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...

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A reduction in provocation inventory scores immediately after the group was more likely to occur if the participant was accompanied by a member of staff who knew them and if they had a higher score on the test of receptive vocabulary. This pattern changed with time. The implications of the results will be discussed and the relatively large amount of variance that is not accounted for will also be considered.

A panel of experts was convened by the International Society for Infectious Diseases (ISID) to overview evidence based strategies to reduce the transmission of pathogens via the hands of healthcare workers and the subsequent incidence of hospital acquired infections with a focus on implementing these strategies in low-and middle-income countries. Existing data suggests that hospital patients in low-and middle-income countries are exposed to rates of healthcare associated infections at least 2-fold higher than in high income countries. In addition to the universal challenges to the implementation of effective hand hygiene strategies, hospitals in low-and middle-income countries face a range of unique barriers, including overcrowding and securing a reliable and sustainable supply of alcohol-based handrub. The WHO Multimodal Hand Hygiene Improvement Strategy and its associated resources represent an evidence-based framework for developing a locally-adapted implementation plan for hand hygiene promotion.

BackgroundBuruli ulcer (BU) is a geographically-restricted infection caused by Mycobacterium ulcerans; contact with an endemic region is the primary risk factor for disease acquisition. Globally, efforts to estimate the incubation period of BU are often hindered as most patients reside permanently in endemic areas. However, in the south-eastern Australian state of Victoria, a significant proportion of people who acquire BU are visitors to endemic regions. During a sustained outbreak of BU on the Bellarine peninsula we estimated a mean incubation period of 4.5 months. Since then cases on the Bellarine peninsula have declined but a new endemic area has developed centred on the Mornington peninsula.MethodRetrospective review of 443 cases of BU notified in Victoria between 2013 and 2016. Telephone interviews were performed to identify all cases with a single visit to an endemic region, or multiple visits within a one month period. The incubation period was defined as the time between exposure to an endemic region and symptom onset. Data were subsequently combined with those from our earlier study incorporating cases from 2002 to 2012.ResultsAmong the 20 new cases identified in short-term visitors, the mean incubation period was 143 days (4.8 months), very similar to the previous estimate of 135 days (4.5 months). This was despite the predominant exposure location shifting from the Bellarine peninsula to the Mornington peninsula. We found no association between incubation period and age, sex, location of exposure, duration of exposure to an endemic region or location of BU lesion.ConclusionsOur study confirms the mean incubation period of BU in Victoria to be between 4 and 5 months. This knowledge can guide clinicians and suggests that the mode of transmission of BU is similar in different geographic regions in Victoria.