Relevant bibliographies by topics / SIR infection model

Academic literature on the topic 'SIR infection model'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "SIR infection model"

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Lefèvre, Claude, and Matthieu Simon. "SIR epidemics with stages of infection." Advances in Applied Probability 48, no. 3 (September 2016): 768–91. http://dx.doi.org/10.1017/apr.2016.27.

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AbstractIn this paper we are concerned with a stochastic model for the spread of an epidemic in a closed homogeneously mixing population when an infective can go through several stages of infection before being removed. The transitions between stages are governed by either a Markov process or a semi-Markov process. An infective of any stage makes contacts amongst the population at the points of a Poisson process. Our main purpose is to derive the distribution of the final epidemic size and severity, as well as an approximation by branching, using simple matrix analytic methods. Some illustrations are given, including a model with treatment discussed by Gani (2006).
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WU, JIANJUN, ZIYOU GAO, and HUIJUN SUN. "SIMULATION OF TRAFFIC CONGESTION WITH SIR MODEL." Modern Physics Letters B 18, no. 30 (December 30, 2004): 1537–42. http://dx.doi.org/10.1142/s0217984904008031.

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The spread of traffic congestion is related to the rate of infection and the recovery rate. In this paper, we describe the traffic congestion spread with SIR model of a complex network. From the point of the complex network, the spread of the traffic congestion with different parameters are simulated. By simulation, we find that the behavior of the traffic system is tightly related to the average rate of infection, the average recovery rate and the topological properties of traffic network.
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Acemoglu, Daron, Victor Chernozhukov, Iván Werning, and Michael D. Whinston. "Optimal Targeted Lockdowns in a Multigroup SIR Model." American Economic Review: Insights 3, no. 4 (December 1, 2021): 487–502. http://dx.doi.org/10.1257/aeri.20200590.

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We study targeted lockdowns in a multigroup SIR model where infection, hospitalization, and fatality rates vary between groups—in particular between the “young,” the “middle-aged,” and the “old.” Our model enables a tractable quantitative analysis of optimal policy. For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter protective measures such as lockdowns on the more vulnerable, old group. Intuitively, a strict and long lockdown for the old both reduces infections and enables less strict lockdowns for the lower-risk groups. (JEL H51, I12, I18, J13, J14)
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Obolonkin, Vladimir, and Anatoly Zherelo. "Stochastic Generalization of the Epidemiological SIR Model." Nonlinear Phenomena in Complex Systems 24, no. 4 (December 10, 2021): 409–14. http://dx.doi.org/10.33581/1561-4085-2021-24-4-409-414.

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In this paper we propose stochastic modification of well-known in epidemiology SIR model. This modification allows us to simulate various scenarios of infection and can be used for the risk management.
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Dubey, Balram, Preeti Dubey, and Uma S. Dubey. "Role of media and treatment on an SIR model." Nonlinear Analysis: Modelling and Control 21, no. 2 (March 25, 2016): 185–200. http://dx.doi.org/10.15388/na.2016.2.3.

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n this paper, the impact of awareness programs as well as treatment on an SIR model has been investigated. We assume that the whole population is divided into four compartments, named as susceptible (S), infected (I), aware susceptible (Sa) and recovered (R). Analytical findings and numerical simulations of the model show that if the exposure to the awareness program is high and adequate treatment is available, then the infection can be eliminated. Analysis of the model also depicts that if treatment is not available, then infection is high even if enough awareness is present. But in absence of awareness an infection can not be eliminated inspite of adequate treatment. Effective treatment can led to a diminished level of infection. Stability analysis of the model is investigated by using stability theory of differential equations. Further, numerical simulations are carried out to validate the analytical results.
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JIN, ZHEN, MAINUL HAQUE, and QUANXING LIU. "PULSE VACCINATION IN THE PERIODIC INFECTION RATE SIR EPIDEMIC MODEL." International Journal of Biomathematics 01, no. 04 (December 2008): 409–32. http://dx.doi.org/10.1142/s1793524508000370.

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In this paper a pulse vaccination SIR model with periodic infection rate β(t) is studied. The basic reproductive number R0 is defined. The dynamical behavior of the model is analyzed. It is proved that the infection-free periodic solution is globally stable if R0 < 1. The infection-free periodic solution is unstable and the disease will uniform persistence when R0 > 1. We use standard bifurcation theory to show the existence of the positive periodic solution when R0 → 1+. Numerical simulation can give suggestion, the system has a unique positive periodic, and it is globally stable when R0 > 1.
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Liu, Ting, Yanling Bai, Mingmei Du, Yueming Gao, and Yunxi Liu. "Susceptible-Infected-Removed Mathematical Model under Deep Learning in Hospital Infection Control of Novel Coronavirus Pneumonia." Journal of Healthcare Engineering 2021 (October 27, 2021): 1–11. http://dx.doi.org/10.1155/2021/1535046.

