Modelling the dynamic relationship between spread of infection and observed crowd movement patterns at large scale events.

Understanding how contact patterns arise from crowd movement is crucial for assessing the spread of infection at mass gathering events. Here we study contact patterns from Wi-Fi mobility data of large sports and entertainment events in the Johan Cruijff ArenA stadium in Amsterdam. We show that crowd movement behaviour at mass gathering events is not homogeneous in time, but naturally consists of alternating periods of movement and rest. As a result, contact duration distributions are heavy-tailed, an observation which is not explained by models assuming that pedestrian contacts are analogous to collisions in the kinetic gas model. We investigate the effect of heavy-tailed contact duration patterns on the spread of infection using various random walk models. We show how different types of intermittent movement behaviour interact with a time-dependent infection probability. Our results point to the existence of a crossover point where increased contact duration presents a higher level of transmission risk than increasing the number of contacts. In addition, we show that different types of intermittent movement behaviour give rise to different mass-action kinetics, but also show that neither one of two mass-action mechanisms uniquely describes events.

Correction: A Screen Identifies the Oncogenic Micro-RNA miR-378a-5p as a Negative Regulator of Oncogene-Induced Senescence.

[This corrects the article DOI: 10.1371/journal.pone.0091034.].

Behavioural thermal regulation explains pedestrian path choices in hot urban environments.

Due to phenomena such as urban heat islands, outdoor thermal comfort of the cities' residents emerges as a growing concern. A major challenge for mega-cities in changing climate is the design of urban spaces that ensure and promote pedestrian thermal comfort. Understanding pedestrian behavioural adaptation to urban thermal environments is critically important to attain this goal. Current research in pedestrian behaviour lacks controlled experimentation, which limits the quantitative modelling of such complex behaviour. Combining well-controlled experiments with human participants and computational methods inspired by behavioural ecology and decision theory, we examine the effect of sun exposure on route choice in a tropical city. We find that the distance walked in the shade is discounted by a factor of 0.86 compared to the distance walked in the sun, and that shadows cast by buildings have a stronger effect than trees. The discounting effect is mathematically formalised and thus allows quantification of the behaviour that can be used in understanding pedestrian behaviour in changing urban climates. The results highlight the importance of assessment of climate through human responses to it and point the way forward to explore scenarios to mitigate pedestrian heat stress.

Maximum expected survival rate model for public access defibrillator placement.

AIM: Mathematical optimization of automated external defibrillator (AED) placement has demonstrated potential to improve survival of out-of-hospital cardiac arrest (OHCA). Existing models mostly aim to improve accessibility based on coverage radius and do not account for detailed impact of delayed defibrillation on survival. We aimed to predict OHCA survival based on time to defibrillation and developed an AED placement model to directly maximize the expected survival rate. METHODS: We stratified OHCAs occurring in Singapore (2010-2017) based on time to defibrillation and developed a regression model to predict the Utstein survival rate. We then developed a novel AED placement model, the maximum expected survival rate (MESR) model. We compared the performance of MESR with a maximum coverage model developed for Canada that was shown to be generalizable to other settings (Denmark). The survival gain of MESR was assessed through 10-fold cross-validation for placement of 20 to 1000 new AEDs in Singapore. Statistical analysis was performed using χ2 and McNemar's tests. RESULTS: During the study period, 15,345 OHCAs occurred. The power-law approximation with R2 of 91.33% performed best among investigated models. It predicted a survival of 54.9% with defibrillation within the first two minutes after collapse that was reduced by more than 60% without defibrillation within the first 4 minutes. MESR outperformed the maximum coverage model with P-value < 0.05 (<0.0001 in 22 of 30 experiments). CONCLUSION: We developed a novel AED placement model based on the impact of time to defibrillation on OHCA outcomes. Mathematical optimization can improve OHCA survival.

A review of mathematical modeling of addiction regarding both (neuro-) psychological processes and the social contagion perspectives.

