Ensuring progress on sustainable access to effective antibiotics at the 2024 UN General Assembly: a target-based approach.

Rising antimicrobial resistance (AMR) is a global health crisis for countries of all economic levels, alongside the broader challenge of access to antibiotics. As a result, development goals for child survival, healthy ageing, poverty reduction, and food security are at risk. Preserving antimicrobial effectiveness, a global public good, requires political will, targets, accountability frameworks, and funding. The upcoming second high-level meeting on AMR at the UN General Assembly (UNGA) in September, 2024, is evidence of political interest in addressing the problem of AMR, but action on targets, accountability, and funding, absent from the 2016 UNGA resolution, is needed. We propose ambitious yet achievable global targets for 2030 (relative to a prepandemic 2019 baseline): a 10% reduction in mortality from AMR; a 20% reduction in inappropriate human antibiotic use; and a 30% reduction in inappropriate animal antibiotic use. Given national variation in current levels of antibiotic use, these goals (termed the 10-20-30 by 2030) should be met within a framework of universal access to effective antibiotics. The WHO Access, Watch, Reserve (AWARE) system can be used to define, monitor, and evaluate appropriate levels of antibiotic use and access. Some countries should increase access to narrow-spectrum, safe, and affordable (Access) antibiotics, whereas others should discourage the inappropriate use of broader-spectrum (Watch) and last-resort (Reserve) antibiotics; AWARE targets should use a risk-based, burden-adjusted approach. Improved infection prevention and control, access to clean water and sanitation, and vaccination coverage can offset the selection effects of increased antibiotic use in low-income settings. To ensure accountability and global scientific guidance and consensus, we call for the establishment of the Independent Panel on Antimicrobial Access and Resistance and the support of leaders from low-income and middle-income countries.

Reducing the Antigen Prevalence Target Threshold for Stopping and Restarting Mass Drug Administration for Lymphatic Filariasis Elimination: A Model-Based Cost-effectiveness Simulation in Tanzania, India and Haiti.

BACKGROUND: The Global Programme to Eliminate Lymphatic Filariasis (GPELF) aims to reduce and maintain infection levels through mass drug administration (MDA), but there is evidence of ongoing transmission after MDA in areas where Culex mosquitoes are the main transmission vector, suggesting that a more stringent criterion is required for MDA decision making in these settings. METHODS: We use a transmission model to investigate how a lower prevalence threshold (<1% antigenemia [Ag] prevalence compared with <2% Ag prevalence) for MDA decision making would affect the probability of local elimination, health outcomes, the number of MDA rounds, including restarts, and program costs associated with MDA and surveys across different scenarios. To determine the cost-effectiveness of switching to a lower threshold, we simulated 65% and 80% MDA coverage of the total population for different willingness to pay per disability-adjusted life-year averted for India ($446.07), Tanzania ($389.83), and Haiti ($219.84). RESULTS: Our results suggest that with a lower Ag threshold, there is a small proportion of simulations where extra rounds are required to reach the target, but this also reduces the need to restart MDA later in the program. For 80% coverage, the lower threshold is cost-effective across all baseline prevalences for India, Tanzania, and Haiti. For 65% MDA coverage, the lower threshold is not cost-effective due to additional MDA rounds, although it increases the probability of local elimination. Valuing the benefits of elimination to align with the GPELF goals, we find that a willingness to pay per capita government expenditure of approximately $1000-$4000 for 1% increase in the probability of local elimination would be required to make a lower threshold cost-effective. CONCLUSIONS: Lower Ag thresholds for stopping MDAs generally mean a higher probability of local elimination, reducing long-term costs and health impacts. However, they may also lead to an increased number of MDA rounds required to reach the lower threshold and, therefore, increased short-term costs. Collectively, our analyses highlight that lower target Ag thresholds have the potential to assist programs in achieving lymphatic filariasis goals.

Detecting changes in population trends in infection surveillance using community SARS-CoV-2 prevalence as an exemplar.

