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- Ikuta, K. S., et al.
(författare)
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Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019
- 2022
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Ingår i: Lancet. - : Elsevier BV. - 0140-6736. ; 400:10369, s. 2221-2248
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Tidskriftsartikel (refereegranskat)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. Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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| 3. |
- Udeh-Momoh, CT, et al.
(författare)
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Health, Lifestyle, and Psycho-Social Determinants of Poor Sleep Quality During the Early Phase of the COVID-19 Pandemic: A Focus on UK Older Adults Deemed Clinically Extremely Vulnerable
- 2021
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Ingår i: Frontiers in public health. - : Frontiers Media SA. - 2296-2565. ; 9, s. 753964-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Several studies have assessed the impact of COVID-19-related lockdowns on sleep quality across global populations. However, no study to date has specifically assessed at-risk populations, particularly those at highest risk of complications from coronavirus infection deemed “clinically-extremely-vulnerable-(COVID-19CEV)” (as defined by Public Health England).Methods: In this cross-sectional study, we surveyed 5,558 adults aged ≥50 years (of whom 523 met criteria for COVID-19CEV) during the first pandemic wave that resulted in a nationwide-lockdown (April–June 2020) with assessments of sleep quality (an adapted sleep scale that captured multiple sleep indices before and during the lockdown), health/medical, lifestyle, psychosocial and socio-demographic factors. We examined associations between these variables and sleep quality; and explored interactions of COVID-19CEV status with significant predictors of poor sleep, to identify potential moderating factors.Results: Thirty-seven percent of participants reported poor sleep quality which was associated with younger age, female sex and multimorbidity. Significant associations with poor sleep included health/medical factors: COVID-19CEV status, higher BMI, arthritis, pulmonary disease, and mental health disorders; and the following lifestyle and psychosocial factors: living alone, higher alcohol consumption, an unhealthy diet and higher depressive and anxiety symptoms. Moderators of the negative relationship between COVID-19CEV status and good sleep quality were marital status, loneliness, anxiety and diet. Within this subgroup, less anxious and less lonely males, as well as females with healthier diets, reported better sleep.Conclusions: Sleep quality in older adults was compromised during the sudden unprecedented nation-wide lockdown due to distinct modifiable factors. An important contribution of our study is the assessment of a “clinically-extremely-vulnerable” population and the sex differences identified within this group. Male and female older adults deemed COVID-19CEV may benefit from targeted mental health and dietary interventions, respectively. This work extends the available evidence on the notable impact of lack of social interactions during the COVID-19 pandemic on sleep, and provides recommendations toward areas for future work, including research into vulnerability factors impacting sleep disruption and COVID-19-related complications. Study results may inform tailored interventions targeted at modifiable risk factors to promote optimal sleep; additionally, providing empirical data to support health policy development in this area.
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