scholarly journals EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

2021 ◽  
Vol 71 ◽  
pp. 479-519
Author(s):  
Cédric Colas ◽  
Boris Hejblum ◽  
Sebastien Rouillon ◽  
Rodolphe Thiébaut ◽  
Pierre-Yves Oudeyer ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Optimization Problems ◽  
Control Strategies ◽  
Decision Makers ◽  
Epidemiological Models ◽  
Long Term Effects ◽  
Nsga Ii ◽  
Health Decision ◽  
Standard Interface

Modeling the dynamics of epidemics helps to propose control strategies based on pharmaceuticaland non-pharmaceutical interventions (contact limitation, lockdown, vaccination,etc). Hand-designing such strategies is not trivial because of the number of possibleinterventions and the difficulty to predict long-term effects. This task can be cast as an optimization problem where state-of-the-art machine learning methods such as deep reinforcement learning might bring significant value. However, the specificity of each domain|epidemic modeling or solving optimization problems|requires strong collaborationsbetween researchers from different fields of expertise. This is why we introduce EpidemiOptim, a Python toolbox that facilitates collaborations between researchers inepidemiology and optimization. EpidemiOptim turns epidemiological models and cost functions into optimization problems via a standard interface commonly used by optimization practitioners (OpenAI Gym). Reinforcement learning algorithms based on QLearning with deep neural networks (DQN) and evolutionary algorithms (NSGA-II) are already implemented. We illustrate the use of EpidemiOptim to find optimal policies fordynamical on-o  lockdown control under the optimization of the death toll and economic recess using a Susceptible-Exposed-Infectious-Removed (SEIR) model for COVID-19. Using EpidemiOptim and its interactive visualization platform in Jupyter notebooks, epidemiologists, optimization practitioners and others (e.g. economists) can easily compare epidemiological models, costs functions and optimization algorithms to address important choicesto be made by health decision-makers. Trained models can be explored by experts and non-experts via a web interface. This article is part of the special track on AI and COVID-19.

scholarly journals MEG signatures of long-term effects of agreement and disagreement with the majority

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Gorin ◽  
V. Klucharev ◽  
A. Ossadtchi ◽  
I. Zubarev ◽  
V. Moiseeva ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Social Influence ◽  
Temporal Dynamics ◽  
Peer Group ◽  
Long Term Effects ◽  
Learning Mechanisms ◽  
Source Imaging ◽  
The Face ◽  
First Session

AbstractPeople often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

scholarly journals Elite Exploitation: A Combination of Mathematical Concept and EMO Approach for Multi-Objective Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 136
Author(s):  
Wenxiao Li ◽  
Yushui Geng ◽  
Jing Zhao ◽  
Kang Zhang ◽  
Jianxin Liu
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Hybrid Genetic Algorithm ◽  
Decision Makers ◽  
Superior Performance ◽  
Test Problems ◽  
Mathematical Function ◽  
Hyperbolic Tangent ◽  
Nsga Ii ◽  
Multi Objective

This paper explores the combination of a classic mathematical function named “hyperbolic tangent” with a metaheuristic algorithm, and proposes a novel hybrid genetic algorithm called NSGA-II-BnF for multi-objective decision making. Recently, many metaheuristic evolutionary algorithms have been proposed for tackling multi-objective optimization problems (MOPs). These algorithms demonstrate excellent capabilities and offer available solutions to decision makers. However, their convergence performance may be challenged by some MOPs with elaborate Pareto fronts such as CFs, WFGs, and UFs, primarily due to the neglect of diversity. We solve this problem by proposing an algorithm with elite exploitation strategy, which contains two parts: first, we design a biased elite allocation strategy, which allocates computation resources appropriately to elites of the population by crowding distance-based roulette. Second, we propose a self-guided fast individual exploitation approach, which guides elites to generate neighbors by a symmetry exploitation operator, which is based on mathematical hyperbolic tangent function. Furthermore, we designed a mechanism to emphasize the algorithm’s applicability, which allows decision makers to adjust the exploitation intensity with their preferences. We compare our proposed NSGA-II-BnF with four other improved versions of NSGA-II (NSGA-IIconflict, rNSGA-II, RPDNSGA-II, and NSGA-II-SDR) and four competitive and widely-used algorithms (MOEA/D-DE, dMOPSO, SPEA-II, and SMPSO) on 36 test problems (DTLZ1–DTLZ7, WGF1–WFG9, UF1–UF10, and CF1–CF10), and measured using two widely used indicators—inverted generational distance (IGD) and hypervolume (HV). Experiment results demonstrate that NSGA-II-BnF exhibits superior performance to most of the algorithms on all test problems.

scholarly journals Effectiveness of COVID-19 Vaccines against Delta (B.1.617.2) Variant: A Systematic Review and Meta-Analysis of Clinical Studies

Vaccines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 23
Author(s):  
Ali Pormohammad ◽  
Mohammad Zarei ◽  
Saied Ghorbani ◽  
Mehdi Mohammadi ◽  
Saeideh Aghayari Sheikh Neshin ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Severe Infection ◽  
Vaccination Rate ◽  
Decision Makers ◽  
Morbidity Rate ◽  
Short Term ◽  
Mortality And Morbidity ◽  
Public Health Decision ◽  
Health Decision