Addiction is a complex biopsychosocial phenomenon, impacted by biological predispositions, psychological processes, and the social environment. Using mathematical and computational models that allow for surrogative reasoning may be a promising avenue for gaining a deeper understanding of this complex behavior. This paper reviews and classifies a selection of formal models of addiction focusing on the intra- and inter-individual dynamics, i.e., (neuro) psychological models and social models. We find that these modeling approaches to addiction are too disjoint and argue that in order to unravel the complexities of biopsychosocial processes of addiction, models should integrate intra- and inter-individual factors.

The non-linear impact of data handling on network diffusion models.

Many computational models rely on real-world data, and the steps required in moving from data collection, to data preparation, to model calibration, and input are becoming increasingly complex. Errors in data can lead to errors in model output that might invalidate conclusions in extreme cases. While the challenge of errors in data collection have been analyzed in the literature, here we highlight the importance of data handling in the modeling and simulation process, and how particular data handling errors can lead to errors in model output. We develop a framework for assessing the impact of potential data errors for models of spreading processes on networks, a broad class of models that capture many important real-world phenomena (e.g., epidemics, rumor spread, etc.). We focus on the susceptible-infected-removed (SIR) and Threshold models and examine how systematic errors in data handling impact the predicted spread of a virus (or information). Our results demonstrate that data handling errors can have significant impact on model conclusions especially in critical regions of a system.

The impact of pace of life on pedestrian heat stress: A computational modelling approach.

Elevated walking speed is an indicator of increased pace of life in cities, caused by environmental pressures inherent to urban environments, which lead to short- and long-term consequences for health and well-being. In this paper we investigate the effect of walking speed on heat stress. We define the heat-stress-optimal walking speed and estimate its values for a wide range of air temperatures with the use of computational modelling of metabolic heat production and thermal regulation. The heat-stress-optimal walking speed shows three distinct phases in relation to air temperature, determined by different modes of interaction between the environment and physiology. Simulation results suggest that different temperature regimes require walking speed adaptation to preserve heat balance. Empirical data collected for Singapore reveals elevated average walking speed, which is not responsive to slight changes in microclimate (4-5 °C). The proposed computational model predicts the amount of additional heat produced by an individual due to the high pace of life. We conclude that there are direct implications of the high pace of life in cities on the immediate heat stress of people, and we show how a lower walking speed significantly reduces self-overheating and improves thermal comfort.

The present and future burden of previously treated advanced non-small cell lung cancer (NSCLC) by histology and line of therapy in France, Germany, Italy, and Spain: model-based predictions.

BACKGROUND: The burden of advanced non-small cell lung cancer (NSCLC) is not well understood, and the number of patients likely to receive treatment in Europe has not been quantified. The aim of this study was to forecast the annual number of patients with squamous and non-squamous advanced NSCLC likely to receive second and third lines of therapy (LOT) from 2016 to 2020 in France, Germany, Italy, and Spain. METHODS: A patient count model (PCM) was developed in Microsoft Excel to estimate the number of patients with refractory advanced NSCLC eligible to receive systemic treatment. Using historical population-based cancer registry data, segmented linear regression ("Joinpoint") was used to forecast age- and sex-stratified lung cancer incidence rates in each country through 2020. Yearly incident case count totals by country were apportioned according to NSCLC histology and stage at diagnosis. Country-specific treatment rates came from a recent medical chart review study, and early- to advanced-stage disease progression rates were estimated over a 10-year interval. A probabilistic sensitivity analysis (PSA) was performed to estimate variability in the patient counts. RESULTS: The combined number of squamous and non-squamous advanced NSCLC patients estimated to receive second and third LOT, respectively, in 2016 were France = 11,600 and 3500; Germany = 15,100 and 4900; Italy = 13,500 and 2500; Spain = 9400 and 2100. The forecasted numbers of patients receiving second and third LOT, respectively, in 2020 were France = 13,900 and 4200; Germany = 16,200 and 5200; Italy = 15,100 and 2600; Spain = 11,000 and 2500. CONCLUSIONS: Driven by growth in the incidence of NSCLC among women, the model forecasts an overall increase in the number of patients with advanced-stage squamous and non-squamous NSCLC likely to receive systemic treatment in the year 2020. The results highlight the significant burden of refractory advanced NSCLC and the need for more robust surveillance data to accurately quantify the burden of disease.

Time to really share real-world data?

