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1.
J Environ Qual ; 49(3): 517-533, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-33016389

RESUMO

Nutrient pollution is considered a wicked problem because of its many significant economic, social, and environmental impacts that are caused by multiple pollutants originating from a variety of sources and pathways that exist across different temporal and spatial scales. Further adding to the difficulty in managing nutrient pollution is that it is a global, rural, and urban problem. A systems approach can improve nutrient management by incorporating technological, environmental, and societal considerations. This approach can consider valuation of monetized and nonmonetized co-benefits and the inherent consequences that make up a nutrient management program. In this introduction to a special collection of papers on nutrient pollution, we describe several systems frameworks that can be used to support nutrient management and evaluation of system performance as it relates to impacts, then highlight several attributes and barriers of nutrient management that point to the need for a systems framework, and conclude with thoughts on implementing systems approaches to nutrient management with effective community engagement and use of new technologies. This special collection presents results from a USEPA Science to Achieve Results (STAR) initiative to advance solutions to nutrient pollution through innovative and sustainable research and demonstration projects for nutrient management based on a systems approach. These studies evaluate several promising nutrient control technologies for stormwater or domestic wastewater, investigate the effects of agricultural conservation practices and stream restoration strategies on nutrient loads, and discuss several challenges and opportunities-social, policy, institutional, and financial considerations-that can accelerate adoption of reliable technologies to achieve system-level outcomes.


Assuntos
Nutrientes , Rios , Agricultura , Análise de Sistemas , Águas Residuárias
3.
Phys Rev E ; 102(2-1): 022310, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32942454

RESUMO

The frequent emergence of diseases with the potential to become threats at local and global scales, such as influenza A(H1N1), SARS, MERS, and recently COVID-19 disease, makes it crucial to keep designing models of disease propagation and strategies to prevent or mitigate their effects in populations. Since isolated systems are exceptionally rare to find in any context, especially in human contact networks, here we examine the susceptible-infected-recovered model of disease spreading in a multiplex network formed by two distinct networks or layers, interconnected through a fraction q of shared individuals (overlap). We model the interactions through weighted networks, because person-to-person interactions are diverse (or disordered); weights represent the contact times of the interactions. Using branching theory supported by simulations, we analyze a social distancing strategy that reduces the average contact time in both layers, where the intensity of the distancing is related to the topology of the layers. We find that the critical values of the distancing intensities, above which an epidemic can be prevented, increase with the overlap q. Also we study the effect of the social distancing on the mutual giant component of susceptible individuals, which is crucial to keep the functionality of the system. In addition, we find that for relatively small values of the overlap q, social distancing policies might not be needed at all to maintain the functionality of the system.


Assuntos
Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Modelos Biológicos , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Simulação por Computador , Infecções por Coronavirus/epidemiologia , Suscetibilidade a Doenças , Humanos , Modelos Estatísticos , Pandemias/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Distância Social , Rede Social , Análise de Sistemas , Teoria de Sistemas
4.
PLoS One ; 15(8): e0236716, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32745125

RESUMO

OBJECTIVE: The aim of this study is to assess network-based weight loss interventions in the Chinese setting using agent-based simulation. METHODS: An agent-based model incorporating social, environmental and personal influence is developed to simulate the obesity epidemic through an interconnected social network among a population of 2197 individuals from the nationally representative survey. Model parameters are collected from literature and existing database. To ensure the robustness of our findings, the model is validated against empirical observations and sensitivity analyses are performed on calibrated parameters. RESULTS: When compared with the baseline model, significant weight difference is detected using paired samples t tests for network-based intervention strategies (p<0.05) but no difference is observed for the two conventional intervention strategies including choosing random or high-risk individuals (p>0.05). Targeting the most connected individuals minimizes the average population weight, average BMI, and generates a reduction of 2.70% and 1.38% in overweight and obesity prevalence. CONCLUSIONS: The simulations shows that targeting individuals on the basis of their social network attributes outperforms conventional targeting strategies. Future work needs to focus on how to further leverage social networks to curb obesity prevalence and enhance interventions for other chronic conditions using agent-based simulation.


