Suchergebnisse

Dengue's re-emerging epidemiology poses a major global health threat. India contributes significantly to the global communicable disease burden has been declared highly dengue-endemic, exposing public health authorities to severe challenges. Our study aims to provide a deeper understanding of India's urban dengue surveillance policies as well as to explore the organisation, functioning and integration of existing disease control pillars. We conducted a qualitative regional case study, consisting of semi-structured expert interviews and observational data, covering the urban region of Hyderabad in South India. Our findings indicate that Hyderabad's dengue surveillance system predominantly relies on public reporting units, neglecting India's large private health sector. The surveillance system requires further strengthening and additional efforts to efficiently integrate existing governmental initiatives at all geographical levels and administrative boundaries. We concluded with recommendations for improved consistency, accuracy, efficiency and reduction of system fragmentation to enhance the integration of dengue surveillance and improved health information in urban India. Finally, our study underlines India's overall need to increase investment in public health and health infrastructures. That requires coordinated and multi-level action targeting the development of a competent, effective and motivated public health cadre, as well as truly integrated surveillance and epidemic response infrastructure, for dengue and beyond.

Infectious disease surveillance, timely detection and early warning of outbreaks present a complex challenge to health authorities in India. Approaches based on the use of unexplored data sources, like emergency medical services (EMS) data, can contribute to the further advancement of public health surveillance capacities in India and support and strengthen the Integrated Disease Surveillance Programme (IDSP) strategy. This research followed a mixed method approach including a series of semi-structured interviews and fever data analysis of the EMS operating dispatch system in Andra Pradesh, India. In this paper, we explore whether routinely collected EMS health data can improve sustainable infectious disease surveillance and early warning capacity. The result highlights the need for improved surveillance systems for early warning of infectious diseases in India. The data availability at the EMS dispatch centre includes patient data and spatial information and can be used for near real-time analysis. Routine data relevant for health surveillance can be extracted to provide timely health information that supplements and enhances more traditional surveillance mechanisms and thus provides a cost-efficient, near real-time early warning system for the operating states. The designed intervention is sustainable and can improve infectious disease surveillance to potentially help the government officials to appropriately prioritize timely interventions to prevent infectious disease spread.

PURPOSE: In India, people with diabetes (PwDM) often seek care in the government-approved alternative medicine system, AYUSH (Ayurveda, Yoga and naturopathy, Unani, Siddha and Homeopathy). The purpose of this pilot study was to assess whether health education plus retinal imaging for diabetic retinopathy (DR) within an AYUSH hospital increased the uptake of screening for DR compared with health education and referral. METHODS: The study was a nonrandomized pilot conducted in two AYUSH hospitals. Both hospitals received intervention on educating the AYUSH practitioners about DR screening and distributing health education materials to diabetic patients. In one hospital in addition to education, retinal imaging by a trained technician with remote grading by an ophthalmologist was provided, while in another hospital PwDM were referred to nearby eye hospitals for screening. The uptake of screening was assessed through registers and phone calls. RESULTS: At baseline, only 10.7% of 178 PwDM were aware of DR and only 8% had undergone DR screening. After the intervention, in the hospital where screening was provided, all (100%) eligible patients (101) underwent digital imaging, whereas in the other hospital only 25% of 77 eligible patients underwent screening in eye hospitals (P < 0.001). CONCLUSION: AYUSH hospitals could provide a feasible and acceptable location for providing DR screening services. Further studies are required to assess scale-up of such intervention.

