Evaluating the risk of conflict on recent Ebola outbreaks in Guinea and the Democratic Republic of the Congo.

BACKGROUND: Reducing Ebola virus transmission relies on the ability to identify cases and limit contact with infected bodily fluids through biosecurity, safe sex practices, safe burial and vaccination. Armed conflicts can complicate outbreak detection and interventions due to widespread disruption to governments and populations. Guinea and the Democratic Republic of the Congo (DRC) have historically reported the largest and the most recent Ebola virus outbreaks. Understanding if conflict played a role in these outbreaks may help in identifying key risks factors to improve disease control. METHODS: We used data from a range of publicly available data sources for both Ebola virus cases and conflict events from 2018 to 2021 in Guinea and the DRC. We fitted these data to conditional logistic regression models using the Self-Controlled Case Series methodology to evaluate the magnitude in which conflict increased the risk of reported Ebola virus cases in terms of incidence rate ratio. We re-ran the analysis sub-nationally, by conflict sub-event type and tested any lagged effects. RESULTS: Conflict was significantly associated with an increased risk of reported Ebola virus cases in both the DRC and Guinea in recent outbreaks. The effect was of a similar magnitude at 1.88- and 1.98-times increased risk for the DRC and Guinea, respectively. The greatest effects (often higher than the national values) were found in many conflict prone areas and during protest/riot-related conflict events. Conflict was influential in terms of Ebola virus risk from 1 week following the event and remained important by 10 weeks. CONCLUSION: Extra vigilance is needed following protests and riot-related conflict events in terms of Ebola virus transmission. These events are highly disruptive, in terms of access to transportation and healthcare and are often in urban areas with high population densities. Additional public health messaging around these types of conflict events, relating to the risks and clinical symptoms may be helpful in reducing transmission. Future work should aim to further understand and quantify conflict severity and intensity, to evaluate dose-response relationships in terms of disease risk.

Comparative Effectiveness of mRNA-1273 and BNT162b2 COVID-19 Vaccines Among Older Adults: Systematic Literature Review and Meta-Analysis Using the GRADE Framework.

INTRODUCTION: The mRNA vaccines mRNA-1273 and BNT162b2 demonstrated high efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in phase 3 clinical trials, including among older adults. To inform coronavirus disease 2019 (COVID-19) vaccine selection, this systematic literature review (SLR) and meta-analysis assessed the comparative effectiveness of mRNA-1273 versus BNT162b2 in older adults. METHODS: We systematically searched for relevant studies reporting COVID-19 outcomes with mRNA vaccines in older adults aged ≥ 50 years by first cross-checking relevant published SLRs. Based on the cutoff date from a previous similar SLR, we then searched the WHO COVID-19 Research Database for relevant articles published between April 9, 2022, and June 2, 2023. Outcomes of interest were SARS-CoV-2 infection, symptomatic SARS-CoV-2 infection, severe SARS-CoV-2 infection, COVID-19-related hospitalization, and COVID-19-related death following ≥ 2 vaccine doses. Random effects meta-analysis models were used to pool risk ratios (RRs) across studies. Heterogeneity was evaluated using chi-square testing. Evidence certainty was assessed per GRADE framework. RESULTS: Twenty-four non-randomized real-world studies reporting clinical outcomes with mRNA vaccines in individuals aged ≥ 50 years were included in the meta-analysis. Vaccination with mRNA-1273 was associated with significantly lower risk of SARS-CoV-2 infection (RR 0.72 [95% confidence interval (CI) 0.64‒0.80]), symptomatic SARS-CoV-2 infection (RR 0.72 [95% CI 0.62‒0.83]), severe SARS-CoV-2 infection (RR 0.67 [95% CI 0.57‒0.78]), and COVID-19-related hospitalization (RR 0.65 [95% CI 0.53‒0.79]) but not COVID-19-related death (RR 0.80 [95% CI 0.64‒1.00]) compared with BNT162b2. There was considerable heterogeneity between studies for all outcomes (I2 > 75%) except death (I2 = 0%). Multiple subgroup and sensitivity analyses excluding specific studies generally demonstrated consistent results. Certainty of evidence across outcomes was rated as low (type 3) or very low (type 4), reflecting the lack of randomized controlled trial data. CONCLUSION: Meta-analysis of 24 observational studies demonstrated significantly lower risk of asymptomatic, symptomatic, and severe infections and hospitalizations with the mRNA-1273 versus BNT162b2 vaccine in older adults aged ≥ 50 years.

