Cost and efficiency of public sector sexually transmitted infection clinics in Andhra Pradesh, India

Abstract

Background: Control of sexually transmitted infections (STIs) is an important part of the effort to reduce the risk of HIV/AIDS. STI clinics in the government hospitals in India provide services predominantly to the poor. Data on the cost and efficiency of providing STI services in India are not available to help guide efficient use of public resources for these services.

Is the HIV burden in India being overestimated?

“…Similarly, with the sentinel surveillance based HIV estimation method used in India, the STI component made up over a third of the total HIV estimate for Karnataka in 2005 (STI HIV prevalence 13.6%, antenatal HIV prevalence 1.25%), about a third for Maharashtra (STI HIV prevalence 10.4%, antenatal HIV prevalence 1.25%), and about half for Tamil Nadu (STI HIV prevalence 9.2%, antenatal HIV prevalence 0.5%) [2]. These observed high HIV prevalence in the STI sentinel surveillance are to a large degree due to the location of sentinel STI clinics mostly at large medical college or district headquarters hospitals that get advanced STI patients by referral [12]. …”

A population-based study of human immunodeficiency virus in south India reveals major differences from sentinel surveillance-based estimates

“…The STI component was a major contributor to the HIV overestimation with the NACO method in our comparison, causing an excess of 70% over our total population-based estimate. The location of sentinel surveillance STI clinics, mostly at large medical college or district headquarter hospitals, makes the magnitude of this overestimation very high, as these clinics get patients with advanced STI, often by referral, who are likely to have a very high risk of HIV [30], as is evident from the median HIV prevalence of 22.8% in these clinics in the sentinel surveillance of 2005 in Andhra Pradesh.…”

What Determines HIV Prevention Costs at Scale? Evidence from the Avahan Programme in India

“…Based on previous literature (Meyer‐Rath and Over ; Siapka et al, ; Dandona et al, ; Chandrashekar et al, ; Guinness et al, ; Guinness et al, ; Kumaranayake and Watts, ; Marseille et al, ; Menzies et al, ; Rosen et al, ), several potential categories of determinants of average cost were explored. The justification of covariates in each of these six categories is detailed in Table .…”

“…Following this, to include extreme values and also remove skewness in the residuals, the average unit costs were log transformed. Based on previous literature (Meyer-Rath and Over 2012; Siapka et al, 2013;Dandona et al, 2005;Chandrashekar et al, 2010;Guinness et al, 2005;Guinness et al, 2007;Kumaranayake and Watts, 2000;Marseille et al, 2007a;Menzies et al, 2012;Rosen et al, 2008), several potential categories of determinants of average cost were explored. The justification of covariates in each of these six categories is detailed in Table II. Regarding the functional form, we tested a logarithmic form versus a quadratic functional form.…”