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Objective. This research aimed to explore the application of a mathematical model based on deep learning in hospital infection control of novel coronavirus (COVID-19) pneumonia. Methods. First, the epidemic data of Beijing, China, were utilized to make a definite susceptible-infected-removed (SIR) model fitting to determine the estimated value of the COVID-19 removal intensity β, which was then used to do a determined SIR model and a stochastic SIR model fitting for the hospital. In addition, the reasonable β and γ estimates of the hospital were determined, and the spread of the epidemic in hospital was simulated, to discuss the impact of basal reproductive number changes, isolation, vaccination, and so forth on COVID-19. Results. There was a certain gap between the fitting of SIR to the remover and the actual data. The fitting of the number of infections was accurate. The growth rate of the number of infections decreased after measures, such as isolation, were taken. The effect of herd immunity was achieved after the overall immunity reached 70.9%. Conclusion. The SIR model based on deep learning and the stochastic SIR fitting model were accurate in judging the development trend of the epidemic, which can provide basis and reference for hospital epidemic infection control.
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Jing, Wenjun, Zhen Jin, and Juping Zhang. "An SIR pairwise epidemic model with infection age and demography." Journal of Biological Dynamics 12, no. 1 (January 1, 2018): 486–508. http://dx.doi.org/10.1080/17513758.2018.1475018.

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Ichinose, Toshiaki, Danhe Tian, and Yifeng Li. "Verification of Infection Prevention Control Using a Spatial Random Walk Model." International Journal of Social Science Studies 8, no. 6 (September 29, 2020): 35. http://dx.doi.org/10.11114/ijsss.v8i6.4955.

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To stop pandemic of the 2019 novel coronavirus (COVID-19), "an 80 percent reduction of person to person contact opportunities" was proposed by the Japanese government. This guideline was based on the result of macroscopic differential equation model akin to the SIR (Susceptible-Infected-Recovered) model. For the purpose of indicating person to person’s infection mechanism intuitively, we built a new model to calculate infections between two persons who are in contact each other. This model adopted a spatial random walk model to express random movement of people in a specific 2-D geographical space. This model was applied to verify the effect of the proposed infection control procedure, "80 percent reduction". The result of the numerical simulation supported a proposed infection control procedure of "an 80 percent reduction" derived by the SIR model.
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Sagar, Surendra Kumar. "SIR-SI Mathematical Model for Zika Virus Progression Dynamics in India: A Case Study." Journal of Communicable Diseases 53, no. 02 (June 30, 2021): 100–104. http://dx.doi.org/10.24321/0019.5138.202132.

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Viral diseases are very hazardous for humanity because in the case of most viral diseases, drugs are not effective. At present, the whole world is living with the fear of COVID-19. From time to time, several viral diseases have been troubling human life. In this article, we have tried to capture the progression dynamics of Zika Virus (ZIKV) infection in the Indian scenario. A constructed model is based on compartment modelling. In the model, Susceptible-Infected-Recovered (SIR) structure is used for the human population and Susceptible-Infected (SI) structure is used for mosquito population. The value of the basic reproduction number (R0) is computed 0.36 at baseline values of parameters involved in the model. The lower value of R0 suggests that infection was unable to spread in the human population. Sensitive analysis for R0 revealed that the most accountable parameter in the spread of infection was mosquito biting rate. The modelling technique might be useful for other diseases also.
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Dissertations / Theses on the topic "SIR infection model"

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Medlock, Jan P. "The effect of stochastic migration on an SIR model for the transmission of HIV." Thesis, Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/30547.

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Smailhodzic, Armin. "Adapting the Standard SIR Disease Model in Order to Track and Predict the Spreading of the EBOLA Virus Using Twitter Data." TopSCHOLAR®, 2015. http://digitalcommons.wku.edu/theses/1465.

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A method has been developed to track infectious diseases by using data mining of active Twitter accounts and its efficacy was demonstrated during the West African Ebola outbreak of 2014. Using a meme based n-gram semantic usage model to search the Twitter database for indications of illness, flight and death from the spread of Ebola in Africa, principally from Guinea, Sierra Leone and Liberia. Memes of interest relate disease to location and severity and are coupled to the density of Tweets and re-Tweets. The meme spreads through the community of social users in a fashion similar to nonlinear wave propagation- like a shock wave, visualized as a spike in Tweet activity. The spreading was modeled as a system isomorphic to a modified SIR (Susceptible, Infected, Removed disease model) system of three coupled nonlinear differential equations using Twitter variables. The nonlinear terms in this model lead to feedback mechanisms that result in unusual behavior that does not always reduce the spread of the disease. The resulting geographic Tweet densities are coupled to geographic maps of the region. These maps have specific threat levels that are ported to a mobile application (app) and can be used by travelers to assess the relative safety of the region they will be in.
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Siddiqui, Sameeha Qaiser. "Backward bifurcation in SIR endemic models : this thesis is presented in partial fulfillment of the requirements for the degree of Masters of Information Science in Mathematics at Massey University, Albany, Auckland, New Zealand." Massey University, 2008. http://hdl.handle.net/10179/929.

