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This study is aimed at evaluating the contribution of IFB to economic development of the country-Ethiopia, the level of stakeholder awareness and attitude towards the IFB services, the comparative advantages of IFB, the factors that account for the growth of IFB, and challenges and prospect in the Ethiopian context by considering two banks that are providing IFB services: Oromia International Bank S.C. and Commercial Bank of Ethiopia. The study used both primary and secondary data. The secondary data was collected from clients' files, reports, directives and working documents while the primary data was collected through structured questionnaire having Likert scale and other forms of measurement. Out of 200 target population of the study, 150 individuals' sample was taken through stratified sampling techniques. The collected data was analyzed using descriptive analysis like tables, percentages and charts (using SPSS 20 version software) and t-test. The finding of the study depicts inadequacy of stakeholder awareness and experience in one hand, and limiting impact of the prevailing IFB provision on the service IFB on the other. Most respondents believe that IFB can potentially serve as an alternative banking channel in filling the gap left unaddressed by conventional banking and economic development: idle monetary resource mobilization and allocation, inviting to use banking system, creating employment opportunity, supporting GDP growth and assisting in stabilizing crisis and arresting inflation. On top of that, the respondents suggested various factors that account for growth of IFB and forwarded valuable recommendations that help IFB to play the expected role in economic development. IFB prohibition on business dealings that are against the public interest is regarded by the writer as a new insight towards engaging in sustainable business while caring for the society. Some scholars around the world consider the use of IFB as more convenient for economic development. The result of this research also indicates that considering revisiting the infrastructure of IFB in Ethiopia could enhance its comfortable operation and its role in assisting economic development. In conclusion, IFB is deemed to play an integral role in Ethiopia in catalyzing the economic development subject to adequate awareness creation about its governing principles, compliance with prohibitions, familiarity with operating philosophies, expertise capacity building of operators-bankers, experience sharing from Islamic banking-pioneering countries, and devising enabling regulatory environment. Accordingly, plausible courses of action were forwarded by the researcher based on the conclusive results of the findings in conjunction with literature review reflections: creating awareness, providing tailored and sustainable training for practitioners, best-practice experience sharing from Islamic banking-pioneering countries, government support, revisiting the IFB provision for possible revision where applicable to an enabling level. Key words; IFB/Islamic banking/, CB, Sharia principle, economic development, Ethiopia

Cholera remains a significant public health problem among the vulnerable populations living in many resource-limited settings with poor access to safe and clean water and hygiene practice. Around 2.86 million cholera cases and 95,000 deaths are estimated to occur in endemic countries. In Ethiopia, cholera has been one of the major epidemic diseases since 1634 when the first cholera outbreak was recorded in-country. Several cholera epidemics occurred with recent outbreaks in 2019–2021. Cholera has been often reported as acute watery diarrhea due to limited diagnostic capacity in remote areas in Ethiopia and sensitivities around cholera outbreaks. The government of Ethiopia has been executing several phases of multi-year health sector development plan in the past decades and has recently developed a national cholera control plan. Here, we aim to present the existing cholera control guidelines and health system in Ethiopia, including case detection and reporting, outbreak declaration, case management, and transmission control. Challenges and way forward on further research and public health interventions are also discussed to address the knowledge and health service gaps related to cholera control in Ethiopia.

Cara Lynn Kim,1 Ligia Maria Cruz Espinoza,1 Kirsten S Vannice,2 Birkneh Tilahun Tadesse,1,3,4 Ellis Owusu-Dabo,5 Raphaël Rakotozandrindrainy,6 Ilesh V Jani,7 Mekonnen Teferi,8 Abdramane Bassiahi Soura,9 Octavie Lunguya,10,11 A Duncan Steele,2 Florian Marks1,6,12,13 1International Vaccine Institute, Seoul, Republic of Korea; 2Enteric and Diarrheal Diseases, Bill & Melinda Gates Foundation, Seattle, WA, USA; 3Division of Clinical Pharmacology, Department of Laboratory Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden; 4Center for Innovative Drug Development and Therapeutic Trials for Africa, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia; 5School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana; 6University of Antananarivo, Antananarivo, Madagascar; 7Instituto Nacional de Saúde (INS), Maputo Province, Mozambique; 8Armauer Hansen Research Institute, Addis Ababa, Ethiopia; 9Institut Supérieur des Sciences de la Population, Université Joseph Ki-Zerbo de Ouagadougou, Ouagadougou, Burkina Faso; 10Department of Microbiology, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; 11Department of Medical Biology, University Teaching Hospital of Kinshasa, Kinshasa, Democratic Republic of the Congo; 12Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK; 13Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, GermanyCorrespondence: Florian Marks, Tel +82-2-881-1133, Email fmarks@ivi.intAbstract: While typhoid fever has largely been eliminated in high-income regions which have developed modern water, sanitation, and hygiene facilities, it remains a significant public health burden resulting in morbidity and mortality among millions of individuals in resource-constrained settings. Prevention and control efforts are needed that integrate several high-impact interventions targeting facilities and infrastructure, including those addressing improvements in sanitation, access to safe water, and planned urbanization, together with parallel efforts directed at effective strategies for use of typhoid conjugate vaccines (TCV). The use of TCVs is a critical tool with the potential of having a rapid impact on typhoid fever disease burden; their introduction will also serve as an important strategy to combat evolving antimicrobial resistance to currently available typhoid fever treatments. Well-designed epidemiological surveillance studies play a critical role in establishing the need for, and monitoring the impact of, typhoid fever control and prevention strategies implemented by public health authorities. Here, we present a perspective based on a narrative review of the impact of typhoid fever on morbidity and mortality in sub-Saharan Africa and discuss ongoing surveillance activities and the role of vaccination in prevention and control efforts.Keywords: typhoid, burden, mortality, sub-Saharan Africa, conjugate-vaccine, antimicrobial resistance

