scholarly journals Introducing a drift and diffusion framework for childhood growth research

2020 ◽  
Vol 4 ◽  
pp. 71
Author(s):  
Fraser I Lewis ◽  
Godfrey Guga ◽  
Paschal Mdoe ◽  
Esto Mduma ◽  
Cloupas Mahopo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Population Level ◽  
Child Growth ◽  
Additive Models ◽  
Growth Trajectories ◽  
Trajectory Data ◽  
Childhood Growth ◽  
Individual Level ◽  
Wide Range ◽  
And Diffusion

Background: Growth trajectories are highly variable between children, making epidemiological analyses challenging both to the identification of malnutrition interventions at the population level and also risk assessment at individual level. We introduce stochastic differential equation (SDE) models into child growth research. SDEs describe flexible dynamic processes comprising: drift - gradual smooth changes – such as physiology or gut microbiome, and diffusion - sudden perturbations, such as illness or infection. Methods: We present a case study applying SDE models to child growth trajectory data from the Haydom, Tanzania and Venda, South Africa sites within the MAL-ED cohort. These data comprise n=460 children aged 0-24 months. A comparison with classical curve fitting (linear mixed models) is also presented. Results: The SDE models offered a wide range of new flexible shapes and parameterizations compared to classical additive models, with performance as good or better than standard approaches. The predictions from the SDE models suggest distinct longitudinal clusters that form distinct ‘streams’ hidden by the large between-child variability. Conclusions: Using SDE models to predict future growth trajectories revealed new insights in the observed data, where trajectories appear to cluster together in bands, which may have a future risk assessment application. SDEs offer an attractive approach for child growth modelling and potentially offer new insights.

scholarly journals Introducing a drift and diffusion framework for childhood growth research

2020 ◽  
Vol 4 ◽  
pp. 71
Author(s):  
Fraser I Lewis ◽  
Godfrey Guga ◽  
Paschal Mdoe ◽  
Esto Mduma ◽  
Cloupas Mahopo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Population Level ◽  
Child Growth ◽  
Additive Models ◽  
Growth Trajectories ◽  
Trajectory Data ◽  
Childhood Growth ◽  
Individual Level ◽  
Wide Range ◽  
And Diffusion

Background: Growth trajectories are highly variable between children, making epidemiological analyses challenging both to the identification of malnutrition interventions at the population level and also risk assessment at individual level. We introduce stochastic differential equation (SDE) models into child growth research. SDEs describe flexible dynamic processes comprising: drift - gradual smooth changes – such as physiology or gut microbiome, and diffusion - sudden perturbations, such as illness or infection. Methods: We present a case study applying SDE models to child growth trajectory data from the Haydom, Tanzania and Venda, South Africa sites within the MAL-ED cohort. These data comprise n=460 children aged 0-24 months. A comparison with classical curve fitting (linear mixed models) is also presented. Results: The SDE models offered a wide range of new flexible shapes and parameterizations compared to classical additive models, with performance as good or better than standard approaches. The predictions from the SDE models suggest distinct longitudinal clusters that form distinct ‘streams’ hidden by the large between-child variability. Conclusions: Using SDE models to predict future growth trajectories revealed new insights in the observed data, where trajectories appear to cluster together in bands, which may have a future risk assessment application. SDEs offer an attractive approach for child growth modelling and potentially offer new insights.

scholarly journals Cystic fibrosis carriers are at increased risk for a wide range of cystic fibrosis-related conditions

2019 ◽  
Vol 117 (3) ◽  
pp. 1621-1627 ◽  
Author(s):  
Aaron C. Miller ◽  
Alejandro P. Comellas ◽  
Douglas B. Hornick ◽  
David A. Stoltz ◽  
Joseph E. Cavanaugh ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Failure To Thrive ◽  
Population Level ◽  
Population Based ◽  
Carrier State ◽  
Individual Level ◽  
Relative Odds ◽  
Increased Risk ◽  
Wide Range ◽  
Autosomal Recessive Diseases

