Abstract
Background: Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods: We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings: From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation: The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. Funding: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care, using UK aid funding managed by the Fleming Fund.
Original language | English (US) |
---|---|
Pages (from-to) | 2221-2248 |
Number of pages | 28 |
Journal | The Lancet |
Volume | 400 |
Issue number | 10369 |
DOIs | |
State | Published - Dec 17 2022 |
Keywords
- Child
- Male
- Female
- Humans
- Global Burden of Disease
- Syndrome
- Africa South of the Sahara
- Global Health
- Bacterial Infections/epidemiology
- Risk Factors
- Bacteria
- Sepsis
ASJC Scopus subject areas
- General Medicine
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In: The Lancet, Vol. 400, No. 10369, 17.12.2022, p. 2221-2248.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Global mortality associated with 33 bacterial pathogens in 2019
T2 - a systematic analysis for the Global Burden of Disease Study 2019
AU - GBD 2019 Antimicrobial Resistance Collaborators
AU - Ikuta, Kevin S.
AU - Swetschinski, Lucien R.
AU - Robles Aguilar, Gisela
AU - Sharara, Fablina
AU - Mestrovic, Tomislav
AU - Gray, Authia P.
AU - Davis Weaver, Nicole
AU - Wool, Eve E.
AU - Han, Chieh
AU - Gershberg Hayoon, Anna
AU - Aali, Amirali
AU - Abate, Semagn Mekonnen
AU - Abbasi-Kangevari, Mohsen
AU - Abbasi-Kangevari, Zeinab
AU - Abd-Elsalam, Sherief
AU - Abebe, Getachew
AU - Abedi, Aidin
AU - Abhari, Amir Parsa
AU - Abidi, Hassan
AU - Aboagye, Richard Gyan
AU - Absalan, Abdorrahim
AU - Abubaker Ali, Hiwa
AU - Acuna, Juan Manuel
AU - Adane, Tigist Demssew
AU - Addo, Isaac Yeboah
AU - Adegboye, Oyelola A.
AU - Adnan, Mohammad
AU - Adnani, Qorinah Estiningtyas Sakilah
AU - Afzal, Muhammad Sohail
AU - Afzal, Saira
AU - Aghdam, Zahra Babaei
AU - Ahinkorah, Bright Opoku
AU - Ahmad, Aqeel
AU - Ahmad, Araz Ramazan
AU - Ahmad, Rizwan
AU - Ahmad, Sajjad
AU - Ahmad, Sohail
AU - Ahmadi, Sepideh
AU - Ahmed, Ali
AU - Ahmed, Haroon
AU - Ahmed, Jivan Qasim
AU - Ahmed Rashid, Tarik
AU - Ajami, Marjan
AU - Aji, Budi
AU - Akbarzadeh-Khiavi, Mostafa
AU - Akunna, Chisom Joyqueenet
AU - Al Hamad, Hanadi
AU - Alahdab, Fares
AU - Al-Aly, Ziyad
AU - Aldeyab, Mamoon A.
N1 - Funding Information: Funding for this study was provided by the Bill & Melinda Gates Foundation (OPP1176062), the Wellcome Trust (A126042), and the UK Department of Health and Social Care using UK aid funding managed by the Fleming Fund (R52354 CN001). J M Acuna acknowledges academic support from the Universidad Espiritu Santo. S Afzal acknowledges institutional support from the Department of Community Medicine and Epidemiology for timely revising and completing the modifications and corrections in the manuscript. A Ahmad acknowledges support from the Scientific Research Unit at Shaqra University. S M Aljunid acknowledges support from the Department of Health Policy and Management, College of Public Health, Kuwait University for the support and approval to participate in this research project. M Ausloos acknowledges support from the Romanian National Authority for Scientific Research and Innovation (under CNDS-UEFISCDI: PN-III-P4-ID-PCCF-2016-0084 research grant; Understanding and modelling time-space patterns of psychology-related inequalities and polarization). I Banerjee acknowledges support from Sir Seewoosagur Ramgoolam Medical College (SSRMC), Belle Rive, Mauritius. S J Dunachie acknowledges funding support from an NIHR Global Research Professorship (NIHR300791). T C Ekundayo acknowledges support from the African-German Network of Excellence in Science (AGNES), the Federal Ministry of Education and Research (BMBF), and the Alexander von Humboldt Foundation (AvH) for financial support. A Fatehizadeh acknowledges support from the Department of Environmental Health Engineering of Isfahan University of Medical Sciences, Isfahan, Iran. J C Fernandes acknowledges support from UID/Multi/50016/2019 with funding from Fundação para a Ciência e a Tecnologia; support with funding from Fundação para a Ciência e a Tecnologia (FCT)/Ministro da Ciência, Tecnologia e Ensino Superior (MCTES) through national funds. A Goodridge, I Landires, and V Nuñez-Samudio are supported by the Sistema Nacional de Investigación (SNI) de Panamá, which is supported by Panamá's Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). V B Gupta and V K Gupta acknowledge funding support form National Health and Medical Research Council (NHMRC) Australia. C Herteliu acknowledges support from a grant of the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084), and from a grant of the Romanian Ministry of Research Innovation and Digitalization (MCID, project number ID-585-CTR-42-PFE-2021). P Hoogar acknowledges support from the Centre for Bio Cultural Studies, Directorate of Research, Manipal Academy of Higher Education (Manipal, India), and Centre for Holistic Development and Research (Kalaghatgi, India). S Hussain acknowledges support from the Operational Programme Research, Development and Education- Project, Postdoc2MUNI (No.CZ.02.2.69/0.0/0.0/18_053/0016952). M Jakovljevic