Background: Lower respiratory tract infections (LRTIs) remain a leading cause of morbidity and mortality worldwide, with a disproportionate impact in low- and middle-income regions. Reliable, up-to-date burden estimates are essential for informing public health strategies, particularly in Latin America and the Caribbean, where respiratory infections remain a persistent challenge. High incidence strains the healthcare system capacity and quality, while prevention and management strategies remain limited or heterogeneous across countries. Methods: We analysed estimates from the Global Burden of Disease (GBD) 2023 study to quantify the burden of LRTIs in Latin America and the Caribbean between 1990 and 2023. Cause-specific estimates of mortality, incidence, and disability-adjusted life years (DALYs), expressed as years of life lost (YLL) plus years lived with disability (YLD), were extracted from the GBD Results Tool. Estimates were produced following the standardised GBD protocol, coordinated by the Institute for Health Metrics and Evaluation (IHME), which synthesises multiple data sources using validated statistical models. Findings: Globally, LRTIs accounted for 41·0 (36·0–48·0) deaths per 100 000 person-years in 2023, representing a 33·2% decline from 62 (53·0–72·0) per 100 000 in 1990. Within Latin America and the Caribbean, trends were heterogeneous across countries. Mortality rates declined substantially in Chile (from 48·0 [44·1–51·8] to 27·9 [24·1–31·4] deaths per 100 000; annualized rates of change [ARC] -1·63) and Mexico (from 36·3 [33·3–39·8] to 28·2 [24·6–32·3]; ARC -0·76), while reductions were most pronounced among children under five years, notably in Brazil (from 150·6 [131·2–175·2] to 18·5 [15·9–21·3] per 100 000; ARC -6·16) and Chile (from 55·1 [50·6–60·1] to 5·4 [4·3–6·5]; ARC -6·79). DALY rates also declined markedly in several countries, with the largest reductions observed in Peru (from 5771·5 [4896·0–6845·4] to 1629·9 [1357·9–1940·8] per 100 000; ARC -3·76) and Mexico (from 2359·6 [2123·0–2619·1] to 825·5 [727·2–927·7]; ARC -3·13). Following a sustained decline in incidence from 1990 to 2019, the post-COVID-19 era saw a marked reversal across all age groups, with incidence rates rising steadily through 2023, most notably among children under five years in Brazil (ARC +7·919) and Suriname (ARC +8·844), and older adults over 70 years in Cuba (ARC +5·050) and Chile (ARC +5·138). Based on aetiological causes, in 2023 Streptococcus pneumoniae remained the leading agent of LRTI mortality in the region (7·84 [6·99–8·92] deaths per 100 000), followed by Staphylococcus aureus (3·36 [3·02–3·69] deaths per 100 000). Interpretation: LRTIs remain a leading cause of death and disability in Latin America and the Caribbean, yet our findings demonstrate substantial progress in reducing mortality and DALY burden over three decades. We document marked heterogeneity across countries and age groups, with the greatest gains among children under five years old. Shifts in pathogen distribution are evident: S. pneumoniae persists as the leading cause of LRTI mortality, while S. aureus and non-tuberculous mycobacteria (NTM) have emerged as increasingly important contributors. The post-COVID period has reversed prior incidence trends across all age groups, underscoring the vulnerability of regional health systems to pandemic disruptions. These findings highlight the urgent need for sustained investment in vaccination programmes, equitable access to care, and strengthened epidemiological surveillance to reduce the burden of LRTI in the region.

