Atrial thrombus detection on transoesophageal echocardiography in patients with atrial fibrillation undergoing cardioversion or catheter ablation: A pooled analysis of rates and predictors

Objective: To summarize data on the rates and predictors of left atrial thrombus/ left atrial appendage thrombus (LAT/LAAT) detection by transoesophageal echocardiography (TEE) before electrical cardioversion (ECV) or catheter ablation (CA) for atrial fibrillation (AF). Methods: EMBASE, MEDLINE, and Web of Science Core Collection were searched to identify all studies providing relevant data and published by October 7, 2020. A random‐effects meta‐analysis method was used to pool effect size estimates. Results: A total of 85 studies were included, reporting data from 56 660 patients with AF. In patients undergoing CA and ECV, the pooled prevalence of LAT/LAAT was 1.8% and 7.5% in those not on oral anticoagulation (OAC), 1.8% and 5.5% in those taking OAC, and 1.3% and 4.9% in case of adequate OAC, respectively. According to the type of OAC, the prevalence was 2.0% and 7.6% for vitamin K antagonist, 1.3% and 3.5% for direct oral anticoagulant. Predictors of LAT/LAAT detection were nonparoxysmal AF (odds ratio [OR]: 3.6, 95% confidence interval: 2.4–5.2), hypertension (OR: 2.9, 1.2–7.0), previous stroke (OR: 3.0, 1.6–5.63), heart failure (OR: 4.3, 2.7–6.8), and CHADS2 score ≥2 (OR: 3.3, 1.9–5.8) for patients undergoing CA; and heart failure (OR: 2.8, 1.3–6.2) and the CHA2DS2‐VASc score (OR: 2.55, 1.5–4.5) for those undergoing ECV. Conclusion: The prevalence of LAT/LAAT in AF patients undergoing ECV or CA varies widely, mainly due to differences in patient risk profiles and OAC types. Further research should determine whether the predictors of LAT/LAAT detection identified by this study could be used to select patients who require preprocedural TEE.Jean Jacques Noubiap, Thomas A. Agbaedeng, Aude Laetitia Ndoadoumgue, Ulrich Flore Nyaga, Andre Pascal Kengn

Atrial fibrillation detection using insertable cardiac monitor after stroke: a real-word cohort study

First published: 09 November 2022Objective: This study aimed to report the real‐world atrial fibrillation (AF) diagnostic yield of the implantable cardiac monitor (ICM) in patients with stroke or transient ischemic attack (TIA), and compare it to patients with an ICM for unexplained syncope. Methods: We used patient data from device clinics across the United States of America with ICM remote monitoring via PaceMate™, implanted for stroke or TIA, and unexplained syncope. Patients with known AF or atrial flutter were excluded. The outcome was AF lasting ≥2 min, adjudicated by International Board of Heart Rhythm Examiners certified cardiac device specialists. Results: We included a total of 2469 patients, 51.1% with stroke or TIA (mean age: 69.7 [SD: 12.2] years, 41.1% female) and 48.9% with syncope (mean age: 67.0 [SD: 17.1] years, 59.4% female). The cumulative AF detection rate in patients with stroke or TIA was 5.5%, 8.9%, and 14.0% at 12, 24, and 36 months, respectively. The median episode duration was 73 (interquartile range: 10–456) min, ranging from 2 min to 40.9 days, with 52.3%, 28.6%, and 4.4% of episodes lasting at least 1, 6, and 24 h, respectively. AF detection was increased by age (adjusted hazard ratio [for every 1‐year increase]: 1.024, 95% confidence interval: 1.008–1.040; p = .003), but was not influenced by sex (p = .089). For comparison, the cumulative detection rate at 12, 24, and 36 months were, respectively, 2.4%, 5.2%, and 7.4% in patients with syncope. Conclusion: Patients with stroke or TIA have a higher rate of AF detection. However, this real‐world study shows significantly lower AF detection rates than what has been previously reported.Jean J. Noubiap, Gijo Thomas, Melissa E. Middeldorp, John L. Fitzgerald, Curtis Harper, Prashanthan Sander