acknowledges partial financial support through the grant OI 175 014 of the Ministry of Education Science and Technological Development of Serbia. T Joo acknowledges support from the National Research, Development and Innovation Office of Hungary grants and RRF-2.3.1-21-2022-00006 Data-driven Health Division of Health Security National Laboratory. S L Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education (Manipal, India). F Krapp Lopez acknowledges support from the Framework Agreement Belgian Directorate of Development Cooperation, the Institute of Tropical Medicine in Antwerp, and the Fogarty International Center, and National Institute of Child Health & Human Development of the National Institutes of Health (D43 TW009763). K Krishan acknowledges support from the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University (Chandigarh, India). A Majeed acknowledges support from the NIHR Research Applied Research Collaboration (ARC) Northwest London; the views expressed in this publication are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. L Monasta acknowledges support related to the present study received from the Italian Ministry of Health on project Ricerca Corrente 34/2017 at the Institute for Maternal and Child Health IRCCS Burlo Garofolo. JR Padubidri acknowledges support from Kasturba Medical College (Mangalore) and Manipal Academy of Higher Education (Manipal) for their continual support for Research. Z Z Piracha acknowledges support from the International Center of Medical Sciences (ICMSR), Islamabad (44000), Pakistan. A Riad acknowledges support from Masaryk University (grant number MUNI/IGA/1104/2021), and the NPO Systemic Risk Institute LX22NPO5101. U Saeed acknowledges support from the International Center of Medical Sciences (ICMSR), Islamabad (44000), Pakistan. A M Samy acknowledges the support from The Egyptian Fulbright Mission program and Ain Shams University. B Sartorius acknowledges grant support from the UK Department of Health and Social Care using UK aid funding managed by the Fleming Fund (R52354 CN001). P A Shah acknowledges academic support from Bangalore Medical College and Research Institute. P H Shetty acknowledges support from Kasturba Medical College, Mangalore and Manipal Academy of Higher Education, Manipal, India. S S Siwal acknowledges support from Department of Chemistry and Research & Development Cell of Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, India. S B Zaman acknowledges scholarship support from the Australian Government Research Training Program (RTP) to support his academic career. R Suliankatchi Abdulkader acknowledges support from the ICMR-National Institute of Epidemiology. A Zumla acknowledges support as co-principal investigator of The Pan-African Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET, CANTAM-3, and EACCR-3) funded by the European and Developing Countries Clinical Trials Partnership, supported by the EU Horizon 2020 Framework Programme, UK-NIHR Senior Investigator award, and is a Mahathir Science Award and EU-EDCTP Pascoal Mocumbi Prize Laureate. Funding Information: Funding for this study was provided by the Bill & Melinda Gates Foundation (OPP1176062), the Wellcome Trust (A126042), and the UK Department of Health and Social Care using UK aid funding managed by the Fleming Fund (R52354 CN001). J M Acuna acknowledges academic support from the Universidad Espiritu Santo. S Afzal acknowledges institutional support from the Department of Community Medicine and Epidemiology for timely revising and completing the modifications and corrections in the manuscript. A Ahmad acknowledges support from the Scientific Research Unit at Shaqra University. S M Aljunid acknowledges support from the Department of Health Policy and Management, College of Public Health, Kuwait University for the support and approval to participate in this research project. M Ausloos acknowledges support from the Romanian National Authority for Scientific Research and Innovation (under CNDS-UEFISCDI: PN-III-P4-ID-PCCF-2016-0084 research grant; Understanding and modelling time-space patterns of psychology-related inequalities and polarization). I Banerjee acknowledges support from Sir Seewoosagur Ramgoolam Medical College (SSRMC), Belle Rive, Mauritius. S J Dunachie acknowledges funding support from an NIHR Global Research Professorship (NIHR300791). T C Ekundayo acknowledges support from the African-German Network of Excellence in Science (AGNES), the Federal Ministry of Education and Research (BMBF), and the Alexander von Humboldt Foundation (AvH) for financial support. A Fatehizadeh acknowledges support from the Department of Environmental Health Engineering of Isfahan University of Medical Sciences, Isfahan, Iran. J C Fernandes acknowledges support from UID/Multi/50016/2019 with funding from Fundação para a Ciência e a Tecnologia; support with funding from Fundação para a Ciência e a Tecnologia (FCT)/Ministro da Ciência, Tecnologia e Ensino Superior (MCTES) through national funds. A Goodridge, I Landires, and V Nuñez-Samudio are supported by the Sistema Nacional de Investigación (SNI) de Panamá, which is supported by Panamá's Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). V B Gupta and V K Gupta