INTRODUCTION: The objective of the Health Population Africa (HPAfrica) study is to determine health behaviour and population-based factors, including socioeconomic, ethnographic, hygiene and sanitation factors, at sites of the Severe Typhoid Fever in Africa (SETA) programme. SETA aims to investigate healthcare facility-based fever surveillance in Burkina Faso, the Democratic Republic of the Congo, Ethiopia, Ghana, Madagascar and Nigeria. Meaningful disease burden estimates require adjustment for health behaviour patterns, which are assumed to vary among a study population. METHODS AND ANALYSIS: For the minimum sample size of household interviews required, the assumptions of an infinite population, a design effect and age-stratification and sex-stratification are considered. In the absence of a population sampling frame or household list, a spatial approach will be used to generate geographic random points with an Aeronautical Reconnaissance Coverage Geographic Information System tool. Printouts of Google Earth Pro satellite imagery visualise these points. Data of interest will be assessed in different seasons by applying population-weighted stratified sampling. An Android-based application and a web service will be developed for electronic data capturing and synchronisation with the database server in real time. Sampling weights will be computed to adjust for possible differences in selection probabilities. Descriptive data analyses will be performed in order to assess baseline information of each study population and age-stratified and sex-stratified health behaviour. This will allow adjusting disease burden estimates. In addition, multivariate analyses will be applied to look into associations between health behaviour, population-based factors and the disease burden as determined in the SETA study. ETHICS AND DISSEMINATION: Ethic approvals for this protocol were obtained by the Institutional Review Board of the International Vaccine Institute (No. 2016-0003) and by all collaborating institutions of participating countries. It is anticipated to disseminate findings from this study through publication on a peer-reviewed journal.