Assuntos
Obesidade , Análise de Sistemas , Perda de Peso , Adulto , Idoso , Idoso de 80 Anos ou mais , Índice de Massa Corporal , Peso Corporal , Simulação por Computador , Feminino , Comportamentos Relacionados com a Saúde , Humanos , Intervenção Baseada em Internet , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Obesidade/prevenção & controle , Sobrepeso , Rede Social
5.
J Contin Educ Nurs ; 51(9): 402-411, 2020 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-32833030

RESUMO

This article provides the most current guidelines for nurse educators and nurses to use systems thinking to manage COVID-19 in health systems. A working definition of systems thinking is offered, with a review of basic knowledge and care in the context of the system awareness model (SAM). Seven key messages assist nurse educators and nurses in the management of COVID-19 patients culminating in leadership of complex health care systems using systems thinking. [J Contin Educ Nurs. 2020;51(9):402-411.].


Assuntos
Infecções por Coronavirus/terapia , Enfermagem de Cuidados Críticos/educação , Enfermagem de Cuidados Críticos/normas , Assistência à Saúde/organização & administração , Assistência à Saúde/estatística & dados numéricos , Pessoal de Saúde/educação , Pneumonia Viral/terapia , Guias de Prática Clínica como Assunto , Adulto , Betacoronavirus , Currículo , Educação Continuada em Enfermagem/organização & administração , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Análise de Sistemas
7.
PLoS Comput Biol ; 16(8): e1008121, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32797077

RESUMO

Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed.


Assuntos
Anopheles/genética , Tecnologia de Impulso Genético/métodos , Resistência a Inseticidas/genética , Malária , Mosquitos Vetores/genética , Animais , Aptidão Genética , Humanos , Malária/prevenção & controle , Malária/transmissão , Análise de Sistemas
8.
J Eval Clin Pract ; 26(5): 1352-1360, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32820573

RESUMO

BACKGROUND: Our purpose is to assess epidemiological agent-based models-or ABMs-of the SARS-CoV-2 pandemic methodologically. The rapid spread of the outbreak requires fast-paced decision-making regarding mitigation measures. However, the evidence for the efficacy of non-pharmaceutical interventions such as imposed social distancing and school or workplace closures is scarce: few observational studies use quasi-experimental research designs, and conducting randomized controlled trials seems infeasible. Additionally, evidence from the previous coronavirus outbreaks of SARS and MERS lacks external validity, given the significant differences in contagiousness of those pathogens relative to SARS-CoV-2. To address the pressing policy questions that have emerged as a result of COVID-19, epidemiologists have produced numerous models that range from simple compartmental models to highly advanced agent-based models. These models have been criticized for involving simplifications and lacking empirical support for their assumptions. METHODS: To address these voices and methodologically appraise epidemiological ABMs, we consider AceMod (the model of the COVID-19 epidemic in Australia) as a case study of the modelling practice. RESULTS: Our example shows that, although epidemiological ABMs involve simplifications of various sorts, the key characteristics of social interactions and the spread of SARS-CoV-2 are represented sufficiently accurately. This is the case because these modellers treat empirical results as inputs for constructing modelling assumptions and rules that the agents follow; and they use calibration to assert the adequacy to benchmark variables. CONCLUSIONS: Given this, we claim that the best epidemiological ABMs are models of actual mechanisms and deliver both mechanistic and difference-making evidence. Consequently, they may also adequately describe the effects of possible interventions. Finally, we discuss the limitations of ABMs and put forward policy recommendations.


Assuntos
Infecções por Coronavirus/epidemiologia , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Análise de Sistemas , Betacoronavirus , Humanos , Pandemias
9.
Math Biosci ; 328: 108436, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32758501

