Spatial transferability of an agent-based model to simulate Taenia solium control interventions.

BACKGROUND: Models can be used to study and predict the impact of interventions aimed at controlling the spread of infectious agents, such as Taenia solium, a zoonotic parasite whose larval stage causes epilepsy and economic loss in many rural areas of the developing nations. To enhance the credibility of model estimates, calibration against observed data is necessary. However, this process may lead to a paradoxical dependence of model parameters on location-specific data, thus limiting the model's geographic transferability. METHODS: In this study, we adopted a non-local model calibration approach to assess whether it can improve the spatial transferability of CystiAgent, our agent-based model of local-scale T. solium transmission. The calibration dataset for CystiAgent consisted of cross-sectional data on human taeniasis, pig cysticercosis and pig serology collected in eight villages in Northwest Peru. After calibration, the model was transferred to a second group of 21 destination villages in the same area without recalibrating its parameters. Model outputs were compared to pig serology data collected over a period of 2 years in the destination villages during a trial of T. solium control interventions, based on mass and spatially targeted human and pig treatments. RESULTS: Considering the uncertainties associated with empirical data, the model produced simulated pre-intervention pig seroprevalences that were successfully validated against data collected in 81% of destination villages. Furthermore, the model outputs were able to reproduce validated pig seroincidence values in 76% of destination villages when compared to the data obtained after the interventions. The results demonstrate that the CystiAgent model, when calibrated using a non-local approach, can be successfully transferred without requiring additional calibration. CONCLUSIONS: This feature allows the model to simulate both baseline pre-intervention transmission conditions and the outcomes of control interventions across villages that form geographically homogeneous regions, providing a basis for developing large-scale models representing T. solium transmission at a regional level.

Quantifying the Effects of Social Distancing on the Spread of COVID-19.

This paper studies the interplay between social distancing and the spread of the COVID-19 disease-a global pandemic that has affected most of the world's population. Our goals are to (1) to observe the correlation between the strictness of social distancing policies and the spread of disease and (2) to determine the optimal adoption level of social distancing policies. The earliest instances of the virus were found in China, and the virus has reached the United States with devastating consequences. Other countries severely affected by the pandemic are Brazil, Russia, the United Kingdom, Spain, India, Italy, and France. Although it is impossible to stop it, it is possible to slow down its spread to reduce its impact on the society and economy. Governments around the world have deployed various policies to reduce the virus spread in response to the pandemic. To assess the effectiveness of these policies, the system's dynamics of the society needs to be analyzed, which is generally not possible with mathematical linear equations or Monte Carlo methods because human society is a complex adaptive system with continuous feedback loops. Because of the challenges with the other methods, we chose agent-based methods to conduct our study. Moreover, recent agent-based modeling studies for the COVID-19 pandemic show significant promise in assisting decision-makers in managing the crisis by applying policies such as social distancing, disease testing, contact tracing, home isolation, emergency hospitalization, and travel prevention to reduce infection rates. Based on modeling studies conducted in Imperial College, increasing levels of interventions could slow the spread of disease and infection. We ran the model with six different percentages of social distancing while keeping the other parameters constant. The results show that social distancing affects the spread of COVID-19 significantly, in turn decreasing the spread of disease and infection rates when implemented at higher levels. We also validated these results by using the behavior space tool with ten experiments with varying social distancing levels. We conclude that applying and increasing social distancing policy levels leads to a significant reduction in infection spread and the number of deaths. Both experiments show that infection rates are reduced drastically when social distancing intervention is implemented between 80% to 100%.

Application of the theory of planned behavior with agent-based modeling for sustainable management of vegetative filter strips.

