Estimating the contribution of HIV-infected adults to household pneumococcal transmission in South Africa, 2016–2018: A hidden Markov modelling study

Human immunodeficiency virus (HIV) infected adults are at a higher risk of pneumococcal colonisation and disease, even while receiving antiretroviral therapy (ART). To help evaluate potential indirect effects of vaccination of HIV-infected adults, we assessed whether HIV-infected adults disproportionately contribute to household transmission of pneumococci. We constructed a hidden Markov model to capture the dynamics of pneumococcal carriage acquisition and clearance observed during a longitudinal household-based nasopharyngeal swabbing study, while accounting for sample misclassifications. Households were followed-up twice weekly for approximately 10 months each year during a three-year study period for nasopharyngeal carriage detection via real-time PCR. We estimated the effect of participant’s age, HIV status, presence of a HIV-infected adult within the household and other covariates on pneumococcal acquisition and clearance probabilities. Of 1,684 individuals enrolled, 279 (16.6%) were younger children (<5 years-old) of whom 4 (1.5%) were HIV-infected and 726 (43.1%) were adults (≥18 years-old) of whom 214 (30.4%) were HIV-infected, most (173, 81.2%) with high CD4+ count. The observed range of pneumococcal carriage prevalence across visits was substantially higher in younger children (56.9–80.5%) than older children (5–17 years-old) (31.7–50.0%) or adults (11.5–23.5%). We estimate that 14.4% (95% Confidence Interval [CI]: 13.7–15.0) of pneumococcal-negative swabs were false negatives. Daily carriage acquisition probabilities among HIV-uninfected younger children were similar in households with and without HIV-infected adults (hazard ratio: 0.95, 95%CI: 0.91–1.01). Longer average carriage duration (11.4 days, 95%CI: 10.2–12.8 vs 6.0 days, 95%CI: 5.6–6.3) and higher median carriage density (622 genome equivalents per millilitre, 95%CI: 507–714 vs 389, 95%CI: 311.1–435.5) were estimated in HIV-infected vs HIV-uninfected adults. The use of ART and antibiotics substantially reduced carriage duration in all age groups, and acquisition rates increased with household size. Although South African HIV-infected adults on ART have longer carriage duration and density than their HIV-uninfected counterparts, they show similar patterns of pneumococcal acquisition and onward transmission.

Human learning follows the dynamics of gradient descent

Artificial neural networks (ANNs) have achieved near human-level performance on many tasks and can account for human behavioural and brain measures in a number of domains. Although a principal strength of ANNs is learning representations from experience, only a handful of contributions have evaluated this process to ask whether ANN learning dynamics provide a good model of human learning. We investigated whether humans learn similarly to an ANN, which adjusts its representations through gradient descent. Gradient descent learning is steep at first and initially ignores covariance between features. ANNs can theoretically display a non-monotonic behaviour in which early in learning, multiple weak predictors determine the ANN’s decision whereas late in learning a single strong predictor can dominate. This initial behaviour was confirmed in a simple ANN and in half of human participants performing a comparable task. Later in gradient descent learning, the ANN changed to placing a greater weight on the stronger predictor, and humans also shifted their preferences in the same way. Hidden Markov modelling of the behaviour of ANNs and humans predicted similar transitions from weak-feature to strong-feature states. Our results suggest a significant proportion of people learn about categories in a manner analogous to ANNs, possibly by updating their mental representations by a process akin to gradient descent. Our findings demonstrate how ANNs can be used to not only explain the products of human learning but also the process.

Human learning follows the dynamics of gradient descent

Artificial neural networks (ANNs) have achieved near human-level performance on many tasks and can account for human behavioural and brain measures in a number of domains. Although a principal strength of ANNs is learning representations from experience, only a handful of contributions have evaluated this process to ask whether ANN learning dynamics provide a good model of human learning. We investigated whether humans learn similarly to an ANN, which adjusts its representations through gradient descent. Gradient descent learning is steep at first and initially ignores covariance between features. ANNs can theoretically display a non-monotonic behaviour in which early in learning, multiple weak predictors determine the ANN’s decision whereas late in learning a single strong predictor can dominate. This initial behaviour was confirmed in a simple ANN and in half of human participants performing a comparable task. Later in gradient descent learning, the ANN changed to placing a greater weight on the stronger predictor, and humans also shifted their preferences in the same way. Hidden Markov modelling of the behaviour of ANNs and humans predicted similar transitions from weak-feature to strong-feature states. Our results suggest a significant proportion of people learn about categories in a manner analogous to ANNs, possibly by updating their mental representations by a process akin to gradient descent. Our findings demonstrate how ANNs can be used to not only explain the products of human learning but also the process.