Perception of noise from unmanned aircraft systems: Efficacy of metrics for indoor and outdoor listener positions.

This paper presents the results of a listening experiment designed to assess annoyance and perceived loudness (PL) for several unmanned aircraft system (UAS) operations, with the listener simulated in indoor and outdoor positions. This research investigated (i) how participant responses change depending on UAS operation, (ii) which broadband metrics are most suitable for representing annoyance and PL, (iii) differences in noise level required to result in equal participant responses to different operations, and (iv) which sound quality metrics (SQMs) are significant for UAS noise perception. Results indicate annoyance and PL responses were greatest for landing operations with flyovers being the least annoying or loud. LAeq, LASmax, and loudness (N5) were the strongest predictors in representing annoyance. Offset analysis predicted small differences in annoyance responses between flyovers and other operations, but also indicated that flyovers would require an increase to LASmax of 3.3 to 6.3 dB compared to other operations to achieve equal PL. Loudness was the most significant SQM, with minor contributions from impulsivity for annoyance and PL when outside, and tonality for PL when indoors. These findings contribute to the understanding of UAS noise perception for the development of metrics and assessment methods accounting for the characteristics of UAS operations.

A cost-effectiveness analysis of hypertrophic cardiomyopathy sudden cardiac death risk algorithms for implantable cardioverter defibrillator decision-making.

AIMS: To conduct a contemporary cost-effectiveness analysis examining the use of implantable cardioverter defibrillators (ICD) for primary prevention in patients with hypertrophic cardiomyopathy (HCM). METHODS: A discrete-time Markov model was used to determine the cost-effectiveness of different ICD decision-making rules for implantation. Several scenarios were investigated including the reference scenario of implantation rates according to observed real world practice. A 12-year time horizon with an annual cycle length was used. Transition probabilities used in the model were obtained using Bayesian analysis. The study has been reported according to the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. RESULTS: Using a 5-year SCD risk threshold of 6% was cheaper than current practice and has marginally better total quality adjusted life years (QALYs). This is the most cost-effective of the options considered, with an incremental cost effectiveness ratio of £834 per QALY. Sensitivity analyses highlighted that this decision is largely driven by what health related quality of life (HRQL) is attributed to ICD patients and time horizon. CONCLUSION: We present a timely new perspective on HCM ICD cost-effectiveness, using methods reflecting real-world practice. While we have shown that a 6% 5-year SCD risk cut-off provides the best cohort stratification to aid ICD decision-making, this will also be influenced by the particular values of costs and HRQL for subgroups or at a local level. The process of explicitly demonstrating the main factors which drive conclusions from such an analysis will help to inform shared decision-making in this complex area for all stakeholders concerned.

Extensions of Health Economic Evaluations in R for Microsoft Excel Users: A Tutorial for Incorporating Heterogeneity and Conducting Value of Information Analyses.

Advanced health economic analysis techniques currently performed in Microsoft Excel, such as incorporating heterogeneity, time-dependent transitions and a value of information analysis, can be easily transferred to R. Often the outputs of survival analyses (such as Weibull regression models) will estimate the impacts of correlated patient characteristics on patient outcomes, and are utilised directly as inputs for health economic decision models. This tutorial provides a step-by-step guide of how to conduct such analyses with a Markov model developed in R, and offers a comparison with established analyses performed in Microsoft Excel. This is done through the conversion of a previously published Microsoft Excel case study of a hip replacement surgery cost-effectiveness model. We hope that this paper can act as a facilitator in switching decision models from Microsoft Excel to R for complex health economic analyses, providing open-access code and data, suitable for future adaptation.

Blended Survival Curves: A New Approach to Extrapolation for Time-to-Event Outcomes from Clinical Trials in Health Technology Assessment.

