Prevalence of Disability in Children and Adolescents in India, 2011

Background: Child disability is an emerging global health priority. There is lack of statebased analysis of all types of disabilities in children and adolescents in India. Objective: To measure the prevalence of disability and describe the types of disability by gender, advancing age, states and geographical regions in Indian population aged 19 years and below. Methods: Disability data restricted to age 19 years and below of the 2011 Census of India was analyzed. Disability rates per 100,000 children and adolescent population and age-adjusted disability rates were calculated. Results: Disability rate of 1640 per 100,000 was observed in those aged 19 years and below in India in 2011. Nine Indian states and Union Territories had disability rates above the national average. Of the total disability, hearing, seeing and movement related disabilities were 20, 18 and 13% respectively. Disability rates increased with the advancement of age; highest disability rate of 1926 per 100,000 in those aged 10 to 19 years. Males had higher disability rates compared to females (1754 vs. 1516 per 100,000). The disability rates were higher in urban than in rural areas (1805 vs. 1582 per 100,000). Conclusion: There was 1.6% of those aged 19 years and below in India with either physical or mental disability. Further studies on the underlying causes and prevention strategies are essential to reduce the burden of disability in the population aged 19 years and below

A Bayesian approach to study the space time variation of leprosy in an endemic area of Tamil Nadu, South India

<p>Abstract</p> <p>Background</p> <p>In leprosy endemic areas, patients are usually spatially clustered and not randomly distributed. Classical statistical techniques fail to address the problem of spatial clustering in the regression model. Bayesian method is one which allows itself to incorporate spatial dependence in the model. However little is explored in the field of leprosy. The Bayesian approach may improve our understanding about the variation of the disease prevalence of leprosy over space and time.</p> <p>Methods</p> <p>Data from an endemic area of leprosy, covering 148 panchayats from two taluks in South India for four time points between January 1991 and March 2003 was used. Four Bayesian models, namely, space-cohort and space-period models with and without interactions were compared using the Deviance Information Criterion. Cohort effect, period effect over four time points and spatial effect (smoothed) were obtained using WinBUGS. The spatial or panchayat effect thus estimated was compared with the raw standardized morbidity (leprosy prevalence) rate (SMR) using a choropleth map. The possible factors that might have influenced the variations of prevalence of leprosy were explored.</p> <p>Results</p> <p>Bayesian models with the interaction term were found to be the best fitted model. Leprosy prevalence was higher than average in the older cohorts. The last two cohorts 1987–1996 and 1992–2001 showed a notable decline in leprosy prevalence. Period effect over 4 time points varied from a high of 3.2% to a low of 1.8%. Spatial effect varied between 0.59 and 2. Twenty-six panchayats showed significantly higher prevalence of leprosy than the average when Bayesian method was used and it was 40 panchayats with the raw SMR.</p> <p>Conclusion</p> <p>Reduction of prevalence of leprosy was 92% for persons born after 1996, which could be attributed to various intervention and treatment programmes like vaccine trial and MDT. The estimated period effects showed a gradual decline in the risk of leprosy which could be due to better nutrition, hygiene and increased awareness about the disease. Comparison of the maps of the relative risk using the Bayesian smoothing and the raw SMR showed the variation of the geographical distribution of the leprosy prevalence in the study area. Panchayat or spatial effects using Bayesian showed clustersing of leprosy cases towards the northeastern end of the study area which was overcrowded and population belonging to poor economic status.</p

Estimation of HIV Prevalence among the Female Population in South India: A Bayesian Approach

Introduction: The HIV Sentinel Surveillance (HSS) conducted by National AIDS Control Organization (NACO) is the predominant data source for HIV estimations in India. While the HSS targets the key populations at risk of HIV infection, the National Family Health Survey (NFHS) measures the community- based HIV prevalence. Improvised HIV estimates in India were attributed to the HIV prevalence data obtained from the NACO-HSS and NFHS. Methods: Bayesian analysis was performed to determine the state-level prevalence of HIV among females in seven South Indian States. The analysis involved plotting the prior, likelihood, and posterior distributions, facilitating a visual assessment of the data. The HIV prevalence among females calculated from the NFHS (2015-16) survey data was used for prior distributions. HIV prevalence among pregnant women obtained from the HIV Sentinel Surveillance 2019 was used for likelihood. Bayesian analysis was performed using the R programming (RStudio 2022.02.0). A posterior probability distribution was obtained using the prior distribution and the likelihood by applying the Bayes theorem. Graphical representation was achieved through R's plotting functions. Kerala and Pondicherry were not included in the analysis due to zero or very low prevalence reported in both NFHS and HSS. Results: The Bayesian estimates of HIV prevalence among females were 0.38 % [95% CI:0.29 - 0.47] in Andhra Pradesh, 0.28 [95% CI:0.23 - 0.35] in Karnataka, 0.27 [95% CI:0.20 - 0.34] Odisha, 0.27 % [95% CI:0.19 - 0.36] in Telangana and 0.19 [95% CI:0.15 - 0.24] in Tamil Nadu. Conclusion: Bayesian techniques present a versatile and robust strategy for modelling and analysing HIV- related data, offering a flexible and powerful approach to data analysis

