scholarly journals A Novel Model for Simulating COVID-19 Dynamics Through Layered Infection States that Integrate Concepts from Epidemiology, Biophysics and Medicine: SEI3R2S-Nrec

2020 ◽  
Author(s):  
Jack M Winters
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Disease Process ◽  
Data Access ◽  
Population Diversity ◽  
Optimal Feedback Control ◽  
Model Structure ◽  
Modeling Framework ◽  
Physiological Models ◽  
The Usa

Introduction. Effectively modeling SARS-CoV-2/COVID-19 dynamics requires careful integration of population health (public health motivation) and recovery dynamics (medical interventions motivation). This manuscript proposes a minimal pandemic model, which conceptually separates "complex adaptive systems" (CAS) associated with social behavior and infrastructure (e.g., tractable input events modulating exposure) from idealized bio-CAS (e.g., the immune system). The proposed model structure extends the classic simple SEIR (susceptible, exposed, infected, resistant/recovered) uni-causal compartmental model, widely used in epidemiology, into an 8th-order functional network SEI3R2S-Nrec model structure, with infection partitioned into three severity states (e.g., starts in I1 [mostly asymptomatic], then I2 if notable symptoms, then I3 if ideally hospitalized) that connect via a lattice of fluxes to two "resistant" (R) states. Here Nrec ("not recovered") represents a placeholder for better tying emerging COVID-19 medical research findings with those from epidemiology. Methods. Borrowing from fuzzy logic, a given model represents a "Universe of Discourse" (UoD) that is based on assumptions. Nonlinear flux rates are implemented using the classic Hill function, widely used in the biochemical and pharmaceutical fields and intuitive for inclusion within differential equations. There is support for "encounter" input events that modulate ongoing E (exposures) fluxes via S↔I1 and other I1/2/3 encounters, partitioned into a "social/group" (uSG(t)) behavioral subgroup (e.g., ideally informed by evolving science best-practices), and a smaller uTB(t) subgroup with added "spreader" lifestyle and event support. In addition to signal and flux trajectories (e.g., plotted over 300 days), key cumulative output metrics include fluxes such as I3→D deaths, I2→I3 hospital admittances, I1→I2 related to "cases" and R1+R2 resistant. The code, currently available as a well-commented Matlab Live Script file, uses a common modeling framework developed for a portfolio of other physiological models that tie to a planned textbook; an interactive web-based version will follow. Results. Default population results are provided for the USA as a whole, three states in which this author has lived (Arizona, Wisconsin, Oregon), and several special hypothetical cases of idealized UoDs (e.g., nursing home; healthy lower-risk mostly on I1→R1 path to evaluate reinfection possibilities). Often known events were included (e.g., pulses for holiday weekends; Trump/governor-inspired summer outbreak in Arizona). Runs were mildly tuned by the author, in two stages: i) mild model-tuning (e.g., for risk demographics such as obesity), then ii) iterative input tuning to obtain similar overall March-thru-November curve shapes and appropriate cumulative numbers (recognizing limitations of data like "cases"). Predictions are consistent deaths, and CDC estimates of actual cases and immunity (e.g., antibodies). Results could be further refined by groups with more resources (human, data access, computational). It is hoped that its structure and causal predictions might prove helpful to policymakers, medical professionals, and "on the ground" managers of science-based interventions. Discussion and Future Directions. These include: i) sensitivity of the model to parameters; ii) possible next steps for this SEI3R2S-Nrec framework such as dynamic sub-models to better address compartment-specific forms of population diversity (e.g., for E [host-parasite biophysics], I's [infection diversity], and/or R's [immune diversity]); iii) model's potential utility as a framework for applying optimal/feedback control engineering to help manage the ongoing pandemic response in the context of competing subcriteria and emerging new tools (e.g., more timely testing, vaccines); and iv) ways in which the Nrec medical submodel could be expanded to provide refined estimates of the types of tissue damage, impairments and dysfunction that are known byproducts of the COVID-19 disease process, including as a function of existing comorbidities.

scholarly journals Assessing Future Resilience, Equity, and Sustainability in Scenario Planning