BACKGROUND: Survival extrapolation is essential in cost-effectiveness analysis to quantify the lifetime survival benefit associated with a new intervention, due to the restricted duration of randomized controlled trials (RCTs). Current approaches of extrapolation often assume that the treatment effect observed in the trial can continue indefinitely, which is unrealistic and may have a huge impact on decisions for resource allocation. OBJECTIVE: We introduce a novel methodology as a possible solution to alleviate the problem of survival extrapolation with heavily censored data from clinical trials. METHOD: The main idea is to mix a flexible model (e.g., Cox semiparametric) to fit as well as possible the observed data and a parametric model encoding assumptions on the expected behavior of underlying long-term survival. The two are "blended" into a single survival curve that is identical with the Cox model over the range of observed times and gradually approaching the parametric model over the extrapolation period based on a weight function. The weight function regulates the way two survival curves are blended, determining how the internal and external sources contribute to the estimated survival over time. RESULTS: A 4-y follow-up RCT of rituximab in combination with fludarabine and cyclophosphamide versus fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia is used to illustrate the method. CONCLUSION: Long-term extrapolation from immature trial data may lead to significantly different estimates with various modelling assumptions. The blending approach provides sufficient flexibility, allowing a wide range of plausible scenarios to be considered as well as the inclusion of external information, based, for example, on hard data or expert opinion. Both internal and external validity can be carefully examined. HIGHLIGHTS: Interim analyses of trials with limited follow-up are often subject to high degrees of administrative censoring, which may result in implausible long-term extrapolations using standard approaches.In this article, we present an innovative methodology based on "blending" survival curves to relax the traditional proportional hazard assumption and simultaneously incorporate external information to guide the extrapolation.The blended method provides a simple and powerful framework to allow a careful consideration of a wide range of plausible scenarios, accounting for model fit to the short-term data as well as the plausibility of long-term extrapolations.

Health Economic Evaluation Using Markov Models in R for Microsoft Excel Users: A Tutorial.

A health economic evaluation (HEE) is a comparative analysis of alternative courses of action in terms of both costs and consequences. A cost-effectiveness analysis is a type of HEE that compares an intervention to one or more alternatives by estimating how much it costs to gain an additional unit of health outcome. Cost-effectiveness analyses are commonly performed using Microsoft (MS) Excel. However, there is current interest in using other software that is better suited to more complex problems, methods, and data, as well as improved reproducibility and transparency. That is, it is increasingly important to be able to repeat an analysis of a particular data set and obtain the same results, and access the analysis and results in a clear and comprehensive openly available form. In this tutorial we provide a step-by-step guide on how to implement a mainstay model of HEE, namely a Markov model, in the statistical programming language R. The adoption of R for the purpose of cost-effectiveness analysis is highly dependent on the ability of the health economic modeller to understand, learn, and apply programming-type skills. R is likely to be less familiar than MS Excel for many modellers and so coding a cost-effectiveness model in R can be a large jump. We describe the technical details from the perspective of a MS Excel user to help bridge the gap between software and reduce the learning curve by providing for the first-time side-by-side comparisons of the Markov model example in MS Excel and R.

Requirements for Drone Operations to Minimise Community Noise Impact.

The number of applications for drones under R&D have growth significantly during the last few years; however, the wider adoption of these technologies requires ensuring public trust and acceptance. Noise has been identified as one of the key concerns for public acceptance. Although substantial research has been carried out to better understand the sound source generation mechanisms in drones, important questions remain about the requirements for operational procedures and regulatory frameworks. An important issue is that drones operate within different airspace, closer to communities than conventional aircraft, and that the noise produced is highly tonal and contains a greater proportion of high-frequency broadband noise compared with typical aircraft noise. This is likely to cause concern for exposed communities due to impacts on public health and well-being. This paper presents a modelling framework for setting recommendations for drone operations to minimise community noise impact. The modelling framework is based on specific noise targets, e.g., the guidelines at a receiver position defined by WHO for sleep quality inside a residential property. The main assumption is that the estimation of drone noise exposure indoors is highly relevant for informing operational constraints to minimise noise annoyance and sleep disturbance. This paper illustrates the applicability of the modelling framework with a case study, where maximum A-weighted sound pressure levels LAmax and sound exposure levels SEL as received in typical indoor environments are used to define drone-façade minimum distance to meet WHO recommendations. The practical and scalable capabilities of this modelling framework make it a useful tool for inferring and assessing the impact of drone noise through compliance with appropriate guideline noise criteria. It is considered that with further refinement, this modelling framework could prove to be a significant tool in assisting with the development of noise metrics, regulations specific to drone operations and the assessment of future drone operations and associated noise.

Cost-effectiveness of a medication event monitoring system for tuberculosis management in Morocco.