Cholera Outbreak Linked with Lack of Safe Water Supply Following a Tropical Cyclone in Pondicherry, India, 2012

In the aftermath of a severe cyclonic storm on 7 January 2012, a cluster of acute diarrhoea cases was reported from two localities in Pondicherry, Southern India. We investigated the outbreak to identify causes and recommend control measures. We defined a case as occurrence of diarrhoea of more than three loose stools per day with or without vomiting in a resident of affected areas during 6-18 January 2012. We used active (door-to-door survey) and stimulated passive (healthy facility-based) surveillance to identify cases. We described the outbreak by time, place, and person. We compared the case-patients with up to three controls without any apparent signs and symptoms of diarrhoea and matched for age, gender, and neighbourhood. We calculated matched odds ratio (MOR), 95% confidence intervals (CI), and population attributable fractions (PAF). We collected rectal swabs and water samples for laboratory diagnosis and tested water samples for microbiological quality. We identified 921 cases and one death among 8,367 residents (attack rate: 11%, case-fatality: 0.1%). The attack rate was the highest among persons of 50 years and above (14%) and females (12%). The outbreak started on 6 January and peaked on the 9th and lasted till 14 January. Cases were clustered around two major leakages in water supply system. Nine of the 16 stool samples yielded V. cholerae O1 Ogawa. We identified that consumption of water from the public distribution system (MOR=37, 95% CI 4.9-285, PAF: 97%), drinking unboiled water (MOR=35, 95% CI 4.5-269, PAF: 97%), and a common latrine used by two or more households (MOR=2.7, 95% CI 1.3-5.6) were independently associated with cholera. Epidemiological evidence suggested that this outbreak was due to ingestion of water contaminated by drainage following rains during cyclone. We recommended repair of the water supply lines, cleaning-up of the drains, handwashing, and drinking of boiled water

Burden of obesity in the Eastern Mediterranean Region: findings from the Global Burden of Disease 2015 study

Mokdad AH, El Bcheraoui C, Afshin A, et al. Burden of obesity in the Eastern Mediterranean Region: findings from the Global Burden of Disease 2015 study. INTERNATIONAL JOURNAL OF PUBLIC HEALTH. 2018;63(Suppl. 1):165-176.We used the Global Burden of Disease (GBD) 2015 study results to explore the burden of high body mass index (BMI) in the Eastern Mediterranean Region (EMR). We estimated the prevalence of overweight and obesity among children (2-19 years) and adults (20 years) in 1980 and 2015. The burden of disease related to high BMI was calculated using the GBD comparative risk assessment approach. The prevalence of obesity increased for adults from 15.1% (95% UI 13.4-16.9) in 1980 to 20.7% (95% UI 18.8-22.8) in 2015. It increased from 4.1% (95% UI 2.9-5.5) to 4.9% (95% UI 3.6-6.4) for the same period among children. In 2015, there were 417,115 deaths and 14,448,548 disability-adjusted life years (DALYs) attributable to high BMI in EMR, which constitute about 10 and 6.3% of total deaths and DALYs, respectively, for all ages. This is the first study to estimate trends in obesity burden for the EMR from 1980 to 2015. We call for EMR countries to invest more resources in prevention and health promotion efforts to reduce this burden

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18 : a modelling study

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2 ·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676· 5 (513· 6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8–8120·3]) cases per 100000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0–1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81· 1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020. Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas

Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016

Copyright © 2018 The Author(s). Published by Elsevier Ltd. Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle- SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view - and subsequent provision - of quality health care for all populations

Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016

Background: A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97\ub71 (95% UI 95\ub78-98\ub71) in Iceland, followed by 96\ub76 (94\ub79-97\ub79) in Norway and 96\ub71 (94\ub75-97\ub73) in the Netherlands, to values as low as 18\ub76 (13\ub71-24\ub74) in the Central African Republic, 19\ub70 (14\ub73-23\ub77) in Somalia, and 23\ub74 (20\ub72-26\ub78) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91\ub75 (89\ub71-93\ub76) in Beijing to 48\ub70 (43\ub74-53\ub72) in Tibet (a 43\ub75-point difference), while India saw a 30\ub78-point disparity, from 64\ub78 (59\ub76-68\ub78) in Goa to 34\ub70 (30\ub73-38\ub71) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4\ub78-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20\ub79-point to 17\ub70-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17\ub72-point to 20\ub74-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle- SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016