This study proposes an innovative socio-hydrological modeling framework for the development of environmental policies that are tailored to farmers' attitudes and economic interests but also optimize environmental criteria. From a farmers' on-site survey, a behavior model is developed based on a modified Theory of Planned Behavior (TPB). The dynamics of the social and environmental system is implemented by coupling an agent-based model (ABM) with an agro-hydrological model for vegetative filter strips (VFS). A case study is conducted with farmers from the Larqui river basin, Chile to understand their standpoint on VFS to reduce soil loss in their agricultural fields and protect water bodies. Partial least square structural equation modeling is used to analyze the survey on farmers' aspiration and attitudes. It showed that the constructs added to TPB (behavioral morality, behavioral willingness, knowledge) had a significant effect on modeling the intention and behavior of farmers to have VFS. Based on the survey, the farmers were categorized into perceptive, proactive, bounded rational and interactive agents. An ABM was developed using the behavioral categorization, related decision rules, and utility functions of agricultural activities including the VFS implementation and management. The results of the ABM corroborate with the survey of the farmers. The survey supports the view that the decision on the width of VFS is not solely dependent on the utility generated and the reduction in soil losses but also on the behavior of farmers. This behavioral sociohydrological modeling framework is capable of supporting policy-makers in developing tailored environmental policies that might improve the acceptance of sustainable agricultural practices by farmers.

The Theory-Practice Gap in the Evaluation of Agent-Based Social Simulations.

Agent-based social simulations have historically been evaluated using two criteria: verification and validation. This article questions the adequacy of this dual evaluation scheme. It claims that the scheme does not conform to everyday practices of evaluation, and has, over time, fostered a theory-practice gap in the assessment of social simulations. This gap originates because the dual evaluation scheme, inherited from computer science and software engineering, on one hand, overemphasizes the technical and formal aspects of the implementation process and, on the other hand, misrepresents the connection between the conceptual and the computational model. The mismatch between evaluation theory and practice, it is suggested, might be overcome if practitioners of agent-based social simulation adopt a single criterion evaluation scheme in which: i) the technical/formal issues of the implementation process are tackled as a matter of debugging or instrument calibration, and ii) the epistemological issues surrounding the connection between conceptual and computational models are addressed as a matter of validation.

Modeling the spread of COVID-19 on construction workers: An agent-based approach.

As the spread of COVID-19 has continued since December 2019, stay at home orders around the globe have changed how we live our lives, mostly from physical to virtual interactions, such as going to college and doing our jobs; however, some activities are basically impossible to perform virtually, such as construction activities. Thus, the construction sector has been highly disrupted by the current pandemic. The construction sector represents a key component of countries' economies-it is approximately 13% of global GDP-as such, having the availability to perform construction activities with a minimum spread of COVID-19 may help to the financial response to the pandemic. Given this context, this study aims to understand the potential impact of COVID-19 on construction workers using an agent-based modeling approach. Activities are classified as being of low-medium-high risk for workers, and the spread of COVID-19 is simulated among construction workers in a project. This study found that the workforce from a construction project may be reduced by 30% to 90% due to the spread of COVID-19. Understanding how COVID-19 may spread among construction workers may assist construction project managers in creating adequate conditions for workers to perform their job, minimizing the chances of getting infected with COVID-19.

An agent-based model of the fission yeast cell cycle.

The objective of this paper is to develop a computational model of the fission yeast (Schizosaccharomyces pombe) cell cycle using agent-based modeling (ABM), to study the sequence of states of the proteins and time of the cell cycle phases, under the action of proteins that regulate its cell cycle. The model relies only on the conceptual model of the yeast cell cycle regulatory network, where each protein has been represented as an agent with a property called activity that represents its biological function and a stochastic Brownian movement. The results indicate that the simulated phase time did have similar results in comparison with other models using mathematical approaches. Similarly, the correct sequence of states was achieved, and the model was run under different initial states to understand its emergent behaviors. The cell reached the G1 stationary state 94% of the times when running the model under biological initial conditions and 87% of the times when running the model through all the different combinations of initial states. Such results imply that the cell was capable to fix toward the biological expected phenomena. These results show that ABM is a suitable technique to study protein-protein interactions without using, often unavailable, kinetic parameters, or differential equations. This model sets as a base for further studies that involve the cell cycle of the fission yeast, with a special attention to studies and development of drug treatments for specific types of cancer.

Cost-effectiveness of a potential Zika vaccine candidate: a case study for Colombia.

