[show abstract][hide abstract] ABSTRACT: Haryana was the first state in India to launch a conditional cash transfer (CCT) scheme in 1994. Initially it targeted all disadvantaged girls but was revised in 2005 to restrict it to second girl children of all groups. The benefit which accrued at girl attaining 18 years and subject to conditionalities of being fully immunized, studying till class 10 and remaining unmarried, was increased from about US$ 500 to US $ 2000. Using a mixed methods approach, we evaluated the implementation and possible impact of these two schemes.
A survey was conducted among 200 randomly selected respondents of Ballabgarh Block in Haryana to assess their perceptions of girl children and related schemes. A cohort of births during this period was assembled from population database of 28 villages in this block and changes in sex ratio at birth and in immunization coverage at one year of age among boys and girls was measured. Education levels and mean age at marriage of daughters were compared with daughters-in-law from outside Haryana. In-depth interviews were conducted among district level implementers of these schemes to assess their perceptions of programs' implementation and impact. These were analyzed using a thematic approach.
The perceptions of girls as a liability and poor (9% to 15%) awareness of the schemes was noted. The cohort analysis showed that while there has been an improvement in the indicators studied, these were similar to those seen among the control groups. Qualitative analysis identified a "conspiracy of silence" - an underplaying of the pervasiveness of the problem coupled with a passive implementation of the program and a clash between political culture of giving subsidies and a bureaucratic approach that imposed many conditionalities and documentary needs for availing of benefits.
The apparent lack of impact on the societal mindset calls for a revision in the current approach of addressing a social issue by a purely conditional cash transfer program.
International Journal for Equity in Health 01/2014; 13(1):11. · 1.71 Impact Factor
[show abstract][hide abstract] ABSTRACT: Maternal morbidity is more common than maternal death, and population-based estimates of the burden of maternal morbidity could provide important indicators for monitoring trends, priority setting and evaluating the health impact of interventions. Methods based on lay reporting of obstetric events have been shown to lack specificity and there is a need for new approaches to measure the population burden of maternal morbidity. A computer-based probabilistic tool was developed to estimate the likelihood of maternal morbidity and its causes based on self-reported symptoms and pregnancy/delivery experiences. Development involved the use of training datasets of signs, symptoms and causes of morbidity from 1734 facility-based deliveries in Benin and Burkina Faso, as well as expert review. Preliminary evaluation of the method compared the burden of maternal morbidity and specific causes from the probabilistic tool with clinical classifications of 489 recently-delivered women from Benin, Bangladesh and India.
Using training datasets, it was possible to create a probabilistic tool that handled uncertainty of women's self reports of pregnancy and delivery experiences in a unique way to estimate population-level burdens of maternal morbidity and specific causes that compared well with clinical classifications of the same data. When applied to test datasets, the method overestimated the burden of morbidity compared with clinical review, although possible conceptual and methodological reasons for this were identified.
The probabilistic method shows promise and may offer opportunities for standardised measurement of maternal morbidity that allows for the uncertainty of women's self-reported symptoms in retrospective interviews. However, important discrepancies with clinical classifications were observed and the method requires further development, refinement and evaluation in a range of settings.
Emerging Themes in Epidemiology 01/2014; 11(1):3. · 2.59 Impact Factor
[show abstract][hide abstract] ABSTRACT: Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other.
We compared the performance of open-source random forest, open-source tariff method, InterVA-4, and the King-Lu method to PCVA on five datasets comprising over 24,000 verbal autopsies from low- and middle-income countries. Metrics to assess performance were positive predictive value and partial chance-corrected concordance at the individual level, and cause-specific mortality fraction accuracy and cause-specific mortality fraction error at the population level.
The positive predictive value for the most probable COD predicted by the four CCVA methods averaged about 43% to 44% across the datasets. The average positive predictive value improved for the top three most probable CODs, with greater improvements for open-source random forest (69%) and open-source tariff method (68%) than for InterVA-4 (62%). The average partial chance-corrected concordance for the most probable COD predicted by the open-source random forest, open-source tariff method and InterVA-4 were 41%, 40% and 41%, respectively, with better results for the top three most probable CODs. Performance generally improved with larger datasets. At the population level, the King-Lu method had the highest average cause-specific mortality fraction accuracy across all five datasets (91%), followed by InterVA-4 (72% across three datasets), open-source random forest (71%) and open-source tariff method (54%).
