Abstract Background World AIDS Day has been observed on the first of December every year. Whilst there are specific themes during the commemoration, the role of conflict on HIV seems neglected and needs prioritization given the rise of conflicts globally.
Discussion The global HIV response brought substantial reduction of new HIV infections and HIV-related deaths, and increment of antiretroviral therapy coverage. Nevertheless, there is substantial inequity on the benefit of the response. Individuals with HIV in conflict zones have suffered immensely and are often neglected. The fact that the level, intensity, and number of conflicts is increasing mean more HIV people in conflict or post-conflict settings such as in Ethiopia, South Sudan, the Democratic Republic of Congo, Myanmar, Yemen Russia and Ukraine are at risk of negative HIV care and treatment outcomes. In particular, some conflicts such as the case of Ethiopia's Tigray have been marked by severe public and humanitarian crises, including medical siege, intentional damage of healthcare infrastructure, targeted attacks on health workers, displacement, and appalling incidents of conflict-related sexual violence. Yet, people living with HIV in these conflict settings seem often overlooked. It is crucial to address the unique challenges in these areas to achieve the goals of AIDS/HIV care.
Conclusion There is no ideal forum to remind the intricate relationship between conflict and the HIV epidemic other than the World AIDS Day. Thus, this this year's World AIDS Day should focus on prioritizing on tackling the direct and indirect effects of conflict on HIV transmission and treatment. This way, we can achieve the ambitious UNAIDS 95-95-95 goals and Ending AIDS by 2030.
Abstract Background Despite the fact that Sub-Saharan Africa bears a disproportionate burden of armed conflicts and HIV infection, there has been inadequate synthesis of the impact of armed conflict on HIV treatment outcomes. We summarized the available evidence on the impact of armed conflicts on HIV treatment outcomes in Sub-Saharan Africa from 2002 to 2022.
Methods We searched four databases; MEDLINE, PubMed, CINHAL, and Scopus. We also explored grey literature sources and reviewed the bibliographies of all articles to identify any additional relevant studies. We included quantitative studies published in English from January 1, 2002 to December 30, 2022 that reported on HIV treatment outcomes for patients receiving antiretroviral therapy (ART) in conflict and post-conflict areas, IDP centers, or refugee camps, and reported on their treatment outcomes from sub-Saharan Africa. Studies published in languages other than English, reporting on non-ART patients and reporting on current or former military populations were excluded. We used EndNote X9 and Covidence to remove duplicates, extracted data using JBI-MAStARI, assessed risk of bias using AHRQ criteria, reported results using PRISMA checklist, and determined Statistical heterogeneity using Cochran Q test and Higgins I2, R- and RevMan-5 software were used for meta-analysis.
Results The review included 16 studies with participant numbers ranging from 102 to 2572. Lost To Follow-Up (LTFU) percentages varied between 5.4% and 43.5%, virologic non-suppression rates ranged from 25 to 33%, adherence rates were over 88%, and mortality rates were between 4.2% and 13%. A pooled meta-analysis of virologic non-suppression rates from active conflict settings revealed a non-suppression rate of 30% (0.30 (0.26–0.33), I2 = 0.00%, p = 0.000). In contrast, a pooled meta-analysis of predictors of loss to follow-up (LTFU) from post-conflict settings identified a higher odds ratio for females compared to males (1.51 (1.05, 2.17), I2 = 0%, p = 0.03).
Conclusion The review highlights a lack of research on the relationship between armed conflicts and HIV care outcomes in SSA. The available documents lack quality of designs and data sources, and the depth and diversity of subjects covered.