Detecting and quantifying changes in growth rates of infectious diseases is vital to informing public health strategy and can inform policymakers' rationale for implementing or continuing interventions aimed at reducing impact. Substantial changes in SARS-CoV-2 prevalence with emergence of variants provides opportunity to investigate different methods to do this. We included PCR results from all participants in the UK's COVID-19 Infection Survey between August 2020-June 2022. Change-points for growth rates were identified using iterative sequential regression (ISR) and second derivatives of generalised additive models (GAMs). Consistency between methods and timeliness of detection were compared. Of 8,799,079 visits, 147,278 (1.7%) were PCR-positive. Change-points associated with emergence of major variants were estimated to occur a median 4 days earlier (IQR 0-8) in GAMs versus ISR. When estimating recent change-points using successive data periods, four change-points (4/96) identified by GAMs were not found when adding later data or by ISR. Change-points were detected 3-5 weeks after they occurred in both methods but could be detected earlier within specific subgroups. Change-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel.

Employment outcomes of people with Long Covid symptoms: community-based cohort study.

BACKGROUND: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and employment outcomes. METHODS: This was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16-64 years and not in education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks. RESULTS: Of 206 299 participants (mean age 45 years, 54% female, 92% white), 15% were ever labour market inactive and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks [adjusted odds ratio (aOR): 1.45; 95% CI: 1.17-1.81] or 40 to <52 weeks (aOR: 1.34; 95% CI: 1.05-1.72) post-infection. Combining with official statistics on Long Covid prevalence, and assuming a correct statistical model, our estimates translate to 27 000 (95% CI: 6000-47 000) working-age adults in the UK being inactive because of Long Covid in July 2022. CONCLUSIONS: Long Covid is likely to have contributed to reduced participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.

Associations between BMI and hospital resource use in patients hospitalised for COVID-19 in England: a community-based cohort study.

BACKGROUND: Excess weight is a major risk factor for severe disease after infection with SARS-CoV-2. However, the effect of BMI on COVID-19 hospital resource use has not been fully quantified. This study aimed to identify the association between BMI and hospital resource use for COVID-19 admissions with the intention of informing future national hospital resource allocation. METHODS: In this community-based cohort study, we analysed patient-level data from 57 415 patients admitted to hospital in England with COVID-19 between April 1, 2020, and Dec 31, 2021. Patients who were aged 20-99 years, had been registered with a general practitioner (GP) surgery that contributed to the QResearch database for the whole preceding year (2019) with at least one BMI value measured before April 1, 2020, available in their GP record, and were admitted to hospital for COVID-19 were included. Outcomes of interest were duration of hospital stay, transfer to an intensive care unit (ICU), and duration of ICU stay. Costs of hospitalisation were estimated from these outcomes. Generalised linear and logit models were used to estimate associations between BMI and hospital resource use outcomes. FINDINGS: Patients living with obesity (BMI >30·0 kg/m2) had longer hospital stays relative to patients in the reference BMI group (18·5-25·0 kg/m2; IRR 1·07, 95% CI 1·03-1·10); the reference group had a mean length of stay of 8·82 days (95% CI 8·62-9·01). Patients living with obesity were more likely to be admitted to ICU than the reference group (OR 2·02, 95% CI 1·86-2·19); the reference group had a mean probability of ICU admission of 5·9% (95% CI 5·5-6·3). No association was found between BMI and duration of ICU stay. The mean cost of COVID-19 hospitalisation was £19 877 (SD 17 918) in the reference BMI group. Hospital costs were estimated to be £2736 (95% CI 2224-3248) higher for patients living with obesity. INTERPRETATION: Patients admitted to hospital with COVID-19 with a BMI above the healthy range had longer stays, were more likely to be admitted to ICU, and had higher health-care costs associated with hospital treatment of COVID-19 infection as a result. This information can inform national resource allocation to match hospital capacity to areas where BMI profiles indicate higher demand. FUNDING: National Institute for Health Research.

Costs-effectiveness and cost components of pharmaceutical and non-pharmaceutical interventions affecting antibiotic resistance outcomes in hospital patients: a systematic literature review.