Sex disparities in enrolment and reporting of outcomes by sex in contemporary clinical trials of atrial fibrillation

Background:Underrepresentation of females in randomized controlled trials (RCTs)limits generalizability and quality of the evidence guiding treatment of females. This study aimed to measure the sex disparities in participants' recruitment in RCTs of atrial fibrillation (AF) and determine associated factors, and to describe the frequency of outcomes reported by sex. Methods:MEDLINE was searched to identify RCTs of AF published between January 1, 2011, and November 20, 2021, in 12 top‐tier journals. We measured the enrollment of females using the enrollment disparity difference (EDD) which is the difference between the proportion of females in the trial and the proportion of females with AF in the underlying general population (obtained from the Global Burden of Disease). Random‐effects meta‐analyses of the EDD were performed, and multivariable meta‐regression was used to explore factors associated with disparity estimates. We also determined the proportion of trials that included sex‐stratified results. Results:Out of 1133 records screened, 142 trials were included, reporting on a total of 133 532 participants. The random‐effects summary EDD was−0.125 (95%confidence interval [CI] =−0.143 to−0.108), indicating that females were under‐enrolled by 12.5 percentage points. Female enrollment was higher in trials with higher sample size (750, adjusted odds ratio [aOR] 1.065, 95% CI:1.008–1.125), higher mean participants' age (aOR: 1.006, 95% CI: 1.002–1.009), and lower in trials conducted in North America compared to Europe (aOR: 0.945, 95% CI:0.898–0.995). Only 36 trials (25.4%) reported outcomes by sex, and of these 29(80.6%) performed statistical testing of the sex‐by‐treatment interaction. Conclusion:Females remain substantially less represented in RCTs of AF, and sex‐stratified reporting of primary outcomes is infrequent. These findings call for urgent action to improve sex equity in enrollment and sex‐stratified outcomes' reporting in RCTs of AF.Jean Jacques Noubiap, Gijo Thomas, Ulrich Flore Nyaga, John L. Fitzgerald, Celine Gallagher, Melissa E. Middeldorp, Prashanthan Sander

GJB2 and GJB6 mutations in hereditary recessive non-syndromic hearing impairment in Cameroon

This study aimed to investigate GJB2 (connexin 26) and GJB6 (connexin 30) mutations associated with familial non-syndromic childhood hearing impairment (HI) in Cameroon. We selected only families segregating HI, with at least two affected individuals and with strong evidence of non-environmental causes. DNA was extracted from peripheral blood, and the entire coding region of GJB2 was interrogated using Sanger sequencing. Multiplex PCR and Sanger sequencing were used to analyze the prevalence of the GJB6-D3S1830 deletion. A total of 93 patients, belonging to 41 families, were included in the analysis. Hearing impairment was sensorineural in 51 out of 54 (94.4%) patients. Pedigree analysis suggested autosomal recessive inheritance in 85.4% (35/41) of families. Hearing impairment was inherited in an autosomal dominant and mitochondrial mode in 12.2% (5/41) and 2.4% (1/41) of families, respectively. Most HI participants were non-syndromic (92.5%; 86/93). Four patients from two families presented with type 2 Waardenburg syndrome, and three cases of type 2 Usher syndrome were identified in one family. No GJB2 mutations were found in any of the 29 families with non-syndromic HI. Additionally, the GJB6-D3S1830 deletion was not identified in any of the HI patients. This study confirms that mutations in the GJB2 gene and the del(GJB6-D13S1830) mutation do not contribute to familial HI in Cameroon.Edmond Tingang Wonkam, Emile Chimusa, Jean Jacques Noubiap, Samuel Mawuli Adadey, Jean Valentin F. Fokouo and Ambroise Wonka