BACKGROUND: A number of Zika vaccine platforms are currently being investigated, some of which have entered clinical trials. We sought to evaluate the cost-effectiveness of a potential Zika vaccine candidate under the WHO Vaccine Target Product Profile for outbreak response, prioritizing women of reproductive age to prevent microcephaly and other neurological disorders. METHODS: Using an agent-based simulation model of ZIKV transmission dynamics in a Colombian population setting, we conducted cost-effectiveness analysis with and without pre-existing herd immunity. The model was parameterized with estimates associated with ZIKV infection, risks of microcephaly in different trimesters, direct medical costs, and vaccination costs. We assumed that a single dose of vaccine provides a protection efficacy in the range 60% to 90% against infection. Cost-effectiveness analysis was conducted from a government perspective. RESULTS: Under a favorable scenario when the reproduction number is relatively low (R0 = 2.2) and the relative transmissibility of asymptomatic infection is 10% compared with symptomatic infection, a vaccine is cost-saving (with negative incremental cost-effective ratio; ICER) for vaccination costs up to US$6 per individual without herd immunity, and up to US$4 per individual with 8% herd immunity. For positive ICER values, vaccination is highly cost-effective for vaccination costs up to US$10 (US$7) in the respective scenarios with the willingness-to-pay of US$6610 per disability-adjusted life-year, corresponding to the average per capita GDP of Colombia between 2013 and 2017. Our results indicate that the effect of other control measures targeted to reduce ZIKV transmission decreases the range of vaccination costs for cost-effectiveness due to reduced returns of vaccine-induced herd immunity. In all scenarios investigated, the median reduction of microcephaly exceeded 64% with vaccination. CONCLUSIONS: Our study suggests that a Zika vaccine with protection efficacy as low as 60% could significantly reduce the incidence of microcephaly. From a government perspective, Zika vaccination is highly cost-effective, and even cost-saving in Colombia if vaccination costs per individual is sufficiently low. Efficacy data from clinical trials and number of vaccine doses will be important requirements in future studies to refine our estimates, and conduct similar studies in other at-risk populations.

Reconstruction of endosomal organization and function by a combination of ODE and agent-based modeling strategies.

BACKGROUND: Reproducing cell processes using an in silico system is an essential tool for understanding the underlying mechanisms and emergent properties of this extraordinary complex biological machine. However, computational models are seldom applied in the field of intracellular trafficking. In a cell, numerous molecular interactions occur on the surface or in the interior of membrane-bound compartments that continually change position and undergo dynamic processes of fusion and fission. At present, the available simulation tools are not suitable to develop models that incorporate the dynamic evolution of the cell organelles. RESULTS: We developed a modeling platform combining Repast (Agent-Based Modeling, ABM) and COPASI (Differential Equations, ODE) that can be used to reproduce complex networks of molecular interactions. These interactions occur in dynamic cell organelles that change position and composition over the course of time. These two modeling strategies are fundamentally different and comprise of complementary capabilities. The ODEs can easily model the networks of molecular interactions, signaling cascades, and complex metabolic reactions. On the other hand, ABM software is especially suited to simulate the movement, interaction, fusion, and fission of dynamic organelles. We used the combined ABM-ODE platform to simulate the transport of soluble and membrane-associated cargoes that move along an endocytic route composed of early, sorting, recycling and late endosomes. We showed that complex processes that strongly depend on transport can be modeled. As an example, the hydrolysis of a GM2-like glycolipid was programmed by adding a trans-Golgi network compartment, lysosomal enzyme trafficking, endosomal acidification, and cholesterol processing to the simulation model. CONCLUSIONS: The model captures the highly dynamic nature of cell compartments that fuse and divide, creating different conditions for each organelle. We expect that this modeling strategy will be useful to understand the logic underlying the organization and function of the endomembrane system. REVIEWERS: This article was reviewed by Drs. Rafael Fernández-Chacón, James Faeder, and Thomas Simmen.