BACKGROUND:The 2017 WHO Bacterial Priority Pathogens List (BPPL) has been instrumental in guiding global policy, research and development, and investments to address the most urgent threats from antibiotic-resistant pathogens, and it is a key public health tool for the prevention and control of antimicrobial resistance (AMR). Since its release, at least 13 new antibiotics targeting bacterial priority pathogens have been approved. The 2024 WHO BPPL aims to refine and build on the previous list by incorporating new data and evidence, addressing previous limitations, and improving pathogen prioritisation to better guide global efforts in combating AMR. METHODS:The 2024 WHO BPPL followed a similar approach to the first prioritisation exercise, using a multicriteria decision analysis framework. 24 antibiotic-resistant bacterial pathogens were scored based on eight criteria, including mortality, non-fatal burden, incidence, 10-year resistance trends, preventability, transmissibility, treatability, and antibacterial pipeline status. Pathogens were assessed on each of the criteria on the basis of available evidence and expert judgement. A preferences survey using a pairwise comparison was administered to 100 international experts (among whom 79 responded and 78 completed the survey) to determine the relative weights of the criteria. Applying these weights, the final ranking of pathogens was determined by calculating a total score in the range of 0-100% for each pathogen. Subgroup and sensitivity analyses were conducted to assess the impact of experts' consistency, background, and geographical origin on the stability of the rankings. An independent advisory group reviewed the final list, and pathogens were subsequently streamlined and grouped into three priority tiers based on a quartile scoring system: critical (highest quartile), high (middle quartiles), and medium (lowest quartile). FINDINGS:The pathogens' total scores ranged from 84% for the top-ranked bacterium (carbapenem-resistant Klebsiella pneumoniae) to 28% for the bottom-ranked bacterium (penicillin-resistant group B streptococci). Antibiotic-resistant Gram-negative bacteria (including K pneumoniae, Acinetobacter spp, and Escherichia coli), as well as rifampicin-resistant Mycobacterium tuberculosis, were ranked in the highest quartile. Among the bacteria commonly responsible for community-acquired infections, the highest rankings were for fluoroquinolone-resistant Salmonella enterica serotype Typhi (72%), Shigella spp (70%), and Neisseria gonorrhoeae (64%). Other important pathogens on the list include Pseudomonas aeruginosa and Staphylococcus aureus. The results of the preferences survey showed a strong inter-rater agreement, with Spearman's rank correlation coefficient and Kendall's coefficient of concordance both at 0·9. The final ranking showed high stability, with clustering of the pathogens based on experts' backgrounds and origins not resulting in any substantial changes to the ranking. INTERPRETATION:The 2024 WHO BPPL is a key tool for prioritising research and development investments and informing global public health policies to combat AMR. Gram-negative bacteria and rifampicin-resistant M tuberculosis remain critical priority pathogens, underscoring their persistent threat and the limitations of the current antibacterial pipeline. Focused efforts and sustained investments in novel antibacterials are needed to address AMR priority pathogens, which include high-burden antibiotic-resistant bacteria such as Salmonella and Shigella spp, N gonorrhoeae, and S aureus. Beyond research and development, efforts to address these pathogens should also include expanding equitable access to existing drugs, enhancing vaccine coverage, and strengthening infection prevention and control measures. FUNDING:This work is based on the development of the 2024 WHO BPPL, which was conducted by the WHO AMR Division through grants from the Government of Austria, the Government of Germany, the Government of Saudi Arabia, and the European Commission's Health Emergency Preparedness and Response Authority. TRANSLATIONS:For the Arabic, French, Italian, Japanese and Spanish translations of the abstract see Supplementary Materials section.

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 Weestimated 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.Copyright (c) 2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

AIM:To deliver the most wide-ranging set of antimicrobial resistance (AMR) burden estimates for Croatia to date.METHODS:A complex modeling approach with five broad modeling components was used to estimate the disease burden for 12 main infectious syndromes and one residual group, 23 pathogenic bacteria, and 88 bug-drug combinations. This was represented by two relevant counterfactual scenarios: deaths/disability-adjusted life years (DALYs) that are attributable to AMR considering a situation where drug-resistant infections are substituted with sensitive ones, and deaths/DALYs associated with AMR considering a scenario where people with drug-resistant infections would instead present without any infection. The 95% uncertainty intervals (UI) were based on 1000 posterior draws in each modeling step, reported at the 2.5% and 97.5% of the draws' distribution, while out-of-sample predictive validation was pursued for all the models.RESULTS:The total burden associated with AMR in Croatia was 2546 (95% UI 1558-3803) deaths and 46958 (28,033-71,628) DALYs, while the attributable burden was 614 (365-943) deaths and 11321 (6,544-17,809) DALYs. The highest number of deaths was established for bloodstream infections, followed by peritoneal and intra-abdominal infections and infections of the urinary tract. Five leading pathogenic bacterial agents were responsible for 1808 deaths associated with resistance: Escherichia coli, Staphylococcus aureus, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa (ordered by the number of deaths). Trimethoprim/sulfamethoxazole-resistant E coli and methicillin-resistant S. aureus were dominant pathogen-drug combinations in regard to mortality associated with and attributable to AMR, respectively.CONCLUSION:We showed that AMR represented a substantial public health concern in Croatia, which reflects global trends; hence, our detailed country-level findings may fast-track the implementation of multipronged strategies tailored in accordance with leading pathogens and pathogen-drug combinations.

