Relevant bibliographies by topics / HIV Models

Academic literature on the topic 'HIV Models'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "HIV Models"

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Darvishian, Maryam, Zahid A. Butt, Stanley Wong, Eric M. Yoshida, Jaskaran Khinda, Michael Otterstatter, Amanda Yu, et al. "Elevated risk of colorectal, liver, and pancreatic cancers among HCV, HBV and/or HIV (co)infected individuals in a population based cohort in Canada." Therapeutic Advances in Medical Oncology 13 (January 2021): 175883592199298. http://dx.doi.org/10.1177/1758835921992987.

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Introduction:Studies of the impact of hepatitis C virus (HCV), hepatitis B virus (HBV) and HIV mono and co-infections on the risk of cancer, particularly extra-hepatic cancer, have been limited and inconsistent in their findings.Methods:In the British Columbia Hepatitis Testers Cohort, we assessed the risk of colorectal, liver, and pancreatic cancers in association with HCV, HBV and HIV infection status. Using Fine and Gray adjusted proportional subdistribution hazards models, we assessed the impact of infection status on each cancer, accounting for competing mortality risk. Cancer occurrence was ascertained from the BC Cancer Registry.Results:Among 658,697 individuals tested for the occurrence of all three infections, 1407 colorectal, 1294 liver, and 489 pancreatic cancers were identified. Compared to uninfected individuals, the risk of colorectal cancer was significantly elevated among those with HCV (Hazard ration [HR] 2.99; 95% confidence interval [CI] 2.55–3.51), HBV (HR 2.47; 95% CI 1.85–3.28), and HIV mono-infection (HR 2.30; 95% CI 1.47–3.59), and HCV/HIV co-infection. The risk of liver cancer was significantly elevated among HCV and HBV mono-infected and all co-infected individuals. The risk of pancreatic cancer was significantly elevated among individuals with HCV (HR 2.79; 95% CI 2.01–3.70) and HIV mono-infection (HR 2.82; 95% CI 1.39–5.71), and HCV/HBV co-infection.Discussion/Conclusion:Compared to uninfected individuals, the risk of colorectal, pancreatic and liver cancers was elevated among those with HCV, HBV and/or HIV infection. These findings highlight the need for targeted cancer prevention and diligent clinical monitoring for hepatic and extrahepatic cancers in infected populations.
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Wei, Yu, Wei Li, Tengfei Du, Zhangyong Hong, and Jianping Lin. "Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method." International Journal of Molecular Sciences 20, no. 14 (July 22, 2019): 3572. http://dx.doi.org/10.3390/ijms20143572.

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Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain populations. However, the treatment of coinfection is a challenge because of the special considerations needed to ensure hepatic safety and avoid drug–drug interactions. Multitarget inhibitors with less toxicity may provide a promising therapeutic strategy for HIV/HCV coinfection. However, the identification of one molecule that acts on multiple targets simultaneously by experimental evaluation is costly and time-consuming. In silico target prediction tools provide more opportunities for the development of multitarget inhibitors. In this study, by combining Naïve Bayes (NB) and support vector machine (SVM) algorithms with two types of molecular fingerprints, MACCS and extended connectivity fingerprints 6 (ECFP6), 60 classification models were constructed to predict compounds that were active against 11 HIV-1 targets and four HCV targets based on a multiple quantitative structure–activity relationships (multiple QSAR) method. Five-fold cross-validation and test set validation were performed to measure the performance of the 60 classification models. Our results show that the 60 multiple QSAR models appeared to have high classification accuracy in terms of the area under the ROC curve (AUC) values, which ranged from 0.83 to 1 with a mean value of 0.97 for the HIV-1 models and from 0.84 to 1 with a mean value of 0.96 for the HCV models. Furthermore, the 60 models were used to comprehensively predict the potential targets of an additional 46 compounds, including 27 approved HIV-1 drugs, 10 approved HCV drugs and nine selected compounds known to be active against one or more targets of HIV-1 or HCV. Finally, 20 hits, including seven approved HIV-1 drugs, four approved HCV drugs, and nine other compounds, were predicted to be HIV/HCV coinfection multitarget inhibitors. The reported bioactivity data confirmed that seven out of nine compounds actually interacted with HIV-1 and HCV targets simultaneously with diverse binding affinities. The remaining predicted hits and chemical-protein interaction pairs with the potential ability to suppress HIV/HCV coinfection are worthy of further experimental investigation. This investigation shows that the multiple QSAR method is useful in predicting chemical-protein interactions for the discovery of multitarget inhibitors and provides a unique strategy for the treatment of HIV/HCV coinfection.
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Abiodun, Oluwakemi E., Olukayode Adebimpe, James A. Ndako, Olajumoke Oludoun, Benedicta Aladeitan, and Michael Adeniyi. "Mathematical modeling of HIV-HCV co-infection model: Impact of parameters on reproduction number." F1000Research 11 (October 10, 2022): 1153. http://dx.doi.org/10.12688/f1000research.124555.1.