OBJECTIVE: This paper aims to evaluate the potential solutions to address negative outcomes of HIV care and treatment, that were proposed by HIV care providers, researchers and HIV programme managers in Southwest Ethiopia. METHODS: A nominal group technique (NGT) was conducted with 25 experts in December 2017 in Jimma, Southwest Ethiopia. The NGT process included (a) an analysis of the previously qualitative study conducted with various Ethiopian HIV stakeholders who proposed possible solutions for HIV care and treatment; (b) recruitment of a panel of HIV experts in policy and practice to rate the proposed solutions in Ethiopia before a discussion (first round rating); (c) discussion with the panel of experts on the suggested solutions; and (d) conducting a second round of rating of proposed solutions. Content analysis and Wilcoxon signed rank test were applied to analyse the data. RESULTS: Eighteen of the 25 invited panel of experts participated in the NGT. The following proposed solutions were rated and discussed as relevant, feasible and acceptable. In order of decreasing importance, the solutions were as follows: filling gaps in legislation, HIV self‐testing, the teach‐test‐link‐trace strategy, house‐to‐house HIV testing, community antiretroviral therapy (ART) groups, providing ART in private clinics and providing ART at health posts. CONCLUSIONS: The current study findings suggested that, to address HIV negative outcomes, priority solutions could include mandatory notification of partner's HIV status, HIV self‐testing and the involvement of peer educators on the entire HIV care programme.
BACKGROUND: The present study aimed to assess the magnitude and factors associated with neglected and non-consented care during childbirth in public health facilities in Central Tigray, Ethiopia. METHODS: A health facility-based cross-sectional survey supplemented by a qualitative study was conducted from April to May 2020 among women giving birth. We included 415 participants and recruited via a systematic random sampling technique. To collect the data, a pre-tested, face-to-face exit interview using an interviewer-administered structured questionnaire was used. Neglected and non-consented care and its outcomes (yes and no) were the dependent variables, and Socio-demographic data such as (age, educational level, region, and income), and other variables associated with compassionate and respective maternity care were the independent variables. We applied bivariate and multivariate logistic regression to determine predictors for non-consented and non-confidential care components of disrespect or abuse. The in-depth interviews were analyzed using content analysis. RESULTS: Among the participants, 82.4% and 78.6% had neglected care and non-consented care among women giving birth respectively. No formal education level (AOR: 0.37, 95%, CI (0.18–0.78)) and primary education level (AOR: 0.18, 95%, CI (0.05–0.57))., mode of delivery (AOR 3.79, 95% CI 1.42–10.09), sex of skilled healthcare providers (AOR: 0.56, 95%, CI (0.34–0.93)), number of deliveries in a health Centre (AOR: 1.89, 95% CI (1.03–3.47)) predicted non-consented care, and history ANC (AOR: 8.10, 95% CI (1.33–49.51)), and federal government employee (AOR: 0.24, 95% CI (0.07–0.78)) predicted neglected care during childbirth. In-depth interview result shows the mode of delivery and sex of healthcare providers were factor associated with non-consented care and women's stay at health facilities were factor associated with neglected care. CONCLUSION: The level of neglected and non-consented care during delivery was high reflecting substantial mistreatment. ...
BACKGROUND: While in general a country's life expectancy increases with national income, some countries "punch above their weight", while some "punch below their weight" – achieving higher or lower life expectancy than would be predicted by their per capita income. Discovering which conditions or policies contribute to this outcome is critical to improving population health globally. METHODS: We conducted a mixed-method study which included: analysis of life expectancy relative to income for all countries; an expert opinion study; and scoping reviews of literature and data to examine factors that may impact on life expectancy relative to income in three countries: Ethiopia, Brazil, and the United States. Punching above or below weight status was calculated using life expectancy at birth and gross domestic product per capita for 2014–2018. The scoping reviews covered the political context and history, social determinants of health, civil society, and political participation in each country. RESULTS: Possible drivers identified for Ethiopia's extra 3 years life expectancy included community-based health strategies, improving access to safe water, female education and gender empowerment, and the rise of civil society organisations. Brazil punched above its weight by 2 years. Possible drivers identified included socio-political and economic improvements, reduced inequality, female education, health care coverage, civil society, and political participation. The United States' neoliberal economics and limited social security, market-based healthcare, limited public health regulation, weak social safety net, significant increases in income inequality and lower levels of political participation may have contributed to the country punching 2.9 years below weight. CONCLUSIONS: The review highlighted potential structural determinants driving differential performance in population health outcomes cross-nationally. These included greater equity, a more inclusive welfare system, high political participation, strong civil ...
