A simulation-based approach for estimating the time-dependent reproduction number from temporally aggregated disease incidence time series data.

Tracking pathogen transmissibility during infectious disease outbreaks is essential for assessing the effectiveness of public health measures and planning future control strategies. A key measure of transmissibility is the time-dependent reproduction number, which has been estimated in real-time during outbreaks of a range of pathogens from disease incidence time series data. While commonly used approaches for estimating the time-dependent reproduction number can be reliable when disease incidence is recorded frequently, such incidence data are often aggregated temporally (for example, numbers of cases may be reported weekly rather than daily). As we show, commonly used methods for estimating transmissibility can be unreliable when the timescale of transmission is shorter than the timescale of data recording. To address this, here we develop a simulation-based approach involving Approximate Bayesian Computation for estimating the time-dependent reproduction number from temporally aggregated disease incidence time series data. We first use a simulated dataset representative of a situation in which daily disease incidence data are unavailable and only weekly summary values are reported, demonstrating that our method provides accurate estimates of the time-dependent reproduction number under such circumstances. We then apply our method to two outbreak datasets consisting of weekly influenza case numbers in 2019-20 and 2022-23 in Wales (in the United Kingdom). Our simple-to-use approach will allow accurate estimates of time-dependent reproduction numbers to be obtained from temporally aggregated data during future infectious disease outbreaks.

Validity of submaximal aerobic capacity and strength tests in firefighters.

BACKGROUND: Typically, the fitness of UK firefighters is assessed via submaximal estimate methods due to the low demands on time, money, expertise and equipment. However, the firefighter-specific validity of such testing in relation to maximum aerobic capacity (V˙O2max) and particularly muscular strength is not well established. AIMS: To examine the validity of submaximal methods to estimate V˙O2max and maximal strength in operational firefighters. METHODS: Twenty-two full-time operational firefighters (3 female) completed same-day submaximal (Chester Step Test; CST) and maximal (treadmill) assessments of V˙O2max, with a sub-sample of 10 firefighters (1 female) also completing submaximal and maximal back-squat (i.e. one repetition maximum; 1RM) assessments. All participants then completed the Firefighter Simulation Test (FFST) within 2-4 days. RESULTS: CST underestimated actual V˙O2max by 1.4 ml·kg-1·min-1 (~3%), although V˙O2max values were positively correlated (r = 0.61, P < 0.01) and not significantly different. Estimated V˙O2max values negatively correlated with FFST performance (r = -0.42). Predicted 1RM underestimated actual 1RM by ~2%, although these values were significantly correlated (r = 0.99, P < 0.001) and did not significantly differ. The strongest predictive model of FFST performance included age, body mass index, and direct maximal measures of 1RM and V˙O2max. CONCLUSIONS: Submaximal back-squat testing offers good validity in estimating maximum firefighter strength without exposure to the fatigue associated with maximal methods. The CST provides a reasonably valid and cost-effective V˙O2max estimate which translates to firefighting task performance, although the error observed means it should be used cautiously when making operational decisions related to V˙O2max benchmarks.

Exact calculation of end-of-outbreak probabilities using contact tracing data.

A key challenge for public health policymakers is determining when an infectious disease outbreak has finished. Following a period without cases, an estimate of the probability that no further cases will occur in future (the end-of-outbreak probability) can be used to inform whether or not to declare an outbreak over. An existing quantitative approach (the Nishiura method), based on a branching process transmission model, allows the end-of-outbreak probability to be approximated from disease incidence time series, the offspring distribution and the serial interval distribution. Here, we show how the end-of-outbreak probability under the same transmission model can be calculated exactly if data describing who-infected-whom (the transmission tree) are also available (e.g. from contact tracing studies). In that scenario, our novel approach (the traced transmission method) is straightforward to use. We demonstrate this by applying the method to data from previous outbreaks of Ebola virus disease and Nipah virus infection. For both outbreaks, the traced transmission method would have determined that the outbreak was over earlier than the Nishiura method. This highlights that collection of contact tracing data and application of the traced transmission method may allow stringent control interventions to be relaxed quickly at the end of an outbreak, with only a limited risk of outbreak resurgence.