We thank Andrew Conner and colleagues for their careful and thoughtful review of our Article.1GBD 2019 Police Violence US Subnational CollaboratorsFatal police violence by race and state in the USA, 1990–2019: a network meta-regression.Lancet. 2021; 398: 1239-1255Summary Full Text Full Text PDF Google Scholar We greatly appreciate the feedback. We have a few clarifications on the points they have raised. First, the network meta-regression we used is capable of accounting for consistent differences between case definitions in datasets, allowing us to combine spatial-temporal information from different sources and adjust them to the level of a gold standard. For this reason, The Counted and Fatal Encounters can use different case definitions and both be included in the regression. We excluded vehicle deaths from Fatal Encounters but not from The Counted, our gold standard case definition, because vehicle deaths where police were present but not directly involved are very high in Fatal Encounters, which could have altered the temporal trend of these data in a way that the regression could not account for. As such, we acknowledge that sources like the National Violent Death Reporting System (NVDRS) did not necessarily need to be excluded on the basis of their case definition alone. However, the NVDRS was also excluded because this study was a sub-national analysis, and the regression approach we used required coverage of all 50 US states and District of Columbia by each dataset to be solvable. The NVDRS did not make the data available for every state.2Centers for Disease Control and PreventionNational Violent Death Reporting System.https://www.cdc.gov/injury/wisqars/nvdrs.htmlDate: 2021Date accessed: January 24, 2022Google Scholar If comprehensive state-level data are available through a request process that we were not aware of, we would be happy to include it in future iterations of police violence estimates. However, we do agree that because the NVDRS is an official surveillance system with notable coverage, we should have discussed it further in the Discussion section rather than in the appendix. Thank you for bringing this gap to our attention. Second, we understand that each source uses a different case definition, but we believe that the case definition we used is the most accurate to capture police violence. Our definition is used by both Mapping Police Violence and The Counted. However, if we are able to attain NVDRS data from all 50 US states and District of Columbia in the future, we would be happy to include it with its respective case definition in our analyses. We declare no competing interests. Fatal police violence by race and state in the USA, 1980–2019: a network meta-regressionWe found that more than half of all deaths due to police violence that we estimated in the USA from 1980 to 2018 were unreported in the NVSS. Compounding this, we found substantial differences in the age-standardised mortality rate due to police violence over time and by racial and ethnic groups within the USA. Proven public health intervention strategies are needed to address these systematic biases. State-level estimates allow for appropriate targeting of these strategies to address police violence and improve its reporting. Full-Text PDF Open AccessHomicides by law enforcement: case definitions matterConsistent with previous studies, the Article by the GBD 2019 Police Violence US Subnational Collaborators1 finds that the National Vital Statistics System (NVSS) data under-report approximately half of all violent deaths of civilians that occur following encounters with law enforcement.2–5 The decision not to assess the National Violent Death Reporting System (NVDRS) is unfortunate for two reasons. First, the NVDRS is the most promising surveillance database for tracking homicides by police in the USA; second, the NVDRS is excluded on the basis of the misconception that it does not capture homicides by police involving methods other than firearms. Full-Text PDF

BACKGROUND:People with severe mental illness have a mortality rate higher than the general population, living an average of 10-20 years less. Most studies of mortality among people with severe mental illness have occurred in high-income countries (HICs). We aimed to estimate all-cause and cause-specific relative risk (RR) and excess mortality rate (EMR) in a nationwide cohort of inpatients with severe mental illness compared with inpatients without severe mental illness in a middle income country, Brazil. METHODS:This national retrospective cohort study included all patients hospitalised through the Brazilian Public Health System (Sistema Único de Saúde [SUS]-Brazil) between Jan 1, 2000, and April 21, 2015. Probabilistic and deterministic record linkages integrated data from the Hospital Information System (Sistema de informações Hospitalares) and the National Mortality System (Sistema de Informação sobre Mortalidade). Follow-up duration was measured from the date of the patients' first hospitalisation until their death, or until April 21, 2015. Severe mental illness was defined as schizophrenia, bipolar disorder, or depressive disorder by ICD-10 codes used for the admission. RR and EMR were calculated with 95% CIs, comparing mortality among patients with severe mental illness with those with other diagnoses for patients aged 15 years and older. We redistributed deaths using the Global Burden of Diseases, Injuries, and Risk Factors Study methodology if ill-defined causes of death were stated as an underlying cause. FINDINGS:From Jan 1, 2000, to April 21, 2015, 72 021 918 patients (31 510 035 [43·8%] recorded as male and 40 974 426 [56·9%] recorded as female; mean age 41·1 (SD 23·8) years) were admitted to hospital, with 749 720 patients (372 458 [49·7%] recorded as male and 378 670 [50·5%] as female) with severe mental illness. 5 102 055 patient deaths (2 862 383 [56·1%] recorded as male and 2 314 781 [45·4%] as female) and 67 485 deaths in patients with severe mental illness (39 099 [57·9%] recorded as male and 28 534 [42·3%] as female) were registered. The RR for all-cause mortality in patients with severe mental illness was 1·27 (95% CI 1·27-1·28) and the EMR was 2·52 (2·44-2·61) compared with non-psychiatric inpatients during the follow-up period. The all-cause RR was higher for females and for younger age groups; however, EMR was higher in those aged 30-59 years. The RR and EMR varied across the leading causes of death, sex, and age groups. We identified injuries (suicide, interpersonal violence, and road injuries) and cardiovascular disease (ischaemic heart disease) as having the highest EMR among those with severe mental illness. Data on ethnicity were not available. INTERPRETATION:In contrast to studies from HICs, inpatients with severe mental illness in Brazil had high RR for idiopathic epilepsy, tuberculosis, HIV, and acute hepatitis, and no significant difference in mortality from cancer compared with inpatients without severe mental illness. These identified causes should be addressed as a priority to maximise mortality prevention among people with severe mental illness, especially in a middle-income country like Brazil that has low investment in mental health. FUNDING:Bill and Melinda Gates Foundation, Fundação de Amparo a Pesquisa do Estado de Minas Gerais, FAPEMIG, and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil.