On an individual level, no single method was able to replicate the physician assignment of COD more than about half the time. At the population level, the King-Lu method was the best method to estimate cause-specific mortality fractions, though it does not assign individual CODs. Future testing should focus on combining different computer-coded verbal autopsy tools, paired with PCVA strengths. This includes using open-source tools applied to larger and varied datasets (especially those including a random sample of deaths drawn from the population), so as to establish the performance for age- and sex-specific CODs.
BMC Medicine 01/2014; 12(1):20. · 6.68 Impact Factor
[show abstract][hide abstract] ABSTRACT: Computer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern.
The reviewed studies assessed methods' performance through various metrics: sensitivity, specificity, and chance-corrected concordance for coding individual deaths, and cause-specific mortality fraction (CSMF) error and CSMF accuracy at the population level. These results were summarized into means, medians, and ranges.
The 19 studies ranged from 200 to 50,000 deaths per study (total over 116,000 deaths). Sensitivity of PCVA versus hospital-assigned COD varied widely by cause, but showed consistently high specificity. PCVA and CCVA methods had an overall chance-corrected concordance of about 50% or lower, across all ages and CODs. At the population level, the relative CSMF error between PCVA and hospital-based deaths indicated good performance for most CODs. Random Forest had the best CSMF accuracy performance, followed closely by PCVA and the other CCVA methods, but with lower values for InterVA-3.
There is no single best-performing coding method for verbal autopsies across various studies and metrics. There is little current justification for CCVA to replace PCVA, particularly as physician diagnosis remains the worldwide standard for clinical diagnosis on live patients. Further assessments and large accessible datasets on which to train and test combinations of methods are required, particularly for rural deaths without medical attention.
BMC Medicine 01/2014; 12(1):22. · 6.68 Impact Factor
[show abstract][hide abstract] ABSTRACT: To test the hypothesis that a gender differential exists in the effect on child mortality of BCG, DTP, measles vaccine as administered under programme conditions in Ballabgarh HDSS area.
All live births in 28 villages of Ballabgarh block in North India from 2006 to 2011 were followed until 31 December 2011 or 36 months of age whichever was earlier. The period of analysis was divided into four time periods based on eligibility for vaccines under the national immunisation schedule (BCG for tuberculosis, primary and booster doses of diphtheria-tetanus-pertussis and measles). Cox proportional hazards regression was used to assess the association between sex and risk of mortality by vaccination status using age as the timescale in survival analysis and adjusting for wealth index, access to health care, the presence of a health facility in the village, parental education, type of family, birth order of the child and year of birth.
702 deaths (332 boys and 370 girls) occurred among 12 142 children in the cohort in the 3 years of follow-up giving a cumulative mortality rate of 57.5 per 1000 live births with 35% excess girl child mortality. Age at vaccination for the four vaccines did not differ by sex. There was significant excess mortality among girls after immunisation with DTP, for both primary (HR 1.65; 95% CI:1.17-2.32) and DTPb (2.21; 1.24-3.93) vaccinations. No significant excess morality among girls was noted after exposure to BCG 1.06 (0.67-1.67) or measles 1.34 (0.85-2.12) vaccine.
This study supports the contention that DTP vaccination is partially responsible for higher mortality among girls in this study population.
Tropical Medicine & International Health 09/2013; · 2.94 Impact Factor
[show abstract][hide abstract] ABSTRACT: We analyzed data from the electronic database of Health and Demographic Surveillance System (HDSS) site in Ballabgarh in North India to assess sex-specific differentials in child survival from 1992-2011. Sex ratio at birth was adverse for girls throughout the study period (821 to 866 girls per 1,000 boys) and was lowest in the period 2004-2006 at 821 girls per 1,000 boys. Overall, under-five mortality rates during the period 1992-2011 remained stagnant due to increasing neonatal mortality rate (9.2 to 27.7 P< 0.001). Mortality rates among girls were consistently and significantly higher than boys during the post-neonatal period (160% to 200% higher) as well as in childhood (160% to 230% higher). We recommend strategies to address the neonatal mortality and gender differences for further reductions in child mortality in India.