A practical guide to mathematical methods for estimating infectious disease outbreak risks.

Mathematical models are increasingly used throughout infectious disease outbreaks to guide control measures. In this review article, we focus on the initial stages of an outbreak, when a pathogen has just been observed in a new location (e.g., a town, region or country). We provide a beginner's guide to two methods for estimating the risk that introduced cases lead to sustained local transmission (i.e., the probability of a major outbreak), as opposed to the outbreak fading out with only a small number of cases. We discuss how these simple methods can be extended for epidemiological models with any level of complexity, facilitating their wider use, and describe how estimates of the probability of a major outbreak can be used to guide pathogen surveillance and control strategies. We also give an overview of previous applications of these approaches. This guide is intended to help quantitative researchers develop their own epidemiological models and use them to estimate the risks associated with pathogens arriving in new host populations. The development of these models is crucial for future outbreak preparedness. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

A direct comparison of methods for assessing the threat from emerging infectious diseases in seasonally varying environments.

Seasonal variations in environmental conditions lead to changing infectious disease epidemic risks at different times of year. The probability that early cases initiate a major epidemic depends on the season in which the pathogen enters the population. The instantaneous epidemic risk (IER) can be tracked. This quantity is straightforward to calculate, and corresponds to the probability of a major epidemic starting from a single case introduced at time t=t0, assuming that environmental conditions remain identical from that time onwards (i.e. for all t≥t0). However, the threat when a pathogen enters the population in fact depends on changes in environmental conditions occurring within the timescale of the initial phase of the outbreak. For that reason, we compare the IER with a different metric: the case epidemic risk (CER). The CER corresponds to the probability of a major epidemic starting from a single case entering the population at time t=t0, accounting for changes in environmental conditions after that time. We show how the IER and CER can be calculated using different epidemiological models (the stochastic Susceptible-Infectious-Removed model and a stochastic host-vector model that is parameterised using temperature data for Miami) in which transmission parameter values vary temporally. While the IER is always easy to calculate numerically, the adaptable method we provide for calculating the CER for the host-vector model can also be applied easily and solved using widely available software tools. In line with previous research, we demonstrate that, if a pathogen is likely to either invade the population or fade out on a fast timescale compared to changes in environmental conditions, the IER closely matches the CER. However, if this is not the case, the IER and the CER can be significantly different, and so the CER should be used. This demonstrates the need to consider future changes in environmental conditions carefully when assessing the risk posed by emerging pathogens.

A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics: influenza A as a case study.

Multi-scale epidemic forecasting models have been used to inform population-scale predictions with within-host models and/or infection data collected in longitudinal cohort studies. However, most multi-scale models are complex and require significant modelling expertise to run. We formulate an alternative multi-scale modelling framework using a compartmental model with multiple infected stages. In the large-compartment limit, our easy-to-use framework generates identical results compared to previous more complicated approaches. We apply our framework to the case study of influenza A in humans. By using a viral dynamics model to generate synthetic patient-level data, we explore the effects of limited and inaccurate patient data on the accuracy of population-scale forecasts. If infection data are collected daily, we find that a cohort of at least 40 patients is required for a mean population-scale forecasting error below 10%. Forecasting errors may be reduced by including more patients in future cohort studies or by increasing the frequency of observations for each patient. Our work, therefore, provides not only an accessible epidemiological modelling framework but also an insight into the data required for accurate forecasting using multi-scale models.

Accurate forecasts of the effectiveness of interventions against Ebola may require models that account for variations in symptoms during infection.