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In the well known SIR endemic model, the infection-free steady state is globally stable for R0 < 1 and unstable for R0 > 1. Hence, we have a forward bifurcation when R0 = 1. When R0 > 1, an asymptotically stable endemic steady state exists. The basic reproduction number R0 is the main threshold bifurcation parameter used to determine the stability of steady states of SIR endemic models. In this thesis we study extensions of the SIR endemic model for which a backward bifurcation may occur at R0 = 1. We investigate the biologically reasonable conditions for the change of stability. We also analyse the impact of di erent factors that lead to a backward bifurcation both numerically and analytically. A backward bifurcation leads to sub-critical endemic steady states and hysteresis. We also provide a general classi cation of such models, using a small amplitude expansion near the bifurcation. Additionally, we present a procedure for projecting three dimensional models onto two dimensional models by applying some linear algebraic techniques. The four extensions examined are: the SIR model with a susceptible recovered class; nonlinear transmission; exogenous infection; and with a carrier class. Numerous writers have mentioned that a nonlinear transmission function in relation to the infective class, can only lead to a system with an unstable endemic steady state. In spite of this we show that in a nonlinear transmission model, we have a function depending on the infectives and satisfying certain biological conditions, and leading to a sub-critical endemic equilibriums.
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Marmara, Vincent Anthony. "Prediction of Infectious Disease outbreaks based on limited information." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/24624.

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The last two decades have seen several large-scale epidemics of international impact, including human, animal and plant epidemics. Policy makers face health challenges that require epidemic predictions based on limited information. There is therefore a pressing need to construct models that allow us to frame all available information to predict an emerging outbreak and to control it in a timely manner. The aim of this thesis is to develop an early-warning modelling approach that can predict emerging disease outbreaks. Based on Bayesian techniques ideally suited to combine information from different sources into a single modelling and estimation framework, I developed a suite of approaches to epidemiological data that can deal with data from different sources and of varying quality. The SEIR model, particle filter algorithm and a number of influenza-related datasets were utilised to examine various models and methodologies to predict influenza outbreaks. The data included a combination of consultations and diagnosed influenza-like illness (ILI) cases for five influenza seasons. I showed that for the pandemic season, different proxies lead to similar behaviour of the effective reproduction number. For influenza datasets, there exists a strong relationship between consultations and diagnosed datasets, especially when considering time-dependent models. Individual parameters for different influenza seasons provided similar values, thereby offering an opportunity to utilise such information in future outbreaks. Moreover, my findings showed that when the temperature drops below 14°C, this triggers the first substantial rise in the number of ILI cases, highlighting that temperature data is an important signal to trigger the start of the influenza epidemic. Further probing was carried out among Maltese citizens and estimates on the under-reporting rate of the seasonal influenza were established. Based on these findings, a new epidemiological model and framework were developed, providing accurate real-time forecasts with a clear early warning signal to the influenza outbreak. This research utilised a combination of novel data sources to predict influenza outbreaks. Such information is beneficial for health authorities to plan health strategies and control epidemics.
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Teissier, Yoann. "Metapopulation dynamics of dengue epidemics in French Polynesia." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB008.

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La dengue circule en Polynésie française sur un mode épidémique depuis plus de 35 ans. Néanmoins, en dépit de la taille relativement faible de la population de Polynésie française, la circulation de la dengue peut persister à de faibles niveaux pendant de nombreuses années. L’objectif de ce travail de thèse est de déterminer si l'épidémiologie de la dengue dans le système insulaire de la Polynésie française répond aux critères d’un contexte de métapopulation. Après avoir constitué une base de données regroupant les cas de dengue répertoriés sur les 35 dernières années, nous avons réalisé des analyses épidémiologiques descriptives et statistiques. Celles-ci ont révélé des disparités spatio-temporelles distinctes pour l’incidence de la dengue des archipels et des îles, mais la structure de l'épidémie globale à l’échelle de la Polynésie française pour un même sérotype ne semble pas être affectée. Les analyses de la métapopulation ont révélé l'incidence asynchrone de la dengue dans un grand nombre d’îles. Celle-ci s’observe plus particulièrement par la différence de dynamique de l’incidence entre les îles plus peuplées et celles ayant une population plus faible. La taille critique de la communauté nécessaire à la persistance de la dengue n’est même pas atteinte par la plus grande île de Polynésie Française, Tahiti. Ce résultat suggère que la dengue peut uniquement persister grâce à sa propagation d’île en île. L'incorporation de la connectivité des îles à travers des modèles de migration humaine dans un modèle mathématique a produit une dynamique de la dengue davantage en adéquation avec les données observées, que les tentatives de modélisation traitant la population dans son ensemble. Le modèle de la métapopulation a été capable de simuler la même dynamique que les cas de dengue observés pour l'épidémie et la transmission endémique qui a suivi pour la période de 2001 à 2008. Des analyses complémentaires sur la différenciation de l'incidence de la maladie et de l'infection seront probablement instructives pour affiner le modèle de métapopulation de l'épidémiologie de la dengue en Polynésie française
Dengue has been epidemic in French Polynesia for the past 35 years. Despite the relatively small population size in French Polynesia, dengue does not disappear and can persist at low levels for many years. In light of the large number of islands comprising French Polynesia, this thesis addresses the extent to which a metapopulation context may be the most appropriate to describe the epidemiology and persistence of dengue in this case. After compiling a database of dengue cases over the last 35 years, we used a number of descriptive and statistical epidemiological analyses that revealed distinct spatio-temporal disparity in dengue incidence for archipelago and islands. But the global structure of the epidemics of the same serotype were not affected. Metapopulation analyses revealed asynchronous dengue incidence among many of the islands and most notably larger islands lagged behind the smaller islands. The critical community size, which determines dengue persistence, was found to exceed even the largest island of Tahiti, suggesting that dengue can only exist by island-hopping. Incorporation of island connectedness through patterns of human migration into a mathematical model enabled a much better fit to the observed data than treating the population as a whole. The metapopulation model was able to capture to some extent the epidemic and low level transmission dynamics observed for the period of 2001-2008. Further analyses on differentiating incidence of disease and infection will likely prove informative for the metapopulation model of dengue epidemiology in French Polynesia
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Ballard, Peter Geoffrey. "Epidemic fade-out in the Markovian SIR-with-demography infection model." Thesis, 2018. http://hdl.handle.net/2440/118214.