RESUMO

Residential colleges and universities face unique challenges in providing in-person instruction during the COVID-19 pandemic. Administrators are currently faced with decisions about whether to open during the pandemic and what modifications of their normal operations might be necessary to protect students, faculty and staff. There is little information, however, on what measures are likely to be most effective and whether existing interventions could contain the spread of an outbreak on campus. We develop a full-scale stochastic agent-based model to determine whether in-person instruction could safely continue during the pandemic and evaluate the necessity of various interventions. Simulation results indicate that large scale randomized testing, contact-tracing, and quarantining are important components of a successful strategy for containing campus outbreaks. High test specificity is critical for keeping the size of the quarantine population manageable. Moving the largest classes online is also crucial for controlling both the size of outbreaks and the number of students in quarantine. Increased residential exposure can significantly impact the size of an outbreak, but it is likely more important to control non-residential social exposure among students. Finally, necessarily high quarantine rates even in controlled outbreaks imply significant absenteeism, indicating a need to plan for remote instruction of quarantined students.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Análise de Sistemas , Universidades , Técnicas de Laboratório Clínico , Simulação por Computador , Busca de Comunicante , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Surtos de Doenças/prevenção & controle , Surtos de Doenças/estatística & dados numéricos , Educação a Distância , Habitação , Humanos , Máscaras , Conceitos Matemáticos , Pandemias/prevenção & controle , Pandemias/estatística & dados numéricos , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Quarentena , Processos Estocásticos
10.
PLoS One ; 15(8): e0237638, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32822357

RESUMO

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-based-model applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.


Assuntos
Agricultura/normas , Mudança Climática , Conservação dos Recursos Naturais , Ecossistema , Modelos Teóricos , Análise de Sistemas , Humanos
11.
J Environ Manage ; 270: 110864, 2020 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-32721310

RESUMO

The innovative Agrophotovoltaics (APV) system technology combines agricultural biomass and solar power production on the same site and aims at reducing the conflict between food and power production. Unrelated to this benefit, this technology may impact the landscape negatively and could thus be subject to public opposition and/or restraining frameworks. The presented study offers a System Dynamics (SD) approach, through Causal Loop Diagrams (CLDs) models, based on the results of citizen workshops, literature research, and expert discussions on the technology. A comprehensive analysis of the driving and restraining forces for the implementation of APV-technology and expected or potential impacts reveals influential factors. Hence, this SD approach identifies bottlenecks and conflicting objectives in the technology implementation that need to be further addressed. A key finding is that successful APV-projects would require stakeholder involvement to achieve greater local acceptance. When it comes to production on agricultural land, APV-systems may drive the land use efficiency to up to 186 percent when the PV-panels serve for protection against heat stress. On the other hand, altered precipitation patterns and impacts on agricultural cultivation and, especially, the landscape caused by the technical system, may restrain the application of APV. Finally, system design factors and operator modes are amongst the criteria that may influence the local acceptance in society, farmers' motivation for APV and economic factors for the market launch of APV.


Assuntos
Agricultura , Fazendeiros , Humanos , Modelos Teóricos , Análise de Sistemas , Tecnologia
12.
13.
Lancet ; 396(10243): 25-26, 2020 07 04.
Artigo em Inglês | MEDLINE | ID: mdl-32622391
14.
Artigo em Inglês | MEDLINE | ID: mdl-32727142

RESUMO

Airborne transmission of viruses, such as the coronavirus 2 (SARS-CoV-2), in hospital systems are under debate: it has been shown that transmission of SARS-CoV-2 virus goes beyond droplet dynamics that is limited to 1 to 2 m, but it is unclear if the airborne viral load is significant enough to ensure transmission of the disease. Surgical smoke can act as a carrier for tissue particles, viruses, and bacteria. To quantify airborne transmission from a physical point of view, we consider surgical smoke produced by thermal destruction of tissue during the use of electrosurgical instruments as a marker of airborne particle diffusion-transportation. Surgical smoke plumes are also known to be dangerous for human health, especially to surgical staff who receive long-term exposure over the years. There are limited quantified metrics reported on long-term effects of surgical smoke on staff's health. The purpose of this paper is to provide a mathematical framework and experimental protocol to assess the transport and diffusion of hazardous airborne particles in every large operating room suite. Measurements from a network of air quality sensors gathered during a clinical study provide validation for the main part of the model. Overall, the model estimates staff exposure to airborne contamination from surgical smoke and biological material. To address the clinical implication over a long period of time, the systems approach is built upon previous work on multi-scale modeling of surgical flow in a large operating room suite and takes into account human behavior factors.