2021 ◽  
pp. 113-127
Author(s):  
Marta Berbés-Blázquez ◽  
Nancy B. Grimm ◽  
Elizabeth M. Cook ◽  
David M. Iwaniec ◽  
Tischa A. Muñoz-Erickson ◽  
...  
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Assessment Tool ◽  
Scenario Planning ◽  
Research Network ◽  
Municipal Governments ◽  
Weather Events ◽  
Sustainability Research ◽  
Complex Adaptive ◽  
The Usa

AbstractIn the absence of strong international agreements, many municipal governments are leading efforts to build resilience to climate change in general and to extreme weather events in particular. However, it is notoriously difficult to guide and activate processes of change in complex adaptive systems such as cities. Participatory scenario planning with city professionals and members of civil society provides an opportunity to coproduce positive visions of the future. Yet, not all visions are created equal. In this chapter, we introduce the Resilience, Equity, and Sustainability Qualitative (RESQ) assessment tool that we have applied to compare positive scenario visions for cities in the USA and Latin America. We use the tool to examine the visions of the two desert cities in the UrbanResilience to Extreme Events Sustainability Research Network (UREx SRN), which are Hermosillo (Mexico) and Phoenix (United States).

scholarly journals Ambition meets reality: lessons from the taro boom in Nicaragua

2018 ◽  
Vol 8 (1) ◽  
pp. 77-98 ◽  
Author(s):  
Jason Donovan ◽  
Nigel Poole ◽  
Keith Poe ◽  
Ingrid Herrera-Arauz
Keyword(s):  
Complex Adaptive Systems ◽  
Value Chain ◽  
Adaptive Systems ◽  
Production Systems ◽  
Primary Data ◽  
New Production ◽  
Content Type ◽  
Local Actors ◽  
The Usa ◽  
Business Relations

Purpose Between 2006 and 2011, Nicaragua shipped an average of US$9.4 million per year of smallholder-produced fresh taro (Colocasia esculenta) to the USA; however, by 2016, the US market for Nicaraguan taro had effectively collapsed. The purpose of this paper is to analyze the short-lived taro boom from the perspective of complex adaptive systems, showing how shocks, interactions between value chain actors, and lack of adaptive capacity among chain actors together contributed to the collapse of the chain. Design/methodology/approach Primary data were collected from businesses and smallholders in 2010 and 2016 to understand the actors involved, their business relations, and the benefits and setbacks they experienced along the way. Findings The results show the capacity of better-off smallholders to engage in a demanding market, but also the struggles faced by more vulnerable smallholders to build new production systems and respond to internal and external shocks. Local businesses were generally unprepared for the uncertainties inherent in fresh horticultural trade or for engagement with distant buyers. Research limitations/implications Existing guides and tools for designing value chain interventions will benefit from greater attention to the circumstances of local actors and the challenges of building productive inter-business relations under higher levels of risk and uncertainty. Originality/value This case serves as a wake-up call for practitioners, donors, researchers, and the private sector on how to identify market opportunities and the design of more robust strategies to respond to them.

scholarly journals A Novel Formal Agent-Based Simulation Modeling Framework of an AIDS Complex Adaptive System

2013 ◽  
Vol 5 (3) ◽  
pp. 33-53 ◽  
Author(s):  
Amnah Siddiqa ◽  
Muaz Niazi
Keyword(s):  
Complex Adaptive Systems ◽  
Formal Specification ◽  
Simulation Modeling ◽  
Adaptive Systems ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based Simulation ◽  
Modeling Framework ◽  
Agent Based ◽  
Complex Adaptive

HIV/AIDS spread depends upon complex patterns of interaction among various subsets emerging at population level. This added complexity makes it difficult to study and model AIDS and its dynamics. AIDS is therefore a natural candidate to be modeled using agent-based modeling, a paradigm well-known for modeling Complex Adaptive Systems (CAS). While agent-based models are well-known to effectively model CAS, often times models can tend to be ambiguous and using only using text-based specifications (such as ODD) making models difficult to be replicated. Previous work has shown how formal specification may be used in conjunction with agent-based modeling to develop models of various CAS. However, to the best of the authors’ knowledge, no such model has been developed in conjunction with AIDS. In this paper, we present a Formal Agent-Based Simulation modeling framework (FABS-AIDS) for an AIDS-based CAS. FABS-AIDS employs the use of a formal specification model in conjunction with an agent-based model to reduce ambiguity as well as improve clarity in the model definition. The proposed model demonstrates the effectiveness of using formal specification in conjunction with agent-based simulation for developing models of CAS in general and, social network-based agent-based models, in particular.