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Published Online August 27, 2020Background: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings: Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC.GBD 2019 Universal Health Coverage Collaborators. Rafael Lozano ... Peter S Azzopardi ... Bernhard T Baune ... Dinesh Bhandari ... Liliana G Ciobanu ... Tiffany K Gill ... Ratilal Lalloo ... Jean Jacques Noubiap ... et al

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Published online: 12 October 2021Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Damaris Kinyoki, Aaron E. Osgood-Zimmerman, Natalia V. Bhattacharjee, Local Burden of Disease Anaemia Collaborators, Nicholas J. Kassebaum, and Simon I. Hay. (Local Burden of Disease Anaemia Collaborators: Lauren E. Schaeffer ...Muktar Beshir Ahmed ... Habtamu Abera Areri ... Dinesh Bhandari ... Tiffany K. Gill ... Jean Jacques Noubiap ... Andrew T. Olagunju ... et al.

Primary stroke prevention worldwide : translating evidence into action

Funding Information: The stroke services survey reported in this publication was partly supported by World Stroke Organization and Auckland University of Technology. VLF was partly supported by the grants received from the Health Research Council of New Zealand. MOO was supported by the US National Institutes of Health (SIREN U54 HG007479) under the H3Africa initiative and SIBS Genomics (R01NS107900, R01NS107900-02S1, R01NS115944-01, 3U24HG009780-03S5, and 1R01NS114045-01), Sub-Saharan Africa Conference on Stroke Conference (1R13NS115395-01A1), and Training Africans to Lead and Execute Neurological Trials & Studies (D43TW012030). AGT was supported by the Australian National Health and Medical Research Council. SLG was supported by a National Heart Foundation of Australia Future Leader Fellowship and an Australian National Health and Medical Research Council synergy grant. We thank Anita Arsovska (University Clinic of Neurology, Skopje, North Macedonia), Manoj Bohara (HAMS Hospital, Kathmandu, Nepal), Denis ?erimagi? (Poliklinika Glavi?, Dubrovnik, Croatia), Manuel Correia (Hospital de Santo Ant?nio, Porto, Portugal), Daissy Liliana Mora Cuervo (Hospital Moinhos de Vento, Porto Alegre, Brazil), Anna Cz?onkowska (Institute of Psychiatry and Neurology, Warsaw, Poland), Gloria Ekeng (Stroke Care International, Dartford, UK), Jo?o Sargento-Freitas (Centro Hospitalar e Universit?rio de Coimbra, Coimbra, Portugal), Yuriy Flomin (MC Universal Clinic Oberig, Kyiv, Ukraine), Mehari Gebreyohanns (UT Southwestern Medical Centre, Dallas, TX, USA), Ivete Pillo Gon?alves (Hospital S?o Jos? do Avai, Itaperuna, Brazil), Claiborne Johnston (Dell Medical School, University of Texas, Austin, TX, USA), Kristaps Jurj?ns (P Stradins Clinical University Hospital, Riga, Latvia), Rizwan Kalani (University of Washington, Seattle, WA, USA), Grzegorz Kozera (Medical University of Gda?sk, Gda?sk, Poland), Kursad Kutluk (Dokuz Eylul University, ?zmir, Turkey), Branko Malojcic (University Hospital Centre Zagreb, Zagreb, Croatia), Micha? Maluchnik (Ministry of Health, Warsaw, Poland), Evija Migl?ne (P Stradins Clinical University Hospital, Riga, Latvia), Cassandra Ocampo (University of Botswana, Princess Marina Hospital, Botswana), Louise Shaw (Royal United Hospitals Bath NHS Foundation Trust, Bath, UK), Lekhjung Thapa (Upendra Devkota Memorial-National Institute of Neurological and Allied Sciences, Kathmandu, Nepal), Bogdan Wojtyniak (National Institute of Public Health, Warsaw, Poland), Jie Yang (First Affiliated Hospital of Chengdu Medical College, Chengdu, China), and Tomasz Zdrojewski (Medical University of Gda?sk, Gda?sk, Poland) for their comments on early draft of the manuscript. The views expressed in this article are solely the responsibility of the authors and they do not necessarily reflect the views, decisions, or policies of the institution with which they are affiliated. We thank WSO for funding. The funder had no role in the design, data collection, analysis and interpretation of the study results, writing of the report, or the decision to submit the study results for publication. Funding Information: The stroke services survey reported in this publication was partly supported by World Stroke Organization and Auckland University of Technology. VLF was partly supported by the grants received from the Health Research Council of New Zealand. MOO was supported by the US National Institutes of Health (SIREN U54 HG007479) under the H3Africa initiative and SIBS Genomics (R01NS107900, R01NS107900-02S1, R01NS115944-01, 3U24HG009780-03S5, and 1R01NS114045-01), Sub-Saharan Africa Conference on Stroke Conference (1R13NS115395-01A1), and Training Africans to Lead and Execute Neurological Trials & Studies (D43TW012030). AGT was supported by the Australian National Health and Medical Research Council. SLG was