Cost effectiveness of screening for intracranial aneurysms among patients with bicuspid aortic valve: a Markov modelling study

ObjectiveBicuspid aortic valve (BAV) is common and 7.7%–9.8% of patients with BAV have intracranial aneuryms (IAs) which might lead to a devastating subarachnoid haemorrhage (SAH). We aimed to evaluate different screening and follow-up strategies using magnetic resonance angiography for IAs among patients with BAV.MethodsA decision-analytic model was built to evaluate the costs and effectiveness of different management strategies from the Chinese healthcare payer’s perspective. The evaluated strategies included natural history without screening for possible IAs, regular screening and no follow-up for detected IAs, and regular screening with regular follow-up (Screen strategy/Follow-up strategy). Base case calculation, as well as probabilistic, one-way, and two-way sensitivity analyses, were performed.ResultsAccording to the base case calculation, natural history had the least cost and effectiveness while Every 5 years (y)/Annual gained the highest cost and effectiveness. Every 10y/Biennial was cost effective when compared with Every 10y/Every 5y under the willingness-to-pay threshold of ¥211 743 (US$30 162). Probabilistic sensitivity analysis showed that Every 10y/Biennial was superior in 88.3% of the cases when compared with Every 10y/Every 5y. One-way and two-way sensitivity analyses proved that Every 10y/Biennial was the dominant strategy under most circumstances.ConclusionsScreening for possible IAs among patients with BAV and follow-up for detected IAs would increase the effectiveness. Every 10y/Biennial was the optimal strategy from the Chinese healthcare payer’s perspective.

Is non-contrast enhanced magnetic resonance imaging cost-effective for screening of hepatocellular carcinoma?

Introduction: Ultrasound (US) is current standard of care for imaging surveillance in patients at risk for hepatocellular carcinoma (HCC). Magnetic resonance imaging (MRI) has been explored as an alternative, given the higher sensitivity of MRI, although this comes at a higher cost. We performed a cost-effective analysis comparing US and a dual-sequence non-contrast MRI (NCEMRI) for HCC surveillance, in the local setting. Methods: Cost-effectiveness analysis of no surveillance, US surveillance and NCEMRI surveillance was performed using Markov modelling and microsimulation. At-risk patient cohort was simulated and followed-up for 40 years to estimate their disease status, direct medical costs, and effectiveness. Quality-adjusted life years (QALYs) and incremental cost effectiveness ratio were calculated. Results: 482,000 patients with an average age of 40 years were simulated and followed up for 40 years. The average total costs and QALYs for the three scenarios – no surveillance, US surveillance and NCEMRI surveillance were S$1,193/7.460 QALYs; S$8,099/11.195 QALYs; S$9,720/11.366 QALYs, respectively. Conclusion: Despite NCEMRI having a superior diagnostic accuracy, it is a less cost-effective strategy than US for HCC surveillance in the general at-risk population. Future local cost-effectiveness analyses should include stratifying surveillance methods with a variety of imaging techniques (US, NCEMRI, CEMRI) based on patients’ risk profiles.

SP5.1.12 Discrete Event Micro Simulation Modeling for the Treatment of Resectable Malignancy of the Oesophagus and Gastrooesophageal Junction

Aims To assist decision-making by creation of a statistical model that simulates treatment pathways and subsequent outcomes for the management of resectable malignancy of the oesophagus and gastrooesophageal junction. Methods: Discrete Event Simulation (DES) modelling is a statistical modelling technique that models the operation of a system as a sequence of events in time to support decision-making. This approach lends itself well to disease modelling by incorporating different treatment strategies targeted at different groups. It offers an advantage over previous decision analysis studies that have relied on Markov modelling which can have reduced accuracy due to lack of memory within the Markov model, the effect of depletion of susceptibles, and the timing of transitioning within the model. This simulation model was populated with data from best available evidence from contemporary randomised controlled trials and ran over 100,000 iterations. Results Neoadjuvant chemoradiotherapy was the superior treatment pathway with superior pathway selection frequency of 87.16%. For squamous cell carcinoma neoadjuvant chemoradiotherapy was the superior treatment option with 73.30 months survival time (65.60 QALMs) and had a superior pathway selection frequency of 100%. Conclusions DES simulation modeling for decision analysis in treatment of resectable malignancy of the oesophagus and gastrooesophageal junction supports the use of neoadjuvant chemoradiotherapy.

Scenario-based Analysis of the Impacts of Lake Drying on Sustainable Food Production

In many parts of the world, lake drying is caused by water management failures, while the phenomenon is exacerbated by climate change. Lake Urmia in Northern Iran is drying up at such an alarming rate that it is considered to be a dying lake, which has dire consequences for the whole region. While salinization caused by a dying lake is well understood and known to influence the local and regional food production, other potential impacts are as yet unknown. Food production in the Urmia region has predominantly been regionally-oriented and sustainable, particularly in terms of water demand. To explore current and projected impacts of the dying lake on sustainable food production (SFP) we investigated changes in climatic conditions, land use, and land degradation for the period 1990-2020. We examined the environmental impacts of lake drought on SFP through an integrated scenario-based geoinformation framework. The results show that the lake drought has significantly affected food production and has reduced the proportion of SFP over the past three decades. Based on a combination of cellular automata and Markov modelling, the conditions are projected for the next 30 years and are predicted to exacerbate further. To mitigate these issues and support SFP, this research provides some policy recommendations and results for tangible action plans. We consider the modification of cropping patterns towards low water demand crops as one the cheapest and most efficient solutions for reducing the overall agricultural water consumption.