Data other than that from clinical trials are important for healthcare decision making. However, unlike the vocal calls seen for more open access to trial data, there are limited efforts being made to ensure that agencies that collect real-world data (RWD) share this, despite its importance. There are many RWD sources across the world that could be readily exploited for research once shared. There are policy and privacy questions that need to be tackled, but opening up and sharing RWD offers remarkable potential for improvements in care for individuals and more effective use of limited healthcare resources. Open science should become the standard for RWD as well as clinical trials, especially those that have a high likelihood to influence practice.

An exploratory case study of the impact of expanding cost-effectiveness analysis for second-line nivolumab for patients with squamous non-small cell lung cancer in Canada: Does it make a difference?

INTRODUCTION: Health technology appraisal agencies often rely on cost-effectiveness analyses to inform coverage decisions for new treatments. These assessments, however, frequently measure a treatment's value from the payer's perspective, and may not capture value generated from reduced caregiving costs, increased productivity, value based on patient risk preferences, option value or the insurance value to non-patients. METHODS: To examine how using a broader societal perspective of treatment value affects cost-effectiveness estimates, this case study analyzed the net monetary benefit (NMB) of second-line nivolumab treatment of patients with squamous non-small cell lung cancer (NSCLC) in Canada. The comparator was treatment with docetaxel. NMB was measured from three perspectives: (i) traditional payer, (ii) traditional societal and (iii) broad societal. RESULTS: Nivolumab was more effective (increased quality-adjusted life years by 0.66 versus docetaxel), but also increased costs by $100,168 CAD. When valuing a quality-adjusted life year at $150,000, the net monetary benefit from the payer perspective suggested that costs modestly exceed benefits (NMB: -$1031). Adopting a societal perspective, however, nivolumab's benefits outweighed its costs (NMB: +$6752 and +$91,084 from the traditional and broad societal perspectives, respectively). CONCLUSION: Broadening cost-effectiveness analysis beyond the traditional payer perspective had a significant impact on the result and should be considered in order to capture all treatment benefits and costs of societal relevance.

Survey-based socio-economic data from slums in Bangalore, India.

In 2010, an estimated 860 million people were living in slums worldwide, with around 60 million added to the slum population between 2000 and 2010. In 2011, 200 million people in urban Indian households were considered to live in slums. In order to address and create slum development programmes and poverty alleviation methods, it is necessary to understand the needs of these communities. Therefore, we require data with high granularity in the Indian context. Unfortunately, there is a paucity of highly granular data at the level of individual slums. We collected the data presented in this paper in partnership with the slum dwellers in order to overcome the challenges such as validity and efficacy of self reported data. Our survey of Bangalore covered 36 slums across the city. The slums were chosen based on stratification criteria, which included geographical location of the slum, whether the slum was resettled or rehabilitated, notification status of the slum, the size of the slum and the religious profile. This paper describes the relational model of the slum dataset, the variables in the dataset, the variables constructed for analysis and the issues identified with the dataset. The data collected includes around 267,894 data points spread over 242 questions for 1,107 households. The dataset can facilitate interdisciplinary research on spatial and temporal dynamics of urban poverty and well-being in the context of rapid urbanization of cities in developing countries.

Modelling the Survival Outcomes of Immuno-Oncology Drugs in Economic Evaluations: A Systematic Approach to Data Analysis and Extrapolation.

BACKGROUND: New immuno-oncology (I-O) therapies that harness the immune system to fight cancer call for a re-examination of the traditional parametric techniques used to model survival from clinical trial data. More flexible approaches are needed to capture the characteristic I-O pattern of delayed treatment effects and, for a subset of patients, the plateau of long-term survival. OBJECTIVES: Using a systematic approach to data management and analysis, the study assessed the applicability of traditional and flexible approaches and, as a test case of flexible methods, investigated the suitability of restricted cubic splines (RCS) to model progression-free survival (PFS) in I-O therapy. METHODS: The goodness of fit of each survival function was tested on data from the CheckMate 067 trial of monotherapy versus combination therapy (nivolumab/ipilimumab) in metastatic melanoma using visual inspection and statistical tests. Extrapolations were validated using long-term data for ipilimumab. RESULTS: Modelled PFS estimates using traditional methods did not provide a good fit to the Kaplan-Meier (K-M) curve. RCS estimates fit the K-M curves well, particularly for the plateau phase. RCS with six knots provided the best overall fit, but RCS with one knot performed best at the plateau phase and was preferred on the grounds of parsimony. CONCLUSIONS: RCS models represent a valuable addition to the range of flexible approaches available to model survival when assessing the effectiveness and cost-effectiveness of I-O therapy. A systematic approach to data analysis is recommended to compare the suitability of different approaches for different diseases and treatment regimens.

