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. 2010 Mar 22;7:22. doi: 10.1186/1742-4690-7-22

Table 4.

Bayesian estimates of population dynamic parameters of the HIV-1 CRF12_BF and CRF38_BF epidemics.

Subtype Demographic model Molecular Clock Gene r λ
CRF12_BF Logistic growth Strict pol (PR-RT) 1.08
(0.79-1.44)
0.64
(0.48-0.88)


Relaxed 1.22
(0.85-1.64)
0.57
(0.42-0.81)

CRF38_BF Logistic growth Strict pol (PR-RT) 0.83
(0.31-1.81)
0.83
(0.38-2.24)


Relaxed 0.92
(0.41-1.75)
0.75
(0.40-1.69)

CRF12_BFa Logistic growth Relaxed vpu 2.24
(0.21-4.56)
0.31
(0.15-3.30)

Bb Logistic growth env (C2-V3) 0.46
(0.33-0.59)
1.51
(1.22-2.10)
Strict

pol (PR-RT) 0.56
(0.35-0.80)
1.24
(0.87-1.98)

Fb Logistic growth env (C2-V3) 0.61
(0.40-0.86)
1.14
(0.81-1.73)
Strict

pol (PR-RT) 0.59
(0.31-0.92)
1.17
(0.75-2.24)

Cc Logistic growth Strict pol (RT) 0.70
(0.41-1.00)
0.99
(0.69-1.69)


Relaxed 0.81
(0.40-1.26)
0.86
(0.55-1.73)

CRF31_BCc Logistic growth Strict pol (RT) 1.26
(0.61-2.10)
0.55
(0.33-1.14)


Relaxed 1.27
(0.44-2.26)
0.55
(0.31-1.57)

Estimates of the median growth rate (r, yr-1) and epidemic doubling time (λ, yr) for the HIV-1 CRF12_BF and CRF38_BF epidemics (95% HPD in parentheses). Growth rate estimates were used to calculate the time taken for the epidemic to double in size (λ) using the relation λ = ln(2)/r. a Data from Aulicino et al. [26]. bData from Bello et al. [23]. c Data from Bello et al. [47].