BACKGROUND: Digital health technologies have been used to enhance adherence to TB medication, but the cost-effectiveness remains unclear. METHODS: We used the real data from the study conducted from April 2014 to December 2020 in Morocco using a smart pillbox with a web-based medication monitoring system, called Medication Event Monitoring Systems (MEMS). Cost-effectiveness was evaluated using a decision analysis model including Markov model for Multi-drug resistant (MDR) TB from the health system perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER) per disability adjusted life-year (DALY) averted. Two-way sensitive analysis was done for the treatment success rate between MEMS and standard of care. RESULTS: The average total per-patient health system costs for treating a new TB patient under MEMS versus standard of care were $398.70 and $155.70, respectively. The MEMS strategy would reduce the number of drug-susceptible TB cases by 0.17 and MDR-TB cases by 0.01 per patient over five years. The ICER of MEMS was $434/DALY averted relative to standard of care, and was most susceptible to the TB treatment success rate of both strategies followed by the managing cost of MEMS. CONCLUSION: MEMS is considered cost-effective for managing infectious active TB in Morocco.

An evidence synthesis approach for combining different data sources illustrated using entomological efficacy of insecticides for indoor residual spraying.

BACKGROUND: Prospective malaria public health interventions are initially tested for entomological impact using standardised experimental hut trials. In some cases, data are collated as aggregated counts of potential outcomes from mosquito feeding attempts given the presence of an insecticidal intervention. Comprehensive data i.e. full breakdowns of probable outcomes of mosquito feeding attempts, are more rarely available. Bayesian evidence synthesis is a framework that explicitly combines data sources to enable the joint estimation of parameters and their uncertainties. The aggregated and comprehensive data can be combined using an evidence synthesis approach to enhance our inference about the potential impact of vector control products across different settings over time. METHODS: Aggregated and comprehensive data from a meta-analysis of the impact of Pirimiphos-methyl, an indoor residual spray (IRS) product active ingredient, used on wall surfaces to kill mosquitoes and reduce malaria transmission, were analysed using a series of statistical models to understand the benefits and limitations of each. RESULTS: Many more data are available in aggregated format (N = 23 datasets, 4 studies) relative to comprehensive format (N = 2 datasets, 1 study). The evidence synthesis model had the smallest uncertainty at predicting the probability of mosquitoes dying or surviving and blood-feeding. Generating odds ratios from the correlated Bernoulli random sample indicates that when mortality and blood-feeding are positively correlated, as exhibited in our data, the number of successfully fed mosquitoes will be under-estimated. Analysis of either dataset alone is problematic because aggregated data require an assumption of independence and there are few and variable data in the comprehensive format. CONCLUSIONS: We developed an approach to combine sources from trials to maximise the inference that can be made from such data and that is applicable to other systems. Bayesian evidence synthesis enables inference from multiple datasets simultaneously to give a more informative result and highlight conflicts between sources. Advantages and limitations of these models are discussed.

Economic burden of female genital mutilation in 27 high-prevalence countries.

BACKGROUND: Female genital mutilation (FGM) is a traditional harmful practice affecting 200 million women and girls globally. Health complications of FGM occur immediately and over time, and are associated with healthcare costs that are poorly understood. Quantifying the global FGM-related burden is essential for supporting programmes and policies for prevention and mitigation. METHODS: Health complications of FGM are derived from a meta-analysis and stratified by acute, uro-gynaecological, obstetric and psychological/sexual. Treatment costs are calculated from national cohort models of 27 high-burden countries over 30 years. Savings associated with full/partial abandonment are compared with a current incidence reference scenario, assuming no changes in FGM practices. RESULTS: Our model projects an increasing burden of FGM due to population growth. As a reference scenario assuming no change in practices, prevalent cases in 27 countries will rise from 119.4 million (2018) to 205.8 million (2047). Full abandonment could reduce this to 80.0 million (2047), while partial abandonment is insufficient to reduce cases. Current incidence economic burden is US$1.4 billion/year, rising to US$2.1 billion/year in 2047. Full abandonment would reduce the future burden to US$0.8 billion/year by 2047. CONCLUSION: FGM is a human rights violation, a public health issue and a substantial economic burden that can be avoided through effective prevention strategies. While decreasing trends are observed in some countries, these trends are variable and not consistently observed across settings. Additional resources are needed to prevent FGM to avoid human suffering and growing costs. The findings of this study warrant increased political commitment and investment in the abandonment of FGM.

The association of age with acute toxicities in NRG oncology combined modality lower GI cancer trials.

