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Modeling the population dynamics of HIV/AIDS

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Modeling the population dynamics of HIV/AIDS. Brandy L. Rapatski. James A. Yorke. Frederick Suppe ... BLR_at_math.umd.edu. http://www.killi.com/brandy ... – PowerPoint PPT presentation

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Title: Modeling the population dynamics of HIV/AIDS


1
Modeling the population dynamics of HIV/AIDS
  • Brandy L. Rapatski
  • James A. Yorke
  • Frederick Suppe

2
Primary Goal
  • To determine how infectiousness of HIV varies as
    an untreated infected gay man progresses through
    3 stages of the disease.
  • Any attempt to measure these infectivities must
    be a highly mathematical analysis of available
    data.

3
Modeling SF Gay Population
  • We model the San Francisco population as
    described by the San Francisco City Clinic Cohort
    Study (SFCCC).

4
San Francisco Transmission Dynamics
  • Analysis of 1978-1984
  • Six Activity Levels (from survey data)
  • Infectiousness depends on stage (3 stages)
  • Bathhouse Assumption
  • Men vary in how often they visit the bathhouses
    but once inside choose partners at random.
  • Model must account for 1978-1984 SF data

5
Infectivity Per Contact Conclusions
2/3 Year
7 Years
3 Years
Death
First Stage Infectivity 0.015
Second Stage Infectivity 0.006
Third Stage Infectivity 0.223
0.0152/30.010
0.00670.042
0.22330.669
Total infections 0.721
6
Infectivity Comparison
7
Viral Loads
Our infectivities correspond to viral loads
------------------2nd Stage-------------------

1st Stage
-----3rd Stage----
Variable viral loads over the course of a typical
untreated individuals HIV infection.
8
  • The infectivities reflect the pattern of semen
    infectivity.
  • Though infectivity depends on mode of
    transmission, third stage remains most
    infectious.

9
Person-to-Person Transition Rate
Africa 1 person to 1,000,000 in approximately
40 years (1950-1990)
1.3 years
1.6
31 generations in 40 years
6.9 years
10
6 generations in 40 years
10
Contact Information
  • BLR_at_math.umd.edu
  • http//www.killi.com/brandy
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