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Background: Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV) are both as classified blood-borne viruses since they are transmitted through contact with contaminated blood. Approximately 1.3 million of the 2.75 million global HIV/HCV carriers inject drugs (PWID). HIV co-infection has a harmful effect on the progression of HCV, resulting in greater rates of HCV persistence after acute infection, higher viral levels, and accelerated progression of liver fibrosis and end-stage liver disease. In this study, we developed and investigated a mathematical model for the dynamical behavior of HIV/AIDS and HCV co-infection, which includes therapy for both diseases, vertical transmission in HIV cases, unawareness and awareness of HIV infection, inefficient HIV treatment follow-up, and efficient condom use. Methods: Positivity and boundedness of the model under investigation were established using well-known theorems. The equilibria were demonstrated by bringing all differential equations to zero. The associative reproduction numbers for mono-infected and dual-infected models were calculated using the next-generation matrix approach. The local and global stabilities of the models were validated using the linearization and comparison theorem and the negative criterion techniques of bendixson and dulac, respectively. Results: The growing prevalence of HIV treatment dropout in each compartment of the HIV model led to a reduction in HIV on treatment compartments while other compartments exhibited an increase in populations. In dually infected patients, treating HCV first reduces co-infection reproduction number Rech, which reduces liver cancer risk. Conclusions: From the model's results, we infer various steps that policymakers could take to reduce the number of mono-infected and co-infected individuals.
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Abiodun, Oluwakemi E., Olukayode Adebimpe, James A. Ndako, Olajumoke Oludoun, Benedicta Aladeitan, and Michael Adeniyi. "Mathematical modeling of HIV-HCV co-infection model: Impact of parameters on reproduction number." F1000Research 11 (December 19, 2022): 1153. http://dx.doi.org/10.12688/f1000research.124555.2.

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Background: Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV) are both classified as blood-borne viruses since they are transmitted through contact with contaminated blood. Approximately 1.3 million of the 2.75 million global HIV/HCV carriers are people who inject drugs (PWID). HIV co-infection has a harmful effect on the progression of HCV, resulting in greater rates of HCV persistence after acute infection, higher viral levels, and accelerated progression of liver fibrosis and end-stage liver disease. In this study, we developed and investigated a mathematical model for the dynamical behavior of HIV/AIDS and HCV co-infection, which includes therapy for both diseases, vertical transmission in HIV cases, unawareness and awareness of HIV infection, inefficient HIV treatment follow-up, and efficient condom use. Methods: Positivity and boundedness of the model under investigation were established using well-known theorems. The equilibria were demonstrated by bringing all differential equations to zero. The associative reproduction numbers for mono-infected and dual-infected models were calculated using the next-generation matrix approach. The local and global stabilities of the models were validated using the linearization and comparison theorem and the negative criterion techniques of bendixson and dulac, respectively. Results: The growing prevalence of HIV treatment dropout in each compartment of the HIV model led to a reduction in HIV on treatment compartments while other compartments exhibited an increase in populations. In dually infected patients, treating HCV first reduces co-infection reproduction number Rech, which reduces liver cancer risk. Conclusions: From the model's results, we infer various steps (such as: campaigns to warn individuals about the consequences of having multiple sexual partners; distributing more condoms to individuals; continuing treatment for chronic HCV and AIDS) that policymakers could take to reduce the number of mono-infected and co-infected individuals.
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Oliveira, Dinamene, Maria do Rosário Martins, Rita Castro, Lemuel Cordeiro, Maria Rosalina Barroso, Maria Antónia Nazaré, and Filomena Pereira. "Seropositivity rate and sociodemographic factors associated to HIV, HBV, HCV and syphilis among parturients from Irene Neto Maternity of Lubango city, Angola." Sexually Transmitted Infections 96, no. 8 (May 18, 2020): 587–89. http://dx.doi.org/10.1136/sextrans-2019-054249.