PURPOSE: Expected toxicity from chemoradiation (CRT) is an important factor in treatment decisions but is poorly understood in older adults with lower gastrointestinal (GI) malignancies. Our objective was to compare acute adverse events (AAEs) of older and younger adults with lower GI malignancies treated on NRG studies. METHODS: Data from 6 NRG trials, testing combined modality therapy in patients with anal or rectal cancer, were used to test the hypothesis that older age was associated with increased AAEs. AAEs and compliance with protocol-directed therapy were compared between patients aged ≥70 and < 70. Categorical variables were compared across age groups using the chi-square test. The association of age on AAEs was evaluated using a covariate-adjusted logistic regression model, with odds ratio (OR) reported. To adjust for multiple comparisons, a p-value <0.01 was considered statistically significant. RESULTS: There were 2525 patients, including 380 patients ≥70 years old (15%) evaluable. Older patients were more likely to have worse baseline performance status (PS 1 or 2) (23% vs. 16%, p = 0.001), but otherwise baseline characteristics were similar. Older patients were less likely to complete their chemotherapy (78% vs. 87%, p < 0.001), but had similar RT duration. On univariate analysis, older patients were more likely to experience grade ≥ 3 GI AAEs (36% vs. 23%, p < 0.001), and less likely to experience grade ≥ 3 skin AAEs (8% vs. 14%, p = 0.002). On multivariable analysis, older age was associated with grade ≥ 3 GI AAE (OR 1.93, 95% CI: 1.52, 2.47, p < 0.001) after adjusting for sex, race, PS, and disease site. CONCLUSIONS: Older patients with lower GI cancers who underwent CRT were less likely to complete chemotherapy and had higher rates of grade 3+ GI AAEs. These results can be used to counsel older adults prior to treatment and manage expected toxicities throughout pelvic CRT.

Global return on investment and cost-effectiveness of WHO's HEAR interventions for hearing loss: a modelling study.

BACKGROUND: To address the growing prevalence of hearing loss, WHO has identified a compendium of key evidence-based ear and hearing care interventions to be included within countries' universal health coverage packages. To assess the cost-effectiveness of these interventions and their budgetary effect for countries, we aimed to analyse the investment required to scale up services from baseline to recommended levels, and the return to society for every US$1 invested in the compendium. METHODS: We did a modelling study using the proposed set of WHO interventions (summarised under the acronym HEAR: hearing screening and intervention for newborn babies and infants, pre-school and school-age children, older adults, and adults at higher risk of hearing loss; ear disease prevention and management; access to technologies such as hearing aids, cochlear implants, or hearing assistive technologies; and rehabilitation service provision), which span the life course and include screening and management of hearing loss and related ear diseases, costs and benefits for the national population cohorts of 172 countries. The return on investment was analysed for the period between 2020 and 2030 using three scenarios: a business-as-usual scenario, a progress scenario with a scale-up to 50% of recommended coverage, and an ambitious scenario with scale-up to 90% of recommended coverage. Using data for hearing loss burden from the Global Burden of Disease Study 2019, a transition model with three states (general population, diagnosed, and those who have died) was developed to model the national populations in countries. For the return-on-investment analysis, the monetary value of disability-adjusted life-years (DALYs) averted in addition to productivity gains were compared against the investment required in each scenario. FINDINGS: Scaling up ear and hearing care interventions to 90% requires an overall global investment of US$238·8 billion over 10 years. Over a 10-year period, this investment promises substantial health gains with more than 130 million DALYs averted. These gains translate to a monetary value of more than US$1·3 trillion. In addition, investment in hearing care will result in productivity benefits of more than US$2 trillion at the global level by 2030. Together, these benefits correspond to a return of nearly US$15 for every US$1 invested. INTERPRETATION: This is the first-ever global investment case for integrating ear and hearing care interventions in countries' universal health coverage services. The findings show the economic benefits of investing in this compendium and provide the basis for facilitating the increase of country's health budget for strengthening ear and hearing care services. FUNDING: None.

Exploring relationships between drought and epidemic cholera in Africa using generalised linear models.

