An agent-based model for the evidence-basec long term planning of power and water critical infrastructures

2017 ◽  
Author(s):  
James R. Thompson ◽  
Damon Frezza ◽  
Burhan Necioglu ◽  
Michael Cohen ◽  
Kenneth Hoffman ◽  
...  
Keyword(s):  
Critical Infrastructures ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Supporting Policy Design for the Diffusion of Cleaner Technologies: A Spatial Empirical Agent-Based Model

2020 ◽  
Vol 9 (10) ◽  
pp. 581 ◽  
Author(s):  
Caterina Caprioli ◽  
Marta Bottero ◽  
Elena De Angelis
Keyword(s):  
Policy Design ◽  
Renewable Energy Resources ◽  
Agent Based Model ◽  
Opinion Formation ◽  
Real World Data ◽  
Agent Based ◽  
Pv Systems ◽  
Definition Of

Renewable energy resources and energy-efficient technologies, as well as building retrofitting, are only some of the possible strategies that can achieve more sustainable cities and reduce greenhouse gas emissions. Subsidies and incentives are often provided by governments to increase the number of people adopting these sustainable energy efficiency actions. However, actual sales of green products are currently not as high as would be desired. The present paper applies a hybrid agent-based model (ABM) integrated with a Geographic Information System (GIS) to simulate a complex socio-economic-architectural adaptive system to study the temporal diffusion and the willingness of inhabitants to adopt photovoltaic (PV) systems. The San Salvario neighborhood in Turin (Italy) is used as an exemplary case study for testing consumer behavior associated with this technology, integrating social network theories, opinion formation dynamics and an adaptation of the theory of planned behavior (TPB). Data/characteristics for both buildings and people are explicitly spatialized with the level of detail at the block scale. Particular attention is given to the comparison of the policy mix for supporting decision-makers and policymakers in the definition of the most efficient strategies for achieving a long-term vision of sustainable development. Both variables and outcomes accuracy of the model are validated with historical real-world data.

scholarly journals Intermediate-term emotional bookkeeping is necessary for long-term reciprocal grooming partner preferences in an agent-based model of macaque groups

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1488 ◽  
Author(s):  
Ellen Evers ◽  
Han de Vries ◽  
Berry M. Spruijt ◽  
Elisabeth H.M. Sterck
Keyword(s):  
Cognitive Abilities ◽  
Social Life ◽  
Emotional Responses ◽  
Emotional Memory ◽  
Agent Based Model ◽  
Agent Based ◽  
Partner Preferences ◽  
Specific Accumulation ◽  
Group Members

Whether and how primates are able to maintain long-term affiliative relationships is still under debate. Emotional bookkeeping (EB), the partner-specific accumulation of emotional responses to earlier interactions, is a candidate mechanism that does not require high cognitive abilities. EB is difficult to study in real animals, due to the complexity of primate social life. Therefore, we developed an agent-based model based on macaque behavior, the EMO-model, that implements arousal and two emotional dimensions, anxiety-FEAR and satisfaction-LIKE, which regulate social behavior. To implement EB, model individuals assign dynamic LIKE attitudes towards their group members, integrating partner-specific emotional responses to earlier received grooming episodes. Two key parameters in the model were varied to explore their effects on long-term affiliative relationships: (1) the timeframe over which earlier affiliation is accumulated into the LIKE attitudes; and (2) the degree of partner selectivity. EB over short and long timeframes gave rise to low variation in LIKE attitudes, and grooming partner preferences were only maintained over one to two months. Only EB over intermediate-term timeframes resulted in enough variation in LIKE attitudes, which, in combination with high partner selectivity, enables individuals to differentiate between regular and incidental grooming partners. These specific settings resulted in a strong feedback between differentiated LIKE attitudes and the distribution of grooming, giving rise to strongly reciprocated partner preferences that could be maintained for longer periods, occasionally up to one or two years. Moreover, at these settings the individual’s internal, socio-emotional memory of earlier affiliative episodes (LIKE attitudes) corresponded best to observable behavior (grooming partner preferences). In sum, our model suggests that intermediate-term LIKE dynamics and high partner selectivity seem most plausible for primates relying on emotional bookkeeping to maintain their social bonds.

scholarly journals Informal risk-sharing between smallholders may be threatened by formal insurance: Lessons from a stylized agent-based model

