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

2020 ◽  
Vol 17 (166) ◽  
pp. 20200230 ◽  
Author(s):  
W. S. Hart ◽  
P. K. Maini ◽  
C. A. Yates ◽  
R. N. Thompson
Keyword(s):  
Cohort Studies ◽  
Influenza A ◽  
Multi Scale ◽  
Patient Level ◽  
Modelling Framework ◽  
Level Data ◽  
Scale Models ◽  
Scale Modelling ◽  
Population Scale

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.

scholarly journals Macroscopic and Multi-Scale Models for Multi-Class Vehicular Dynamics with Uneven Space Occupancy: A Case Study

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 102
Author(s):  
Maya Briani ◽  
Emiliano Cristiani ◽  
Paolo Ranut
Keyword(s):  
Road Network ◽  
Real Data ◽  
Second Order ◽  
Heavy Vehicles ◽  
First Order ◽  
Multi Scale ◽  
Stop And Go ◽  
Scale Models ◽  
Road Space

In this paper, we propose two models describing the dynamics of heavy and light vehicles on a road network, taking into account the interactions between the two classes. The models are tailored for two-lane highways where heavy vehicles cannot overtake. This means that heavy vehicles cannot saturate the whole road space, while light vehicles can. In these conditions, the creeping phenomenon can appear, i.e., one class of vehicles can proceed even if the other class has reached the maximal density. The first model we propose couples two first-order macroscopic LWR models, while the second model couples a second-order microscopic follow-the-leader model with a first-order macroscopic LWR model. Numerical results show that both models are able to catch some second-order (inertial) phenomena such as stop and go waves. Models are calibrated by means of real data measured by fixed sensors placed along the A4 Italian highway Trieste–Venice and its branches, provided by Autovie Venete S.p.A.

scholarly journals A hybrid approach to multi-scale modelling of cancer

2010 ◽  
Vol 368 (1930) ◽  
pp. 5013-5028 ◽  
Author(s):  
J. M. Osborne ◽  
A. Walter ◽  
S. K. Kershaw ◽  
G. R. Mirams ◽  
A. G. Fletcher ◽  
...  
Keyword(s):  
Continuum Model ◽  
Hybrid Approach ◽  
Multi Scale ◽  
Scale Models ◽  
Scale Modelling ◽  
A Cell ◽  
Solid Tumour Growth ◽  
Basic Features ◽  
Cancerous Cells ◽  
Mutant Cells

In this paper, we review multi-scale models of solid tumour growth and discuss a middle-out framework that tracks individual cells. By focusing on the cellular dynamics of a healthy colorectal crypt and its invasion by mutant, cancerous cells, we compare a cell-centre, a cell-vertex and a continuum model of cell proliferation and movement. All models reproduce the basic features of a healthy crypt: cells proliferate near the crypt base, they migrate upwards and are sloughed off near the top. The models are used to establish conditions under which mutant cells are able to colonize the crypt either by top-down or by bottom-up invasion. While the continuum model is quicker and easier to implement, it can be difficult to relate system parameters to measurable biophysical quantities. Conversely, the greater detail inherent in the multi-scale models means that experimentally derived parameters can be incorporated and, therefore, these models offer greater scope for understanding normal and diseased crypts, for testing and identifying new therapeutic targets and for predicting their impacts.

scholarly journals COVID-19 Associated Pulmonary Aspergillosis: Systematic Review and Patient-Level Meta-Analysis

2021 ◽  
Author(s):  
Ruwandi M. Kariyawasam ◽  
Tanis C. Dingle ◽  
Brittany E. Kula ◽  
Wendy I. Sligl ◽  
Ilan S. Schwartz
Keyword(s):  
Cohort Studies ◽  
Excess Mortality ◽  
Meta Analysis ◽  
Case Series ◽  
Rank Test ◽  
Pulmonary Aspergillosis ◽  
Exact Test ◽  
Patient Level ◽  
Level Data ◽  
Antifungal Use