Autosomal recessive diseases, such as cystic fibrosis (CF), require inheritance of 2 mutated genes. However, some studies indicate that CF carriers are at increased risk for some conditions associated with CF. These investigations focused on single conditions and included small numbers of subjects. Our goal was to determine whether CF carriers are at increased risk for a range of CF-related conditions. Using the Truven Health MarketScan Commercial Claims database (2001–2017), we performed a population-based retrospective matched-cohort study. We identified 19,802 CF carriers and matched each carrier with 5 controls. The prevalence of 59 CF-related diagnostic conditions was evaluated in each cohort. Odds ratios for each condition were computed for CF carriers relative to controls. All 59 CF-related conditions were more prevalent among carriers compared with controls, with significantly increased risk (P < 0.05) for 57 conditions. Risk was increased for some conditions previously linked to CF carriers (e.g., pancreatitis, male infertility, bronchiectasis), as well as some conditions not previously reported (e.g., diabetes, constipation, cholelithiasis, short stature, failure to thrive). We compared our results with 23,557 subjects with CF, who were also matched with controls; as the relative odds of a given condition increased among subjects with CF, so did the corresponding relative odds for carriers (P < 0.001). Although individual-level risk remained low for most conditions, because there are more than 10 million carriers in the US, population-level morbidity attributable to the CF carrier state is likely substantial. Genetic testing may inform prevention, diagnosis, and treatment for a broad range of CF carrier-related conditions.

scholarly journals Predation risk triggers copepod small-scale behavior in the Baltic Sea

2020 ◽  
Author(s):  
Klas Ove MÖller ◽  
Michael St. John ◽  
Axel Temming ◽  
Rabea Diekmann ◽  
Janna Peters ◽  
...  
Keyword(s):  
Adaptive Behavior ◽  
Population Level ◽  
Individual Performance ◽  
Predatory Fish ◽  
Small Scale ◽  
Underwater Imaging ◽  
Individual Level ◽  
Wide Range ◽  
The Baltic

Abstract Predators not only have direct impact on biomass but also indirect, non-consumptive effects on the behavior their prey organisms. A characteristic response of zooplankton in aquatic ecosystems is predator avoidance by diel vertical migration (DVM), a behavior which is well studied on the population level. A wide range of behavioral diversity and plasticity has been observed both between- as well as within-species and, hence, investigating predator–prey interactions at the individual level seems therefore essential for a better understanding of zooplankton dynamics. Here we applied an underwater imaging instrument, the video plankton recorder (VPR), which allows the non-invasive investigation of individual, diel adaptive behavior of zooplankton in response to predators in the natural oceanic environment, providing a finely resolved and continuous documentation of the organisms’ vertical distribution. Combing observations of copepod individuals observed with the VPR and hydroacoustic estimates of predatory fish biomass, we here show (i) a small-scale DVM of ovigerous Pseudocalanus acuspes females in response to its main predators, (ii) in-situ observations of a direct short-term reaction of the prey to the arrival of the predator and (iii) in-situ evidence of pronounced individual variation in this adaptive behavior with potentially strong effects on individual performance and ecosystem functioning.

scholarly journals A strengths-based data capture model: mining data-driven and person-centered health assets

JAMIA Open ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 11-14
Author(s):  
Grace Gao ◽  
Madeleine J Kerr ◽  
Ruth A Lindquist ◽  
Chih-Lin Chi ◽  
Michelle A Mathiason ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Care ◽  
Health Care Policy ◽  
Population Level ◽  
Data Capture ◽  
Data Driven ◽  
Individual Level ◽  
Centered Care ◽  
The Individual ◽  
Health Assets

Abstract With health care policy directives advancing value-based care, risk assessments and management have permeated health care discourse. The conventional problem-based infrastructure defines what data are employed to build this discourse and how it unfolds. Such a health care model tends to bias data for risk assessment and risk management toward problems and does not capture data about health assets or strengths. The purpose of this article is to explore and illustrate the incorporation of a strengths-based data capture model into risk assessment and management by harnessing data-driven and person-centered health assets using the Omaha System. This strengths-based data capture model encourages and enables use of whole-person data including strengths at the individual level and, in aggregate, at the population level. When aggregated, such data may be used for the development of strengths-based population health metrics that will promote evaluation of data-driven and person-centered care, outcomes, and value.

scholarly journals Incorporating pushing in exclusion process models of cell migration

2014 ◽  
Author(s):  
Christian A Yates ◽  
Andrew Parker ◽  
Ruth E Baker
Keyword(s):  
Diffusion Coefficient ◽  
Exclusion Process ◽  
Population Level ◽  
Process Models ◽  
Jump Processes ◽  
Lattice Volume ◽  
Individual Level ◽  
Wide Range ◽  
Level Model ◽  
Crowded Environments