[show abstract][hide abstract] ABSTRACT: Peter Byass and colleagues raise questions about the recent, high-profile Global Burden of Disease estimates. Please see later in the article for the Editors' Summary.
PLoS Medicine 07/2013; 10(7):e1001477. · 15.25 Impact Factor
[show abstract][hide abstract] ABSTRACT: BACKGROUND: Model-based estimates of the global proportions of maternal deaths that are in HIV-infected women range from 7% to 21%, and the effects of HIV on the risk of maternal death is highly uncertain. We used longitudinal data from the Analysing Longitudinal Population-based HIV/AIDS data on Africa (ALPHA) network to estimate the excess mortality associated with HIV during pregnancy and the post-partum period in sub-Saharan Africa. METHODS: The ALPHA network pooled data gathered between June, 1989 and April, 2012 in six community-based studies in eastern and southern Africa with HIV serological surveillance and verbal-autopsy reporting. Deaths occurring during pregnancy and up to 42 days post partum were defined as pregnancy related. Pregnant or post-partum person-years were calculated for HIV-infected and HIV-uninfected women, and HIV-infected to HIV-uninfected mortality rate ratios and HIV-attributable rates were compared between pregnant or post-partum women and women who were not pregnant or post partum. FINDINGS: 138 074 women aged 15-49 years contributed 636 213 person-years of observation. 49 568 women had 86 963 pregnancies. 6760 of these women died, 235 of them during pregnancy or the post-partum period. Mean prevalence of HIV infection across all person-years in the pooled data was 17·2% (95% CI 17·0-17·3), but 60 of 118 (50·8%) of the women of known HIV status who died during pregnancy or post partum were HIV infected. The mortality rate ratio of HIV-infected to HIV-uninfected women was 20·5 (18·9-22·4) in women who were not pregnant or post partum and 8·2 (5·7-11·8) in pregnant or post-partum women. Excess mortality attributable to HIV was 51·8 (47·8-53·8) per 1000 person-years in women who were not pregnant or post partum and 11·8 (8·4-15·3) per 1000 person-years in pregnant or post-partum women. INTERPRETATION: HIV-infected pregnant or post-partum women had around eight times higher mortality than did their HIV-uninfected counterparts. On the basis of this estimate, we predict that roughly 24% of deaths in pregnant or post-partum women are attributable to HIV in sub-Saharan Africa, suggesting that safe motherhood programmes should pay special attention to the needs of HIV-infected pregnant or post-partum women. FUNDING: Wellcome Trust, Health Metrics Network (WHO).
The Lancet 05/2013; 381(9879):1763-1771. · 39.06 Impact Factor
[show abstract][hide abstract] ABSTRACT: BACKGROUND: Socioeconomic development has been considered as a solution to the problem of sex differentials at birth and under-five mortality. This paper analyses longitudinal data from the Ballabgarh Health and Demographic Surveillance System (HDSS) site in north India to check its veracity. METHODS: A cohort of children born between 1 January 2006 and 31 December 2011 at Ballabgarh HDSS were followed till death, emigration, 3 years of age or end of the study. Socioeconomic status (SES) was measured by caste, parental combined years of schooling and wealth index and divided into low, mid and high strata for each of them. Sex ratio at birth (SRB) was reported as the number of girls per 1000 boys. The Kaplan-Meier survival curves were drawn and a Cox Proportional HR of girls over boys was estimated. RESULTS: A total of 12 517 native born children (25 797 child years) were enrolled of which 710 died (death rate of 56.7/1000-live births and 27.5/1000 child-years. Socioeconomically advantaged children had significantly lower death rates. The SRB (10-16% lower) and neonatal death rate were consistently adverse for girls in the advantaged groups by all the three indicators of SES. The first month survival rates were better for girls in the lower SES categories (significant only in caste (HR 0.58; 0.37 to 0.91). High SES categories consistently showed adverse survival rates for girls (HR of 1.22 to 1.59). CONCLUSIONS: Better socioeconomic situation worsened the sex differentials, especially at birth. Therefore, specific interventions targeting gender issues are required, at least as a short-term measure.