BACKGROUND: Temperature and precipitation are known to affect Vibrio cholerae outbreaks. Despite this, the impact of drought on outbreaks has been largely understudied. Africa is both drought and cholera prone and more research is needed in Africa to understand cholera dynamics in relation to drought. METHODS: Here, we analyse a range of environmental and socioeconomic covariates and fit generalised linear models to publicly available national data, to test for associations with several indices of drought and make cholera outbreak projections to 2070 under three scenarios of global change, reflecting varying trajectories of CO2 emissions, socio-economic development, and population growth. RESULTS: The best-fit model implies that drought is a significant risk factor for African cholera outbreaks, alongside positive effects of population, temperature and poverty and a negative effect of freshwater withdrawal. The projections show that following stringent emissions pathways and expanding sustainable development may reduce cholera outbreak occurrence in Africa, although these changes were spatially heterogeneous. CONCLUSIONS: Despite an effect of drought in explaining recent cholera outbreaks, future projections highlighted the potential for sustainable development gains to offset drought-related impacts on cholera risk. Future work should build on this research investigating the impacts of drought on cholera on a finer spatial scale and potential non-linear relationships, especially in high-burden countries which saw little cholera change in the scenario analysis.

Maternal and Infant Outcomes Among Pregnant Women Treated for Multidrug/Rifampicin-Resistant Tuberculosis in South Africa.

BACKGROUND: Data on safety and efficacy of second-line tuberculosis drugs in pregnant women and their infants are severely limited due to exclusion from clinical trials and expanded access programs. METHODS: Pregnant women starting treatment for multidrug/rifampicin-resistant (MDR/RR)-tuberculosis at King Dinuzulu Hospital in KwaZulu-Natal, South Africa, from 1 January 2013 to 31 December 2017, were included. We conducted a record review to describe maternal treatment and pregnancy outcomes, and a clinical assessment to describe infant outcomes. RESULTS: Of 108 pregnant women treated for MDR/RR-tuberculosis, 88 (81%) were living with human immunodeficiency virus.. Favorable MDR/RR-tuberculosis treatment outcomes were reported in 72 (67%) women. Ninety-nine (91%) of the 109 babies were born alive, but overall, 52 (48%) women had unfavorable pregnancy outcomes. Fifty-eight (54%) women received bedaquiline, and 49 (45%) babies were exposed to bedaquiline in utero. Low birth weight was reported in more babies exposed to bedaquiline compared to babies not exposed (45% vs 26%; P = .034). In multivariate analyses, bedaquiline and levofloxacin, drugs often used in combination, were both independently associated with increased risk of low birth weight. Of the 86 children evaluated at 12 months, 72 (84%) had favorable outcomes; 88% of babies exposed to bedaquiline were thriving and developing normally compared to 82% of the babies not exposed. CONCLUSIONS: MDR/RR-tuberculosis treatment outcomes among pregnant women were comparable to nonpregnant women. Although more babies exposed to bedaquiline were of low birth weight, over 80% had gained weight and were developing normally at 1 year.

Cost-benefit analysis of surveillance for surgical site infection following caesarean section.

OBJECTIVE: To estimate the economic burden to the health service of surgical site infection following caesarean section and to identify potential savings achievable through implementation of a surveillance programme. DESIGN: Economic model to evaluate the costs and benefits of surveillance from community and hospital healthcare providers' perspective. SETTING: England. PARTICIPANTS: Women undergoing caesarean section in National Health Service hospitals. MAIN OUTCOME MEASURE: Costs attributable to treatment and management of surgical site infection following caesarean section. RESULTS: The costs (2010) for a hospital carrying out 800 caesarean sections a year based on infection risk of 9.6% were estimated at £18 914 (95% CI 11 521 to 29 499) with 28% accounted for by community care (£5370). With inflation to 2019 prices, this equates to an estimated cost of £5.0 m for all caesarean sections performed annually in England 2018-2019, approximately £1866 and £93 per infection managed in hospital and community, respectively. The cost of surveillance for a hospital for one calendar quarter was estimated as £3747 (2010 costs). Modelling a decrease in risk of infection of 30%, 20% or 10% between successive surveillance periods indicated that a variable intermittent surveillance strategy achieved higher or similar net savings than continuous surveillance. Breakeven was reached sooner with the variable surveillance strategy than continuous surveillance when the baseline risk of infection was 10% or 15% and smaller loses with a baseline risk of 5%. CONCLUSION: Surveillance of surgical site infections after caesarean section with feedback of data to surgical teams offers a potentially effective means to reduce infection risk, improve patient experience and save money for the health service.

A cost comparison of amikacin therapy with bedaquiline, for drug-resistant tuberculosis in the UK.

