Additional file 1: of Research protocol for an epidemiological study on estimating disease burden of pediatric HIV in Belgaum district, India

Calculation of Net Inflation factor. (DOC 175 kb

Adjusted Kaplan-Meier survival estimates by duration of programme exposure (per 1000 persons per year).

<p>The line graph presents the adjusted survival probability curves among PLHIV per 1000 persons per year since they tested positive for HIV by duration of programme exposure. The estimates are adjusted by the place of residence of PLHIV. The duration of exposure to programme is divided into four categories, i.e. 1 to 6 months, 7 to 11 months, 1–2 years and more than 2 years.</p

Differential in the profile of PLHIV registered with the programme by their survival status.

<p>Differential in the profile of PLHIV registered with the programme by their survival status.</p

Adjusted Kaplan-Meier survival estimates by CD4 count (per 1000 persons per year).

<p>The line graph shows ten-year survival probability curves among PLHIV per 1000 persons per year since they tested positive for HIV by CD4 status. The estimates are adjusted by their place of residence. The CD4 staus is divided into four categories, i.e.CD4 count less than 100, CD4 count 100–249, CD4 count 250–349 and CD4 count 350 or more.</p

Results from Cox proportional hazard model depicting the risk of mortality by selected socio-demographic, clinical and programme exposure related characteristics.

<p>Results from Cox proportional hazard model depicting the risk of mortality by selected socio-demographic, clinical and programme exposure related characteristics.</p

Mortality rates among PLHIV by selected background characteristics.

<p>The bar diagram demonstrates the estimated mortality rates among PLHIV per 1000 population per year. The estimated mortality rates are also disagreegated by sex of the PLHIV, their age, literacy, place of residence, ART status and presence of co-infection like TB at any stage. TB at any stage is defined as ever had TB since tested positive and last contact prior to end of intervention.</p

Unadjusted percent and adjusted odds ratio and corresponding 95% confidence interval predicting the odds of risky sex among female sex workers with their socio-demographic and behavioral characteristics as predictor variables in Karnataka, India, 2007

1<p><b>Risky sex:</b> Had unprotected sex with any partner and either had anal sex or consumed alcohol before sex or had concurrent sexual partnerships.</p>2<p>AOR: Adjusted Odds Ratio, CI: Confidence Interval.</p>$<p>Unweighted numbers.</p

Percent of female sex workers reporting unprotected sex, concurrent sexual relationships, anal sex and consumption of alcohol prior to sex in Karnataka, India, 2007.

<p><b>Note:</b> The P-values were arrived at using Pearson’s Chi-square test and indicates the strength of association between background characteristics and HIV-related sexual risk factors.</p>$<p>Unweighted numbers.</p

Socio-demographic and sex work related characteristics of female sex workers, Karnataka, India, 2007.

*<p>SD: Standard Deviation.</p>$<p>Unweighted numbers.</p>1<p>A traditional form of sex work where females are married to God in childhood and at puberty they start selling sex.</p

Multilevel Analysis of the Predictors of HIV Prevalence among Pregnant Women Enrolled in Annual HIV Sentinel Surveillance in Four States in Southern India

<div><p>Background</p><p>Heterogeneity of the HIV epidemic across districts of south India is reflected in HIV positivity among antenatal clinic (ANC) attendees. Along with individual factors, contextual factors also need consideration for effective HIV interventions. Thus, identifying district and individual level factors that influence ANC HIV positivity assumes importance to intervene effectively.</p><p>Methods</p><p>Data on HIV sentinel surveillance among the ANC population were obtained from the National AIDS Control Organization (NACO) between years 2004 and 2007. Data from serial cross-sectional studies among female sex workers (FSWs) conducted during this time period in 24 districts were used to generate district level variables corresponding to parameters concerning this high risk population. Other district level data were obtained from various official/governmental agencies. Multilevel logistic regression was used to identify individual and district level factors associated with ANC-HIV positivity.</p><p>Results</p><p>The average ANC-HIV prevalence from 2004 to 2007 in the 24 integrated biological and behavioural assessments (IBBA) districts ranged from 0.25 to 3.25%. HIV positivity was significantly higher among ANC women with age≥25 years [adjusted odds ratio (AOR):1.49; 95% confidence interval (95%CI):1.27 to 1.76] compared to those with age<25 years; illiterate (AOR:1.62; 95%CI:1.03 to 2.54) compared to literate; employed in agriculture (AOR:1.34; 95%CI:1.11 to 1.62) or with occupations like driver/helper/industry/factory workers/hotel staff (AOR:1.59; 95%CI:1.26 to 2.01) compared to unemployed. District level HIV prevalence among FSWs (AOR:1.03; 95%CI:1.0 to 1.05) and percentage women marrying under 18 years were significantly associated with ANC-HIV positivity (AOR:1.02; 95%CI:1.00 to 1.04).</p><p>Conclusion</p><p>Illiteracy of the woman, higher HIV prevalence among FSWs and early marriage were associated with HIV positivity among pregnant women in southern India. In addition to targeted HIV preventive interventions among FSWs, studying and changing the behavior of FSW clients and addressing structural drivers of the epidemic might indirectly help reduce HIV infection among women in southern India.</p></div