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“Epidemic fade-out” refers to the situation in which an infection is eliminated after an initial major wave of infection. This thesis by publication contains three papers (two published, the third submitted and under review) on the subject of epidemic fade-out in the Markovian SIR-with-demography infection model. The first paper [6] surveys previous work containing methods for approximating the probability of epidemic fade-out, then proposes a numerical method which is more accurate. Using this method, it surveys trends over a range of parameters, and observes that the probability of epidemic fade-out has a non-monotonic relationship with respect to β, the transmission rate parameter. It shows that this probability often has a local maximum where R0, the basic reproduction number, is about 2; and gives an explanation for this phenomenon. The second paper [7] examines the possibility of controlling β, in order to maximise the probability of epidemic fade-out. An optimal policy may be found using Markov decision theory, but this requires very large data structures, meaning this is impractical for all but very small population sizes. So the paper also derives a simple formula for an almost-optimal policy, which can be applied for any population size, and is independent of the values of β. The third paper [8] extends the Markovian SIR-with-demography infection model to allow β to be time dependent, as the transmission rate may vary with the time of year. It also extends the work to the Markovian SIRS model. It presents an algorithm for calculating the probability of epidemic fade-out for these models, and considers parameters appropriate to influenza-like and measles-like infections. It concludes that the local maximum in the probability of epidemic fade-out is at a value of R0 somewhat greater than 2, when β is time-dependent.
Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2018
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Huang, Tai-wei, and 黃泰瑋. "A mathematical model for infectious diseases -- an extended SIR model." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/48121779840428569974.

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碩士
國立高雄大學
應用數學系碩士班
96
The model studies the outbreak of an infectious disease which is not transmissible between humans until the virus has mutated. An extended SIR model is derived in which both the susceptibles and the infectives are divided into two classes. The analysis points out a time delay before the disease taking off. Epidemic size and the maximum level of the infectives are also estimated. The model is further extended to investigate the efficiency of quarantine and vaccination schemes for controlling the effect of the disease.
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Gameiro, Sofia Ribeiro. "Pulmonary delivery of liposome-based vaccines application to a murine model of Schistosoma mansoni infection /." 2008. http://proquest.umi.com/pqdweb?did=1546799171&sid=10&Fmt=2&clientId=39334&RQT=309&VName=PQD.

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Thesis (Ph.D.)--State University of New York at Buffalo, 2008.
Title from PDF title page (viewed on Dec. 3, 2008) Available through UMI ProQuest Digital Dissertations. Thesis adviser: Straubinger, Robert M. Includes bibliographical references.
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Smolenski, Derek Joseph Risser Jan Mary Hale Stigler Melissa H. Diamond Pamela M. "The application of latent variable models to the assessment of determinants of HIV risk behavior /." 2009. http://proquest.umi.com.www5.sph.uth.tmc.edu:2048/pqdweb?did=1692359551&sid=3&Fmt=2&clientId=92&RQT=309&VName=PQD.

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Books on the topic "SIR infection model"

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7.

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Jadeja, Mahipal, Vikrant Bhateja, and Rahul Saxena. Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation. Springer, 2022.

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Bianconi, Ginestra. Epidemic Spreading. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0013.

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Epidemic processes are relevant to studying the propagation of infectious diseases, but their current use extends also to the study of propagation of ideas in the society or memes and news in online social media. In most of the relevant applications epidemic spreading does not actually take place on a single network but propagates in a multilayer network where different types of interaction play different roles. This chapter provides a comprehensive view of the effect that multilayer network structures have on epidemic processes. The Susceptible–Infected–Susceptible (SIS) Model and the Susceptible–Infected–Removed (SIR) Model are characterized on multilayer networks. Additionally, it is shown that the multilayer networks framework can also allow us to study interacting Awareness and epidemic spreading, competing networks and epidemics in temporal networks.
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Book chapters on the topic "SIR infection model"

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Srinivas, M. N., B. S. N. Murthy, M. A. S. Srinivas, and M. Naga Raju. "Modeling Simulation of SIR PC Infection Spreading Model with Fuzzy Parameters." In Communication and Intelligent Systems, 1119–35. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2130-8_86.

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Liu, Xinzhi, and Peter Stechlinski. "The Switched SIR Model." In Infectious Disease Modeling, 43–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53208-0_3.

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Gandolfi, Alberto. "Percolation Methods for SEIR Epidemics on Graphs." In Dynamic Models of Infectious Diseases, 31–58. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9224-5_2.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Epidemic Studies and Mathematical Setup of SIR Model." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 5–12. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_2.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "SIR Model-Based Experimental Investigations over Covid-19." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 19–27. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_4.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Result Analysis of SIR-Based Covid-19 Model." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 29–35. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_5.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Exploring Covid-19 Second Wave Dynamics Using SIR Epidemic Model." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 37–50. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_6.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Understanding and Analysing the Spread Pattern of Covid-19." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 13–18. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_3.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Introduction." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 1–4. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_1.

