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Therefore innovative methods are needed to study the impact of migration on sexual network structure and HIV diffusion.
As an example, a simulation of the HIV diffusion problem (computed using the StochKit toolkit for 4 years of simulation time) may easily produce over 5 GBytes of raw data per instance [ 11].
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There are two impacts of this diffusion of HIV morbidity on surveillance requirements.
The data presented here illustrate many of the factors in the international diffusion of HIV among IDUs at modest geographic scale.
In Ghana and in many other West African countries, early diffusion of HIV was due in large part to migration and the spatial distribution of sexual networks (Caldwell 1969; Decosas et al. 1995; Oppong 1998; Voeten et al. 2010).
The primary goal of SATHCAP was to examine the role of substance use and related behaviors in accelerating the sexual diffusion of HIV from high-risk individuals (men who have sex with men [MSM], and drug users [DU]) to the general heterosexual population.
Therefore, we will incorporate such growth rates and diffusions into HIV disease model to investigate viral dynamics under various antiretroviral treatments.
Surprisingly, we discovered a partnership between the lipid and the peptide that impaired early membrane fusion events by reducing CD4 receptor lateral diffusion and HIV-1 fusion peptide-mediated lipid mixing.
Therefore, understanding of the reasons for the emergence and spread of non-B subtypes in certain core groups, such as MSM, is crucial for epidemiological analyses aimed to define the pathway of diffusion of HIV-1 nonnative strains in Europe over time and across the different sexual-risk populations.
These are almost 10,000 times lower than the diffusion coefficient for HIV in water.
The diffusion coefficients for HIV virions in undiluted HEC and MC were 4 ± 2 × 10−12 and 7 ± 1 × 10−12 cm2/s, respectively.
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