Epidemiological models are routinely used to predict the effects of interventions aimed at reducing the impacts of Ebola epidemics. Most models of interventions targeting symptomatic hosts, such as isolation or treatment, assume that all symptomatic hosts are equally likely to be detected. In other words, following an incubation period, the level of symptoms displayed by an individual host is assumed to remain constant throughout an infection. In reality, however, symptoms vary between different stages of infection. During an Ebola infection, individuals progress from initial non-specific symptoms through to more severe phases of infection. Here we compare predictions of a model in which a constant symptoms level is assumed to those generated by a more epidemiologically realistic model that accounts for varying symptoms during infection. Both models can reproduce observed epidemic data, as we show by fitting the models to data from the ongoing epidemic in the Democratic Republic of the Congo and the 2014-16 epidemic in Liberia. However, for both of these epidemics, when interventions are altered identically in the models with and without levels of symptoms that depend on the time since first infection, predictions from the models differ. Our work highlights the need to consider whether or not varying symptoms should be accounted for in models used by decision makers to assess the likely efficacy of Ebola interventions.

New IR imaging modalities for cancer detection and for intra-cell chemical mapping with a sub-diffraction mid-IR s-SNOM.

We present two new modalities for generating chemical maps. Both are mid-IR based and aimed at the biomedical community, but they differ substantially in their technological readiness. The first, so-called "Digistain", is a technologically mature "locked down" way of acquiring diffraction-limited chemical images of human cancer biopsy tissue. Although it is less flexible than conventional methods of acquiring IR images, this is an intentional, and key, design feature. It allows it to be used, on a routine basis, by clinical personnel themselves. It is in the process of a full clinical evaluation and the philosophy behind the approach is discussed. The second modality is a very new, probe-based "s-SNOM", which we are developing in conjunction with a new family of tunable "Quantum Cascade Laser" (QCL) diode lasers. Although in its infancy, this instrument can already deliver ultra-detailed chemical images whose spatial resolutions beat the normal diffraction limit by a factor of ∼1000. This is easily enough to generate chemical maps of the insides of single cells for the first time, and a range of new possible scientific applications are explored.

Indirect treatment comparison of belatacept versus tacrolimus from a systematic review of immunosuppressive therapies for kidney transplant patients.

OBJECTIVE: End-stage renal disease is the final and irreversible stage in chronic kidney disease, leading to patient mortality, unless managed by dialysis or transplantation (the treatment of choice). This study aimed to compare a currently recommended immunosuppressive treatment, tacrolimus, against a newer treatment, belatacept, using indirect treatment comparison (ITC) techniques since no head-to-head randomized controlled trials (RCTs) comparing tacrolimus against belatacept currently exist. METHODS: ITC was employed to calculate estimates for the relative risks and mean difference of tacrolimus against belatacept. The choice of the Bucher ITC model was driven by the available data and the simple indirect treatment comparison involving three treatments was considered appropriate. RESULTS: The results of the indirect analysis showed no significant differences between belatacept and tacrolimus treatments for mortality and graft loss. The acute rejection rate was significantly lower with tacrolimus (Prograf* and Advagraf (*) ) compared with belatacept (0.22 [0.13, 0.39] to 0.44 [0.20, 0.99]). CONCLUSIONS: The results of this systematic review and meta-analysis suggests that tacrolimus is significantly superior to belatacept in terms of acute rejection outcomes but comparable for graft and patient survival. Further research should include a properly designed clinical trial comparing tacrolimus against belatacept directly. LIMITATIONS: These include variations in terms of clinical and design differences among the trials, weaknesses in the Bucher method and the lack of long-term clinical trial data with tacrolimus to compare with the recent long-term (7 years) belatacept trial data.

Facile, room-temperature pre-treatment of rice husks with tetrabutylphosphonium hydroxide: Enhanced enzymatic and acid hydrolysis yields.

