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. MethodsWe 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 drugresistant 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. FindingsOn 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, meticillinresistant S aureus, caused more than 100 000 deaths attributa...

Background The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0•7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19. MethodsIn this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality. FindingsAmong the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23•3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37•4%) of 163 350, diabetes in 43 885 (27•4%) of 159 932, and HIV in 13 793 (9•1%) of 151 779. Tuberculosis was reported in 5282 (3•6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1•34, 95% CI 1•27-1•43), past tuberculosis (1•26, 1•15-1•38), current tuberculosis (1•42, 1•22-1•64), and both past and current tuberculosis (1•48, 1•32-1•67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1•45, 95% CI 1•22-1•72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29•2% compared with 30•8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with...

Background The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves.Methods In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression.Findings Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240•4 cases per 100 000 people vs 136•0 cases per 100 000 people; admissions, 27•9 admissions per 100 000 people vs 16•1 admissions per 100 000 people; deaths, 8•3 deaths per 100 000 people vs 3•6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1•19, 95% CI 1•18-1•20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1•22, 95% CI 1•14-1•31), and older than 65 years (aOR 1•38, 1•25-1•52), compared with younger than 40 years; of Mixed race (aOR 1•21, 1•06-1•38) compared with White race; and admitted in the public sector (aOR 1•65, 1•41-1•92); and less likely to be Black (aOR 0•53, 0•47-0•60) and Indian (aOR 0•77, 0•66-0•91), compared with White; and have a comorbid condition (aOR 0•60, 0•55-0•67).For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1•31, 95% CI 1•28-1•35). In-hospital case-fatality risk increased from 17•7% in weeks of low admission (<3500 admissions) to 26•9% in weeks of very high admission (>8000 admissions; aOR 1•24, 1•17-1•32).Interpretation In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage.

IntroductionGroup B Streptococcus (GBS) is a leading cause of neonatal sepsis and meningitis. We aimed to evaluate the burden of invasive early-onset (0–6 days of life, EOD) and late-onset (7–89 days, LOD) GBS disease and subsequent neurological sequelae in infants from a setting with a high prevalence (29.5%) of HIV among pregnant women.MethodsA case-control study was undertaken at three secondary-tertiary care public hospitals in Johannesburg. Invasive cases in infants <3 months age were identified by surveillance of laboratories from November 2012 to February 2014. Neurodevelopmental screening was done in surviving cases and controls at 3 and 6 months of age.ResultsWe identified 122 cases of invasive GBS disease over a 12 month period. Although the incidence (per 1,000 live births) of EOD was similar between HIV-exposed and HIV-unexposed infants (1.13 vs. 1.46; p = 0.487), there was a 4.67-fold (95%CI: 2.24–9.74) greater risk for LOD in HIV-exposed infants (2.27 vs. 0.49; p<0.001). Overall, serotypes Ia, Ib and III constituted 75.8% and 92.5% of EOD and LOD, respectively. Risk factors for EOD included offensive draining liquor (adjusted Odds Ratio: 27.37; 95%CI: 1.94–386.50) and maternal GBS bacteriuria (aOR: 8.41; 95%CI: 1.44–49.15), which was also a risk-factor for LOD (aOR: 3.49; 95%CI: 1.17–10.40). The overall case fatality rate among cases was 18.0%. The adjusted odds for neurological sequelae at 6 months age was 13.18-fold (95%CI: 1.44–120.95) greater in cases (13.2%) than controls (0.4%).DiscussionThe high burden of invasive GBS disease in South Africa, which is also associated with high case fatality rates and significant neurological sequelae among survivors, is partly due to the heightened risk for LOD in infants born to HIV-infected women. An effective trivalent GBS conjugate vaccine targeted at pregnant women could prevent invasive GBS disease in this setting.