OBJECTIVES: Prioritisation of oral bedaquiline over the injectable agents in the treatment of multidrug-resistant Tuberculosis (MDR-TB) in the World Health Organisations (WHO) 2019 guidelines prompted this UK analysis of cost implications. The objective was to estimate the costs of amikacin versus bedaquiline in MDR TB treatment regimens using a historical cohort where the injectable agents were the standard of care. METHODS: This was a retrospective study using a known cohort of UK patients treated with an injectable agent, with data available on resource use, costs for the use of amikacin were compared with those for bedaquiline, based on recommended monitoring for bedaquiline. RESULTS: The estimated cost of treatment per patient had mean (sd) of £27,236 (4952) for the observed injectable group, £30,264 (3392) and 36,309 (3901) for the 6 and 8 month amikacin groups, and £31,760 (2092) for the bedaquiline group. The cost in the bedaquiline group was £30,772 (1855) with a 10% reduction and £27,079 (1234) with a 33% reduction in-patient stay. CONCLUSIONS: In most scenarios, bedaquiline is close to cost neutral compared with injectable therapy, especially if, as expected, some reduction in duration of admission is possible as a result of bedaquiline's more rapid culture conversion.

Recruitment of a critically endangered sawfish into a riverine nursery depends on natural flow regimes.

The freshwater sawfish (Pristis pristis) was recently listed as the most Evolutionarily Distinct and Globally Endangered (EDGE) animal. The Fitzroy River in the remote Kimberley region of north-western Australia represents a significant stronghold for the species, which uses the freshwater reaches of the river as a nursery. There is also mounting pressure to develop the water resources of the region for agriculture that may substantially affect life history dynamics of sawfish in this system. However, the relationship between hydrology and population dynamics of freshwater sawfish was unknown. We used standardized catch data collected over 17 years to determine how wet season volume influences recruitment of freshwater sawfish into their riverine nursery. Negligible recruitment occurred in years with few days of high flood levels (above 98th percentile of cease-to-flow stage height), and relatively high recruitment occurred in years with 14 or more days of high flood levels. This relationship is indicative of a distinct boom-or-bust cycle, whereby freshwater sawfish rely almost entirely on the few years with large wet season floods, and the brief periods of highest water levels within these years, to replenish juvenile populations in the Fitzroy River nursery. This has direct implications for sustainable water resource management for the Fitzroy River basin in order to preserve one of the last known intact nursery habitats for this globally threatened species.

The health and cost burden of antibiotic resistant and susceptible Escherichia coli bacteraemia in the English hospital setting: A national retrospective cohort study.

INTRODUCTION: Antibiotic resistance poses a threat to public health and healthcare systems. Escherichia coli causes more bacteraemia episodes in England than any other bacterial species. This study aimed to estimate the burden of E. coli bacteraemia and associated antibiotic resistance in the secondary care setting. MATERIALS AND METHODS: This was a retrospective cohort study, with E. coli bacteraemia as the main exposure of interest. Adult hospital in-patients, admitted to acute NHS hospitals between July 2011 and June 2012 were included. English national surveillance and administrative datasets were utilised. Cox proportional hazard, subdistribution hazard and multistate models were constructed to estimate rate of discharge, rate of in-hospital death and excess length of stay, with a unit bed day cost applied to the latter to estimate cost burden from the healthcare system perspective. RESULTS: 14,042 E. coli bacteraemia and 8,919,284 non-infected inpatient observations were included. E. coli bacteraemia was associated with an increased rate of in-hospital death across all models, with an adjusted subdistribution hazard ratio of 5.88 (95% CI: 5.62-6.15). Resistance was not found to be associated with in-hospital mortality once adjusting for patient and hospital covariates. However, resistance was found to be associated with an increased excess length of stay. This was especially true for third generation cephalosporin (1.58 days excess length of stay, 95% CI: 0.84-2.31) and piperacillin/tazobactam resistance (1.23 days (95% CI: 0.50-1.95)). The annual cost of E. coli bacteraemia was estimated to be £14,346,400 (2012 £), with third-generation cephalosporin resistance associated with excess costs per infection of £420 (95% CI: 220-630). CONCLUSIONS: E. coli bacteraemia places a statistically significant burden on patient health and the hospital sector in England. Resistance to front-line antibiotics increases length of stay; increasing the cost burden of such infections in the secondary care setting.