Aqueous solutions of tetrabutylphosphonium hydroxide have been evaluated as pretreatment media for rice husks, prior to sulphuric acid hydrolysis or cellulase enzymatic hydrolysis. Varying the water:tetrabutylphosphonium hydroxide ratio varied the rate of delignification, as well as silica, lignin and cellulose solubility. Pre-treatment with 60wt% hydroxide dissolved the rice husk and the regenerated material was thus heavily disrupted. Sulphuric acid hydrolysis of 60wt%-treated samples yielded the highest amount of glucose per gram of rice husk. Solutions with good lignin and silica solubility but only moderate to negligible cellulose solubility (10-40wt% hydroxide) were equally effective as pre-treatment media for both acid and enzymatic hydrolysis. However, pre-treatment with 60wt% hydroxide solutions was incompatible with downstream enzymatic hydrolysis. This was due to significant incorporation of phosphonium species in the regenerated biomass, which significantly inhibited the activity of the cellulase enzymes.

The cost-effectiveness of solifenacin vs. trospium in the treatment of patients with overactive bladder in the German National Health Service.

OBJECTIVE: To carry out a cost-utility analysis comparing initial treatment of patients with overactive bladder (OAB) with solifenacin 5 mg/day versus either trospium 20 mg twice a day or trospium 60 mg/day from the perspective of the German National Health Service. METHODS: A decision analytic model with a 3 month cycle was developed to follow a cohort of OAB patients treated with either solifenacin or trospium during a 1 year period. Costs and utilities were accumulated as patients transitioned through the four cycles in the model. Some of the solifenacin patients were titrated from 5 mg to 10 mg/day at 3 months. Utility values were obtained from the published literature and pad use was based on a US resource utilization study. Adherence rates for individual treatments were derived from a United Kingdom general practitioner database review. The change in the mean number of urgency urinary incontinence episodes/day from after 12 weeks was the main outcome measure. Baseline effectiveness values for solifenacin and trospium were calculated using the Poisson distribution. Patients who failed second-line therapy were referred to a specialist visit. Results were expressed in terms of incremental cost-utility ratios. RESULTS: Total annual costs for solifenacin, trospium 20 mg and trospium 60 mg were €970.01, €860.05 and €875.05 respectively. Drug use represented 43%, 28% and 29% of total costs and pad use varied between 45% and 57%. Differences between cumulative utilities were small but favored solifenacin (0.6857 vs. 0.6802 to 0.6800). The baseline incremental cost-effectiveness ratio ranged from €16,657 to €19,893 per QALY. LIMITATIONS: The difference in cumulative utility favoring solifenacin was small (0.0055-0.0057 QALYs). A small absolute change in the cumulative utilities can have a marked impact on the overall incremental cost-effectiveness ratios (ICERs) and care should be taken when interpreting the results. CONCLUSION: Solifenacin would appear to be cost-effective with an ICER of no more than €20,000/QALY. However, small differences in utility between the alternatives means that the results are sensitive to adjustments in the values of the assigned utilities, effectiveness and discontinuation rates.

An incidence model of the cost of advanced prostate cancer in Spain.

BACKGROUND: Prostate cancer (PCa) is the second leading cancer diagnosed among men. In Spain the incidence of PCa was 70.75 cases per 100,000 males. Advanced PCa has spread outside of the prostate capsule and may involve other parts of the body. The aim of this study was to estimate the lifetime costs of a cohort of advanced PCa patients diagnosed in Spain in 2012. METHODS: A partitioned economic model was developed in EXCEL incorporating Spanish incidence, mortality, and cost data supplemented with data from the international literature. Progression from Stage III to Stage IV was permitted. Costs were discounted at the standard rate of 3%. Lifetime costs were presented on an individual basis and for the entire cohort of newly diagnosed Stage III and Stage IV PCa patients. RESULTS: Lifetime costs for advanced PCa were ∼€19,961 per patient (mean survival of 8.4 years). Using the projected incident cases for 2012 (3047), the total cost for the incident cohort of patients in 2012 would amount to €61 million. These results were more sensitive to changes in the ongoing costs (post-initial 12 months) of Stage III PCa, the rate of progression from Stage III to Stage IV, and the discount rate applied to costs. CONCLUSIONS: This study provides an estimate of the lifetime costs of advanced PCa in Spain and a framework for further research. The study is limited by the availability of long-term Spanish data and the need to make inferences from international studies. However, until long-term prospective or observational data do become available in Spain, based on the assumptions, the current results indicate that the burden of advanced PCa in Spain is substantial. Any treatments that could potentially reduce the economic burden of the disease should be of interest to healthcare decision makers.

