Global burden associated with 85 pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Despite a global epidemiological transition towards increased burden of non-communicable diseases, communicable diseases continue to cause substantial morbidity and mortality worldwide. Understanding the burden of a wide range of infectious diseases, and its variation by geography and age, is pivotal to research priority setting and resource mobilisation globally.

METHODS

We estimated disability-adjusted life-years (DALYs) associated with 85 pathogens in 2019, globally, regionally, and for 204 countries and territories. The term pathogen included causative agents, pathogen groups, infectious conditions, and aggregate categories. We applied a novel methodological approach to account for underlying, immediate, and intermediate causes of death, which counted every death for which a pathogen had a role in the pathway to death. We refer to this measure as the burden associated with infection, which was estimated by combining different sources of information. To compare the burden among all pathogens, we used pathogen-specific ratios to incorporate the burden of immediate and intermediate causes of death for pathogens modelled previously by the GBD. We created the ratios by using multiple cause of death data, hospital discharge data, linkage data, and minimally invasive tissue sampling data to estimate the fraction of deaths coming from the pathway to death chain. We multiplied the pathogen-specific ratios by age-specific years of life lost (YLLs), calculated with GBD 2019 methods, and then added the adjusted YLLs to age-specific years lived with disability (YLDs) from GBD 2019 to produce adjusted DALYs to account for deaths in the chain. We used standard GBD methods to calculate 95% uncertainty intervals (UIs) for final estimates of DALYs by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. We provided burden estimates pertaining to all ages and specifically to the under 5 years age group.

FINDINGS

Globally in 2019, an estimated 704 million (95% UI 610-820) DALYs were associated with 85 different pathogens, including 309 million (250-377; 43·9% of the burden) in children younger than 5 years. This burden accounted for 27·7% (and 65·5% in those younger than 5 years) of the previously reported total DALYs from all causes in 2019. Comparing super-regions, considerable differences were observed in the estimated pathogen-associated burdens in relation to DALYs from all causes, with the highest burden observed in sub-Saharan Africa (314 million [270-368] DALYs; 61·5% of total regional burden) and the lowest in the high-income super-region (31·8 million [25·4-40·1] DALYs; 9·8%). Three leading pathogens were responsible for more than 50 million DALYs each in 2019: tuberculosis (65·1 million [59·0-71·2]), malaria (53·6 million [27·0-91·3]), and HIV or AIDS (52·1 million [46·6-60·9]). Malaria was the leading pathogen for DALYs in children younger than 5 years (37·2 million [17·8-64·2]). We also observed substantial burden associated with previously less recognised pathogens, including Staphylococcus aureus and specific Gram-negative bacterial species (ie, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii, and Helicobacter pylori). Conversely, some pathogens had a burden that was smaller than anticipated.

INTERPRETATION

Our detailed breakdown of DALYs associated with a comprehensive list of pathogens on a global, regional, and country level has revealed the magnitude of the problem and helps to indicate where research funding mismatch might exist. Given the disproportionate impact of infection on low-income and middle-income countries, an essential next step is for countries and relevant stakeholders to address these gaps by making targeted investments.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Estimating the subnational prevalence of antimicrobial resistant Salmonella enterica serovars Typhi and Paratyphi A infections in 75 endemic countries, 1990-2019: a modelling study

BACKGROUND

Enteric fever, a systemic infection caused by Salmonella enterica serovars Typhi and Paratyphi A, remains a major cause of morbidity and mortality in low-income and middle-income countries. Enteric fever is preventable through the provision of clean water and adequate sanitation and can be successfully treated with antibiotics. However, high levels of antimicrobial resistance (AMR) compromise the effectiveness of treatment. We provide estimates of the prevalence of AMR S Typhi and S Paratyphi A in 75 endemic countries, including 30 locations without data.

METHODS

We used a Bayesian spatiotemporal modelling framework to estimate the percentage of multidrug resistance (MDR), fluoroquinolone non-susceptibility (FQNS), and third-generation cephalosporin resistance in S Typhi and S Paratyphi A infections for 1403 administrative level one districts in 75 endemic countries from 1990 to 2019. We incorporated data from a comprehensive systematic review, public health surveillance networks, and large multicountry studies on enteric fever. Estimates of the prevalence of AMR and the number of AMR infections (based on enteric fever incidence estimates by the Global Burden of Diseases study) were produced at the country, super-region, and total endemic area level for each year of the study.