supported by a National Heart Foundation of Australia Future Leader Fellowship and an Australian National Health and Medical Research Council synergy grant. We thank Anita Arsovska (University Clinic of Neurology, Skopje, North Macedonia), Manoj Bohara (HAMS Hospital, Kathmandu, Nepal), Denis Čerimagić (Poliklinika Glavić, Dubrovnik, Croatia), Manuel Correia (Hospital de Santo António, Porto, Portugal), Daissy Liliana Mora Cuervo (Hospital Moinhos de Vento, Porto Alegre, Brazil), Anna Członkowska (Institute of Psychiatry and Neurology, Warsaw, Poland), Gloria Ekeng (Stroke Care International, Dartford, UK), João Sargento-Freitas (Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal), Yuriy Flomin (MC Universal Clinic Oberig, Kyiv, Ukraine), Mehari Gebreyohanns (UT Southwestern Medical Centre, Dallas, TX, USA), Ivete Pillo Gonçalves (Hospital São José do Avai, Itaperuna, Brazil), Claiborne Johnston (Dell Medical School, University of Texas, Austin, TX, USA), Kristaps Jurjāns (P Stradins Clinical University Hospital, Riga, Latvia), Rizwan Kalani (University of Washington, Seattle, WA, USA), Grzegorz Kozera (Medical University of Gdańsk, Gdańsk, Poland), Kursad Kutluk (Dokuz Eylul University, İzmir, Turkey), Branko Malojcic (University Hospital Centre Zagreb, Zagreb, Croatia), Michał Maluchnik (Ministry of Health, Warsaw, Poland), Evija Miglāne (P Stradins Clinical University Hospital, Riga, Latvia), Cassandra Ocampo (University of Botswana, Princess Marina Hospital, Botswana), Louise Shaw (Royal United Hospitals Bath NHS Foundation Trust, Bath, UK), Lekhjung Thapa (Upendra Devkota Memorial-National Institute of Neurological and Allied Sciences, Kathmandu, Nepal), Bogdan Wojtyniak (National Institute of Public Health, Warsaw, Poland), Jie Yang (First Affiliated Hospital of Chengdu Medical College, Chengdu, China), and Tomasz Zdrojewski (Medical University of Gdańsk, Gdańsk, Poland) for their comments on early draft of the manuscript. The views expressed in this article are solely the responsibility of the authors and they do not necessarily reflect the views, decisions, or policies of the institution with which they are affiliated. We thank WSO for funding. The funder had no role in the design, data collection, analysis and interpretation of the study results, writing of the report, or the decision to submit the study results for publication. Funding Information: VLF declares that the PreventS web app and Stroke Riskometer app are owned and copyrighted by Auckland University of Technology; has received grants from the Brain Research New Zealand Centre of Research Excellence (16/STH/36), Australian National Health and Medical Research Council (NHMRC; APP1182071), and World Stroke Organization (WSO); is an executive committee member of WSO, honorary medical director of Stroke Central New Zealand, and CEO of New Zealand Stroke Education charitable Trust. AGT declares funding from NHMRC (GNT1042600, GNT1122455, GNT1171966, GNT1143155, and GNT1182017), Stroke Foundation Australia (SG1807), and Heart Foundation Australia (VG102282); and board membership of the Stroke Foundation (Australia). SLG is funded by the National Health Foundation of Australia (Future Leader Fellowship 102061) and NHMRC (GNT1182071, GNT1143155, and GNT1128373). RM is supported by the Implementation Research Network in Stroke Care Quality of the European Cooperation in Science and Technology (project CA18118) and by the IRIS-TEPUS project from the inter-excellence inter-cost programme of the Ministry of Education, Youth and Sports of the Czech Republic (project LTC20051). BN declares receiving fees for data management committee work for SOCRATES and THALES trials for AstraZeneca and fees for data management committee work for NAVIGATE-ESUS trial from Bayer. All other authors declare no competing interests. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseStroke is the second leading cause of death and the third leading cause of disability worldwide and its burden is increasing rapidly in low-income and middle-income countries, many of which are unable to face the challenges it imposes. In this Health Policy paper on primary stroke prevention, we provide an overview of the current situation regarding primary prevention services, estimate the cost of stroke and stroke prevention, and identify deficiencies in existing guidelines and gaps in primary prevention. We also offer a set of pragmatic solutions for implementation of primary stroke prevention, with an emphasis on the role of governments and population-wide strategies, including task-shifting and sharing and health system re-engineering. Implementation of primary stroke prevention involves patients, health professionals, funders, policy makers, implementation partners, and the entire population along the life course.publishersversionPeer reviewe