Publisher's version (útgefin grein) ; Background The Nordic countries have commonalities in gender equality, economy, welfare, and health care, but differ in culture and lifestyle, which might create country-wise health differences. This study compared life expectancy, disease burden, and risk factors in the Nordic region.Methods Life expectancy in years and age-standardised rates of overall, cause-specific, and risk factor-specific estimates of disability-adjusted life-years (DALYs) were analysed in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Data were extracted for Denmark, Finland, Iceland, Norway, and Sweden (ie, the Nordic countries), and Greenland, an autonomous area of Denmark. Estimates were compared with global, high-income region, and Nordic regional estimates, including Greenland.Findings All Nordic countries exceeded the global life expectancy; in 2017, the highest life expectancy was in Iceland among females (85·9 years [95% uncertainty interval [UI] 85·5–86·4] vs 75·6 years [75·3–75·9] globally) and Sweden among males (80·8 years [80·2–81·4] vs 70·5 years [70·1–70·8] globally). Females (82·7 years [81·9–83·4]) and males (78·8 years [78·1–79·5]) in Denmark and males in Finland (78·6 years [77·8–79·2]) had lower life expectancy than in the other Nordic countries. The lowest life expectancy in the Nordic region was in Greenland (females 77·2 years [76·2–78·0], males 70·8 years [70·3–71·4]). Overall disease burden was lower in the Nordic countries than globally, with the lowest age-standardised DALY rates among Swedish males (18 555·7 DALYs [95% UI 15 968·6–21 426·8] per 100 000 population vs 35 834·3 DALYs [33 218·2–38 740·7] globally) and Icelandic females (16 074·1 DALYs [13 216·4–19 240·8] vs 29 934·6 DALYs [26 981·9–33 211·2] globally). Greenland had substantially higher DALY rates (26 666·6 DALYs [23 478·4–30 218·8] among females, 33 101·3 DALYs [30 182·3–36 218·6] among males) than the Nordic countries. Country variation was primarily due to differences in causes that largely contributed to DALYs through mortality, such as ischaemic heart disease. These causes dominated male disease burden, whereas non-fatal causes such as low back pain were important for female disease burden. Smoking and metabolic risk factors were high-ranking risk factors across all countries. DALYs attributable to alcohol use and smoking were particularly high among the Danes, as was alcohol use among Finnish males.Interpretation Risk factor differences might drive differences in life expectancy and disease burden that merit attention also in high-income settings such as the Nordic countries. Special attention should be given to the high disease burden in Greenland. ; This study was funded by the Bill & Melinda Gates Foundation. The authors wish to thank Jonas Minet Kinge (Norwegian Institute of Public Health, Oslo, Norway) for valuable input regarding socioeconomic differences in life expectancy in the Nordic countries. CRC has received research funding from Svenska Läkaresällskapet (SLS-779681), Tysta Skolan, Hörselforskningsfonden (#503), the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 72204655 and the GENDERNET Co-Plus Fund (GNP-182). JJC acknowledges grant support from the Swedish Research Council (grant number 2019-01059). JMcG is supported by the Danish National Research Foundation (Niels Bohr Professorship), and is employed by The Queensland Centre for Mental Health Research which receives core funding from the Queensland Health. STS is currently funded by a grant from Region Zealand and a grant from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 801790). OP-R has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 837180. TL is supported by the Academy of Finland (Grant #319200). Where authors are identified as personnel of the International Agency for Research on Cancer/WHO, the authors alone are responsible for the views expressed in this Article and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/WHO. ; "Peer Reviewed"

Background. Invasive salmonellosis is a common community-acquired bacteremia in persons residing in sub-Saharan Africa. However, there is a paucity of data on severe typhoid fever and its associated acute and chronic host immune response and carriage. The Severe Typhoid Fever in Africa (SETA) program, a multicountry surveillance study, aimed to address these research gaps and contribute to the control and prevention of invasive salmonellosis. Methods. A prospective healthcare facility-based surveillance with active screening of enteric fever and clinically suspected severe typhoid fever with complications was performed using a standardized protocol across the study sites in Burkina Faso, the Democratic Republic of Congo (DRC), Ethiopia, Ghana, Madagascar, and Nigeria. Defined inclusion criteria were used for screening of eligible patients for enrollment into the study. Enrolled patients with confirmed invasive salmonellosis by blood culture or patients with clinically suspected severe typhoid fever with perforation were eligible for clinical follow-up. Asymptomatic neighborhood controls and immediate household contacts of each case were enrolled as a comparison group to assess the level of Salmonella-specific antibodies and shedding patterns. Healthcare utilization surveys were performed to permit adjustment of incidence estimations. Postmortem questionnaires were conducted in medically underserved areas to assess death attributed to invasive Salmonella infections in selected sites. Results. Research data generated through SETA aimed to address scientific knowledge gaps concerning the severe typhoid fever and mortality, long-term host immune responses, and bacterial shedding and carriage associated with natural infection by invasive salmonellae. Conclusions. SETA supports public health policy on typhoid immunization strategy in Africa.

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.