FINDINGS

We collated data from 601 sources, comprising 184 225 isolates of S Typhi and S Paratyphi A, covering 45 countries over 30 years. We identified a decline of MDR S Typhi in south Asia and southeast Asia, whereas in sub-Saharan Africa, the overall prevalence increased from 6·0% (95% uncertainty interval 4·3-8·0) in 1990 to 72·7% (67·7-77·3) in 2019. Starting from low levels in 1990, the prevalence of FQNS S Typhi increased rapidly, reaching 95·2% (91·4-97·7) in south Asia in 2019. This corresponded to 2·5 million (1·5-3·8) MDR S Typhi infections and 7·4 million (4·7-11·3) FQNS S Typhi infections in endemic countries in 2019. The prevalence of third-generation cephalosporin-resistant S Typhi remained low across the whole endemic area over the study period, except for Pakistan where prevalence of third-generation cephalosporin resistance in S Typhi reached 61·0% (58·0-63·8) in 2019. For S Paratyphi A, we estimated low prevalence of MDR and third-generation cephalosporin resistance in all endemic countries, but a drastic increase of FQNS, which reached 95·0% (93·7-96·1; 3·5 million [2·2-5·6] infections) in 2019.

INTERPRETATION

This study provides a comprehensive and detailed analysis of the prevalence of MDR, FQNS, and third-generation cephalosporin resistance in S Typhi and S Paratyphi A infections in endemic countries, spanning the last 30 years. Our analysis highlights the increasing levels of AMR in this preventable infection and serves as a resource to guide urgently needed public health interventions, such as improvements in water, sanitation, and hygiene and typhoid fever vaccination campaigns.

FUNDING

Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill and Melinda Gates Foundation.

The burden of bacterial antimicrobial resistance in the WHO African region in 2019: a cross-country systematic analysis

BACKGROUND

A critical and persistent challenge to global health and modern health care is the threat of antimicrobial resistance (AMR). Previous studies have reported a disproportionate burden of AMR in low-income and middle-income countries, but there remains an urgent need for more in-depth analyses across Africa. This study presents one of the most comprehensive sets of regional and country-level estimates of bacterial AMR burden in the WHO African region to date.

METHODS

We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with AMR for 23 bacterial pathogens and 88 pathogen-drug combinations for countries in the WHO African region in 2019. Our methodological approach consisted of five broad components: the number of deaths in which infection had a role, the proportion of infectious deaths attributable to a given infectious syndrome, the proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antimicrobial drug of interest, and the excess risk of mortality (or duration of an infection) associated with this resistance. These components were then used to estimate the disease burden by using two counterfactual scenarios: deaths attributable to AMR (considering an alternative scenario where infections with resistant pathogens are replaced with susceptible ones) and deaths associated with AMR (considering an alternative scenario where drug-resistant infections would not occur at all). We obtained data from research hospitals, surveillance networks, and infection databases maintained by private laboratories and medical technology companies. We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity.

FINDINGS

In the WHO African region in 2019, there were an estimated 1·05 million deaths (95% UI 829 000-1 316 000) associated with bacterial AMR and 250 000 deaths (192 000-325 000) attributable to bacterial AMR. The largest fatal AMR burden was attributed to lower respiratory and thorax infections (119 000 deaths [92 000-151 000], or 48% of all estimated bacterial pathogen AMR deaths), bloodstream infections (56 000 deaths [37 000-82 000], or 22%), intra-abdominal infections (26 000 deaths [17 000-39 000], or 10%), and tuberculosis (18 000 deaths [3850-39 000], or 7%). Seven leading pathogens were collectively responsible for 821 000 deaths (636 000-1 051 000) associated with resistance in this region, with four pathogens exceeding 100 000 deaths each: Streptococcus pneumoniae, Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus. Third-generation cephalosporin-resistant K pneumoniae and meticillin-resistant S aureus were shown to be the leading pathogen-drug combinations in 25 and 16 countries, respectively (53% and 34% of the whole region, comprising 47 countries) for deaths attributable to AMR.