The high transmissibility, mortality, and morbidity rate of the SARS-CoV-2 Delta (B.1.617.2) variant have raised concerns regarding vaccine effectiveness (VE). To address this issue, all publications relevant to the effectiveness of vaccines against the Delta variant were searched in the Web of Science, Scopus, EMBASE, and Medline (via PubMed) databases up to 15 October 2021. A total of 15 studies (36 datasets) were included in the meta-analysis. After the first dose, the VE against the Delta variant for each vaccine was 0.567 (95% CI 0.520–0.613) for Pfizer-BioNTech, 0.72 (95% CI 0.589–0.822) for Moderna, 0.44 (95% CI 0.301–0.588) for AstraZeneca, and 0.138 (95% CI 0.076–0.237) for CoronaVac. Meta-analysis of 2,375,957 vaccinated cases showed that the Pfizer-BioNTech vaccine had the highest VE against the infection after the second dose, at 0.837 (95% CI 0.672–0.928), and third dose, at 0.972 (95% CI 0.96–0.978), as well as the highest VE for the prevention of severe infection or death, at 0.985 (95% CI 0.95–0.99), amongst all COVID-19 vaccines. The short-term effectiveness of vaccines, especially mRNA-based vaccines, for the prevention of the Delta variant infection, hospitalization, severe infection, and death is supported by this study. Limitations include a lack of long-term efficacy data, and under-reporting of COVID-19 infection cases in observational studies, which has the potential to falsely skew VE rates. Overall, this study supports the decisions by public health decision makers to promote the population vaccination rate to control the Delta variant infection and the emergence of further variants.

scholarly journals Sharing hospital-based health technology assessments internationally

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
M Marchetti ◽  
S Daugbjerg
Keyword(s):  
New Technologies ◽  
Health Technology ◽  
Healthcare Systems ◽  
Decision Makers ◽  
Fiscal Sustainability ◽  
Specific Information ◽  
Long Term Effects ◽  
Short And Long Term ◽  
Sustainability Challenges

Abstract Issue/problem National healthcare systems worldwide are at a critical point due to the fiscal sustainability challenges faced. At the same time, healthcare systems are under pressure to meet the global demand for adaptation of medical innovations arriving into the market persistently. Description of the problem Hospitals often serve as the entry point for new technologies to the healthcare system. It is therefore extremely important that Health Technology Assessments (HTA) are available in timely order to accurately inform decision-makers on both short- and long-term effects of a health technology to avoid inappropriate investments. Hospital based HTA (HB-HTA) was developed to accommodate the need for evidence-based hospital-specific information in a timely manner. A substantial increase in the use of HB-HTA has been observed in the last years. However, only few reports are being published. A database for the structured collection of HB-HTA reports could help the dissemination and collaboration between hospitals. Effects/changes A survey answered by an international group of experts knowledgeable in HB-HTA from eighteen different countries has showed that there is an interest to realize the collection and dissemination of HB-HTA reports on an international scale. However, confidentiality and resources for a database are barriers for the dissemination of HB-HTA reports. The challenge will therefore be to overcome these barriers and design a database containing high quality, comparable and complete HB-HTA reports with proper data security, regular maintenance and user support. Lessons International collaboration in HB-HTA is the key to timely inform decision-makers without compromising the quality of the data or the methodology.

scholarly journals Um estudo bibliométrico sobre a pesquisa operacional aplicada à sustentabilidade ## A bibliometric study on operational research applied to sustainability

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Victor Hugo Souza De Abreu ◽  
Marina Leite de Barros Baltar ◽  
Andrea Souza Santos
Keyword(s):  
Public Health ◽  
Literature Review ◽  
Operational Research ◽  
Web Of Science ◽  
Human Action ◽  
Decision Makers ◽  
Bibliometric Study ◽  
Long Term Effects ◽  
Bibliometric Approach

ResumoA sustentabilidade está sendo cada vez mais vista como uma possível solução para os problemas decorrentes, principalmente, da ação humana no meio ambiente. Entretanto, para que seus efeitos sejam observados à longo prazo faz-se necessário que sejam utilizadas abordagens como a Pesquisa Operacional (PO) que busca solucionar, ou pelo menos minimizar, problemas reais e complexos, fornecendo apoio aos tomadores de decisão. Nesse sentido, este estudo busca realizar uma revisão da literatura com abordagem bibliométrica que tem como objetivo identificar estudos que utilizam a PO aplicada à sustentabilidade. Para obter e compilar as informações, foram utilizados os bancos de dados do Web of Science™, que apresenta alcance e cobertura satisfatórios. Os resultados mostram, por exemplo, que o assunto, embora antigo, continua em expansão, sendo publicados estudos em periódicos com elevada relevância científica. Além disso, nota-se que a utilização da PO é uma importante estratégia de suporte aos tomadores de decisão brasileiros de diversas áreas do conhecimento tais como saúde pública, gerenciamento urbano e rural e engenharia para promoção da sustentabilidade. AbstractSustainability is increasingly being seen as a possible solution to problems arising mainly from human action on the environment. However, for its long-term effects to be observed, it is necessary to use approaches such as Operational Research (OR) which seeks to solve, or at least minimize, real and complex problems, providing support to decision makers. Thus, this study conducts a literature review with a bibliometric approach that aims to identify studies that use the OR applied to sustainability. To obtain and compile the data, we used Web of Science ™ databases, which have satisfactory range and coverage. The results show, for example, that the despite being an old subject, it is still expanding, with studies published in journals with high scientific relevance. In addition, it is noted that the use of OR is an important strategy to support Brazilian decision makers from various areas of knowledge such as public health, urban and rural management, and engineering to promote sustainability.