INTRODUCTION: Limited information on costs and the cost-effectiveness of hospital interventions to reduce antibiotic resistance (ABR) hinder efficient resource allocation. METHODS: We conducted a systematic literature review for studies evaluating the costs and cost-effectiveness of pharmaceutical and non-pharmaceutical interventions aimed at reducing, monitoring and controlling ABR in patients. Articles published until 12 December 2023 were explored using EconLit, EMBASE and PubMed. We focused on critical or high-priority bacteria, as defined by the WHO, and intervention costs and incremental cost-effectiveness ratio (ICER). Following Preferred Reporting Items for Systematic review and Meta-Analysis guidelines, we extracted unit costs, ICERs and essential study information including country, intervention, bacteria-drug combination, discount rates, type of model and outcomes. Costs were reported in 2022 US dollars ($), adopting the healthcare system perspective. Country willingness-to-pay (WTP) thresholds from Woods et al 2016 guided cost-effectiveness assessments. We assessed the studies reporting checklist using Drummond's method. RESULTS: Among 20 958 articles, 59 (32 pharmaceutical and 27 non-pharmaceutical interventions) met the inclusion criteria. Non-pharmaceutical interventions, such as hygiene measures, had unit costs as low as $1 per patient, contrasting with generally higher pharmaceutical intervention costs. Several studies found that linezolid-based treatments for methicillin-resistant Staphylococcus aureus were cost-effective compared with vancomycin (ICER up to $21 488 per treatment success, all 16 studies' ICERs

Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection.

OBJECTIVES: To identify patterns in inflammatory marker and vital sign responses in adult with suspected bloodstream infection (BSI) and define expected trends in normal recovery. METHODS: We included patients ≥16 y from Oxford University Hospitals with a blood culture taken between 1-January-2016 and 28-June-2021. We used linear and latent class mixed models to estimate trajectories in C-reactive protein (CRP), white blood count, heart rate, respiratory rate and temperature and identify CRP response subgroups. Centile charts for expected CRP responses were constructed via the lambda-mu-sigma method. RESULTS: In 88,348 suspected BSI episodes; 6908 (7.8%) were culture-positive with a probable pathogen, 4309 (4.9%) contained potential contaminants, and 77,131(87.3%) were culture-negative. CRP levels generally peaked 1-2 days after blood culture collection, with varying responses for different pathogens and infection sources (p < 0.0001). We identified five CRP trajectory subgroups: peak on day 1 (36,091; 46.3%) or 2 (4529; 5.8%), slow recovery (10,666; 13.7%), peak on day 6 (743; 1.0%), and low response (25,928; 33.3%). Centile reference charts tracking normal responses were constructed from those peaking on day 1/2. CONCLUSIONS: CRP and other infection response markers rise and recover differently depending on clinical syndrome and pathogen involved. However, centile reference charts, that account for these differences, can be used to track if patients are recovering line as expected and to help personalise infection.

Overcoming challenges in the economic evaluation of interventions to optimise antibiotic use.

Bacteria are becoming increasingly resistant to antibiotics, reducing our ability to treat infections and threatening to undermine modern health care. Optimising antibiotic use is a key element in tackling the problem. Traditional economic evaluation methods do not capture many of the benefits from improved antibiotic use and the potential impact on resistance. Not capturing these benefits is a major obstacle to optimising antibiotic use, as it fails to incentivise the development and use of interventions to optimise the use of antibiotics and preserve their effectiveness (stewardship interventions). Estimates of the benefits of improving antibiotic use involve considerable uncertainty as they depend on the evolution of resistance and associated health outcomes and costs. Here we discuss how economic evaluation methods might be adapted, in the face of such uncertainties. We propose a threshold-based approach that estimates the minimum resistance-related costs that would need to be averted by an intervention to make it cost-effective. If it is probable that without the intervention costs will exceed the threshold then the intervention should be deemed cost-effective.

Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population.

SARS-CoV-2 reinfections increased substantially after Omicron variants emerged. Large-scale community-based comparisons across multiple Omicron waves of reinfection characteristics, risk factors, and protection afforded by previous infection and vaccination, are limited. Here we studied ~45,000 reinfections from the UK's national COVID-19 Infection Survey and quantified the risk of reinfection in multiple waves, including those driven by BA.1, BA.2, BA.4/5, and BQ.1/CH.1.1/XBB.1.5 variants. Reinfections were associated with lower viral load and lower percentages of self-reporting symptoms compared with first infections. Across multiple Omicron waves, estimated protection against reinfection was significantly higher in those previously infected with more recent than earlier variants, even at the same time from previous infection. Estimated protection against Omicron reinfections decreased over time from the most recent infection if this was the previous or penultimate variant (generally within the preceding year). Those 14-180 days after receiving their most recent vaccination had a lower risk of reinfection than those >180 days from their most recent vaccination. Reinfection risk was independently higher in those aged 30-45 years, and with either low or high viral load in their most recent previous infection. Overall, the risk of Omicron reinfection is high, but with lower severity than first infections; both viral evolution and waning immunity are independently associated with reinfection.