PURPOSE: To document the spectrum of eye diseases in people with type 2 diabetes mellitus (T2DM) reporting to large eye care facilities in India. METHODS: The selection of eye care facilities was based on the zone of the country and robustness of the programs. Only people with known T2DM certified by internist, or taking antidiabetes medications, or referred for diabetes related eye diseases were recruited. The analysis included the demographic characteristics, systemic associations, ocular comorbidities, and visual status. RESULTS: People (11,182) with T2DM were recruited in 14 eye care facilities (3 in north, 2 in south central, 4 in south, 2 in west, and 3 in east zone); two were government and 12 were non-government facilities. Hypertension was the commonest systemic association (n = 5500; 49.2%). Diabetic retinopathy (n = 3611; 32.3%) and lens opacities (n = 6407; 57.3%) were the common ocular disorders. One-fifth of eyes (n = 2077; 20.4%) were pseudophakic; 547 (5.4%) eyes had glaucoma and 277 (2.5%) eyes had retinal vascular occlusion. At presentation, 4.5% (n = 502) were blind (visual acuity 3/60 in the better eye). CONCLUSION: People with T2DM presenting at eye clinics in India have high rates of diabetic retinopathy and vision loss. Cataract is a very common occurrence. Advocacy, infrastructure strengthening, and human resource development are the key to address the growing threats of T2DM and eye care in India.

PURPOSE: Diabetes is a public health concern in India and diabetic retinopathy (DR) is an emerging cause of visual impairment and blindness. Approximately 3.35–4.55 million people with diabetes mellitus (PwDM) are at risk of vision-threatening DR (VTDR) in India. More than 2/3 of India's population resides in rural areas where penetration of modern medicine is mostly limited to the government public health system. Despite the increasing magnitude, there is no systematic screening for the complications of diabetes, including DR in the public health system. Therefore, a pilot project was initiated with the major objectives of management of DR at all levels of the government health system, initiating a comprehensive program for the detection of eye complications among PwDM at public health noncommunicable disease (NCD) clinics, augmenting the capacity of physicians, ophthalmologists and health support personnel and empowering carers/PwDM to control the risk of DR through increased awareness and self-management. METHODS: A national task force (NTF) was constituted to oversee policy formulation and provide strategic direction. 10 districts were identified for implementation across 10 states. Protocols were developed to help implement training and service delivery. RESULTS: Overall, 66,455 PwDM were screened and DR was detected in 16.2% (10,765) while VTDR was detected in 7.5%. 10.1% of those initially screened returned for the next annual assessment. There was a 7-fold increase in the number of PwDM screened and a 7.6-fold increase in the number of PwDM treated between 2016 and 2018. CONCLUSION: Services for detecting and managing DR can be successfully integrated into the existing public health system.

PURPOSE: In India, more than 800 special newborn care units (SNCUs) have been established since 2008 in government facilities. More preterm infants are now surviving and blindness from retinopathy of prematurity (ROP) is increasing. The aim of the Queen Elizabeth Diamond Jubilee Trust's initiative (2012–1019) was to improve the quality of neonatal care and integrate ROP services into the government health system using expertise in the government and nongovernment sector in four states in a sustainable and scalable manner. METHODS: State Ministries of Health were engaged and collaboration was established between three government programs (Ministry of Health and Family Welfare, Rashtriya Bal Swasthya Karyakram, and blindness prevention) and relevant professionals. Extensive training took place and equipment was provided. Implementation was guided by a multidisciplinary National Task Force and was monitored by state coordination committees. The Task Force appointed technical expert groups to support implementation through advocacy, information, education and communication materials, operational guidelines, a competency-based training curriculum, and an online database and website. RESULTS: Twenty-two ophthalmologists in government facilities were trained to screen for ROP and nine to treat ROP. Almost 13,500 preterm infants were screened in 17 SNCUs and 86% of the 456 infants with sight-threatening ROP were treated. An educational resource using latest pedagogy based on key domain areas for best practices for small and preterm neonates including ROP has been developed and pilot tested and is being evaluated and scaled up. CONCLUSION: All four states are scaling up services or have plans to scale up, and several other states have started the initiatives.

The Indian health infrastructure is struggling to handle the burgeoning number of people with diabetes. Managing the complications of diabetes in an organized manner through the government health programs is still a distant reality. Here, we describe a program aimed at addressing the problem of diabetic retinopathy in rural areas of Tumkur district in Karnataka. By amalgamating telescreening and our own novel distributive care model, we were able to screen 85% of the registered diabetics in the Government noncommunicable disease clinics and treat 95% of those needing laser therapy. We also describe the importance of using electronic medical records in public health programs which not only increase the efficiency in screening for disease but help in increasing uptake of treatment by tracking defaulters.