BackgroundWhile in general a country's life expectancy increases with national income, some countries "punch above their weight", while some "punch below their weight" - achieving higher or lower life expectancy than would be predicted by their per capita income. Discovering which conditions or policies contribute to this outcome is critical to improving population health globally.MethodsWe conducted a mixed-method study which included: analysis of life expectancy relative to income for all countries; an expert opinion study; and scoping reviews of literature and data to examine factors that may impact on life expectancy relative to income in three countries: Ethiopia, Brazil, and the United States. Punching above or below weight status was calculated using life expectancy at birth and gross domestic product per capita for 2014-2018. The scoping reviews covered the political context and history, social determinants of health, civil society, and political participation in each country.ResultsPossible drivers identified for Ethiopia's extra 3 years life expectancy included community-based health strategies, improving access to safe water, female education and gender empowerment, and the rise of civil society organisations. Brazil punched above its weight by 2 years. Possible drivers identified included socio-political and economic improvements, reduced inequality, female education, health care coverage, civil society, and political participation. The United States' neoliberal economics and limited social security, market-based healthcare, limited public health regulation, weak social safety net, significant increases in income inequality and lower levels of political participation may have contributed to the country punching 2.9 years below weight.ConclusionsThe review highlighted potential structural determinants driving differential performance in population health outcomes cross-nationally. These included greater equity, a more inclusive welfare system, high political participation, strong civil society and access to employment, housing, safe water, a clean environment, and education. We recommend research comparing more countries, and also to examine the processes driving within-country inequities.
BackgroundWhile in general a country's life expectancy increases with national income, some countries "punch above their weight", while some "punch below their weight" - achieving higher or lower life expectancy than would be predicted by their per capita income. Discovering which conditions or policies contribute to this outcome is critical to improving population health globally.MethodsWe conducted a mixed-method study which included: analysis of life expectancy relative to income for all countries; an expert opinion study; and scoping reviews of literature and data to examine factors that may impact on life expectancy relative to income in three countries: Ethiopia, Brazil, and the United States. Punching above or below weight status was calculated using life expectancy at birth and gross domestic product per capita for 2014-2018. The scoping reviews covered the political context and history, social determinants of health, civil society, and political participation in each country.ResultsPossible drivers identified for Ethiopia's extra 3 years life expectancy included community-based health strategies, improving access to safe water, female education and gender empowerment, and the rise of civil society organisations. Brazil punched above its weight by 2 years. Possible drivers identified included socio-political and economic improvements, reduced inequality, female education, health care coverage, civil society, and political participation. The United States' neoliberal economics and limited social security, market-based healthcare, limited public health regulation, weak social safety net, significant increases in income inequality and lower levels of political participation may have contributed to the country punching 2.9 years below weight.ConclusionsThe review highlighted potential structural determinants driving differential performance in population health outcomes cross-nationally. These included greater equity, a more inclusive welfare system, high political participation, strong civil society and ...