An automated dispensing system for improving medication timing in the emergency department / 世界急诊医学杂志（英文）

BACKGROUND: Numerous medical conditions require timely medication administration in the emergency department (ED). Automated dispensing systems (ADSs) store premixed common doses at the point-of-care to minimize time to administration, but the use of such automation to improved time to medication administration has not been studied. Since vancomycin is a commonly used empiric antimicrobial, we sought to quantify the effect of using an ADS on time to drug delivery in patients presenting to the ED. The study aimed to determine the efficacy of utilizing an ADS to improve time to administration of vancomycin and determine any negative effects on dosing appropriateness.METHODS: The institional review board approved the retrospective quality improvement study took place in a single, urban academic tertiary care ED with an annual census of 80000. Study subjects were all patients receiving vancomycin for the management of sepsis between March 1 to September 30, 2008 and the same time period in 2009. The primary outcome was the proportion of patients who received vancomycin within one hour of bed placement and the secondary outcome was dosing appropriateness.RESULTS: Sixty-three patients had weight and dosing information available (29 before and 34 after intervention) and were included in the study. Before intervention, no patient received vancomycin in less than 60 minutes, while after intervention 14.7％ of the patients received it in less than 60 minutes (difference in proportions 14.7％, 95％ CI 0.39％-30.0％, P=0.04). A similar proportion of the patients received correct dosing before and after intervention (44.8％ vs. 41.2％, difference in proportions 3.7％, 95％ CI -20.0％-26.7％, P=0.770).CONCLUSION: The use of an ADS may improve the timing of medication administration in patients presenting to the ED without affecting dosing appropriateness.

[Clinical reasoning and decision making in clinical practice: a boy with fatigue and abdominal pain]. / Klinisch denken en beslissen in de praktijk: een jongen met vermoeidheidsklachten en buikpijn.

A 14-year-old boy presented with fatigue and abdominal pain. Laboratory tests revealed a primary hypothyroidism with circulating auto-antibodies against thyroid peroxidase (TPO), anaemia and an elevated level of creatine kinase (CK). A diagnosis of auto-immune hypothyroidism with associated anaemia and myopathy was made. Thyroid hormone replacement therapy was started. However, six months later, he still complained of fatigue. He had unexpectedly varying thyroid function tests and the anaemia and the elevated level of CK persisted. Analysis of the other hormonal axes demonstrated a secondary adrenal insufficiency which was treated with hydrocortisone suppletion therapy. If a patient suffering from hypothyroidism does not respond appropriately to therapy or even deteriorates, adrenal insufficiency should always be considered. Patients with one type of auto-immune endocrinopathy have a greater risk at developing other types of auto-immune endocrinopathies.

Excess mortality, length of stay and cost attributable to candidaemia.

BACKGROUND: There were 1967 reports of Candida species isolated from blood specimens in 2007 in the UK (excluding Scotland). Such infections are particularly common in the intensive care unit (ICU). The impact of candidaemia on mortality, length of stay (LOS) and cost in a UK hospital was examined. METHODS: A retrospective analysis of candidaemia episodes and appropriate matched controls was undertaken based on data from the ICU, high dependency units and hospital wards at Wythenshawe Hospital in Manchester. The study covered the period November 2003-February 2007. RESULTS: In total, 48 case-patients of candidaemia and 81 control-patients were identified. The attributable mortality due to candidaemia varied from 21.5% to 34.7%. Candidaemia patients spend on average 5.6 days more in the ICU than matched patients and generate mean additional costs of at least 8252 UK pounds per patient, 16,595 pounds in adults only. CONCLUSION: Candidaemia remains a severe disease associated with high attributable mortality in the UK. In addition, candidaemia leads to additional ICU length of stay and costs. The implication is an attributable cost of at least 16.2 million UK pounds with 683 deaths attributable to candidaemia per year in the UK.