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Saxena, Rahul, Mahipal Jadeja, and Vikrant Bhateja. "Conclusions and Future Scope." In Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation, 51–52. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4175-7_7.

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Conference papers on the topic "SIR infection model"

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Ushirobira, Rosane, Denis Efimov, and Pierre-Alexandre Blirnan. "Estimating the infection rate of a SIR epidemic model via differential elimination." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8795991.

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Yang, Junyuan, Fengqin Zhang, and Xiaoyan Wang. "A class of SIR epidemic model with saturation incidence and age of infection." In Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007). IEEE, 2007. http://dx.doi.org/10.1109/snpd.2007.74.

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Yang, Junyuan, Fengqin Zhang, and Xiaoyan Wang. "A Class of SIR Epidemic Model with Saturation Incidence and Age of Infection." In 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing. IEEE, 2008. http://dx.doi.org/10.1109/snpd.2008.150.

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Khorev, Vladimir, and Victor B. Kazantsev. "Factor of border crossing limitation with an infection hub in the SIR covid model." In 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA). IEEE, 2021. http://dx.doi.org/10.1109/dcna53427.2021.9586890.

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Yang, Fan, and Jian Zhang. "SIR Evolutionary Simulation Model of the Infectious Disease Emergency." In 2015 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII). IEEE, 2015. http://dx.doi.org/10.1109/iciicii.2015.153.

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Tao, Ji. "Ebola Infectious Model Based on SEIR." In 2015-1st International Symposium on Social Science. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/isss-15.2015.70.

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Liu, Luju, Weiyun Cai, and Shifei Wang. "Global Stability for an SIR Infectious Diseases Model with Dispersal." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.81.

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Darapaneni, Narayana, Arjun Panwar, Anwesh Reddy Paduri, Ankit Patel, Chaitanya Shah, Jigar Gada, and Milind Majrekar. "COVID-19 Infection Dynamics for India-Forecasting the Disease using SIR models." In 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2020. http://dx.doi.org/10.1109/iciis51140.2020.9342660.

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Zhai, Yiming, Yifan Liu, Ning Ding, Zhenyu Fan, and Guosheng Fang. "Improved SEIR model based on asymptomatic infection of COVID-19." In 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE). IEEE, 2021. http://dx.doi.org/10.1109/aemcse51986.2021.00135.

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Yang, Guang. "Isolate Control for a SIR Model With Nonlinear Saturation Infectious Force." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5162989.

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Reports on the topic "SIR infection model"

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Berger, David, Kyle Herkenhoff, and Simon Mongey. An SEIR Infectious Disease Model with Testing and Conditional Quarantine. Cambridge, MA: National Bureau of Economic Research, March 2020. http://dx.doi.org/10.3386/w26901.

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Eldar, Avigdor, and Donald L. Evans. Streptococcus iniae Infections in Trout and Tilapia: Host-Pathogen Interactions, the Immune Response Toward the Pathogen and Vaccine Formulation. United States Department of Agriculture, December 2000. http://dx.doi.org/10.32747/2000.7575286.bard.

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In Israel and in the U.S., Streptococcus iniae is responsible for considerable losses in various fish species. Poor understanding of its virulence factors and limited know-how-to of vaccine formulation and administration are the main reasons for the limited efficacy of vaccines. Our strategy was that in order to Improve control measures, both aspects should be equally addressed. Our proposal included the following objectives: (i) construction of host-pathogen interaction models; (ii) characterization of virulence factors and immunodominant antigens, with assessment of their relative importance in terms of protection and (iii) genetic identification of virulence factors and genes, with evaluation of the protective effect of recombinant proteins. We have shown that two different serotypes are involved. Their capsular polysaccharides (CPS) were characterized, and proved to play an important role in immune evasion and in other consequences of the infection. This is an innovative finding in fish bacteriology and resembles what, in other fields, has become apparent in the recent years: S. iniae alters surface antigens. By so doing, the pathogen escapes immune destruction. Immunological assays (agar-gel immunodiffusion and antibody titers) confirmed that only limited cross recognition between the two types occurs and that capsular polysaccharides are immunodominant. Vaccination with purified CPS (as an acellular vaccine) results in protection. In vitro and ex-vivo models have allowed us to unravel additional insights of the host-pathogen interactions. S. iniae 173 (type II) produced DNA fragmentation of TMB-8 cells characteristic of cellular necrosis; the same isolate also prevented the development of apoptosis in NCC. This was determined by finding reduced expression of phosphotidylserine (PS) on the outer membrane leaflet of NCC. NCC treated with this isolate had very high levels of cellular necrosis compared to all other isolates. This cellular pathology was confirmed by observing reduced DNA laddering in these same treated cells. Transmission EM also showed characteristic necrotic cellular changes in treated cells. To determine if the (in vitro) PCD/apoptosis protective effects of #173 correlated with any in vivo activity, tilapia were injected IV with #173 and #164 (an Israeli type I strain). Following injection, purified NCC were tested (in vitro) for cytotoxicity against HL-60 target cells. Four significant observations were made : (i) fish injected with #173 had 100-400% increased cytotoxicity compared to #164 (ii) in vivo activation occurred within 5 minutes of injection; (iii) activation occurred only within the peripheral blood compartment; and (iv) the isolate that protected NCC from apoptosis in vitro caused in vivo activation of cytotoxicity. The levels of in vivo cytotoxicity responses are associated with certain pathogens (pathogen associated molecular patterns/PAMP) and with the tissue of origin of NCC. NCC from different tissue (i.e. PBL, anterior kidney, spleen) exist in different states of differentiation. Random amplified polymorphic DNA (RAPD) analysis revealed the "adaptation" of the bacterium to the vaccinated environment, suggesting a "Darwinian-like" evolution of any bacterium. Due to the selective pressure which has occurred in the vaccinated environment, type II strains, able to evade the protective response elicited by the vaccine, have evolved from type I strains. The increased virulence through the appropriation of a novel antigenic composition conforms with pathogenic mechanisms described for other streptococci. Vaccine efficacy was improved: water-in-oil formulations were found effective in inducing protection that lasted for a period of (at least) 6 months. Protection was evaluated by functional tests - the protective effect, and immunological parameters - elicitation of T- and B-cells proliferation. Vaccinated fish were found to be resistant to the disease for (at least) six months; protection was accompanied by activation of the cellular and the humoral branches.
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Shpigel, Nahum, Raul Barletta, Ilan Rosenshine, and Marcelo Chaffer. Identification and characterization of Mycobacterium paratuberculosis virulence genes expressed in vivo by negative selection. United States Department of Agriculture, January 2004. http://dx.doi.org/10.32747/2004.7696510.bard.