Assuntos
Microbiologia do Ar , Infecções por Coronavirus/transmissão , Modelos Teóricos , Salas Cirúrgicas , Pneumonia Viral/transmissão , Movimentos do Ar , Poluição do Ar , Betacoronavirus , Difusão , Humanos , Hidrodinâmica , Pandemias , Material Particulado , Fumaça/análise , Análise de Sistemas
15.
J Environ Manage ; 272: 111053, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-32669255

RESUMO

Local energy transition processes are complex socio-technical transitions requiring careful study. The use of System Dynamics (SD) in modelling and analyzing local energy transitions is especially suitable given the characteristics of SD. Our aim is to systematically categorize the different ways SD is used and useful to scrutinize local energy transitions, and to see if we can discern any common themes that can be useful to researchers looking to scrutinize local energy transitions, using SD. The study is exploratory in nature, with peer-reviewed journal and conference articles analyzed using content analysis. The six categories on which the articles are analyzed are: the sector the article studies; the transition that is studied in the article; the modelling depth in the article; the objective of the article; the justification for using SD provided in the article and the levels of interaction with 'local'. Our findings show most of the local energy transitions have been studied using simulatable Stock and Flow Diagrams in SD methodology. The important sectors in the energy field are represented in terms of SD modelling of local energy transitions, including electricity, transport, district heating etc. Most of the local energy transitions scrutinized by SD in the articles have descriptive objectives, with some prescriptive, and just one evaluative objective. In terms of justification for using SD provided by the articles analyzed in this study, we found four major themes along which the justifications that were provided. They are dynamics, feedbacks, delays and complexity, systematic thinking, bridging disciplines and actor interactions and behaviour. The 'dynamics, feedbacks, delays and complexity' theme is the most cited justification for the use of SD in scrutinizing local energy transitions, followed by systematic thinking.


Assuntos
Conservação de Recursos Energéticos , Análise de Sistemas , Calefação
16.
Nat Med ; 26(9): 1417-1421, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32665655

RESUMO

Many European countries have responded to the COVID-19 pandemic by implementing nationwide protection measures and lockdowns1. However, the epidemic could rebound when such measures are relaxed, possibly leading to a requirement for a second or more, repeated lockdowns2. Here, we present results of a stochastic agent-based microsimulation model of the COVID-19 epidemic in France. We examined the potential impact of post-lockdown measures, including physical distancing, mask-wearing and shielding individuals who are the most vulnerable to severe COVID-19 infection, on cumulative disease incidence and mortality, and on intensive care unit (ICU)-bed occupancy. While lockdown is effective in containing the viral spread, once lifted, regardless of duration, it would be unlikely to prevent a rebound. Both physical distancing and mask-wearing, although effective in slowing the epidemic and in reducing mortality, would also be ineffective in ultimately preventing ICUs from becoming overwhelmed and a subsequent second lockdown. However, these measures coupled with the shielding of vulnerable people would be associated with better outcomes, including lower mortality and maintaining an adequate ICU capacity to prevent a second lockdown. Benefits would nonetheless be markedly reduced if most people do not adhere to these measures, or if they are not maintained for a sufficiently long period.


Assuntos
Betacoronavirus/patogenicidade , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Análise de Sistemas , Betacoronavirus/genética , Infecções por Coronavirus/patologia , Infecções por Coronavirus/virologia , França/epidemiologia , Humanos , Pneumonia Viral/patologia , Pneumonia Viral/virologia , Quarentena , Processos Estocásticos
17.
Fam Process ; 59(3): 922-936, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32677711

RESUMO

The COVID-19 pandemic has a pervasive effect on all aspects of family life. We can distinguish the collective societal and community effects of the global pandemic and the risk and disease impact for individuals and families. This paper draws on Rolland's Family Systems-Illness (FSI) model to describe some of the unique challenges through a multisystemic lens. Highlighting the pattern of psychosocial issues of COVID-19 over time, discussion emphasizes the evolving interplay of larger systems public health pandemic challenges and mitigation strategies with individual and family processes. The paper addresses issues of coping with myriad Covid-19 uncertainties in the initial crisis wave and evolving phases of the pandemic in the context of individual and family development, pre-existing illness or disability, and racial and socio-economic disparities. The discussion offers recommendations for timely family oriented consultation and psychoeducation, and for healthcare clinician self-care.