Practical implications of using real-world evidence (RWE) in comparative effectiveness research: learnings from IMI-GetReal.

In light of increasing attention towards the use of real-world evidence (RWE) in decision making in recent years, this commentary aims to reflect on the experiences gained in accessing and using RWE for comparative effectiveness research as a part of the Innovative Medicines Initiative GetReal Consortium and discuss their implications for RWE use in decision-making.

The influence of memory on indoor environment exploration: A numerical study.

Understanding human behavior in the context of exploration and navigation is an important but challenging problem. Such understanding can help in the design of safe structures and spaces that implicitly aid humans during evacuation or other emergency situations. In particular, the role that memory plays in this process is something that is crucial to understand. In this paper, we develop a novel serious game-based experimental approach to understanding the non-randomness and the impact of memory on the human exploration process. We show that a simple memory model, with a depth of between 6 and 8 steps, is sufficient to approximate a 'human-like' level of exploration efficiency. We also demonstrate the advantages that a game-based experimental methodology brings to these kinds of experiments in the amount of data that can be collected as compared to traditional experiments. We feel that these findings have important implications for 'safety-by-design' in complex infrastructural structures.

Cyclin F suppresses B-Myb activity to promote cell cycle checkpoint control.

Cells respond to DNA damage by activating cell cycle checkpoints to delay proliferation and facilitate DNA repair. Here, to uncover new checkpoint regulators, we perform RNA interference screening targeting genes involved in ubiquitylation processes. We show that the F-box protein cyclin F plays an important role in checkpoint control following ionizing radiation. Cyclin F-depleted cells initiate checkpoint signalling after ionizing radiation, but fail to maintain G2 phase arrest and progress into mitosis prematurely. Importantly, cyclin F suppresses the B-Myb-driven transcriptional programme that promotes accumulation of crucial mitosis-promoting proteins. Cyclin F interacts with B-Myb via the cyclin box domain. This interaction is important to suppress cyclin A-mediated phosphorylation of B-Myb, a key step in B-Myb activation. In summary, we uncover a regulatory mechanism linking the F-box protein cyclin F with suppression of the B-Myb/cyclin A pathway to ensure a DNA damage-induced checkpoint response in G2.

Cloning and tissue distribution of novel splice variants of the ovine ghrelin gene.

BACKGROUND: The ghrelin axis is involved in the regulation of metabolism, energy balance, and the immune, cardiovascular and reproductive systems. The manipulation of this axis has potential for improving economically valuable traits in production animals, and polymorphisms in the ghrelin (GHRL) and ghrelin receptor (GHSR) genes have been associated with growth and carcass traits. Here we investigate the structure and expression of the ghrelin gene (GHRL) in sheep, Ovis aries. RESULTS: We identify two ghrelin mRNA isoforms, which we have designated Δex2 preproghrelin and Δex2,3 preproghrelin. Expression of Δex2,3 preproghrelin is likely to be restricted to ruminants, and would encode truncated ghrelin and a novel C-terminal peptide. Both Δex2 preproghrelin and canonical preproghrelin mRNA isoforms were expressed in a range of tissues. Expression of the Δex2,3 preproghrelin isoform, however, was restricted to white blood cells (WBC; where the wild-type preproghrelin isoform is not co-expressed), and gastrointestinal tissues. Expression of Δex2 preproghrelin and Δex2,3 preproghrelin mRNA was elevated in white blood cells in response to parasitic worm (helminth) infection in genetically susceptible sheep, but not in resistant sheep. CONCLUSIONS: The restricted expression of the novel preproghrelin variants and their distinct WBC expression pattern during parasite infection may indicate a novel link between the ghrelin axis and metabolic and immune function in ruminants.