scholarly journals Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

2013 ◽  
Vol 10 (11) ◽  
pp. 7553-7574 ◽  
Author(s):  
A. P. Palacz ◽  
M. A. St. John ◽  
R. J. W. Brewin ◽  
T. Hirata ◽  
W. W. Gregg
Keyword(s):  
Remote Sensing ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Dynamic Models ◽  
Trophic Levels ◽  
Ecological Indicator ◽  
Diagnostic Model ◽  
Modeling Framework ◽  
Functional Types ◽  
Indicator Approach

Abstract. Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom–coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

scholarly journals Distribution of phytoplankton functional types in high-nitrate low-chlorophyll waters in a new diagnostic ecological indicator model

2013 ◽  
Vol 10 (5) ◽  
pp. 8103-8157 ◽  
Author(s):  
A. P. Palacz ◽  
M. A. St. John ◽  
R. J. W. Brewin ◽  
T. Hirata ◽  
W. W. Gregg
Keyword(s):  
Remote Sensing ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Dynamic Models ◽  
Trophic Levels ◽  
Ecological Indicator ◽  
Diagnostic Model ◽  
Modeling Framework ◽  
Functional Types ◽  
Indicator Approach

Abstract. Modeling and monitoring plankton functional types (PFTs) is challenged by insufficient amount of field measurements to ground-truth both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically-sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs, and focus on resolving the question of diatom-coccolithophore co-existence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high latitude areas, and indicate seasonal co-existence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, was so far not captured by state-of-the-art dynamic models which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

A 21st century appreciation for: quality, excellence and complex human adaptive systems

2019 ◽  
Vol 32 (1) ◽  
pp. 2-20 ◽  
Author(s):  
Bob Kennedy
Keyword(s):  
Interest Group ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Service Providers ◽  
First Century ◽  
Individual Interest ◽  
Quality Outcomes ◽  
Content Type ◽  
The Usa ◽  
Twenty First Century

Purpose The purpose of this paper is to develop a coherent theory and strategy for the achievement of quality outcomes that is meaningful and relevant to people at all levels of society. These should help the quality professional engage with people at all levels of society in the development of a culture that appreciates quality, systems and excellence. The research draws on the work of the community quality councils movement in the USA and sought to build on this experience in a village in northwest Ireland. Design/methodology/approach Action research employing an ethnographic type approach to a four year immersion period in a small industrious community. Its inductive nature and naturalist mode of enquiry did not lend itself to either the generation or analysis of quantitative data. Nevertheless it yielded many rich complex pictures or patterns of qualitative information requiring long periods of reflection to decipher the sense and meaning in them. Findings The findings can be encapsulated in one sentence “To achieve quality outcomes we must practise excellence and maintain systems that are fit for purpose”. This requires a radical reworking of Deming’s system of profound knowledge (SoPK) to make it relevant to the human complex adaptive systems that permeate the twenty-first century. These operate as autonomous service providers in a rapidly changing environment. Research limitations/implications The findings of this research have transferability to all sectors in society pursuing purposeful activity. It is relevant at individual, interest-group, industry, institution and community level. It should make the development of a “quality culture” more attainable at all levels. Practical implications Provides quality professionals with new terminology and imagery to engage with, analyse and help autonomous human activity systems in the twenty-first century. It moves Deming’s SoPK to a new level more suited to human systems. Social implications By explaining quality, excellence and systems in easily understood and accepted terms the Grange Excellence Model allows every individual, interest-group, industry and institution share the same language and images as they pursue quality outcomes. This unified approach could transform communities and society in general. Originality/value The research generates a seismic shift in the appreciation of quality, excellence and systems making them relevant and meaningful to people at all levels of society. This provides quality professionals with a methodology, images and vocabulary that will facilitate productive engagement with purposeful systems at all levels of complexity.

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