Assuntos
Infecções por Coronavirus/psicologia , Relações Familiares/psicologia , Pneumonia Viral/psicologia , Quarentena/psicologia , Adaptação Psicológica , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Humanos , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Análise de Sistemas
18.
Math Biosci ; 328: 108434, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32730811

RESUMO

The pandemic of coronavirus disease 2019 (COVID-19) has caused several million confirmed cases worldwide. The necessity of keeping open and accessible public commercial establishments such as supermarkets or pharmacies increases during the pandemic provided that distancing rules and crowd control are satisfied. Herein, using agent-based models, we explore the potential spread of the novel SARS-CoV-2 considering the case of a small size supermarket. For diverse distancing rules and number of simultaneous users (customers), we question flexible and limited movement policies, guiding the flow and interactions of users in place. Results indicate that a guided, limited in movement and well-organized policy combined with a distance rule of at least 1 m and a small number of users may aid in the mitigation of potential new contagions in more than 90% compared to the usual policy of flexible movement with more users which may reach up to 64% of mitigation of potential new infections under the same distancing conditions. This study may guide novel strategies for the mitigation of the current COVID-19 pandemic, at any stage, and prevention of future outbreaks of SARS-CoV-2 or related viruses.


Assuntos
Betacoronavirus , Comércio , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , Análise de Sistemas , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Indústria Alimentícia , Abastecimento de Alimentos , Desinfecção das Mãos , Humanos , Máscaras , Conceitos Matemáticos , Modelos Biológicos , Pandemias/prevenção & controle , Farmácias , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle
19.
Nat Med ; 26(9): 1398-1404, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32647358

RESUMO

In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China1,2. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.


Assuntos
Betacoronavirus/genética , Infecções por Coronavirus/genética , Genoma Viral/genética , Pandemias , Pneumonia Viral/genética , Betacoronavirus/patogenicidade , Infecções por Coronavirus/transmissão , Infecções por Coronavirus/virologia , Humanos , Pneumonia Viral/transmissão , Pneumonia Viral/virologia , Análise de Sistemas , Sequenciamento Completo do Genoma
20.
Comput Biol Med ; 121: 103827, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32568667

RESUMO

The rapid spread of the coronavirus disease (COVID-19) has become a global threat affecting almost all countries in the world. As countries reach the infection peak, it is planned to return to a new normal under different coexistence conditions in order to reduce the economic effects produced by the total or partial closure of companies, universities, shops, etc. Under such circumstances, the use of mathematical models to evaluate the transmission risk of COVID-19 in various facilities represents an important tool in assisting authorities to make informed decisions. On the other hand, agent-based modeling is a relatively new approach to model complex systems composed of agents whose behavior is described using simple rules. Different from classical mathematical models (which consider a homogenous population), agent-based approaches model individuals with distinct characteristics and provide more realistic results. In this paper, an agent-based model to evaluate the COVID-19 transmission risks in facilities is presented. The proposed scheme has been designed to simulate the spatiotemporal transmission process. In the model, simulated agents make decisions depending on the programmed rules. Such rules correspond to spatial patterns and infection conditions under which agents interact to characterize the transmission process. The model also includes an individual profile for each agent, which defines its main social characteristics and health conditions used during its interactions. In general, this profile partially determines the behavior of the agent during its interactions with other individuals. Several hypothetical scenarios have been considered to show the performance of the proposed model. Experimental results have demonstrated that the simulations provide useful information to produce strategies for reducing the transmission risks of COVID-19 within the facilities.


Assuntos
Betacoronavirus , Infecções por Coronavirus/transmissão , Pneumonia Viral/transmissão , Análise de Sistemas , Biologia Computacional , Simulação por Computador , Infecções por Coronavirus/epidemiologia , Suscetibilidade a Doenças/epidemiologia , Comportamentos Relacionados com a Saúde , Instalações de Saúde , Humanos , Modelos Biológicos , Pandemias/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Dinâmica Populacional/estatística & dados numéricos
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