Modelagem baseada em agentes para a simulação da dispersão de poluentes em cursos d'água / Agent-based modeling for simulation of pollutants dispersion in water courses

RESUMO A atividade antrópica em bacias hidrográficas frequentemente gera efluentes que poluem cursos d'água e tendem a gerar problemas ambientais diversos. Uma ferramenta muito útil para auxiliar a avaliação desses problemas é a modelagem matemática. Uma classe específica de modelos matemáticos com aplicações promissoras na área de recursos hídricos e controle da poluição são os modelos baseados em agentes. Neste trabalho se demonstrou como um modelo baseado em agentes pode ser desenvolvido e utilizado para a simulação de plumas de constituintes conservativos e não conservativos em cursos d'água. Foram apresentadas as suposições feitas para a representação dos fenômenos de advecção, dispersão e decaimento de primeira ordem no modelo. Posteriormente, foi feita uma comparação entre os resultados do modelo e a solução analítica unidimensional da equação de advecção-dispersão. Os resultados das comparações apontaram boa representação dos processos pelo modelo baseado em agentes e evidenciaram a importância da definição da discretização da massa dos constituintes lançados para essa classe de modelo. As soluções desenvolvidas e apresentadas mostram-se promissoras para a aplicação de modelos baseados em agentes na simulação de impactos de despejos em cursos d'água, bem como o modelo desenvolvido consiste atualmente em uma ferramenta educacional simples para o entendimento desses fenômenos.

ABSTRACT Human activity often generates effluents that pollute waterways and tend to generate serious environmental problems. A very useful tool to help assess these issues is the mathematical modeling. A specific class of models that are very promising for water resources and pollution control are the agent-based models. This paper presents an agent-based model developed and used to simulate plumes of conservatives and non-conservatives constituents in water courses. The assumptions made for the representation of advection, dispersion and first order decay phenomena's on the development of the model are presented, and these solutions are evaluated against the analytical solution of one-dimensional advection-dispersion equation. The results of the comparisons show a good representation of the agent-based model, and show the importance of the released constituent's mass discretization definition. The solutions developed and presented are promising for the application of agent based models in the simulation of impacts of discharges into watercourses, as well as the developed model presents itself as an educational tool for simple understanding of the simulated phenomena.

Falhas de mercado e redes em políticas públicas: desafios e possibilidades ao Sistema Único de Saúde / Market and public policy network failures: challenges and possibilities for the Brazilian Unified Health System

Os princípios e as diretrizes do Sistema Único de Saúde (SUS) impõem uma estrutura de assistência baseada em redes de políticas públicas que, combinada ao modelo de financiamento adotado, conduz a falhas de mercado. Isso impõe barreiras à gestão do sistema público de saúde e à concretização dos objetivos do SUS. As características institucionais e a heterogeneidade dos atores, aliadas à existência de diferentes redes de atenção à saúde, geram complexidade analítica no estudo da dinâmica global da rede do SUS. Há limitações ao emprego de métodos quantitativos baseados em análise estática com dados retrospectivos do sistema público de saúde. Assim, propõe-se a abordagem do SUS como sistema complexo, a partir da utilização de metodologia quantitativa inovadora baseada em simulação computacional. O presente artigo buscou analisar desafios e potencialidades na utilização de modelagem com autômatos celulares combinada com modelagem baseada em agentes para simulação da evolução da rede de serviços do SUS. Tal abordagem deve permitir melhor compreensão da organização, heterogeneidade e dinâmica estrutural da rede de serviços do SUS e possibilitar minimização dos efeitos das falhas de mercado no sistema de saúde brasileiro.

The principles and guidelines of the Brazilian Unified Health System (SUS) impose a healthcare service structure based on public policy networks which, combined with the financing model adopted, leads to market failings. This imposes barriers to the management of the public health system and the enactment of SUS objectives. The institutional characteristics and the heterogeneity of players, allied to the existence of different healthcare approaches, generate analytical complexity in the study of the global dynamics of the SUS network. There are limitations in the use of quantitative methods based on static analysis of retrospective SUS data. Thus, an approach taking SUS as a complex system using innovative quantitative methodology based on computational simulation is proposed. This paper sought to analyze challenges and possibilities of the combined application of cellular automata modeling and agent-based modeling for simulation of the evolution of the SUS healthcare service network. This approach should permit better understanding of the organization, heterogeneity and structural dynamics of the SUS service network and a minimization of the effects of market failings on the Brazilian health system.