BackgroundHealth protocols need to be guided by current data on survival and benefits of interventions within the local context. Periodic clinical audits are required to inform and update health care protocols. This study aimed to review morbidity and mortality in very low birth weight (VLBW) infants in 2013 compared with similar data from 2006/2007.MethodsWe performed a retrospective review of patients’ records from a neonatal computer database for 562 VLBW infants. These neonates weighed between 500 and 1500 g at birth, and were admitted within 48 hours after birth between 01 January 2013 and 31 December 2013. Patients’ characteristics, complications of prematurity, and therapeutic interventions were compared with 2006/2007 data. Univariate analysis and multiple logistic regression were performed to establish significant associations of various factors with survival to discharge for 2013.ResultsSurvival in 2013 was similar to that in 2006/2007 (73.4% vs 70.2%, p = 0.27). However, survival in neonates who weighed 750–900 g significantly improved from 20.4% in 2006/2007 to 52.4% in 2013 (p = 0.001). The use of nasal continuous positive airway pressure (NCPAP) increased from 20.3% to 62.9% and surfactant use increased from 19.2% to 65.5% between the two time periods (both p < 0.001). Antenatal care attendance improved from 54.4% to 70.6% (p = 0.001) and late onset sepsis (>72 hours after birth) increased from 12.5% to 19% (p = 0.006) between the two time periods. Other variables remained unchanged between 2006/2007 and 2013. The main determinants of survival to discharge in 2013 were birth weight (odds ratio 1.005, 95% confidence interval 1.003–1.0007, resuscitation at birth (2.673, 1.375–5.197), NCPAP (0.247, 0.109–0.560), necrotising enterocolitis (4.555, 1.659–12.51), and mode of delivery, including normal vaginal delivery (0.456, 0.231–0.903) and vaginal breech (0.069, 0.013–0.364).ConclusionsThere was a marked improvement in the survival of neonates weighing between 750 and 900 g at birth, most likely due to provision of surfactant and NCPAP. Provision of NCPAP, prevention of necrotising enterocolitis, and control of infection need to be prioritised in VLBW infants to improve their outcome.

Background The Bayley Scales of Infant and Toddler Development (III) is a tool developed in a Western setting. Aim To evaluate the development of a group of inner city children in South Africa with no neonatal risk factors using the Bayley Scales of Infant and Toddler Development (III), to determine an appropriate cut-off to define developmental delay, and to establish variation in scores done in the same children before and after one year of age. Methods Cohort follow-up study. Results 74 children had at least one Bayley III assessment at a mean age of 19.4 months (95% CI 18.4 to 20.4). The mean composite cognitive score was 92.2 (95% CI 89.4 to 95.0), the mean composite language score was 94.8 (95% CI 92.5 to 97.1), and mean composite motor score was 98.8 (95% CI 96.8 to 101.0). No child had developmental delay using a cut-off score of 70. In paired assessments above and below one year of age, the cognitive score remained unchanged, the language score decreased significantly (p = 0.001), and motor score increased significantly (p = 0.004) between the two ages. Conclusion The Bayley Scales of Infant and Toddler Development (III) is a suitable tool for assessing development in urban children in southern Africa.

Background Neonatal sepsis is a leading cause of child mortality, and increasing antimicrobial resistance threatens progress towards the Sustainable Development Goals. Evidence to guide antibiotic treatment for sepsis in neonates and young infants from randomized controlled trials or observational studies in low- and middle-income countries (LMICs) is scarce. We aimed to describe patterns of antibiotic use, pathogens and outcomes in LMIC hospital settings globally to inform future clinical trials on the management of neonatal sepsis. Methods & Findings Hospitalised infants aged <60 days with clinical sepsis were enrolled during 2018-2020 by 19 sites in 11 countries (mainly Asia and Africa). Prospective daily data was collected on clinical signs, supportive care, antibiotic treatment, microbiology and clinical outcome at 28 days. The study was observational, with no changes to routine clinical practice. 3204 infants were enrolled, with median birth weight 2500g (IQR 1400-3000) and postnatal age 5 days (IQR 2-15). Of 309 enrolled aged 28-60 days, 58.6% (n=181) were ex-preterm and/or a neonate at admission. 2215 (69%) infants had been in hospital since birth. 206 different empiric antibiotic combinations were used, which were structured into 5 groups that were developed from the World Health Organisation (WHO) AWaRe classification. 25.9% (n=814) of infants started a WHO first line regimen (Group 1 Access, penicillin-based regimen) and 13.8% (n=432) started WHO second-line cephalosporins (cefotaxime/ceftriaxone) (Group 2 Low Watch). The largest group (34.0%, n=1068) started a regimen providing partial extended-spectrum beta-lactamase (ESBL)/pseudomonal coverage (piperacillin-tazobactam, ceftazidime, or fluoroquinolone-based) (Group 3 Medium Watch), 18.0% (n=566) started a carbapenem (Group 4 High Watch), and 1.8% (n=57) started a Reserve antibiotic (Group 5, largely colistin-based). Predictors of starting non-WHO recommended regimens included lower birth weight, longer in-hospital stay, central vascular catheter use, previous culture positive sepsis or antibiotic exposure, previous surgery and greater sepsis severity. 728/2880 (25.3%) of initial regimens in Group 1-4 were escalated, mainly to carbapenems, and usually for clinical indications (n=480; 65.9%). 564 infants (17.6%) isolated a pathogen from their baseline blood culture, of which 62.9% (n=355) had a Gram-negative organism, predominantly Klebsiella pneumoniae (n=132) and Acinetobacter spp. (n=72). These leading Gram-negatives were both mostly resistant to WHO-recommended regimens, and also resistant to carbapenems in 32.6% and 71.4% of cases respectively. MRSA accounted for 61.1% of Staphylococcus aureus (n=54) isolates. Overall, 350/3204 infants died (11.3%; 95%CI 10.2-12.5%), with 17.7% case fatality rate among infants with a pathogen in baseline culture (95%CI 14.7-20.1%, n=99/564). Gram-negative infections accounted for 75/99 (75.8%) of pathogen-positive deaths, especially Klebsiella pneumoniae (n=28; 28.3%), and Acinetobacter spp. (n=24; 24.2%). Conclusion A very wide range of antibiotic regimens are now used to treat neonatal sepsis globally. There is common use of higher-level Watch antibiotics, frequent early switching and very infrequent de-escalation of therapy. Future hospital based neonatal sepsis trials will ideally need to account for the multiple regimens used as standard of care globally and include both empiric first line regimens and subsequent switching in the trial design.

