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Table 1 Model Input parameters and distribution types used in uncertainty analysis

From: Modelling the impact and cost-effectiveness of the HIV intervention programme amongst commercial sex workers in Ahmedabad, Gujarat, India

Definition of model inputs

Model inputs (boundaries or in italics: 95% CI)

Probability Distribution

Date of behavioural survey and reference for model input values

Coverage and Impact

   

Overall number of sex workers in Ahmedabad

4000 (3500–4500)

Triangular

Estimated by staff and peer educators of Jyoti Sangh through snow-balling method. Also personal communication with GJ on 7 July 2005.

Proportion of CSW recently reached by Jyoti Sangh intervention

0.586 (0.521–0.669)

Triangular

Average number of CSWs covered by the intervention program.

Number covered/Total number = 2342/4000 = 0.5855

Max.: Number covered/min. total number = 2342/4500 = 0.5205

Min: Number covered/max. total number = 2342/3500 = 0.6692

(According to the routine data collected in monthly reports between Jan 2001 and Dec 2003)

Proportion of CSW reached using STD services per month

0.028 (0.028–0.041)

Uniform

Average of percentage of STD treatments (Female) in those CSWs covered by the programme who are believed to have STIs (Low estimate: 51.6%; High estimate: 75.5%; figures from [6] calculated from the percentage of CSW who do not have any STIs)

Average proportion of STDs treated effectively cured

0.8 (0.7–0.9)

Triangular

No data, treatment is assumed to be fairly effective.

Proportion reporting using condoms:

  

Intervention survey data from 1999 and 2003 [4]. 95% CI confidence intervals calculated using STATA.

Before/Unreached:

   

Never

0.38 (0.33–0.44)

Normal

 

Sometimes

0.29

(0.24–0.34)

Normal

 

Always

0.33

(0.27–0.37)

Normal

 

After/Reached:

   

Never

0.047 (0.028–0.073)

Normal

 

Sometimes

0.14 (0.11–0.18)

Normal

 

Always

0.80 (0.75–0.84)

Normal

 

Epidemiological

   

Initial HIV prevalence amongst sex workers (first survey from 1999)

11.7% (8.4%–15.9%)

Normal

Survey data from 1999 [4] (Lower and upper estimates are 95% confidence intervals of the point estimates).

Average duration of generic STD included in model (months)

  

Varied in order to fit the STD prevalence in 1999 and 2003 surveys [6].

CSW

1 (0.5–1.5)

Uniform

 

CL

1 (0.5–1.5)

Uniform

 

Average duration of initial high infectivity phase (months)

1.5 (1–2)

Triangular

[10]

Average median duration between HIV infection and morbidity (months)

95

Constant

Median disease progression from HIV infection to AIDS takes 7.9 years in a cohort study in Mumbai, India. This was drawn from a truncated Weibull distribution [36].

Behavioural

   

Average time span women sell sex (months)

(90–180)

Uniform

In the 2003 survey, average age of CSW = 33 years, average age when became CSW = 25.4 years [6]. Difference was used to estimate the lower bound, and the upper bound was set to twice the lower bound.

Average time span men buy sex (months)

(60–120)

Uniform

Median age (range) of CL is 28 (18,49); Median age at first sex with any commercial female partner (range) is 23 (10,40) [37]. Difference was used to estimate the lower bound, and the upper bound was set to twice the lower bound

Average number of clients per month per unreached CSW (using 1999 figure)

133 (119–157)

N/A

Average number of sexual partners per day during last month [6] and data from routine monthly reports between May 2002 and December 2003 were used to calculate an average.

Average number of clients per month per reached sex worker (using 2003 figure)

119 (107–140)

Triangular

Monthly reports of Jyoti Sangh from May 2002 to Dec 2003.

Average additional number of clients per month per unreached CSW

14 (11.6–17.0)

Uniform

Difference between the two figures above, calculated using Solver, using percentages from the two surveys [6].

Number of sex acts between one client and one sex worker in one encounter

1

--

No data. It is assumed to be near one, and that after discussion with GJ it was decided to be one.

Average number of CSWs seen by clients per month

(1–8)

Uniform

NACO survey reported median number of commercial female partners seen by a client in the last 3 months is 6 (1,27) [37]. However, high estimates of this parameter result in very high STI prevalences and so a lower range was used for modeling.

Proportion of time condom used, corresponding to:

   

"None of the time"

0 (0–0.2)

Triangular

Zero was chosen as point estimate as it is the conservative estimation based on the definition "None of the time".

"Some of the time"

0.5 (0.2–0.7)

Triangular

Question framed in the questionnaire is 2 or 3 out of 5. So mean of 40% and 60% is 50% [6].

"All of the time"

0.8 (0.7–1)

Triangular

Question framed in the questionnaire is > 3 out of 5. So mean of 60% and 100% is 80% [6].

Transmission Probabilities

   

Transmission probability of HIV per sex act:

  

[12, 14, 38]

Male to Female

0.002 (0.001–0.003)

Uniform

 

Female to Male

0.001 (0.0005–0.003)

N/A

 

Ratio of transmission probability: (Female to Male)/(Male to Female)

0.5 (0.5–1)

Triangular

 

Transmission probability of generic STD per sex act:

  

[13, 15-20]

Male to Female

0.25 (0.1–0.5)

Triangular

 

Female to Male

0.25 (0.1–0.5)

Triangular

 

STD cofactor effect per sex act

3.1 (1.2–5)

Triangular

[8, 9]

Multiplicative cofactor during high viraemia phase of HIV infection

15 (10–20)

Triangular

[21, 22]

Proportion of time condom used that provides protection

0.85 (0.8–0.9)

Triangular

[23, 24]

  1. CSW: commercial sex workers. GJ: Prof. Gaurang Jani. STI: sexually transmitted infection. STD: sexually transmitted disease. Note: If a certain value was calculated from a population sample, then a normal distribution was used and the range is the 95% confidence interval. If it was not produced from a population sample, then the range is the proposed uncertainty in the parameter used for the model uncertainty analysis, and if it was thought that one value was more likely then a triangle distribution was used. If no information existed on which value was more likely, then a non-informative uniform distribution was used.