals less than 30 years old and strong mixing between children less than 5 years and adults between 20 and 50 years old. When the two matrices were jointly linearly regressed, their elements were well correlated with an R2 ~ 0.6. The RAS model was capable of capturing the age-specific disease and the temporal epidemic nature of RSV in the specified location. Introduction of routine universal vaccination at ages varying from the first month of life to the 10th year of life resulted in optimal long-term benefit at 7 months (for the diary contact model) and 5 months (for the synthetic contact model). The greatest benefit arose under the assumption of age-related mixing with the contact diary data with no great deal of effectiveness lost when the vaccine is delayed between 5 and 12 months of age from birth. Vaccination was also shown to change the temporal dynamics of RSV hospitalizations and also to increase the average age at primary infection. From the sensitivity analysis, we identified the duration of RSV specific maternal antibodies, duration of primary and tertiary infections as the most important parameters in explaining the imprecision observed in predicting both the age specific hospitalizations and the optimal month at vaccination. Results from the household model have demonstrated that the household epidemic profile may be different from the general population with strong interaction of the viruses in the household that do not necessarily reflect at the population level. Conclusion: The synthetic matrix method would be a preferable alternative route in estimating mixing patterns in populations with the required socio-demographic data. Retrospectively, the synthetic mixing data can be used to reconstruct contact patterns in the past and therefore beneficial in assessing the effect of demographic transition in disease transmission. Universal infant vaccination has the potential to significantly reduce the burden of RSV associated disease, even with delayed vaccination between 5 and 12 months. This age class represents the group that is being targeted by vaccines that are currently under development. More accurate data measuring the duration of RSV specific maternal antibodies and the duration of infections are required to reduce the uncertainty in the model predictions

Calibrating a large network model describing the transmission dynamics of the human papillomavirus (HPV) using a Particle Swarm Optimization (PSO) algorithm in a distributed computing environment

[EN] Working in large networks applied to epidemiological-type models has led us to design a simple but e↵ective computed distributed environment to perform a large amount of model simulations in a reasonable time in order to study the behavior of these models and to calibrate them. Finding the model parameters that best fit the available data in the designed distributed computing environment becomes a challenge and it is necessary to implement reliable algorithms for model calibration. In this paper, we have adapted the random PSO algorithm to our distributed computing environment to be applied to the calibration of a Papillomavirus transmission dynamics model on a lifetime sexual partners network. And we have obtained a good fitting saving time and calculations compared with the exhaustive searching strategy we have been using so far.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been partially supported by the Ministerio de Economa y Competitividad Grants MTM2013-41765-P and TIN 2014-54806-R.Acedo Rodríguez, L.; Burgos-Simon, C.; Hidalgo, J.; Sánchez-Alonso, V.; Villanueva Micó, RJ.; Villanueva-Oller, J. (2018). Calibrating a large network model describing the transmission dynamics of the human papillomavirus (HPV) using a Particle Swarm Optimization (PSO) algorithm in a distributed computing environment. International Journal of High Performance Computing Applications. 32(5):721-728. https://doi.org/10.1177/1094342017697862S721728325Acedo, L., Lamprianidou, E., Moraño, J.-A., Villanueva-Oller, J., & Villanueva, R.-J. (2015). Firing patterns in a random network cellular automata model of the brain. Physica A: Statistical Mechanics and its Applications, 435, 111-119. doi:10.1016/j.physa.2015.05.017Acedo, L., Moraño, J.-A., Villanueva, R.-J., Villanueva-Oller, J., & Díez-Domingo, J. (2011). Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia. Mathematical and Computer Modelling, 54(7-8), 1650-1654. doi:10.1016/j.mcm.2010.11.068Castellsagué, X., Iftner, T., Roura, E., Vidart, J. A., Kjaer, S. K., … Bosch, F. X. (2012). Prevalence and genotype distribution of human papillomavirus infection of the cervix in Spain: The CLEOPATRE study. Journal of Medical Virology, 84(6), 947-956. doi:10.1002/jmv.23282Cortés, J.-C., Colmenar, J.-M., Hidalgo, J.-I., Sánchez-Sánchez, A., Santonja, F.-J., & Villanueva, R.-J. (2016). Modeling and predicting the Spanish Bachillerato academic results over the next few years using a random network model. Physica A: Statistical Mechanics and its Applications, 442, 36-49. doi:10.1016/j.physa.2015.08.032Elbasha, E. H., Dasbach, E. J., & Insinga, R. P. (2007). Model for Assessing Human Papillomavirus Vaccination Strategies. Emerging Infectious Diseases, 13(1), 28-41. doi:10.3201/eid1301.060438González-Parra, G., Villanueva, R.-J., Ruiz-Baragaño, J., & Moraño, J.-A. (2015). Modelling influenza A(H1N1) 2009 epidemics using a random network in a distributed computing environment. Acta Tropica, 143, 29-35. doi:10.1016/j.actatropica.2014.12.008Khemka, N., & Jacob, C. (2010). Exploratory Toolkit for Evolutionary and Swarm-Based Optimization. The Mathematica Journal, 11(3), 376-391. doi:10.3888/tmj.11.3-

Epidemiology of respiratory syncytial virus associated acute lower respiratory infection in young children