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ObjectivesTo characterise infections by HIV, Treponema pallidum, hepatitis B (HBV) and C virus (HCV) in parturients admitted to Irene Neto Maternity, Lubango city, Huíla province, Angola, namely its seropositivity rate and its association with sociodemographic factors.MethodsAn observational, cross-sectional and analytical facility-based survey was conducted among 500 parturients at Irene Neto Maternity, from October 2016 to September 2017. Women in labour were screened for antibodies against HIV-1/2, T. pallidum and HCV. Antigen detection was used to diagnose HBV infections. Sociodemographic data were also collected. The seropositivity rate and respective CIs were estimated at a level of 95%. Multivariable logistic regression models were performed to explore the association between the studied infections and sociodemographic factors.ResultsIn 11.8% of the parturients (95% CI 9.3 to 14.9), at least one infection was detected. HBV infection was the most common (8.6%), followed by HIV infection (3.0%) and syphilis (1.0%). Coinfection with HBV and HIV was observed in two parturients (0.4%) and HBV, HIV and T. pallidum were all detected in one parturient (0.2%). No HCV infection was detected. For each additional year of formal education, pregnant women had a 10.0% lower chance of being infected with HBV (adjusted OR=0.900, 95% CI 0.816 to 0.992).ConclusionsThis study is one of the few reports contributing for the knowledge of some sexually transmitted infections epidemiology in Angola. The seropositivity rate of the studied infections is of concern, especially the high endemicity of HBV. There is a need for a stronger commitment and further research to design cost-effective public health and clinical interventions to improve the situation.
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Anderson, Russell W. "Mathematical models of HIV pathogenesis." Nature Medicine 3, no. 9 (September 1997): 936. http://dx.doi.org/10.1038/nm0997-936a.

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Grossman, Zvi, and Ronald B. Herberman. "Mathematical models of HIV pathogenesis." Nature Medicine 3, no. 9 (September 1997): 936–37. http://dx.doi.org/10.1038/nm0997-936b.

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Gore, S. M. "HIV Epidemiology--models and methods." Sexually Transmitted Infections 70, no. 5 (October 1, 1994): 364–65. http://dx.doi.org/10.1136/sti.70.5.364-b.

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Pace, Matthew J., Luis Agosto, Erin H. Graf, and Una O'Doherty. "HIV reservoirs and latency models." Virology 411, no. 2 (March 2011): 344–54. http://dx.doi.org/10.1016/j.virol.2010.12.041.

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Klotman, Paul E., Jay Rappaport, Patricio Ray, Jeffrey B. Kopp, Roberta Franks, Leslie A. Bruggeman, and Abner L. Notkins. "Transgenic models of HIV-1." AIDS 9, no. 4 (April 1995): 313–24. http://dx.doi.org/10.1097/00002030-199504000-00001.

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Dissertations / Theses on the topic "HIV Models"

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Nelson, Patrick William. "Mathematical models of HIV pathogenesis and immunology /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/6783.

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De, la Harpe Alana. "A comparative analysis of mathematical models for HIV epidemiology." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96983.