Journal of epidemiology and community health 01/2013; · 3.04 Impact Factor
[show abstract][hide abstract] ABSTRACT: Current methods for estimating maternal mortality lack precision, and are not suitable for monitoring progress in the short run. In addition, national maternal mortality ratios (MMRs) alone do not provide useful information on where the greatest burden of mortality is located, who is concerned, what are the causes, and more importantly what sub-national variations occur. This paper discusses a maternal death surveillance and response (MDSR) system. MDSR systems are not yet established in most countries and have potential added value for policy making and accountability and can build on existing efforts to conduct maternal death reviews, verbal autopsies and confidential enquiries. Accountability at national and sub-national levels cannot rely on global, regional and national retrospective estimates periodically generated from academia or United Nations organizations but on routine counting, investigation, sub national data analysis, long term investments in vital registration and national health information systems. Establishing effective maternal death surveillance and response will help achieve MDG 5, improve quality of maternity care and eliminate maternal mortality (MMR <= 30 per 100,000 by 2030).
Reproductive Health 01/2013; 10(1):1. · 1.31 Impact Factor
[show abstract][hide abstract] ABSTRACT: Reliable population-based data on HIV infection and AIDS mortality in sub-Saharan Africa are scanty, even though that is the region where most of the world's AIDS deaths occur. There is therefore a great need for reliable and valid public health tools for assessing AIDS mortality.
The aim of this article is to validate the InterVA-4 verbal autopsy (VA) interpretative model within African populations where HIV sero-status is recorded on a prospective basis, and examine the distribution of cause-specific mortality among HIV-positive and HIV-negative people.
Data from six sites of the Alpha Network, including HIV sero-status and VA interviews, were pooled. VA data according to the 2012 WHO format were extracted, and processed using the InterVA-4 model into likely causes of death. The model was blinded to the sero-status data. Cases with known pre-mortem HIV infection status were used to determine the specificity with which InterVA-4 could attribute HIV/AIDS as a cause of death. Cause-specific mortality fractions by HIV infection status were calculated, and a person-time model was built to analyse adjusted cause-specific mortality rate ratios.
The InterVA-4 model identified HIV/AIDS-related deaths with a specificity of 90.1% (95% CI 88.7-91.4%). Overall sensitivity could not be calculated, because HIV-positive people die from a range of causes. In a person-time model including 1,739 deaths in 1,161,688 HIV-negative person-years observed and 2,890 deaths in 75,110 HIV-positive person-years observed, the mortality ratio HIV-positive:negative was 29.0 (95% CI 27.1-31.0), after adjustment for age, sex, and study site. Cause-specific HIV-positive:negative mortality ratios for acute respiratory infections, HIV/AIDS-related deaths, meningitis, tuberculosis, and malnutrition were higher than the all-cause ratio; all causes had HIV-positive:negative mortality ratios significantly higher than unity.
These results were generally consistent with relatively small post-mortem and hospital-based diagnosis studies in the literature. The high specificity in cause of death attribution achieved in relation to HIV status, and large differences between specific causes by HIV status, show that InterVA-4 is an effective and valid tool for assessing HIV-related mortality.
Global Health Action 01/2013; 6:22448. · 2.06 Impact Factor
[show abstract][hide abstract] ABSTRACT: Objective : Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. Methods : A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. Findings : A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. Conclusions : The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians.
Global Health Action 01/2013; 6:21518. · 2.06 Impact Factor
[show abstract][hide abstract] ABSTRACT: Despite considerable global attention to the issues of climate change, relatively little priority has been given to the likely effects on human health of current and future changes in the global climate. We identify three major societal determinants that influence the impact of climate change on human health, namely the application of scholarship and knowledge; economic and commercial considerations; and actions of governments and global agencies.
The three major areas are each discussed in terms of the ways in which they facilitate and frustrate attempts to protect human health from the effects of climate change. Academia still pays very little attention to the effects of climate on health in poorer countries. Enterprise is starting to recognise that healthy commerce depends on healthy people, and so climate change presents long-term threats if it compromises health. Governments and international agencies are very active, but often face immovable vested interests in other sectors. Overall, there tends to be too little interaction between the three areas, and this means that potential synergies and co-benefits are not always realised.
More attention from academia, enterprise, and international agencies needs to be given to the potential threats the climate change presents to human health. However, there needs to also be much closer collaboration between all three areas in order to capitalise on possible synergies that can be achieved between them.
Global Health Action 01/2013; 6:1-6. · 2.06 Impact Factor