Excess resource use and cost of drug-resistant infections for six key pathogens in Europe: a systematic review and Bayesian meta-analysis.

BACKGROUND: Quantifying the resource use and cost of antimicrobial resistance establishes the magnitude of the problem and drives action. OBJECTIVES: Assessment of resource use and cost associated with infections with six key drug-resistant pathogens in Europe. METHODS: A systematic review and Bayesian meta-analysis. DATA SOURCES: MEDLINE (Ovid), Embase (Ovid), Econlit databases, and grey literature for the period 1 January 1990, to 21 June 2022. STUDY ELIGIBILITY CRITERIA: Resource use and cost outcomes (including excess length of stay, overall costs, and other excess in or outpatient costs) were compared between patients with defined antibiotic-resistant infections caused by carbapenem-resistant (CR) Pseudomonas aeruginosa and Acinetobacter baumannii, CR or third-generation cephalosporin Escherichia coli (3GCREC) and Klebsiella pneumoniae, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococcus faecium, and patients with drug-susceptible or no infection. PARTICIPANTS: All patients diagnosed with drug-resistant bloodstream infections (BSIs). INTERVENTIONS: NA. ASSESSMENT OF RISK OF BIAS: An adapted version of the Joanna Briggs Institute assessment tool, incorporating case-control, cohort, and economic assessment frameworks. METHODS OF DATA SYNTHESIS: Hierarchical Bayesian meta-analyses were used to assess pathogen-specific resource use estimates. RESULTS: Of 5969 screened publications, 37 were included in the review. Data were sparse and heterogeneous. Most studies estimated the attributable burden by, comparing resistant and susceptible pathogens (32/37). Four studies analysed the excess cost of hospitalization attributable to 3GCREC BSIs, ranging from -€ 2465.50 to € 6402.81. Eight studies presented adjusted excess length of hospital stay estimates for methicillin-resistant S. aureus and 3GCREC BSIs (4 each) allowing for Bayesian hierarchical analysis, estimating means of 1.26 (95% credible interval [CrI], -0.72 to 4.17) and 1.78 (95% CrI, -0.02 to 3.38) days, respectively. CONCLUSIONS: Evidence on most cost and resource use outcomes and across most pathogen-resistance combinations was severely lacking. Given the importance of this evidence for rational policymaking, further research is urgently needed.

Improving the representativeness of UK's national COVID-19 Infection Survey through spatio-temporal regression and post-stratification.

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK's national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21 percentage points), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

Health and economic impacts of Lassa vaccination campaigns in West Africa.

Lassa fever is a zoonotic disease identified by the World Health Organization (WHO) as having pandemic potential. This study estimates the health-economic burden of Lassa fever throughout West Africa and projects impacts of a series of vaccination campaigns. We also model the emergence of "Lassa-X" - a hypothetical pandemic Lassa virus variant - and project impacts of achieving 100 Days Mission vaccination targets. Our model predicted 2.7M (95% uncertainty interval: 2.1M-3.4M) Lassa virus infections annually, resulting over ten years in 2.0M (793.8K-3.9M) disability-adjusted life years (DALYs). The most effective vaccination strategy was a population-wide preventive campaign primarily targeting WHO-classified "endemic" districts. Under conservative vaccine efficacy assumptions, this campaign averted $20.1M ($8.2M-$39.0M) in lost DALY value and $128.2M ($67.2M-$231.9M) in societal costs (International dollars 2021). Reactive vaccination in response to local outbreaks averted just one-tenth the health-economic burden of preventive campaigns. In the event of Lassa-X emerging, spreading throughout West Africa and causing approximately 1.2M DALYs within two years, 100 Days Mission vaccination averted 22% of DALYs given a vaccine 70% effective against disease, and 74% of DALYs given a vaccine 70% effective against both infection and disease. These findings suggest how vaccination could alleviate Lassa fever's burden and assist in pandemic preparedness.