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Thesis (MSc)--Stellenbosch University, 2015.
ENGLISH ABSTRACT: HIV infection is one of the world’s biggest health problems, with millions of people infected worldwide. HIV infects cells in the immune system, where it primarily targets CD4+ T helper cells and without treatment, the disease leads to the collapse of the host immune system and ultimately death. Mathematical models have been used extensively to study the epidemiology of HIV/AIDS. They have proven to be effective tools in studying the transmission dynamics of HIV. These models provide predictions that can help better our understanding of the epidemiological patterns of HIV, especially the mechanism associated with the spread of the disease. In this thesis we made a functional comparison between existing epidemiological models for HIV, with the focus of the comparison on the force of infection (FOI). The spread of infection is a crucial part of any infectious disease, as the dynamics of the disease depends greatly on the rate of transmission from an infectious individual to a susceptible individual. First, a review was done to see what deterministic epidemiological models exist. We found that many manuscripts do not provide the necessary information to recreate the authors’ results and only a small amount of the models could be simulated. The reason for this is mainly due to a lack of information or due to mistakes in the article. The models were divided into four categories for the analysis. On the basis of the FOI, we distinguished between frequency- or density-dependent transmission, and as a second criterion we distinguished models on the sexual activity of the AIDS group. Subsequently, the models were compared in terms of their FOI, within and between these classes. We showed that for larger populations, frequency-dependent transmission should be used. This is the case for HIV, where the disease is mainly spread through sexual contact. Inclusion of AIDS patients in the group of infectious individuals is important for the accuracy of transmission dynamics. More than half of the studies that were selected in the review assumed that AIDS patients are too sick to engage in risky sexual behaviour. We see that including AIDS patients in the infectious individuals class has a significant effect on the FOI when the value for the probability of transmission for an individual with AIDS is bigger than that of the other classes. The analysis shows that the FOI can vary depending on the parameter values and the assumptions made. Many models compress various parameter values into one, most often the transmission probability. Not showing the parameter values separately makes it difficult to understand how the FOI works, since there are unknown factors that have an influence. Improving the accuracy of the FOI can help us to better understand what factors influence it, and also produce more realistic results. Writing the probability of transmission as a function of the viral load can help to make the FOI more accurate and also help in the understanding of the effects that viral dynamics have on the population transmission dynamics.
AFRIKAANSE OPSOMMING: MIV-infeksie is een van die wêreld se grootste gesondheidsprobleme, met miljoene mense wat wêreldwyd geïnfekteer is. MIV infekteer selle in die immuunstelsel, waar dit hoofsaaklik CD4+ T-helperselle teiken. Sonder behandeling lei die siekte tot die ineenstorting van die gasheer se immuunstelsel en uiteindelik sy dood. Wiskundige modelle word breedvoerig gebruik om die epidemiologie van MIV/vigs te bestudeer. Die modelle is doeltreffende instrumente in die studie van die oordrag-dinamika van MIV. Hulle lewer voorspellings wat kan help om ons begrip van epidemiologiese patrone van MIV, veral die meganisme wat verband hou met die verspreiding van die siekte, te verbeter. In hierdie tesis het ons ‘n funksionele vergelyking tussen bestaande epidemiologiese modelle vir MIV gedoen, met die fokus van die vergelyking op die tempo van infeksie (TVI). Die verspreiding van infeksie is ‘n belangrike deel van enige aansteeklike siekte, aangesien die dinamika van die siekte grootliks afhang van die tempo van oordrag van ‘n aansteeklike persoon na ‘n vatbare persoon. ‘n Oorsig is gedoen om te sien watter kompartementele epidemiologiese modelle alreeds bestaan. Ons het gevind dat baie van die manuskripte nie die nodige inligting voorsien wat nodig is om die resultate van die skrywers te repliseer nie, en slegs ‘n klein hoeveelheid van die modelle kon gesimuleer word. Die rede hiervoor is hoofsaaklik as gevolg van ‘n gebrek aan inligting of van foute in die artikel. Die modelle is in vier kategorieë vir die analise verdeel. Op grond van die TVI het ons tussen frekwensie- of digtheidsafhanklike oordrag onderskei, en as ‘n tweede kriterium het ons die modelle op die seksuele aktiwiteit van die vigs-groep onderskei. Daarna is die modelle binne en tussen die klasse vergelyk in terme van hul TVIs. Daar is gewys dat frekwensie-afhanklike oordrag gebruik moet word vir groter bevolkings. Dit is die geval van MIV, waar die siekte hoofsaaklik versprei word deur seksuele kontak. Die insluiting van die vigs-pasiënte in die groep van aansteeklike individue is belangrik vir die akkuraatheid van die oordrag-dinamika van MIV. Meer as helfte van die uitgesoekte studies aanvaar dat vigs-pasiënte te siek is om betrokke te raak by riskante seksuele gedrag. Ons sien dat die insluiting van vigs-pasiënte in die groep van aansteeklike individue ‘n beduidende uitwerking op die TVI het wanneer die waarde van die waarskynlikheid van oordrag van ‘n individu met vigs groter is as dié van die ander klasse. Die analise toon dat die TVI kan wissel afhangende van die parameter waardes en die aannames wat gemaak is. Baie modelle voeg verskeie parameter waardes bymekaar vir die waarskynlikheid van oordrag. Wanneer die parameter waardes nie apart gewys word nie, is dit moeilik om die werking van die TVI te verstaan, want daar is onbekende faktore wat ‘n invloed op die TVI het. Die verbetering van die akkuraatheid van die TVI kan ons help om die faktore wat dit beïnvloed beter te verstaan, en dit kan ook help om meer realistiese resultate te produseer. Om die waarskynlikheid van oordrag as ‘n funksie van die viruslading te skryf kan help om die TVI meer akkuraat te maak en dit kan ook help om die effek wat virale dinamika op die bevolkingsoordrag-dinamika het, beter te verstaan.
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Wodarz, Dominik. "Mathematical models of virus immune system interactions." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268104.

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Mishra, Sharmistha. "Using mathematical models to characterize HIV epidemics for the design of HIV prevention strategies." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24913.

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Since 2000, we have been trying to characterize and classify HIV epidemics to guide the strategic design of HIV prevention policies and focus HIV programmes and resource allocation by a regions' epidemic type. We have used arbitrary thresholds of HIV prevalence across different risk-groups in a given population, 'static' mathematical models and classical epidemiological measures of the population attributable fraction that do not account for chains of transmission. As a result, these traditional approaches could be missing the underlying transmission dynamics and the role of key populations - such as female sex workers and their clients - on HIV spread. In this thesis, I build on a growing paradigm shift on how we should re-classify HIV epidemics based on the epidemiological features that lead to HIV emergence and persistence (i.e. the 'epidemic drivers' that influence the basic reproductive ratio, R0). I examine the extent to which our traditional approaches have been underestimating the contribution of sex work to HIV spread and likely misclassifying epidemic type by developing dynamic mathematical models of HIV transmission and simulating a large number of plausible 'synthetic' HIV epidemics. I then develop - as proof-of-concept - a novel algorithm to diagnose epidemic type using these synthetic epidemics and glean the key epidemiological data that would be most useful to help distinguish between 'epidemic drivers', and therefore would be most useful to collect as part of HIV surveillance and future empirical research.
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Akinlotan, Deborah Morenikeji. "Modelling the dynamics of HIV related malignancies." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86573.