Background Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments. Methods We describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings. Results The proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD. Conclusions We provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

INTRODUCTION:Misclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision-making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories.METHODS:The cause of death data were obtained from the World Health Organization Mortality Database and official country-specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics.RESULTS:In 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were "immunodeficiency antibody" (ICD 9: 279-279.1; ICD 10: D80-D80.9) and "immunodeficiency other" (ICD 9: 279, 279.5-279.9; ICD 10: D83-D84.9, D89, D89.8-D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010-012.9; ICD 10: A10-A14, A15-A16.9) contributed the greatest proportion of all HIV misclassified deaths (25-62% per year) over the most years.CONCLUSIONS:Correcting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.

Background The burden of fatal police violence is an urgent public health crisis in the USA. Mounting evidence shows that deaths at the hands of the police disproportionately impact people of certain races and ethnicities, pointing to systemic racism in policing. Recent high-profile killings by police in the USA have prompted calls for more extensive and public data reporting on police violence. This study examines the presence and extent of under-reporting of police violence in US Government-run vital registration data, offers a method for correcting under-reporting in these datasets, and presents revised estimates of deaths due to police violence in the USA. Methods We compared data from the USA National Vital Statistics System (NVSS) to three non-governmental, opensource databases on police violence: Fatal Encounters, Mapping Police Violence, and The Counted. We extracted and standardised the age, sex, US state of death registration, year of death, and race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic of other races, and Hispanic of any race) of each decedent for all data sources and used a network meta-regression to quantify the rate of under-reporting within the NVSS. Using these rates to inform correction factors, we provide adjusted estimates of deaths due to police violence for all states, ages, sexes, and racial and ethnic groups from 1980 to 2019 across the USA. Findings Across all races and states in the USA, we estimate 30 800 deaths (95% uncertainty interval [UI] 30 300-31 300) from police violence between 1980 and 2018; this represents 17 100 more deaths (16 600-17 600) than reported by the NVSS. Over this time period, the age-standardised mortality rate due to police violence was highest in non-Hispanic Black people (0.69 [95% UI 0.67-0.71] per 100 000), followed by Hispanic people of any race (0.35 [0.34-0.36]), nonHispanic White people (0.20 [0.19-0.20]), and non-Hispanic people of other races (0.15 [0.14- 0.16]). This variation is further affected by the decedent's sex and shows large discrepancies between states. Between 1980 and 2018, the NVSS did not report 55.5% (54.8-56.2) of all deaths attributable to police violence. When aggregating all races, the age-standardised mortality rate due to police violence was 0.25 (0.24-0.26) per 100 000 in the 1980s and 0.34 (0.34-0.35) per 100 000 in the 2010s, an increase of 38.4% (32.4-45.1) over the period of study. Interpretation We found that more than half of all deaths due to police violence that we estimated in the USA from 1980 to 2018 were unreported in the NVSS. Compounding this, we found substantial differences in the agestandardised mortality rate due to police violence over time and by racial and ethnic groups within the USA. Proven public health intervention strategies are needed to address these systematic biases. State-level estimates allow for appropriate targeting of these strategies to address police violence and improve its reporting. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.