Rationale Pulmonary aspergillosis may complicate COVID-19 and contribute to excess mortality in intensive care unit (ICU) patients. The incidence is unclear because of discordant definitions across studies. Objective We sought to review the incidence, diagnosis, treatment, and outcomes of COVID-19-associated pulmonary aspergillosis (CAPA), and compare research definitions. Methods We systematically reviewed the literature for ICU cohort studies and case series including ≥3 patients with CAPA. We calculated pooled incidence. Patients with sufficient clinical details were reclassified according to 4 standardized definitions (Verweij, White, Koehler, and Bassetti). Measurements Correlations between definitions were assessed with Spearmans rank test. Associations between antifungals and outcome were assessed with Fishers Exact test. Main Results 38 studies (35 cohort studies and 3 case series) were included. Among 3,297 COVID-19 patients in ICU cohort studies, 313 were diagnosed with CAPA (pooled incidence 9.5%). 197 patients had patient-level data allowing reclassification. Definitions had limited correlation with one another (ρ=0.330 to 0.621, p<0.001). 38.6% of patients reported to have CAPA did not fulfill any research definitions. Patients were diagnosed after a median of 9 days (interquartile range 5-14) in ICUs. Tracheobronchitis occured in 5.3% of patients examined with bronchoscopy. The mortality rate (50.0%) was high, irrespective of antifungal use (p=0.28); this remained true even when the analysis was restricted to patients meeting standardized definitions for CAPA. Conclusions The reported incidence of CAPA is exaggerated by use of non-standard definitions. Further research should focus on identifying patients likely to benefit from antifungals.

scholarly journals Effects of catalyst agglomerate shape in polymer electrolyte fuel cells investigated by a multi-scale modelling framework

Energy ◽  
2017 ◽  
Vol 122 ◽  
pp. 420-430 ◽  
Author(s):  
M.S. Ismail ◽  
D.B. Ingham ◽  
L. Ma ◽  
K.J. Hughes ◽  
M. Pourkashanian
Keyword(s):  
Fuel Cells ◽  
Polymer Electrolyte ◽  
Polymer Electrolyte Fuel Cells ◽  
Multi Scale ◽  
Modelling Framework ◽  
Scale Modelling

scholarly journals Ontology-Based Process Modelling-with Examples of Physical Topologies

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 592
Author(s):  
Heinz A Preisig
Keyword(s):  
Directed Graphs ◽  
Process Modelling ◽  
Process Models ◽  
Application Domain ◽  
Capture Process ◽  
Graphical Language ◽  
Multi Scale ◽  
Modelling Framework ◽  
Scale Models ◽  
Interacting Networks

Reductionism and splitting application domain into disciplines and identify the smallest required model-granules, termed ”basic entity” combined with systematic construction of the behaviour equations for the basic entities, yields a systematic approach to process modelling. We do not aim toward a single modelling domain, but we enable to address specific application domains and object inheritance. We start with reductionism and demonstrate how the basic entities are depending on the targeted application domain. We use directed graphs to capture process models, and we introduce a new concept, which we call ”tokens” that enables us to extend the context beyond physical systems. The network representation is hierarchical so as to capture complex systems. The interacting basic entities are defined in the leave nodes of the hierarchy, making the overall model the interacting networks in the leave nodes. Multi-disciplinary and multi-scale models result in a network of networks. We identify two distinct network communication ports, namely ports that exchange tokens and ports that transfer information of tokens in accumulators. An ontology captures the structural elements and the applicable rules and defines the syntax to establish the behaviour equations. Linking the behaviours to the basic entities defines the alphabet of a graphical language. We use this graphical language to represent processes, which has proven to be efficient and valuable. A set of three examples demonstrates the power of the graphical language. The Process Modelling framework (ProMo) implements the ontology-centred approach to process modelling and uses the graphical language to construct process models.

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