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Thesis (MSc)--Stellenbosch University, 2014.
ENGLISH ABSTRACT: In recent years, HIV-associated cancers have proven to be the bane of our time, since HIV is decimating humanity across the globe, even in the twilight of the last century. Cancer rates continue to rise in developing countries, where 95% of the world’s HIV-infected population lives, yet less than 1% have access to antiretroviral therapy. HIV-infected individuals have a higher proclivity to develop cancers, mainly from immunosuppression. An understanding of the immunopathogenesis of HIV-related cancers (HRC) is therefore a major prerequisite for rationally developing and/or improving therapeutic strategies, developing immunotherapeutics and proplylatic vaccines. In this study, we explore the pathology of HIV-related cancer malignancies, taking into account the pathogenic mechanisms and their potential for improving the treatment of management of these malignancies especially in developing countries. We mathematically model the dynamics of malignant tumors in an HIV-free environment, investigate the impact of cancer malignancies on HIV-positive patients and explore the benefits of various therapeutic intervention strategies in the management of HIV-related cancers. We present two deterministic models of infectious diseases to implement these, and they were analysed. We use HIV-related lymphomas in the Western Cape of South Africa as a case study. We validated the proposed models using lymphoma incidence data from the Tygerberg Lymphoma Study Group (TLSG), Tygerberg Hospital, Western Cape, South Africa. We show that the increasing prevalence of HIV increases lymphoma cases, and thus, other HIV-related cancers. Our models also suggests that an increase in the roll-out of the HAART program can reduce the number of lymphoma cases in the nearest future, while it averts many deaths. Furthermore, the results indicate that a highly crucial factor to consider in the prognosis of the incidence of lymphoma (and other cancer types) in HIV-infected patients is their CD4 cell count, irrespective of whether the patient has developed an HRC or not.
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Lutambi, Angelina Mageni. "Basic properties of models for the spread of HIV/AIDS." Thesis, Stellenbosch : Stellenbosch University, 2007. http://hdl.handle.net/10019.1/19641.

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Thesis (MSc)--University of Stellenbosch, 2007.
ENGLISH ABSTRACT: While research and population surveys in HIV/AIDS are well established in developed countries, Sub-Saharan Africa is still experiencing scarce HIV/AIDS information. Hence it depends on results obtained from models. Due to this dependence, it is important to understand the strengths and limitations of these models very well. In this study, a simple mathematical model is formulated and then extended to incorporate various features such as stages of HIV development, time delay in AIDS death occurrence, and risk groups. The analysis is neither purely mathematical nor does it concentrate on data but it is rather an exploratory approach, in which both mathematical methods and numerical simulations are used. It was found that the presence of stages leads to higher prevalence levels in a short term with an implication that the primary stage is the driver of the disease. Furthermore, it was found that time delay changed the mortality curves considerably, but it had less effect on the proportion of infectives. It was also shown that the characteristic behaviour of curves valid for most epidemics, namely that there is an initial increase, then a peak, and then a decrease occurs as a function of time, is possible in HIV only if low risk groups are present. It is concluded that reasonable or quality predictions from mathematical models are expected to require the inclusion of stages, risk groups, time delay, and other related properties with reasonable parameter values.
AFRIKAANSE OPSOMMING: Terwyl navorsing en bevolkingsopnames oor MIV/VIGS in ontwikkelde lande goed gevestig is, is daar in Afrika suid van die Sahara slegs beperkte inligting oor MIV/VIGS beskikbaar. Derhalwe moet daar van modelle gebruik gemaak word. Dit is weens hierdie feit noodsaaklik om die moontlikhede en beperkings van modelle goed te verstaan. In hierdie werk word ´n eenvoudige model voorgelˆe en dit word dan uitgebrei deur insluiting van aspekte soos stadiums van MIV outwikkeling, tydvertraging by VIGS-sterftes en risikogroepe in bevolkings. Die analise is beklemtoon nie die wiskundage vorme nie en ook nie die data nie. Dit is eerder ´n verkennende studie waarin beide wiskundige metodes en numeriese simula˙sie behandel word. Daar is bevind dat insluiting van stadiums op korttermyn tot ho¨er voorkoms vlakke aanleiding gee. Die gevolgtrekking is dat die primˆere stadium die siekte dryf. Verder is gevind dat die insluiting van tydvestraging wel die kurwe van sterfbegevalle sterk be¨ınvloed, maar dit het min invloed op die verhouding van aangestekte persone. Daar word getoon dat die kenmerkende gedrag van die meeste epidemi¨e, naamlik `n aanvanklike styging, `n piek en dan `n afname, in die geval van VIGS slegs voorkom as die bevolking dele bevat met lae risiko. Die algehele gevolgtrekking word gemaak dat vir goeie vooruitskattings met sinvolle parameters, op grond van wiskundige modelle, die insluiting van stadiums, risikogroepe en vertragings benodig word.
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Mäkitalo, Barbro. "HIV and SIV specific cellular immunity in macaque models /." Stockholm, 2003. http://diss.kib.ki.se/2003/91-7349-751-7/.

