Sustained progress, but no room for complacency: Results of 2015 HIV estimations in India.

BACKGROUND & OBJECTIVES: Evidence-based planning has been the cornerstone of India's response to HIV/AIDS. Here we describe the process, method and tools used for generating the 2015 HIV estimates and provide a summary of the main results. METHODS: Spectrum software supported by the UNAIDS was used to produce HIV estimates for India as a whole and its States/Union Territories. This tool takes into consideration the size and HIV prevalence of defined population groups and programme data to estimate HIV prevalence, incidence and mortality over time as well as treatment needs. RESULTS: India's national adult prevalence of HIV was 0.26 per cent in 2015. Of the 2.1 million people living with HIV/AIDS, the largest numbers were in Andhra Pradesh, Maharashtra and Karnataka. New HIV infections were an estimated 86,000 in 2015, reflecting a decline by around 32 per cent from 2007. The declining trend in incidence was mirrored in most States, though an increasing trend was detected in Assam, Chandigarh, Chhattisgarh, Gujarat, Sikkim, Tripura and Uttar Pradesh. AIDS-related deaths were estimated to be 67,600 in 2015, reflecting a 54 per cent decline from 2007. There were variations in the rate and trend of decline across India for this indicator also. INTERPRETATION & CONCLUSIONS: While key indicators measured through Spectrum modelling confirm success of the National AIDS Control Programme, there is no room for complacency as rising incidence trends in some geographical areas and population pockets remain the cause of concern. Progress achieved so far in responding to HIV/AIDS needs to be sustained to end the HIV epidemic.

Determinants of HIV positivity among injecting drug users in Delhi and Punjab.

CONTEXT: In India, the HIV positivity among injecting drug users (IDUs) stands at a staggering 7.71%. Among the states, HIV positivity among IDUs is highest in Punjab and Delhi, 21.2% and 18.3%, respectively. Interestingly, these two states are near to the "Golden Crescent." AIMS: The aim of this study was to examine the similarities and differences between the IDUs in Punjab and Delhi, in the context of vulnerability to HIV. SETTINGS AND DESIGN: This study uses data from the HIV Sentinel Surveillance-2010-2011 (HSS). The HSS is a cross-sectional data collection process for HIV surveillance in India. HSS, apart from collecting the blood samples from the respondents, also collects basic sociodemographic as well as some information on the drug use patterns of the IDUs. DATA AND METHODS: The raw data from HSS 2010-2011 were used for this study. Bivariate and multivariate analyses performed to obtain the results. RESULTS: Descriptive analyses revealed that the IDUs of Punjab and Delhi are very different from each other. In Delhi, 62.4% of IDUs inject drugs for more than 5 years; whereas in Punjab, it was only 32.4%. Majority of the Delhi IDUs (86.5%) inject more than three times a week whereas the corresponding percentage in Punjab was only 29.5%. The profiles of the HIV positives also differ between these two states. CONCLUSIONS: It would be prudent to adopt state-specific strategies to prevent the spread of HIV among the IDUs.

Consistency and quality check of survey data in India.

OBJECTIVE: Reliability of survey responses on topics such as utilization of health facilities by mother and child has long been a subject of concern. This paper explores consistency of responses from the same individuals over time on utilization of health services involving child delivery and child care. METHODS: A sub-sample survey was carried out by an independent monitoring agency in 13 states as a part of a larger Coverage Evaluation Survey of all states of India in 2009 by UNICEF, to recheck the responses to improve data quality. Our randomly chosen sub-sample consisted of 510 questionnaires regarding mothers and 497 regarding children. Differences of responses were noted and conveyed to field agencies to rectify recurring errors. Statistical analysis was conducted to find consistency of responses. RESULTS: Matching between the original and rechecked responses varied. Generally, however, the overall match was greater than 90%. CONCLUSION: Findings suggest that response inconsistencies and the manner in which they are resolved are shown to have important implications for the overall estimate of indicators of utilization of health facilities. The monitoring exercise has, therefore, addressed the quality and consistency issue, which needs further consideration in large-scale surveys. Otherwise, it poses a validity threat to data quality and results on which national policy is framed.