The macroscale movement behaviour of a wide range of isolated migrating cells has been well characterised experimentally. Recently, attention has turned to understanding the behaviour of cells in crowded environments. In such scenarios it is possible for cells to interact mechanistically, inducing neighbouring cells to move in order to make room for their own movements or progeny. Although the behaviour of interacting cells has been modelled extensively through volume-exclusion processes, no models, thus far, have explicitly accounted for the ability of cells to actively displace each other. In this work we consider both on and off-lattice volume-exclusion position-jump processes in which cells are explicitly allowed to induce movements in their near neighbours in order to create space for themselves (which we refer to as pushing). From these simple individual-level representations we derive continuum partial differential equations for the average occupancy of the domain. We find that, for limited amounts of pushing, the comparison between the averaged individual-level simulations and the population-level model is nearly as good as in the scenario without pushing but, that for larger and more complicated pushing events the assumptions used to derive the population-level model begin to break down. Interestingly, we find that, in the on-lattice case, the diffusion coefficient of the population-level model is increased by pushing, whereas, for the particular off-lattice model that we investigate, the diffusion coefficient is reduced. We conclude therefore, that it is important to consider carefully the appropriate individual-level model to use when representing complex cell-cell interactions such as pushing.

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

scholarly journals A Tale of Odds and Ratios: Political Preference Formation in Postindustrial Democracies

2021 ◽  
Author(s):  
David M. Wineroither ◽  
Rudolf Metz
Keyword(s):  
Social Stratification ◽  
Political Process ◽  
Environment Interaction ◽  
Preference Formation ◽  
Political Preference ◽  
Individual Level ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Wide Range ◽  
The Individual

AbstractThis report surveys four approaches that are pivotal to the study of preference formation: (a) the range, validity, and theoretical foundations of explanations of political preferences at the individual and mass levels, (b) the exploration of key objects of preference formation attached to the democratic political process (i.e., voting in competitive elections), (c) the top-down vs. bottom-up character of preference formation as addressed in leader–follower studies, and (d) gene–environment interaction and the explanatory weight of genetic predisposition against the cumulative weight of social experiences.In recent years, our understanding of sites and processes of (individual) political-preference formation has substantially improved. First, this applies to a greater variety of objects that provide fresh insight into the functioning and stability of contemporary democracy. Second, we observe the reaffirmation of pivotal theories and key concepts in adapted form against widespread challenge. This applies to the role played by social stratification, group awareness, and individual-level economic considerations. Most of these findings converge in recognising economics-based explanations. Third, research into gene–environment interplay rapidly increases the number of testable hypotheses and promises to benefit a wide range of approaches already taken and advanced in the study of political-preference formation.

scholarly journals Blood Pressure Trajectories Across the Life Course

2021 ◽  
Vol 34 (3) ◽  
pp. 234-241
Author(s):  
Norrina B Allen ◽  
Sadiya S Khan
Keyword(s):  
Blood Pressure ◽  
Measurement Errors ◽  
Clinical Care ◽  
Population Level ◽  
Cumulative Exposure ◽  
Older Adulthood ◽  
Individual Level ◽  
The Life Course ◽  
Level Group ◽  
Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

scholarly journals Risk and the Republican National Convention: Application of the Novel COVID-19 Operational Risk Assessment

2021 ◽  
pp. 1-6
Author(s):  
David Callaway ◽  
Jeff Runge ◽  
Lucia Mullen ◽  
Lisa Rentz ◽  
Kevin Staley ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Care ◽  
Care Delivery ◽  
The United States ◽  
Lessons Learned ◽  
World Health ◽  
Local Health ◽  
Mass Gathering ◽  
Wide Range ◽  
National Convention

Abstract The United States Centers for Disease Control and Prevention and the World Health Organization broadly categorize mass gathering events as high risk for amplification of coronavirus disease 2019 (COVID-19) spread in a community due to the nature of respiratory diseases and the transmission dynamics. However, various measures and modifications can be put in place to limit or reduce the risk of further spread of COVID-19 for the mass gathering. During this pandemic, the Johns Hopkins University Center for Health Security produced a risk assessment and mitigation tool for decision-makers to assess SARS-CoV-2 transmission risks that may arise as organizations and businesses hold mass gatherings or increase business operations: The JHU Operational Toolkit for Businesses Considering Reopening or Expanding Operations in COVID-19 (Toolkit). This article describes the deployment of a data-informed, risk-reduction strategy that protects local communities, preserves local health-care capacity, and supports democratic processes through the safe execution of the Republican National Convention in Charlotte, North Carolina. The successful use of the Toolkit and the lessons learned from this experience are applicable in a wide range of public health settings, including school reopening, expansion of public services, and even resumption of health-care delivery.

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