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Dasgupta, Abhijit. "Parametric identifiability and related problems /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/9602.

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Baxley, Dana Ali. "A MATHEMATICAL STUDY OF TWO RETROVIRUSES, HIV AND HTLV-I." Master's thesis, University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2369.

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In this thesis, we examine epidemiological models of two different retroviruses, which infect the human body. The two viruses under study are HIV or the human immunodefiency virus and HTLV-I, which is the human T lymphotropic virus type I. A retrovirus is a virus, which injects its RNA into the host, rather than it's DNA. We will study each of the different mathematical models for each of the viruses separately. Then we use MATLAB-SIMULINK to analyze the models by studying the reproductive numbers in each case and the disease progression by examining the graphs. In Chapter 1, we mention basic ideas associated with HIV and HTLV-I. In Chapter 2 some of the basic mathematical model of epidemiology is presented. Chapter 3 is devoted to a model describing the intra-host dynamics of HIV. Here, we take into account how HIV infects and replicates in the CD4+ T cells. The model studied in this thesis examines the difference between cells, which are susceptible to the virus, and cells, which are not susceptible. Through the graphs associated with this model, we are able to see how this difference affects disease progression. In Chapter 4, we examine the effect of HTLV-I virus on human body. The HTLV-I virus causes a chronic infection in humans and may eventually lead to other diseases. In particular, the development of Adult T-cell Leukemia or ATL is studied in this thesis. The T-cell dynamics and progression to ATL is described using a mathematical model with coupled differential equations. Using mathematical analysis and SIMULINK, we obtain results on stability, asymptotic stability and the manner of progression of the disease. In Chapter 5 and appendices, we mention our inference and the MATLAB-SIMULINK codes used in this thesis, so that a reader can verify the details of the work carried out in this thesis.
M.S.
Department of Mathematics
Sciences
Mathematical Science MS
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Liang, Yanfeng. "Modelling the effect of stochasticity in epidemic and HIV models." Thesis, University of Strathclyde, 2016. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=27380.

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An epidemic of an infectious disease can be modelled by using either a deterministic model or a stochastic model. In this thesis, we consider the effect that different types of noise has on the dynamical behaviour of deterministic SIS models and SIR/SIRS models as well as an HIV model. We start off with a literature review giving previous work and the mathematical background to the area. Next, we introduce demographic stochasticity into the well-established deterministic SIS model with births and deaths and derive a stochastic differential equation (SDE). We assume that an infected individual or a susceptible individual who dies is immediately replaced by a susceptible individual and thus the population size is kept constant. In order for our model to make sense, we then prove that the SDE has a strong unique nonnegative solution which is bounded above and establish the conditions needed for the disease to become extinct. Based on the idea of the Feller test, we also calculate the respective probabilities of the solution first hitting zero or the upper limit. Numerical simulations are then produced using the Milstein method with both theoretical and realistic parameter values to confirm our theoretical results. Motivated by the model discussed in the first topic, we then continue our study on the effect of demographic stochasticity on the deterministic SIS model by now assuming that the births and deaths of individuals are independent of each other and thus the population size can vary with respect to time. In this case, the per capita disease contact rate may be dependent on the population size and we have shown that this model allows us to consider the cases when the population size tends to a large number and when the population size tends to a small number. First we look at the SDE model for the total population size and show that there exists a strong unique nonnegative solution. Then we look at the two-dimensional SDE SIS model and show that there also exists a strong unique nonnegative solution which is bounded above given the total population size. We then obtain the conditions needed in order for the disease to become extinct in finite time almost surely. Numerical simulations with both theoretical and realistic parameter values are also produced to confirm our theoretical results. Next we look at a different type of noise, namely the telegraph noise, which is an example of an environmental noise. Telegraph noise could be modelled as changing between two or more regimes of environment which differ by factors such as rainfalls or nutrition. This form of switching can be modelled using a finite-state Markov Chain. We incorporate the telegraph noise into the SIRS epidemic model. First we start with a two-state Markov Chain and show that there exists a unique nonnegative solution and establish the conditions for extinction and persistence for the stochastic SIRS model. We then explain how the results can be generalised to a finite-state Markov Chain. Furthermore we also show that the results for the SIR model with Markov switching are a special case of the SIRS model. Numerical simulations are produced using theoretical and realistic parameter values to confirm our theoretical results. Lastly we look at the modified Kaplan HIV model amongst injecting drug users. We introduce environmental stochasticity into the deterministic HIV model by the well-known standard technique of parameter perturbation. We then prove that the resulting SDE has a unique global nonnegative solution. As well as constructing the conditions required for extinction and persistence we also show that there exists a stationary distribution for the persistence case. Simulations using the Euler-Maruyama method with realistic parameter values are then constructed to illustrate and support our theoretical results. A brief discussion and summary section is given at the end to conclude the thesis.
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Books on the topic "HIV Models"