INTERPRETATION

This study reveals a high level of AMR burden for several bacterial pathogens and pathogen-drug combinations in the WHO African region. The high mortality rates associated with these pathogens demonstrate an urgent need to address the burden of AMR in Africa. These estimates also show that quality and access to health care and safe water and sanitation are correlated with AMR mortality, with a higher fatal burden found in lower resource settings. Our cross-country analyses within this region can help local governments to leverage domestic and global funding to create stewardship policies that target the leading pathogen-drug combinations.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

The burden of antimicrobial resistance in the Americas in 2019: a cross-country systematic analysis

Background

Antimicrobial resistance (AMR) is an urgent global health challenge and a critical threat to modern health care. Quantifying its burden in the WHO Region of the Americas has been elusive-despite the region's long history of resistance surveillance. This study provides comprehensive estimates of AMR burden in the Americas to assess this growing health threat.

Methods

We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with AMR for 23 bacterial pathogens and 88 pathogen-drug combinations for countries in the WHO Region of the Americas in 2019. We obtained data from mortality registries, surveillance systems, hospital systems, systematic literature reviews, and other sources, and applied predictive statistical modelling to produce estimates of AMR burden for all countries in the Americas. Five broad components were the backbone of our approach: the number of deaths where infection had a role, the proportion of infectious deaths attributable to a given infectious syndrome, the proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of pathogens resistant to an antibiotic class, and the excess risk of mortality (or duration of an infection) associated with this resistance. We then used these components to estimate the disease burden by applying two counterfactual scenarios: deaths attributable to AMR (compared to an alternative scenario where resistant infections are replaced with susceptible ones), and deaths associated with AMR (compared to an alternative scenario where resistant infections would not occur at all). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity.

Findings

We estimated 569,000 deaths (95% UI 406,000-771,000) associated with bacterial AMR and 141,000 deaths (99,900-196,000) attributable to bacterial AMR among the 35 countries in the WHO Region of the Americas in 2019. Lower respiratory and thorax infections, as a syndrome, were responsible for the largest fatal burden of AMR in the region, with 189,000 deaths (149,000-241,000) associated with resistance, followed by bloodstream infections (169,000 deaths [94,200-278,000]) and peritoneal/intra-abdominal infections (118,000 deaths [78,600-168,000]). The six leading pathogens (by order of number of deaths associated with resistance) were Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. Together, these pathogens were responsible for 452,000 deaths (326,000-608,000) associated with AMR. Methicillin-resistant S. aureus predominated as the leading pathogen-drug combination in 34 countries for deaths attributable to AMR, while aminopenicillin-resistant E. coli was the leading pathogen-drug combination in 15 countries for deaths associated with AMR.

Interpretation

Given the burden across different countries, infectious syndromes, and pathogen-drug combinations, AMR represents a substantial health threat in the Americas. Countries with low access to antibiotics and basic health-care services often face the largest age-standardised mortality rates associated with and attributable to AMR in the region, implicating specific policy interventions. Evidence from this study can guide mitigation efforts that are tailored to the needs of each country in the region while informing decisions regarding funding and resource allocation. Multisectoral and joint cooperative efforts among countries will be a key to success in tackling AMR in the Americas.

Funding

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Mapping local variation in household overcrowding across Africa from 2000 to 2018: a modelling study

BACKGROUND

Household overcrowding is a serious public health threat associated with high morbidity and mortality. Rapid population growth and urbanisation contribute to overcrowding and poor sanitation in low-income and middle- income countries, and are risk factors for the spread of infectious diseases, including COVID-19, and antimicrobial resistance. Many countries do not have adequate surveillance capacity to monitor household overcrowding. Geostatistical models are therefore useful tools for estimating household overcrowding. In this study, we aimed to estimate household overcrowding in Africa between 2000 and 2018 by combining available household survey data, population censuses, and other country-specific household surveys within a geostatistical framework.

METHODS

We used data from household surveys and population censuses to generate a Bayesian geostatistical model of household overcrowding in Africa for the 19-year period between 2000 and 2018. Additional sociodemographic and health-related covariates informed the model, which covered 54 African countries.