Background India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality. Methods We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level. Findings U5MR in India decreased from 83·1 (95% uncertainty interval [UI] 76·7–90·1) in 2000 to 42·4 (36·5–50·0) per 1000 livebirths in 2017, and NMR from 38·0 (34·2–41·6) to 23·5 (20·1–27·8) per 1000 livebirths. U5MR varied 5·7 times between the states of India and 10·5 times between the 723 districts of India in 2017, whereas NMR varied 4·5 times and 8·0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9·02% (95% UI 6·30–11·63) reduction to no significant change for U5MR and from an 8·05% (95% UI 5·34–10·74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which 68·2% (65·8–70·7) of under-5 deaths and 83·0% (80·6–85·0) of neonatal deaths in India could be attributed in 2017; 10·8% (9·1–12·4) of under-5 deaths could be attributed to unsafe water and sanitation and 8·8% (7·0–10·3) to air pollution. Interpretation India has made gains in child survival, but there are substantial variations between the states in the magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between districts within states has increased for the majority of the states. The district-level trends presented here can provide crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India.

Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Funding Bill & Melinda Gates Foundation. ; We would like to thank the countless individuals who have contributed to the Global Burden of Disease Study 2015 in various capacities. The data reported here have been supplied by the US Renal Data System (USRDS). Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Collection of these data was made possible by the US Agency for International Development (USAID) under the terms of cooperative agreement GPO-A-00-08-000_D3-00. Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. Parts of this material are based on data and information provided by the Canadian institute for Health Information. However, the analyses, conclusions, opinions and statements expressed herein are those of the author and not those of the Canadian Institute for Health information. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with license no SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law, 2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. This paper uses data from SHARE Waves 1, 2, 3 (SHARELIFE), 4 and 5 (DOIs: 10.6103/SHARE.w1.500, 10.6103/SHARE.w2.500, 10.6103/SHARE.w3.500, 10.6103/SHARE.w4.500, 10.6103/SHARE.w5.500), see Börsch-Supan and colleagues, 2013, for methodological details. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: number 211909, SHARE-LEAP: number 227822, SHARE M4: number 261982). Additional funding from the German Ministry of Education and Research, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, and OGHA_04-064) and from various national funding sources is gratefully acknowledged. This study has been realised using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation. The following individuals would like to acknowledge various forms of institutional support: Simon I Hay is funded by a Senior Research Fellowship from the Wellcome Trust (#095066), and grants from the Bill & Melinda Gates Foundation (OPP1119467, OPP1093011, OPP1106023 and OPP1132415). Amanda G Thrift is supported by a fellowship from the National Health and Medical Research Council (GNT1042600). Panniyammakal Jeemon is supported by the Wellcome Trust-DBT India Alliance, Clinical and Public Health, Intermediate Fellowship (2015–2020). Boris Bikbov, Norberto Percio, and Giuseppe Remuzzi acknowledge that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). Amador Goodridge acknowledges funding from Sistema Nacional de Investigadores de Panamá-SNI. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). Lijing L Yan is supported by the National Natural Sciences Foundation of China grants (71233001 and 71490732). Olanrewaju Oladimeji is an African Research Fellow at Human Sciences Research Council (HSRC) and Doctoral Candidate at the University of KwaZulu-Natal (UKZN), South Africa, and would like to acknowledge the institutional support by leveraging on the existing organisational research infrastructure at HSRC and UKZN. Nicholas Steel received funding from Public Health England as a Visiting Scholar in the Institute for Health Metrics and Evaluation in 2016. No individuals acknowledged received additional compensation for their efforts. ; Peer-reviewed ; Publisher Version

The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. ; Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing. ; Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163). ; Peer reviewed