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Paul, Racz, Letvin Norman L, and Gluckman J. C, eds. Animal models of HIV and other retroviral infections. Basel: Karger, 1993.

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Friedman, Herman, Steven Specter, and Mauro Bendinelli, eds. In vivo Models of HIV Disease and Control. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/b135975.

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Van Ark, James W. 1952-, ed. Modeling HIV transmission and AIDS in the United States. Berlin: Springer-Verlag, 1992.

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Inaba, Hisashi. The exponential phase of HIV/AIDS epidemic in Japan. Tokyo: Institute of Population Problems, Ministry of Health and Welfare, 1994.

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Y, Tan W. Deterministic and stochastic models of AIDS epidemics and HIV infections with intervention. Singapore: World Scientific, 2005.

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Roy, Priti Kumar. Mathematical Models for Therapeutic Approaches to Control HIV Disease Transmission. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-852-6.

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Ojha, Vijay Prakash. The macro-economic and sectoral impacts of HIV and AIDS in India: A CGE analysis. New Delhi: United Nations Development Programme, 2006.

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Models of protection against HIV/SIV: Avoiding AIDS in humans and monkeys. Amsterdam: Academic Press, 2012.

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Hethcote, Herbert W. Modeling HIV transmission and AIDS in the United States. Berlin: Springer-Verlag, 1992.

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Roberts, Carole A. Simulation models of the epidemiological consequences of HIV infection and Aids. Salford: University of Salford Department of Business and Management Studies, 1988.

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Book chapters on the topic "HIV Models"

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Basavarajaiah, D. M., and Bhamidipati Narasimha Murthy. "HIV Projection Models." In HIV Transmission, 209–26. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0151-7_9.

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Brauer, Fred, Carlos Castillo-Chavez, and Zhilan Feng. "Models for HIV/AIDS." In Texts in Applied Mathematics, 273–310. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9828-9_8.

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Liao, Chenzhong, and Marc C. Nicklaus. "HIV-1 Integrase-DNA Models." In HIV-1 Integrase, 429–55. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118015377.ch28.

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Basavarajaiah, D. M., and Bhamidipati Narasimha Murthy. "HIV Vertical Transmission DTSM Simulation Models: Global and National Perspective." In HIV Transmission, 87–126. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0151-7_3.

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Inaba, Hisashi. "Epidemic Models for HIV Infection." In Age-Structured Population Dynamics in Demography and Epidemiology, 333–77. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-0188-8_7.

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Hill, Alison L. "Mathematical Models of HIV Latency." In Current Topics in Microbiology and Immunology, 131–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/82_2017_77.

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Avila-Casado, Carmen, Teresa I. Fortoul, and Sumant S. Chugh. "HIV-Associated Nephropathy: Experimental Models." In Contributions to Nephrology, 270–85. Basel: KARGER, 2011. http://dx.doi.org/10.1159/000320212.

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Chen, Zhiwei. "Monkey Models and HIV Vaccine Research." In HIV Vaccines and Cure, 97–124. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0484-2_5.

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Bauer, Gerhard, and Joseph S. Anderson. "Animal Models Used in HIV Gene Therapy." In Gene Therapy for HIV, 41–47. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0434-1_6.

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Basavarajaiah, D. M., and Bhamidipati Narasimha Murthy. "Statistical Models of Postnatal Transmission of HIV Type-I Infection from Mother to Child on Global Perspectives." In HIV Transmission, 135–67. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0151-7_5.

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Conference papers on the topic "HIV Models"

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De Leenheer, P., and H. L. Smith. "Global analysis of HIV models." In 2003 European Control Conference (ECC). IEEE, 2003. http://dx.doi.org/10.23919/ecc.2003.7086471.

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Raposo, Letícia, Mônica Arruda, Rodrigo Brindeiro, and Flavio Nobre. "SIRA-HIV: A User-friendly System to Evaluate HIV-1 Drug Resistance from Next-generation Sequencing Data." In 11th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0008874700930100.

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Marwala, Tshilidzi, and Bodie Crossingham. "Neuro-rough models for modelling HIV." In 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2008. http://dx.doi.org/10.1109/icsmc.2008.4811770.

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"Detecting Interacting Mutation Clusters in HIV-1 Drug Resistance." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004238800340043.

