On the dynamics of HIV and malaria infection : insights from mathematical models

We develop and apply mathematical models to obtain insights into the dynamics of HIV and malaria infection. We consider three case studies. 1. The duration of the time between exposure and detectability of HIV infection is difficult to estimate because precise dates of exposure are rarely known. Th...

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Main Author: Konrad, Bernhard Paul
Language:English
Published: University of British Columbia 2015
Online Access:http://hdl.handle.net/2429/54829
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spelling ndltd-UBC-oai-circle.library.ubc.ca-2429-548292018-01-05T17:28:31Z On the dynamics of HIV and malaria infection : insights from mathematical models Konrad, Bernhard Paul We develop and apply mathematical models to obtain insights into the dynamics of HIV and malaria infection. We consider three case studies. 1. The duration of the time between exposure and detectability of HIV infection is difficult to estimate because precise dates of exposure are rarely known. Therefore, the reliability of clinical HIV testing during the first few weeks of infections is unknown, creating anxiety among HIV-exposed individuals and their physicians. We address this knowledge gap by fitting stochastic models of early HIV infection to detailed viral load time-courses, taken shortly after exposure, from 78 plasma donors. Since every plasma donor in our data eventually becomes infected, we condition our model to reflect this bias before fitting to the data. Our model prediction for the mean eclipse period is 8-10 days. We further quantify the reliability of a negative test t days after potential exposure to inform physicians about the value of initial and follow-up testing. 2. The recently launched Get Checked Online (GCO) program aims at increasing the HIV testing rate in the Vancouver men who have sex with men population by facilitating test taking and result delivery. We develop mathematical models and extract parameter values from surveys and interviews to quantify GCO's population-level impact. Our models predict that the epidemic is growing overall, that its severeness is increased by the presence of a high-risk group and that, even at modest effectiveness, GCO might avert 34-66 new infections in the next five years. 3. Metarhizium anisopliae is a naturally occurring fungal pathogen of mosquitoes that has been engineered to act against malaria by effectively blocking onward transmission from the mosquito vector. We develop and analyse two mathematical models to examine the efficacy of this fungal pathogen. We find that, in many plausible scenarios, the best effects are achieved with a reduced or minimal pathogen virulence, even if the likelihood of resistance to the fungus is negligible. The results depend on the interplay between two main effects: the ability of the fungus to reduce the mosquito population, and the ability of fungus-infected mosquitoes to compete for resources with non-fungus-infected mosquitoes. Science, Faculty of Mathematics, Department of Graduate 2015-09-21T14:49:11Z 2015-10-24T02:45:14 2015 2015-11 Text Thesis/Dissertation http://hdl.handle.net/2429/54829 eng Attribution-NonCommercial-NoDerivs 2.5 Canada http://creativecommons.org/licenses/by-nc-nd/2.5/ca/ University of British Columbia
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language English
sources NDLTD
description We develop and apply mathematical models to obtain insights into the dynamics of HIV and malaria infection. We consider three case studies. 1. The duration of the time between exposure and detectability of HIV infection is difficult to estimate because precise dates of exposure are rarely known. Therefore, the reliability of clinical HIV testing during the first few weeks of infections is unknown, creating anxiety among HIV-exposed individuals and their physicians. We address this knowledge gap by fitting stochastic models of early HIV infection to detailed viral load time-courses, taken shortly after exposure, from 78 plasma donors. Since every plasma donor in our data eventually becomes infected, we condition our model to reflect this bias before fitting to the data. Our model prediction for the mean eclipse period is 8-10 days. We further quantify the reliability of a negative test t days after potential exposure to inform physicians about the value of initial and follow-up testing. 2. The recently launched Get Checked Online (GCO) program aims at increasing the HIV testing rate in the Vancouver men who have sex with men population by facilitating test taking and result delivery. We develop mathematical models and extract parameter values from surveys and interviews to quantify GCO's population-level impact. Our models predict that the epidemic is growing overall, that its severeness is increased by the presence of a high-risk group and that, even at modest effectiveness, GCO might avert 34-66 new infections in the next five years. 3. Metarhizium anisopliae is a naturally occurring fungal pathogen of mosquitoes that has been engineered to act against malaria by effectively blocking onward transmission from the mosquito vector. We develop and analyse two mathematical models to examine the efficacy of this fungal pathogen. We find that, in many plausible scenarios, the best effects are achieved with a reduced or minimal pathogen virulence, even if the likelihood of resistance to the fungus is negligible. The results depend on the interplay between two main effects: the ability of the fungus to reduce the mosquito population, and the ability of fungus-infected mosquitoes to compete for resources with non-fungus-infected mosquitoes. === Science, Faculty of === Mathematics, Department of === Graduate
author Konrad, Bernhard Paul
spellingShingle Konrad, Bernhard Paul
On the dynamics of HIV and malaria infection : insights from mathematical models
author_facet Konrad, Bernhard Paul
author_sort Konrad, Bernhard Paul
title On the dynamics of HIV and malaria infection : insights from mathematical models
title_short On the dynamics of HIV and malaria infection : insights from mathematical models
title_full On the dynamics of HIV and malaria infection : insights from mathematical models
title_fullStr On the dynamics of HIV and malaria infection : insights from mathematical models
title_full_unstemmed On the dynamics of HIV and malaria infection : insights from mathematical models
title_sort on the dynamics of hiv and malaria infection : insights from mathematical models
publisher University of British Columbia
publishDate 2015
url http://hdl.handle.net/2429/54829
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