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Mycobacterium avium subsp. paratuberculosis (MAP) is the etiological agent of a severe inflammatory bowel disease (IBD) in ruminants, known as Johne’s disease or paratuberculosis. Johne’s disease is considered to be one of the most serious diseases affecting dairy cattle both in Israel and worldwide. Heavy economic losses are incurred by dairy farmers due to the severe effect of subclinical infection on milk production, fertility, lower disease resistance and early culling. Its influence in the United States alone is staggering, causing an estimated loss of $1.5 billion to the agriculture industry every year. Isolation of MAP from intestinal tissue and blood of Crohn's patients has lead to concern that it plays a potential pathogenic role in promoting human IDB including Crohn’s disease. There is great concern following the identification of the organism in animal products and shedding of the organism to the environment by subclinically infected animals. Little is known about the molecular basis for MAP virulence. The goal of the original proposed research was to identify MAP genes that are required for the critical stage of initial infection and colonization of ruminants’ intestine by MAP. We proposed to develop and use signature tag mutagenesis (STM) screen to find MAP genes that are specifically required for survival in ruminants upon experimental infection. This research projected was approved as one-year feasibility study to prove the ability of the research team to establish the animal model for mutant screening and alternative in-vitro cell systems. In Israel, neonatal goat kids were repeatedly inoculated with either one of the following organisms; MAP K-10 strain and three transposon mutants of K-10 which were produced and screened by the US PI. Six months after the commencement of inoculation we have necropsied the goats and taken multiple tissue samples from the jejunum, ileum and mesenteric lymph nodes. Both PCR and histopathology analysis indicated on efficient MAP colonization of all the inoculated animals. We have established several systems in the Israeli PI’s laboratory; these include using IS900 PCR for the identification of MAP and using HSP65-based PCR for the differentiation between MAV and MAP. We used Southern blot analysis for the differentiation among transposon mutants of K-10. In addition the Israeli PI has set up a panel of in-vitro screening systems for MAP mutants. These include assays to test adhesion, phagocytosis and survival of MAP to/within macrophages, assays that determine the rate of MAPinduced apoptosis of macrophages and MAP-induced NO production by macrophages, and assays testing the interference with T cell ã Interferon production and T cell proliferation by MAP infected macrophages (macrophage studies were done in BoMac and RAW cell lines, mouse peritoneal macrophages and bovine peripheral blood monocytes derived macrophages, respectively). All partners involved in this project feel that we are currently on track with this novel, highly challenging and ambitious research project. We have managed to establish the above described research systems that will clearly enable us to achieve the original proposed scientific objectives. We have proven ourselves as excellent collaborative groups with very high levels of complementary expertise. The Israeli groups were very fortunate to work with the US group and in a very short time period to master numerous techniques in the field of Mycobacterium research. The Israeli group has proven its ability to run this complicated animal model. This research, if continued, may elucidate new and basic aspects related to the pathogenesis MAP. In addition the work may identify new targets for vaccine and drug development. Considering the possibility that MAP might be a cause of human Crohn’s disease, better understanding of virulence mechanisms of this organism might also be of public health interest as well.
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Shpigel, Nahum Y., Ynte Schukken, and Ilan Rosenshine. Identification of genes involved in virulence of Escherichia coli mastitis by signature tagged mutagenesis. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7699853.bard.

