To what extent is the HIV epidemic in southern India driven by commercial sex? A modelling analysis

Abstract

In southern India, HIV transmission could be driven by FSWs and their clients. While efforts to reduce HIV transmission due to commercial sex must continue, prevention programmes should also consider strategies to prevent transmission from clients to their noncommercial partners.

Depression and Its Relation with HIV Risk and Social Well-Being among the Brothel-Based Female Sex Workers in Kolkata, India

“…Depression found to be associated with increased rates of substance use amongst FSWs. Moreover, substance use is also associated with increased risk taking behavior, such as reduced condom use, amongst FSWs in India and globally [53][54][55][56][57].…”

Defining the population attributable fraction for infectious diseases

“…There are two main previous approaches: the traditional method using a formula developed by Levin [2] and comparing simulated epidemics with and without a risk group [5,6,10]. The traditional approach is straightforward to calculate and transparent as it relies on two parameters only: the relative risk of disease and the proportion of the population in the risk group.…”

“…A similar approach is to use a mathematical models to simulate the change in cumulative incidence over time when the effect of the risk factor is ``turned down'' by setting the relative risk to one [6,13]. If the cumulative incidence in a population at time If the risk factor in question only affects susceptibility to disease (as is the case for PAF trad ), the basic reproduction number is …”

“…Recently, PAFs have been used to quantify the contribution of risk factors to infectious disease burden, for example the contribution of malnutrition to childhood infections [5], the contribution of commercial sex work to HIV epidemics [6] or the contribution of prisons to tuberculosis incidence [7]. Some approaches have applied methodology developed for noncommunicable diseases [7][8][9].…”

“…However, it has been argued that doing this results in an underestimate of PAF as onward transmission to the general population is not captured [5,6,10] and the disease risk is not independent across groups [11]. Simulation models have been used to estimate the PAF of a risk group by "turning down'' the risk factor and observing the relative decrease in incidence [5,12] or cumulative incidence [6,10,13].…”