acknowledge funding support form National Health and Medical Research Council (NHMRC) Australia. C Herteliu acknowledges support from a grant of the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084), and from a grant of the Romanian Ministry of Research Innovation and Digitalization (MCID, project number ID-585-CTR-42-PFE-2021). P Hoogar acknowledges support from the Centre for Bio Cultural Studies, Directorate of Research, Manipal Academy of Higher Education (Manipal, India), and Centre for Holistic Development and Research (Kalaghatgi, India). S Hussain acknowledges support from the Operational Programme Research, Development and Education- Project, Postdoc2MUNI (No.CZ.02.2.69/0.0/0.0/18_053/0016952). M Jakovljevic acknowledges partial financial support through the grant OI 175 014 of the Ministry of Education Science and Technological Development of Serbia. T Joo acknowledges support from the National Research, Development and Innovation Office of Hungary grants and RRF-2.3.1-21-2022-00006 Data-driven Health Division of Health Security National Laboratory. S L Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education (Manipal, India). F Krapp Lopez acknowledges support from the Framework Agreement Belgian Directorate of Development Cooperation, the Institute of Tropical Medicine in Antwerp, and the Fogarty International Center, and National Institute of Child Health & Human Development of the National Institutes of Health (D43 TW009763). K Krishan acknowledges support from the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University (Chandigarh, India). A Majeed acknowledges support from the NIHR Research Applied Research Collaboration (ARC) Northwest London; the views expressed in this publication are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. L Monasta acknowledges support related to the present study received from the Italian Ministry of Health on project Ricerca Corrente 34/2017 at the Institute for Maternal and Child Health IRCCS Burlo Garofolo. JR Padubidri acknowledges support from Kasturba Medical College (Mangalore) and Manipal Academy of Higher Education (Manipal) for their continual support for Research. Z Z Piracha acknowledges support from the International Center of Medical Sciences (ICMSR), Islamabad (44000), Pakistan. A Riad acknowledges support from Masaryk University (grant number MUNI/IGA/1104/2021), and the NPO Systemic Risk Institute LX22NPO5101. U Saeed acknowledges support from the International Center of Medical Sciences (ICMSR), Islamabad (44000), Pakistan. A M Samy acknowledges the support from The Egyptian Fulbright Mission program and Ain Shams University. B Sartorius acknowledges grant support from the UK Department of Health and Social Care using UK aid funding managed by the Fleming Fund (R52354 CN001). P A Shah acknowledges academic support from Bangalore Medical College and Research Institute. P H Shetty acknowledges support from Kasturba Medical College, Mangalore and Manipal Academy of Higher Education, Manipal, India. S S Siwal acknowledges support from Department of Chemistry and Research & Development Cell of Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, India. S B Zaman acknowledges scholarship support from the Australian Government Research Training Program (RTP) to support his academic career. R Suliankatchi Abdulkader acknowledges support from the ICMR-National Institute of Epidemiology. A Zumla acknowledges support as co-principal investigator of The Pan-African Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET, CANTAM-3, and EACCR-3) funded by the European and Developing Countries Clinical Trials Partnership, supported by the EU Horizon 2020 Framework Programme, UK-NIHR Senior Investigator award, and is a Mahathir Science Award and EU-EDCTP Pascoal Mocumbi Prize Laureate. Editorial note: The Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2022/12/17
Y1 - 2022/12/17
N2 - Background: Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods: We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings: From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation: The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. Funding: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care, using UK aid funding managed by the Fleming Fund.
AB - Background: Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods: We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings: From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation: The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. Funding: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care, using UK aid funding managed by the Fleming Fund.
KW - Child
KW - Male
KW - Female
KW - Humans
KW - Global Burden of Disease
KW - Syndrome
KW - Africa South of the Sahara
KW - Global Health
KW - Bacterial Infections/epidemiology
KW - Risk Factors
KW - Bacteria
KW - Sepsis
UR - http://www.scopus.com/inward/record.url?scp=85143975205&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85143975205&partnerID=8YFLogxK
U2 - 10.1016/S0140-6736(22)02185-7
DO - 10.1016/S0140-6736(22)02185-7
M3 - Article
C2 - 36423648
AN - SCOPUS:85143975205
SN - 0140-6736
VL - 400
SP - 2221
EP - 2248
JO - The Lancet
JF - The Lancet
IS - 10369
ER -