FINDINGS

We analysed 287 surveys and population censuses, covering 78 695 991 households. Spatial and temporal variability arose in household overcrowding estimates over time. In 2018, the highest overcrowding estimates were observed in the Horn of Africa region (median proportion 62% [IQR 57-63]); the lowest regional median proportion was estimated for the north of Africa region (16% [14-19]). Overall, 474·4 million (95% uncertainty interval [UI] 250·1 million-740·7 million) people were estimated to be living in overcrowded conditions in Africa in 2018, a 62·7% increase from the estimated 291·5 million (180·8 million-417·3 million) people who lived in overcrowded conditions in the year 2000. 48·5% (229·9 million) of people living in overcrowded conditions came from six African countries (Nigeria, Ethiopia, Democratic Republic of the Congo, Sudan, Uganda, and Kenya), with a combined population of 538·3 million people.

INTERPRETATION

This study incorporated survey and population censuses data and used geostatistical modelling to estimate continent-wide overcrowding over a 19-year period. Our analysis identified countries and areas with high numbers of people living in overcrowded conditions, thereby providing a benchmark for policy planning and the implementation of interventions such as in infectious disease control.

FUNDING

UK Department of Health and Social Care, Wellcome Trust, Bill & Melinda Gates Foundation.

Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

BACKGROUND

Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen-drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date.

METHODS

We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen-drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level.

FINDINGS

On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62-6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911-1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9-35·3), and lowest in Australasia, at 6·5 deaths (4·3-9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000-1 270 000) deaths attributable to AMR and 3·57 million (2·62-4·78) deaths associated with AMR in 2019. One pathogen-drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000-100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae.

INTERPRETATION

To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen-drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Global antibiotic consumption and usage in humans, 2000-18: a spatial modelling study

BACKGROUND

Antimicrobial resistance (AMR) is a serious threat to global public health. WHO emphasises the need for countries to monitor antibiotic consumption to combat AMR. Many low-income and middle-income countries (LMICs) lack surveillance capacity; we aimed to use multiple data sources and statistical models to estimate global antibiotic consumption.

METHODS

In this spatial modelling study, we used individual-level data from household surveys to inform a Bayesian geostatistical model of antibiotic usage in children (aged <5 years) with lower respiratory tract infections in LMICs. Antibiotic consumption data were obtained from multiple sources, including IQVIA, WHO, and the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). The estimates of the antibiotic usage model were used alongside sociodemographic and health covariates to inform a model of total antibiotic consumption in LMICs. This was combined with a single model of antibiotic consumption in high-income countries to produce estimates of antibiotic consumption covering 204 countries and 19 years.

FINDINGS

We analysed 209 surveys done between 2000 and 2018, covering 284 045 children with lower respiratory tract infections. We identified large national and subnational variations of antibiotic usage in LMICs, with the lowest levels estimated in sub-Saharan Africa and the highest in eastern Europe and central Asia. We estimated a global antibiotic consumption rate of 14·3 (95% uncertainty interval 13·2-15·6) defined daily doses (DDD) per 1000 population per day in 2018 (40·2 [37·2-43·7] billion DDD), an increase of 46% from 9·8 (9·2-10·5) DDD per 1000 per day in 2000. We identified large spatial disparities, with antibiotic consumption rates varying from 5·0 (4·8-5·3) DDD per 1000 per day in the Philippines to 45·9 DDD per 1000 per day in Greece in 2018. Additionally, we present trends in consumption of different classes of antibiotics for selected Global Burden of Disease study regions using the IQVIA, WHO, and ESAC-net input data. We identified large increases in the consumption of fluoroquinolones and third-generation cephalosporins in North Africa and Middle East, and south Asia.

INTERPRETATION

To our knowledge, this is the first study that incorporates antibiotic usage and consumption data and uses geostatistical modelling techniques to estimate antibiotic consumption for 204 countries from 2000 to 2018. Our analysis identifies both high rates of antibiotic consumption and a lack of access to antibiotics, providing a benchmark for future interventions.

FUNDING

Fleming Fund, UK Department of Health and Social Care; Wellcome Trust; and Bill & Melinda Gates Foundation.