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Mastitis, an inflammatory response of the mammary tissue to invading pathogenic bacteria, is the largest health problem in the dairy industry and is responsible for multibillion dollar economic losses. E. coli are a leading cause of acute mastitis in dairy animals worldwide and certainly in Israel and North America. The species E. coli comprises a highly heterogeneous group of pathogens, some of which are commensal residents of the gut, infecting the mammary gland after contamination of the teat skin from the environment. As compared to other gut microflora, mammary pathogenic E. coli (MPEC) may have undergone evolutionary adaptations that improve their fitness for colonization of the unique and varied environmental niches found within the mammary gland. These niches include competing microbes already present or accompanying the new colonizer, soluble and cellular antimicrobials in milk, and the innate immune response elicited by mammary cells and recruited immune cells. However, to date, no specific virulence factors have been identified in E. coli isolates associated with mastitis. The original overall research objective of this application was to develop a genome-wide, transposon-tagged mutant collection of MPEC strain P4 and to use this technology to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. In the course of the project we decided to take an alternative genome-wide approach and to use whole genomes bioinformatics analysis. Using genome sequencing and analysis of six MPEC strains, our studies have shown that type VI secretion system (T6SS) gene clusters were present in all these strains. Furthermore, using unbiased screening of MPEC strains for reduced colonization, fitness and virulence in the murine mastitis model, we have identified in MPEC P4-NR a new pathogenicity island (PAI-1) encoding the core components of T6SS and its hallmark effectors Hcp, VgrG and Rhs. Next, we have shown that specific deletions of T6SS genes reduced colonization, fitness and virulence in lactating mouse mammary glands. Our long-term goal is to understand the molecular mechanisms of host-pathogen interactions in the mammary gland and to relate these mechanisms to disease processes and pathogenesis. We have been able to achieve our research objectives to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. The project elucidated a new basic concept in host pathogen interaction of MPEC, which for the best of our knowledge was never described or investigated before. This research will help us to shed new light on principles behind the infection strategy of MPEC. The new targets now enable prevalence and epidemiology studies of T6SS in field strains of MPEC which might unveil new geographic, management and ecological risk factors. These will contribute to development of new approaches to treat and prevent mastitis by MPEC and perhaps other mammary pathogens. The use of antibiotics in farm animals and specifically to treat mastitis is gradually precluded and thus new treatment and prevention strategies are needed. Effective mastitis vaccines are currently not available, structural components and effectors of T6SS might be new targets for the development of novel vaccines and therapeutics.
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Dickman, Martin B., and Oded Yarden. Role of Phosphorylation in Fungal Spore Germination. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568761.bard.

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Spore germination is a common and fundamental event in fungal development and in many instances an essential phase of fungal infection and dissemination. Spore germination is also critical for hyperparasites to function as biocontrol agents as well as in fermentation proceses. Our common objective is to understand the mechanisms which regulated spore germination and identify factors involved in pathogenicity related prepenetration development. Our approach is to exploit the overall similarity among filamentous fungi using both a plant pathogen (Colletotricum trifolii) and a model system that is genetically sophisticated (Neurospora crassa). The simulataneous use of two organisms has the advantage of the available tools in Neurospora to rapidly advance the functional analysis of genes involved in spore germination and development of an economically important fungal phytopathogen. Towards this we have isolated a protein kinase gene from C. trifolii (TB3) that is maximally expressed during the first hour of conidial germination and prior to any visible gene tube formation. Based on sequence similarities with other organisms, this gene is likely to be involved in the proliferative response in the fungus. In addition, TB3 was able to functionally complement a N. crassa mutant (COT-1). Pharmacological studies indicated the importance of calmodulin in both germination and appressorium differentiation. Using an antisense vector from N. crassa, direct inhibition of calmodulin results in prevention of differentiation as well as pathogenicity. Both cAMP dependent protein kinase (PKA) and protein kinase C (PKC) like genes have been cloned from C. trifolii. Biochemical inhibition of PKA prevents germination; biochemical inhibitors of PKC prevents appressorium differentiation. In order to analyze reversible phosphorylation as a regulatory mechanism, some ser.thr dephosphorylative events have also been analyzed. Type 2A and Type 2B (calcineurin) phosphatases have been identified and structurally and functionally analyzed in N. crassa during this project. Both phosphatases are essential for hyphal growth and maintenance of proper hyphal architecture. In addition, a first novel-type (PPT/PP5-like) ser/thr phosphatase has been identified in a filamentous fungus. The highly collaborative project has improved our understanding of a fundamental process in fungi, and has identified targets which can be used to develop new approaches for control of fungal plant pathogens as well as improve the performance of beneficial fungi in the field and in industry. In addition, the feasibility of molecular technology transfer in comparative mycology has been demonstrated.
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Hajarizadeh, Behzad, Jennifer MacLachlan, Benjamin Cowie, and Gregory J. Dore. Population-level interventions to improve the health outcomes of people living with hepatitis B: an Evidence Check brokered by the Sax Institute for the NSW Ministry of Health, 2022. The Sax Institute, August 2022. http://dx.doi.org/10.57022/pxwj3682.