Background: While in general a country's life expectancy increases with national income, some countries "punch above their weight", while some "punch below their weight" – achieving higher or lower life expectancy than would be predicted by their per capita income. Discovering which conditions or policies contribute to this outcome is critical to improving population health globally. Methods: We conducted a mixed-method study which included: analysis of life expectancy relative to income for all countries; an expert opinion study; and scoping reviews of literature and data to examine factors that may impact on life expectancy relative to income in three countries: Ethiopia, Brazil, and the United States. Punching above or below weight status was calculated using life expectancy at birth and gross domestic product per capita for 2014–2018. The scoping reviews covered the political context and history, social determinants of health, civil society, and political participation in each country. Results: Possible drivers identified for Ethiopia's extra 3 years life expectancy included community-based health strategies, improving access to safe water, female education and gender empowerment, and the rise of civil society organisations. Brazil punched above its weight by 2 years. Possible drivers identified included socio-political and economic improvements, reduced inequality, female education, health care coverage, civil society, and political participation. The United States' neoliberal economics and limited social security, market-based healthcare, limited public health regulation, weak social safety net, significant increases in income inequality and lower levels of political participation may have contributed to the country punching 2.9 years below weight. Conclusions: The review highlighted potential structural determinants driving differential performance in population health outcomes cross-nationally. These included greater equity, a more inclusive welfare system, high political participation, strong civil society and access to employment, housing, safe water, a clean environment, and education. We recommend research comparing more countries, and also to examine the processes driving within-country inequities.
Abstract Background Access to basic health services, notably child health services, is severely hampered by the armed conflict in Tigray, North Ethiopia. Little is known regarding the impacts of the armed conflict during the war in Tigray on access to child health services. The current study investigates the impact of the armed conflict on the utilization of child health services in Tigray.
Methods 4,381 caregivers from randomly recruited households (HHs) with at least one child younger than 1 year old participated in a community-based cross-sectional survey. We collected data on childhood immunizations and illness-related treatment seeking from August 4 to 20, 2021. We describe data using frequency and percentage and carry out an internal comparison among the study participants using chi-square tests.
Results 4,381 children under the age of one included in the study. In total, 39% of infants received no basic vaccines, 61.3% of the children under the age of one received at least one vaccine, and 20% received all the vaccinations recommended for their age. About 61% of children were affected by at least one childhood ailments where majority of them were from rural areas. Mothers who did not seek postnatal care (PNC) were responsible for more than 75% of reported childhood illnesses.
Conclusions A sizable portion of children were unvaccinated and had at least one childhood sickness while the war was in progress. Particularly, people who live in rural areas reported a higher percentage of children's illnesses but a lower use of child health services. To lower childhood morbidity and mortality in the besieged area, such as Tigray, local to global actors need to get coordinated and warrying parties should stop weaponization of vaccination healthcare services.
OBJECTIVE: The aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa. DESIGN: A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa. DATA SOURCES: Data were systematically searched from MEDLINE, Scopus, MedRxiv and BioRxiv. ELIGIBILITY CRITERIA: Studies for review were included if they were published in English and reported at least one risk factor and/or one health outcome. We included all relevant literature published up until 11 August 2020. DATA EXTRACTION AND SYNTHESIS: We performed a systematic narrative synthesis to describe the available studies for each outcome. Data were extracted using a standardised Joanna Briggs Institute data extraction form. RESULTS: Fifteen articles met the inclusion criteria of which four were exclusively on Africa and the remaining 11 papers had a global focus with some data from Africa. Higher rates of infection in Africa are associated with high population density, urbanisation, transport connectivity, high volume of tourism and international trade, and high level of economic and political openness. Limited or poor access to healthcare are also associated with higher COVID-19 infection rates. Older people and individuals with chronic conditions such as HIV, tuberculosis and anaemia experience severe forms COVID-19 leading to hospitalisation and death. Similarly, high burden of chronic obstructive pulmonary disease, high prevalence of tobacco consumption and low levels of expenditure on health and low levels of global health security score contribute to COVID-19 related deaths. CONCLUSIONS: Demographic, institutional, ecological, health system and politico-economic factors influenced the spectrum of COVID-19 infection, severity and death. We recommend multidisciplinary and integrated approaches to mitigate the identified factors and strengthen effective prevention strategies.
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. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations
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. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations
BACKGROUND: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. FUNDING:Bill & Melinda Gates Foundation.