Background There is limited data on antibiotic treatment in hospitalized neonates in low- and middle-income countries (LMICs). We aimed to describe patterns of antibiotic use, pathogens, and clinical outcomes, and to develop a severity score predicting mortality in neonatal sepsis to inform future clinical trial design. Methods and findings Hospitalized infants <60 days with clinical sepsis were enrolled during 2018 to 2020 by 19 sites in 11 countries (mainly Asia and Africa). Prospective daily observational data was collected on clinical signs, supportive care, antibiotic treatment, microbiology, and 28-day mortality. Two prediction models were developed for (1) 28-day mortality from baseline variables (baseline NeoSep Severity Score); and (2) daily risk of death on IV antibiotics from daily updated assessments (NeoSep Recovery Score). Multivariable Cox regression models included a randomly selected 85% of infants, with 15% for validation. A total of 3,204 infants were enrolled, with median birth weight of 2,500 g (IQR 1,400 to 3,000) and postnatal age of 5 days (IQR 1 to 15). 206 different empiric antibiotic combinations were started in 3,141 infants, which were structured into 5 groups based on the World Health Organization (WHO) AWaRe classification. Approximately 25.9% (n = 814) of infants started WHO first line regimens (Group 1—Access) and 13.8% (n = 432) started WHO second-line cephalosporins (cefotaxime/ceftriaxone) (Group 2—“Low” Watch). The largest group (34.0%, n = 1,068) started a regimen providing partial extended-spectrum beta-lactamase (ESBL)/pseudomonal coverage (piperacillin-tazobactam, ceftazidime, or fluoroquinolone-based) (Group 3—“Medium” Watch), 18.0% (n = 566) started a carbapenem (Group 4—“High” Watch), and 1.8% (n = 57) a Reserve antibiotic (Group 5, largely colistin-based), and 728/2,880 (25.3%) of initial regimens in Groups 1 to 4 were escalated, mainly to carbapenems, usually for clinical deterioration (n = 480; 65.9%). A total of 564/3,195 infants (17.7%) were blood culture pathogen positive, of whom 62.9% (n = 355) had a gram-negative organism, predominantly Klebsiella pneumoniae (n = 132) or Acinetobacter spp. (n = 72). Both were commonly resistant to WHO-recommended regimens and to carbapenems in 43 (32.6%) and 50 (71.4%) of cases, respectively. MRSA accounted for 33 (61.1%) of 54 Staphylococcus aureus isolates. Overall, 350/3,204 infants died (11.3%; 95% CI 10.2% to 12.5%), 17.7% if blood cultures were positive for pathogens (95% CI 14.7% to 21.1%, n = 99/564). A baseline NeoSep Severity Score had a C-index of 0.76 (0.69 to 0.82) in the validation sample, with mortality of 1.6% (3/189; 95% CI: 0.5% to 4.6%), 11.0% (27/245; 7.7% to 15.6%), and 27.3% (12/44; 16.3% to 41.8%) in low (score 0 to 4), medium (5 to 8), and high (9 to 16) risk groups, respectively, with similar performance across subgroups. A related NeoSep Recovery Score had an area under the receiver operating curve for predicting death the next day between 0.8 and 0.9 over the first week. There was significant variation in outcomes between sites and external validation would strengthen score applicability. Conclusion Antibiotic regimens used in neonatal sepsis commonly diverge from WHO guidelines, and trials of novel empiric regimens are urgently needed in the context of increasing antimicrobial resistance (AMR). The baseline NeoSep Severity Score identifies high mortality risk criteria for trial entry, while the NeoSep Recovery Score can help guide decisions on regimen change. NeoOBS data informed the NeoSep1 antibiotic trial (ISRCTN48721236), which aims to identify novel first- and second-line empiric antibiotic regimens for neonatal sepsis. Trial registration ClinicalTrials.gov, (NCT03721302).