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248757
Author(s):  
Meike Will ◽  
Jürgen Groeneveld ◽  
Karin Frank ◽  
Birgit Müller
Keyword(s):  
Side Effects ◽  
Low Income ◽  
Risk Sharing ◽  
Agent Based Model ◽  
Long Term Effects ◽  
Agent Based ◽  
Positive Effects ◽  
Negative Side Effects ◽  
Informal Risk Sharing

Microinsurance is promoted as a valuable instrument for low-income households to buffer financial losses due to health or climate-related risks. However, apart from direct positive effects, such formal insurance schemes can have unintended side effects when insured households lower their contribution to traditional informal arrangements where risk is shared through private monetary support. Using a stylized agent-based model, we assess impacts of microinsurance on the resilience of those smallholders in a social network who cannot afford this financial instrument. We explicitly include the decision behavior regarding informal transfers. We find that the introduction of formal insurance can have negative side effects even if insured households are willing to contribute to informal risk arrangements. However, when many households are simultaneously affected by a shock, e.g. by droughts or floods, formal insurance is a valuable addition to informal risk-sharing. By explicitly taking into account long-term effects of short-term transfer decisions, our study allows to complement existing empirical research. The model results underline that new insurance programs have to be developed in close alignment with established risk-coping instruments. Only then can they be effective without weakening functioning aspects of informal risk management, which could lead to increased poverty.

scholarly journals Estimating the Contribution of a Contaminated Wheelchair to Pathogen Spread With an Agent-Based Model

2020 ◽  
Vol 41 (S1) ◽  
pp. s474-s474
Author(s):  
Amanda Wilson ◽  
Curtis Donskey ◽  
Marc Verhougstraete ◽  
Kelly Reynolds
Keyword(s):  
Acute Care ◽  
Long Term Care ◽  
Specialty Care ◽  
Agent Based Model ◽  
Healthcare Associated Infection ◽  
Portable Equipment ◽  
Term Care ◽  
Agent Based ◽  
Care Services

Background: Wheelchairs can contribute to healthcare-associated infection transmission due to direct contact with patients and healthcare workers and due to wide spatial movement in facilities. Objective: We utilized location data of a wheelchair to inform an agent-based model for estimating the contribution of a single contaminated patient ride in a wheelchair to subsequent environmental contamination and to estimate the potential for wheelchair disinfection between patients to disrupt this spread. Methods: The destination and origin of wheelchairs were tracked in several facility locations: specialty care services, long-term care, radiology, acute care, common spaces, domiciliary, and outpatient clinics. An agent-based model was developed in which the probability of the wheelchair traveling directly from one location to another was informed by wheelchair origin and destination data. We assumed that the first patient’s hands were contaminated with methicillin-resistant Staphylococcus aureus (MRSA). For each patient trip, each simulated patient made contact with the wheelchair arm rests and a surface in the destination location. To evaluate potential exposures of uninfected patients, all patients riding in the wheelchair after the contaminated patient were assumed to be uncontaminated. In total, 50 patient rides were simulated. The concentration and number of contaminated surfaces in each hospital area were compared in addition to the average concentration of MRSA on patient hands over time. The intervention simulation involved a disinfection of wheelchair armrests with 90%, 70%, or 50% efficacy. Results: The 3 areas that had the largest estimated number of contaminated surfaces after 50 wheelchair trips following the first patient assumed to be infected were specialty care services, long-term care, and acute care. This finding was consistent with the paths that were most frequented by the wheelchair. Without cleaning between patients, the fiftieth patient to use the wheelchair had an average MRSA concentration of 41.5 CFU/cm2. With cleaning between patients, assuming a 50% cleaning efficacy, average MRSA concentration on the hands for the fiftieth patient was reduced to 7.4 ×10-14 CFU/cm2. Conclusions: We have demonstrated that cleaning, even with efficacies as low as 50%, may protect patients using contaminated wheelchairs from potential pathogen exposures. This study also demonstrates that tracking portable equipment can be useful not only for exposure modeling but also for predicting where the largest number of surfaces contaminated via portable equipment routes may be found. Future steps include performing a sensitivity analysis to evaluate the influence of spatial assumptions.Funding: NoneDisclosures: None

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