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Background An estimated 292 million people are living with chronic hepatitis B virus (HBV) infection globally, including 223,000 people in Australia. HBV diagnosis and linkage of people living with HBV to clinical care is suboptimal in Australia, with 27% of people living with HBV undiagnosed and 77% not receiving regular HBV clinical care. This systematic review aimed to characterize population-level interventions implemented to enhance all components of HBV care cascade and analyse the effectiveness of interventions. Review questions Question 1: What population-level interventions, programs or policy approaches have been shown to be effective in reducing the incidence of hepatitis B; and that may not yet be fully rolled out or evaluated in Australia demonstrate early effectiveness, or promise, in reducing the incidence of hepatitis B? Question 2: What population-level interventions and/or programs are effective at reducing disease burden for people in the community with hepatitis B? Methods Four bibliographic databases and 21 grey literature sources were searched. Studies were eligible for inclusion if the study population included people with or at risk of chronic HBV, and the study conducted a population-level interventions to decrease HBV incidence or disease burden or to enhance any components of HBV care cascade (i.e., diagnosis, linkage to care, treatment initiation, adherence to clinical care), or HBV vaccination coverage. Studies published in the past 10 years (since January 2012), with or without comparison groups were eligible for inclusion. Studies conducting an HBV screening intervention were eligible if they reported proportion of people participating in screening, proportion of newly diagnosed HBV (participant was unaware of their HBV status), proportion of people received HBV vaccination following screening, or proportion of participants diagnosed with chronic HBV infection who were linked to HBV clinical care. Studies were excluded if study population was less than 20 participants, intervention included a pharmaceutical intervention or a hospital-based intervention, or study was implemented in limited clinical services. The records were initially screened by title and abstract. The full texts of potentially eligible records were reviewed, and eligible studies were selected for inclusion. For each study included in analysis, the study outcome and corresponding 95% confidence intervals (95%CIs) were calculated. For studies including a comparison group, odds ratio (OR) and corresponding 95%CIs were calculated. Random effect meta-analysis models were used to calculate the pooled study outcome estimates. Stratified analyses were conducted by study setting, study population, and intervention-specific characteristics. Key findings A total of 61 studies were included in the analysis. A large majority of studies (study n=48, 79%) included single-arm studies with no concurrent control, with seven (12%) randomised controlled trials, and six (10%) non-randomised controlled studies. A total of 109 interventions were evaluated in 61 included studies. On-site or outreach HBV screening and linkage to HBV clinical care coordination were the most frequent interventions, conducted in 27 and 26 studies, respectively. Question 1 We found no studies reporting HBV incidence as the study outcome. One study conducted in remote area demonstrated that an intervention including education of pregnant women and training village health volunteers enhanced coverage of HBV birth dose vaccination (93% post-intervention, vs. 81% pre-intervention), but no data of HBV incidence among infants were reported. Question 2 Study outcomes most relevant to the HBV burden for people in the community with HBV included, HBV diagnosis, linkage to HBV care, and HBV vaccination coverage. Among randomised controlled trials aimed at enhancing HBV screening, a meta-analysis was conducted including three studies which implemented an intervention including community face-to-face education focused on HBV and/or liver cancer among migrants from high HBV prevalence areas. This analysis demonstrated a significantly higher HBV testing uptake in intervention groups with the likelihood of HBV testing 3.6 times higher among those participating in education programs compared to the control groups (OR: 3.62, 95% CI 2.72, 4.88). In another analysis, including 25 studies evaluating an intervention to enhance HBV screening, a pooled estimate of 66% of participants received HBV testing following the study intervention (95%CI: 58-75%), with high heterogeneity across studies (range: 17-98%; I-square: 99.9%). A stratified analysis by HBV screening strategy demonstrated that in the studies providing participants with on-site HBV testing, the proportion receiving HBV testing (80%, 95%CI: 72-87%) was significantly higher compared to the studies referring participants to an external site for HBV testing (54%, 95%CI: 37-71%). In the studies implementing an intervention to enhance linkage of people diagnosed with HBV infection to clinical care, the interventions included different components and varied across studies. The most common component was post-test counselling followed by assistance with scheduling clinical appointments, conducted in 52% and 38% of the studies, respectively. In meta-analysis, a pooled estimate of 73% of people with HBV infection were linked to HBV clinical care (95%CI: 64-81%), with high heterogeneity across studies (range: 28-100%; I-square: 99.2%). A stratified analysis by study population demonstrated that in the studies among general population in high prevalence countries, 94% of people (95%CI: 88-100%) who received the study intervention were linked to care, significantly higher than 72% (95%CI: 61-83%) in studies among migrants from high prevalence area living in a country with low prevalence. In 19 studies, HBV vaccination uptake was assessed after an intervention, among which one study assessed birth dose vaccination among infants, one study assessed vaccination in elementary school children and 17 studies assessed vaccination in adults. Among studies assessing adult vaccination, a pooled estimate of 38% (95%CI: 21-56%) of people initiated vaccination, with high heterogeneity across studies (range: 0.5-93%; I square: 99.9%). A stratified analysis by HBV vaccination strategy demonstrated that in the studies providing on-site vaccination, the uptake was 78% (95%CI: 62-94%), significantly higher compared to 27% (95%CI: 13-42%) in studies referring participants to an external site for vaccination. Conclusion This systematic review identified a wide variety of interventions, mostly multi-component interventions, to enhance HBV screening, linkage to HBV clinical care, and HBV vaccination coverage. High heterogeneity was observed in effectiveness of interventions in all three domains of screening, linkage to care, and vaccination. Strategies identified to boost the effectiveness of interventions included providing on-site HBV testing and vaccination (versus referral for testing and vaccination) and including community education focussed on HBV or liver cancer in an HBV screening program. Further studies are needed to evaluate the effectiveness of more novel interventions (e.g., point of care testing) and interventions specifically including Indigenous populations, people who inject drugs, men who have sex with men, and people incarcerated.
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