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Alwan, Zainab, Gopal Reddy, and Balasubramanyam Karanam. "Novel Role of Transcriptional Factor Kaiso in HIV Infection." In 13th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010781100003123.

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"Probabilistic Neural Network for Predicting Resistance to HIV-Protease Inhibitor Nelfinavir." In International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004735900170023.

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"Comparing Viral (HIV) and Bacterial (Staphylococcus aureus) Infection of the Bone Tissue." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004249801960201.

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Knorn, Steffi, and Richard H. Middleton. "Lymph compartment models and HIV intra patient infection dynamics." In 2014 IEEE Conference on Control Applications (CCA). IEEE, 2014. http://dx.doi.org/10.1109/cca.2014.6981557.

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Adams, Andrew E., Zabrina L. Brumme, Alexander R. Rutherford, and Ralf W. Wittenberg. "Matching models of HIV-1 viral dynamics to clinical data." In 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2015. http://dx.doi.org/10.1109/cibcb.2015.7300326.

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Zhang, Xiao-Yi, Cun Xin Wang, and Kun Zeng. "Two Receptor Based Pharmacophore Models for HIV-1 Integrase DKA Inhibitors." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163720.

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Reports on the topic "HIV Models"

1

Hewett, Paul, Mutinta Nalubamba, Fiammetta Bozzani, Mardieh Dennis, Jean Digitale, Lung Vu, Eileen Yam, and Mary Nambao. REacH: Randomized Evaluation of HIV/FP Service Models. Population Council, 2015. http://dx.doi.org/10.31899/hiv8.1003.

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Banks, H. T., and D. M. Bortz. A Parameter Sensitivity Methodology in the Context of HIV Delay Equation Models. Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada444054.

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Mullick, Saiqa, Mantshi Menziwa, Nzwakie Mosery, Doctor Khoza, and Edwin Maroga. Feasibility, acceptability, effectiveness and cost of models of integrating HIV prevention and counseling and testing for HIV within family planning services in North West Province, South Africa. Population Council, 2008. http://dx.doi.org/10.31899/rh4.1214.

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Greenwood, Jeremy, Philipp Kircher, Cezar Santos, and Michèle Tertilt. An Equilibrium Model of the African HIV/AIDS Epidemic. Cambridge, MA: National Bureau of Economic Research, April 2013. http://dx.doi.org/10.3386/w18953.

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Kalibala, Sam, Waimar Tun, Chabu Kangale, Jill Keesbury, Ray Handema, and Mwaka Monze. Implementing incentive-based HIV interventions in Zambia: The COMPACT model. Population Council, 2013. http://dx.doi.org/10.31899/hiv3.1001.

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Mahal, Ajay, Brendan O'Flaherty, and David Bloom. Needle Sharing and HIV Transmission: A Model with Markets and Purposive Behavior. Cambridge, MA: National Bureau of Economic Research, March 2009. http://dx.doi.org/10.3386/w14823.

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Vu, Lung, Waimar Tun, Louis Apicella, Jeremiah Kidola, Caterina Casalini, Gasper Mbita, Neema Makyao, Todd Koppenhaver, and Erick Mlanga. Community-based HIV treatment service delivery model for female sex workers in Tanzania: Evaluation findings. Population Council, 2020. http://dx.doi.org/10.31899/hiv11.1006.

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Chen, Dan, and Qiang Zhou. Induction of Apoptosis by Targeting the Microtubule Network: Using HIV Tat as a Model System. Fort Belvoir, VA: Defense Technical Information Center, April 2004. http://dx.doi.org/10.21236/ada428033.

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Chen, Dan, and Qiang Zhou. Induction of Apoptosis by Targeting the Microtubule Network: Using HIV Tat as a Model System. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada415803.

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Scobie, Linda, Liam O'Connor, Martin D’Agostino, Nigel Cook, Jonathan Wells, Sarah Berry, Louise Kelly, Anne Wood, and Sue Keenan. Thermal Inactivation Model for Hepatitis E Virus (HEV). Food Standards Agency, February 2022. http://dx.doi.org/10.46756/sci.fsa.sdt366.

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Hepatitis E is an emerging issue, with the number of confirmed cases in the UK increasing in 2009-2015, and decreasing slightly in 2016 and 2017. There is some epidemiological evidence of an association of this virus with undercooked pork and pork products. Currently, there is no standardized method for evaluating thermal stability of HEV and also a lack of a suitable assay that can distinguish between intact HEV that can cause an infection and damaged virus which is not capable of causing an infection. This has raised concerns as it is extremely difficult to extrapolate the risk from pork products in relation to cooking practices. We are seeking to address this knowledge gap, which will not only inform our risk assessment, but will also provide an indication if cooking is sufficient to inactivate the virus in foods
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