Publisher's version (útgefin grein) ; 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. ; Lucas Guimaraes Abreu acknowledges support from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior -Brasil (Capes) -Finance Code 001, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) and Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG). Olatunji O Adetokunboh acknowledges South African Department of Science & Innovation, and National Research Foundation. Anurag Agrawal acknowledges support from the Wellcome Trust DBT India Alliance Senior Fellowship IA/CPHS/14/1/501489. Rufus Olusola Akinyemi acknowledges Grant U01HG010273 from the National Institutes of Health (NIH) as part of the H3Africa Consortium. Rufus Olusola Akinyemi is further supported by the FLAIR fellowship funded by the UK Royal Society and the African Academy of Sciences. Syed Mohamed Aljunid acknowledges the Department of Health Policy and Management, Faculty of Public Health, Kuwait University and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia for the approval and support to participate in this research project. Marcel Ausloos, Claudiu Herteliu, and Adrian Pana acknowledge partial support by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDSUEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Till Winfried Barnighausen acknowledges support from the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. Juan J Carrero was supported by the Swedish Research Council (2019-01059). Felix Carvalho acknowledges UID/MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/MCTES through national funds. Vera Marisa Costa acknowledges support from grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundacao para a Ciencia e a Tecnologia (FCT), IP, under the Norma TransitA3ria DL57/2016/CP1334/CT0006. Jan-Walter De Neve acknowledges support from the Alexander von Humboldt Foundation. Kebede Deribe acknowledges support by Wellcome Trust grant number 201900/Z/16/Z as part of his International Intermediate Fellowship. Claudiu Herteliu acknowledges partial support by a grant co-funded by European Fund for Regional Development through Operational Program for Competitiveness, Project ID P_40_382. Praveen Hoogar acknowledges the Centre for Bio Cultural Studies (CBiCS), Manipal Academy of Higher Education(MAHE), Manipal and Centre for Holistic Development and Research (CHDR), Kalghatgi. Bing-Fang Hwang acknowledges support from China Medical University (CMU108-MF-95), Taichung, Taiwan. Mihajlo Jakovljevic acknowledges the Serbian part of this GBD contribution was co-funded through the Grant OI175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Aruna M Kamath acknowledges funding from the National Institutes of Health T32 grant (T32GM086270). Srinivasa Vittal Katikireddi acknowledges funding from the Medical Research Council (MC_UU_12017/13 & MC_UU_12017/15), Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15) and an NRS Senior Clinical Fellowship (SCAF/15/02). Yun Jin Kim acknowledges support from the Research Management Centre, Xiamen University Malaysia (XMUMRF/2018-C2/ITCM/0001). Kewal Krishan acknowledges support from the DST PURSE grant and UGC Center of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. Manasi Kumar acknowledges support from K43 TW010716 Fogarty International Center/NIMH. Ben Lacey acknowledges support from the NIHR Oxford Biomedical Research Centre and the BHF Centre of Research Excellence, Oxford. Ivan Landires is a member of the Sistema Nacional de InvestigaciA3n (SNI), which is supported by the Secretaria Nacional de Ciencia Tecnologia e Innovacion (SENACYT), Panama. Jeffrey V Lazarus acknowledges support by a Spanish Ministry of Science, Innovation and Universities Miguel Servet grant (Instituto de Salud Carlos III/ESF, European Union [CP18/00074]). Peter T N Memiah acknowledges CODESRIA; HISTP. Subas Neupane acknowledges partial support from the Competitive State Research Financing of the Expert Responsibility area of Tampere University Hospital. Shuhei Nomura acknowledges support from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (18K10082). Alberto Ortiz acknowledges support by ISCIII PI19/00815, DTS18/00032, ISCIII-RETIC REDinREN RD016/0009 Fondos FEDER, FRIAT, Comunidad de Madrid B2017/BMD-3686 CIFRA2-CM. These funding sources had no role in the writing of the manuscript or the decision to submit it for publication. George C Patton acknowledges support from a National Health & Medical Research Council Fellowship. Marina Pinheiro acknowledges support from FCT for funding through program DL 57/2016 -Norma transitA3ria. Alberto Raggi, David Sattin, and Silvia Schiavolin acknowledge support by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C Besta, Linea 4 -Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). Daniel Cury Ribeiro acknowledges support from the Sir Charles Hercus Health Research Fellowship -Health Research Council of New Zealand (18/111). Perminder S Sachdev acknowledges funding from the NHMRC Australia. Abdallah M Samy acknowledges support from a fellowship from the Egyptian Fulbright Mission Program. Milena M Santric-Milicevic acknowledges support from the Ministry of Education, Science and Technological Development of the Republic of Serbia (Contract No. 175087). Rodrigo Sarmiento-Suarez acknowledges institutional support from University of Applied and Environmental Sciences in Bogota, Colombia, and Carlos III Institute of Health in Madrid, Spain. Maria Ines Schmidt acknowledges grants from the Foundation for the Support of Research of the State of Rio Grande do Sul (IATS and PrInt) and the Brazilian Ministry of Health. Sheikh Mohammed Shariful Islam acknowledges a fellowship from the National Heart Foundation of Australia and Deakin University. Aziz Sheikh acknowledges support from Health Data Research UK. Kenji Shibuya acknowledges Japan Ministry of Education, Culture, Sports, Science and Technology. Joan B Soriano acknowledges support by Centro de Investigacion en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. Rafael Tabares-Seisdedos acknowledges partial support from grant PI17/00719 from ISCIII-FEDER. Santosh Kumar Tadakamadla acknowledges support from the National Health and Medical Research Council Early Career Fellowship, Australia. Marcello Tonelli acknowledges the David Freeze Chair in Health Services Research at the University of Calgary, AB, Canada. ; "Peer Reviewed"