Introduction Acute lower respiratory infection (ALRI) remains as a leading cause of childhood morbidity and mortality. With the continued universal vaccination campaign against bacterial pathogens, an increase in relative proportion of respiratory viruses contributing to ALRI is anticipated. Respiratory syncytial virus (RSV) has been recognised as the most common pathogen identified in young children presenting with ALRI as well as an important cause of hospital admission. This thesis aims to estimate the aetiological roles and attributable fractions of common respiratory viruses among ALRI cases and investigate the risk factors for RSV associated ALRI in young children. It also aims to estimate the global and regional incidence of RSV associated ALRI in both community and hospital based settings, and the possible boundaries for RSV associated ALRI mortality in children younger than five years old. Methods Systematic reviews were carried out separately for the following three research questions: aetiological roles of RSV and other common viruses in ALRI cases, risk factors for RSV associated ALRI and global/regional burden of RSV associated ALRI, formulating an overall picture of epidemiology of RSV associated ALRI in young children. They all focused on children younger than five years old. The identified studies were selected according to pre-defined inclusion and exclusion criteria. The whole process was conducted following the PRISMA guidelines for systematic review and meta-analysis. Unpublished data from RSV Global Estimates Network (RSV GEN) were collected from 45 leading researchers on paediatric pneumonia (primarily in developing countries). They either reanalysed data from their already published work with the pre-defined standardised case definitions or shared hitherto unpublished data from ongoing studies. Data from both systematic reviews and RSV GEN working group were included into further meta-analysis. Random effects model was consistently applied in all meta-analyses. Results There were 23 studies identified through literature search satisfying the eligibility criteria, investigated the viral aetiology of ALRI in young children. Strong evidence was observed for RSV in support of its causal contribution in children presenting with ALRI and the association was significant measured in odds ratio: 9.79 (4.98-19.27). Thus, the corresponding attributable fraction among the exposed was estimated as 90% (80%-95%), which means around 90% of RSV associated ALRI cases were in fact attributed to RSV in a causal path. In total, 27 studies (including 4 unpublished studies) were included and contributed to the analysis. Across these studies, 18 risk factors were described and 8 of them were observed to have significant associations with RSV infection: prematurity - gestational age <37 weeks, low birth weight (<2.5 kg), being male, having siblings, maternal smoking, history of atopy, no breastfeeding and crowding - >7 persons in household. Overall, 304 studies met the selection criteria and were included to estimate the global and regional burden of RSV associated ALRI in young children. These included 73 published articles identified through Chinese language databases and 76 unpublished studies provided by RSV GEN working group, mainly from developing countries. It is estimated that in 2015, there were 33.0 (95% CI 20.6-53.2) million episodes of RSV associated ALRI occurring in children younger than 5 years old across the world. 30.5 (95% CI 19.5-47.9) million of them were in developing countries. 3.0 (95% CI 2.2-4.0) million cases were severe enough and warranted hospitalisation. Around 60,000 children died in the hospital settings with 99% of these deaths occurring in developing countries. The overall mortality from RSV associated ALRI was estimated about 131,000. Conclusion This thesis not only enhanced the epidemiological understanding of RSV in young children, but also provided important information for public health decision makers. It incorporated both data through systematic reviews of published articles in the past 20 years and more than 70 unpublished data sets shared by RSV GEN working group. The population based incidence, hospitalisation, mortality and risk factor data are essential to assess the various severity of illness in a specific age group and region, and inform local public health professionals regarding appropriate and prompt cases management, prevention and vaccine allocation strategies. National sentinel systems of RSV surveillance gathering structured and reasonably representative data are needed. Within the surveillance system, a universal definition regarding disease severity in various settings should be developed, and diagnostic methods with higher sensitivity and specificity should be applied

Impact of a Gender-Neutral HPV Vaccination Program in Men Who Have Sex with Men (MSM)

[EN] A major challenge in human papillomavirus (HPV) vaccine programs is the universal gender-neutral recommendation, as well as estimation of its long-term effect. The objective of this study is to predict the added benefit of male vaccination, especially in men who have sex with men (MSM), and to analyze the impact of the program on society. We propose a mathematical model of the HPV infection based on a network paradigm. Data from Spain allowed constructing the sexual network. HPV force of infection was taken from literature. Different scenarios using variable vaccine coverage in both males and females were studied. Strong herd immunity is shown in the heterosexual population, with an important decrease of HPV 6/11 infections both in men and in unvaccinated women with an only-women vaccination at 14 years of age. No impact of this program occurred in the infection incidence in MSM. This group would only benefit from a vaccination program that includes males. However, the impact at short term would be lower than in heterosexual men. The protection of MSM can only be achieved by direct vaccination of males. This may have important consequences for public health.This paper has been supported by the Spanish Ministerio de Economía, Industria y Competitividad (MINECO), the Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P. This paper has been supported by the European Union through the Operational Program of the [European Regional Development Fund (ERDF)/European Social Fund (ESF)] of the Valencian Community 2014¿2020. Files: GJIDI/2018/A/010 and GJIDI/2018/A/009Diez-Domingo, J.; Sánchez-Alonso, V.; Villanueva Micó, RJ.; Acedo, L.; Tuells, J. (2021). Impact of a Gender-Neutral HPV Vaccination Program in Men Who Have Sex with Men (MSM). International Journal of Environmental research and Public Health (Online). 18(3):1-11. https://doi.org/10.3390/ijerph18030963S11118