Mapping child growth failure across low- and middle-income countries

Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0�59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3�5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization�s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99 of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40 and wasting to less than 5 by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications. © 2020, The Author(s)

Mapping subnational HIV mortality in six Latin American countries with incomplete vital registration systems

BackgroundHuman immunodeficiency virus (HIV) remains a public health priority in Latin America. While the burden of HIV is historically concentrated in urban areas and high-risk groups, subnational estimates that cover multiple countries and years are missing. This paucity is partially due to incomplete vital registration (VR) systems and statistical challenges related to estimating mortality rates in areas with low numbers of HIV deaths. In this analysis, we address this gap and provide novel estimates of the HIV mortality rate and the number of HIV deaths by age group, sex, and municipality in Brazil, Colombia, Costa Rica, Ecuador, Guatemala, and Mexico.MethodsWe performed an ecological study using VR data ranging from 2000 to 2017, dependent on individual country data availability. We modeled HIV mortality using a Bayesian spatially explicit mixed-effects regression model that incorporates prior information on VR completeness. We calibrated our results to the Global Burden of Disease Study 2017.ResultsAll countries displayed over a 40-fold difference in HIV mortality between municipalities with the highest and lowest age-standardized HIV mortality rate in the last year of study for men, and over a 20-fold difference for women. Despite decreases in national HIV mortality in all countries-apart from Ecuador-across the period of study, we found broad variation in relative changes in HIV mortality at the municipality level and increasing relative inequality over time in all countries. In all six countries included in this analysis, 50% or more HIV deaths were concentrated in fewer than 10% of municipalities in the latest year of study. In addition, national age patterns reflected shifts in mortality to older age groups-the median age group among decedents ranged from 30 to 45years of age at the municipality level in Brazil, Colombia, and Mexico in 2017.ConclusionsOur subnational estimates of HIV mortality revealed significant spatial variation and diverging local trends in HIV mortality over time and by age. This analysis provides a framework for incorporating data and uncertainty from incomplete VR systems and can help guide more geographically precise public health intervention to support HIV-related care and reduce HIV-related deaths.Peer reviewe

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health