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BackgroundCOVID-19 and antimicrobial resistance (AMR) are two intersecting global public health crises. ObjectiveWe aim to describe the impact of the COVID-19 pandemic on AMR across healthcare settings. Data SourceA search was conducted in December 2021 in World Health Organizations COVID-19 Research Database with forward citation searching up to June 2022. Study EligibilityStudies evaluating the impact of COVID-19 on AMR in any population were included and influencing factors were extracted. MethodsPooling was done separately for Gram-negative and Gram-positive organisms. Random effects meta-analysis was performed. ResultsOf 6036 studies screened, 28 were included and 23 provided sufficient data for meta-analysis. The majority of studies focused on hospital settings (n=25, 89%). The COVID-19 pandemic was not associated with a change in the incidence density (IRR 0.99, 95% CI: 0.67 to 1.47) or proportion (RR 0.91, 95% CI: 0.55 to 1.49) of MRSA or VRE cases. A non-statistically significant increase was noted for resistant Gram-negatives (i.e., ESBL, CRE, MDR or carbapenem-resistant Pseudomonas or Acinetobacter species, IRR 1.64, 95% CI: 0.92 to 2.92; RR 1.08, 95% CI: 0.91 to 1.29). The absence of enhanced IPAC and/or ASP initiatives was associated with an increase in Gram-negative AMR (RR 1.11, 95%CI: 1.03 to 1.20), while studies that did report implementation of these initiatives noted no change in Gram-negative AMR (RR 0.80, 95%CI: 0.38 to 1.70). However, a test for subgroup differences showed no statistically significant difference between these groups (P=0.40) ConclusionThe COVID-19 pandemic could play an important role in the emergence and transmission of AMR, particularly for Gram-negative organisms in hospital settings. There is considerable heterogeneity in both the AMR metrics utilized and the rate of resistance reported across studies. These findings reinforce the need for strengthened infection prevention, antimicrobial stewardship, and AMR surveillance in the context of the COVID-19 pandemic. PROSPERO registration: CRD42022325831This research was carried out as part of routine work, no funding was received Data collection template, data, and analytic code are available upon request.
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BackgroundWhilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. MethodsHere, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. ResultsOur analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61 - 0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. ConclusionsAlthough clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.
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Objective@#The purpose of this survey was to estimate the prevalence of viral load (VL) suppression and emergence of HIV drug resistance (HIVDR) among individuals receiving antiretroviral therapy (ART) for 36 months or longer in Viet Nam using a nationally representative sampling method.@*Methods@#The survey was conducted between May and August 2014 using a two-stage cluster design. Sixteen ART clinics were selected using probability proportional to proxy size sampling, and patients receiving ART for at least 36 months were consecutively enrolled. Epidemiological information and blood specimens were collected for HIV-1 VL and HIVDR testing; HIVDR was defined by the Stanford University HIVDR algorithm.@*Results@#Overall, 365 eligible individuals were recruited with a mean age of 38.2 years; 68.4% were men. The mean time on ART was 75.5 months (95% confidence interval [CI]: 69.0–81.9 months), and 93.7% of the patients were receiving non-nucleoside reverse transcriptase inhibitor-based regimens. Of the 365 individuals, 345 (94.7%, 95% CI: 64.1–99.4%) had VL below 1000 copies/mL and 19 (4.6%, 95% CI: 2.8-–7.5) had HIVDR mutations.@*Discussion@#Our nationally representative survey found a high level of VL suppression and a low prevalence of HIVDR among individuals who received ART for at least 36 months in Viet Nam. Continued surveillance for HIVDR is important for evaluating and improving HIV programs.