scholarly journals A scenario modeling pipeline for COVID-19 emergency planning

2020 ◽  
Author(s):  
Joseph C. Lemaitre ◽  
Kyra H. Grantz ◽  
Joshua Kaminsky ◽  
Hannah R. Meredith ◽  
Shaun A. Truelove ◽  
...  
Keyword(s):  
Present Model ◽  
Federal Agencies ◽  
Decision Makers ◽  
Health Departments ◽  
Epidemiological Models ◽  
Public Health Decision ◽  
Scenario Modeling ◽  
Health Decision ◽  
Multiple Intervention ◽  
Pharmaceutical Interventions

AbstractCoronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.

The Limnological Units of the Lower Great Lakes - St. Lawrence River Corridor and Their Role in the Source and Aquatic Fate of Toxic Contaminants

1986 ◽  
Vol 21 (2) ◽  
pp. 168-186 ◽  
Author(s):  
R.J. Allan
Keyword(s):  
Great Lakes ◽  
Residence Time ◽  
Control Strategies ◽  
Salt Water ◽  
Transport Systems ◽  
Long Term Effects ◽  
Lawrence Estuary ◽  
St Lawrence Estuary ◽  
St Lawrence River

Abstract The waterways of the lower Great Lakes and St. Lawrence River, between Sarnia and the Saguenay Fiord, are made up of four limnological units. The first comprises the high discharge, rapid flow rivers, namely the St. Clair, Detroit, Niagara and St. Lawrence. Second are the four shallow, short residence time, riverine lakes, namely St. Clair, St. Francois, St. Louis and St. Pierre. Third are the two, relatively deep, long residence time, lower Great Lakes Erie and Ontario. Lastly, there is the freshwater-salt water mixing zone of the upper St. Lawrence Estuary. The rivers are essentially sources and transport systems of toxic contaminants on a grand scale. The riverine lakes provide only temporary storage or sinks even for contaminants associated with sediments because these are eventually resuspended and moved on downstream. The major sinks, where long-term effects are most evident are the two lower Great Lakes and the St. Lawrence Estuary. These sites are also where sediment associated contaminants can be permanently removed by deep burial in bottom sediments. However, even here, a proportion of the contaminant load passes on downstream and eventually out to the Gulf of St. Lawrence. The distinctive characteristics of the four limnological units are discussed in relation to sources and fate of toxic contaminants. Understanding the role of the units is critical to development of toxic chemicals control strategies and reduction in aquatic ecosystem contamination.

Tackling Drug-Lords in a Nascent Market: Raids and Drug Crime in Uruguay

2021 ◽  
pp. 088740342110469
Author(s):  
Juan A. Bogliaccini ◽  
Diego Pereira ◽  
Juan Ignacio Pereira ◽  
Cecilia Giambruno ◽  
Ignacio Borba
Keyword(s):  
Control Strategies ◽  
Geographical Area ◽  
Interrupted Time Series ◽  
Drug Market ◽  
Long Term Effects ◽  
Drug Crime ◽  
Intervention Models ◽  
Different Types ◽  
Short And Long Term

This article analyzes the effects of police raids for different types of crime in the most conflictive neighborhoods of Montevideo, Uruguay. Interrupted time-series and intervention models are estimated using different specifications of geographical area where the crackdowns occurred and also different control strategies to produce robust results. The effect of crackdowns on crime reporting is mixed; evidence suggesting crackdowns may produce short- and long-term effects on crime depending on their ability to affect gangs’ competition for the territory and the market. It appears that the effects of raids are sensitive to the context of the criminal situation. Crackdowns are not consistently effective in influencing crime. Evidence shows it is hard to reach levels of critical enforcement through 1-day crackdowns and that crackdowns’ ability to alter drug-market conditions would depend not only on the ability to extract drug dealers from the territory but also in preventing a rapid return.

scholarly journals Trusting and learning from others: immediate and long-term effects of learning from observation and advice

2021 ◽  
Author(s):  
Uri Hertz ◽  
Vaughan Bell ◽  
Nichola Raihani
Keyword(s):  
Reinforcement Learning ◽  
Social Information ◽  
Computational Modelling ◽  
Trial And Error ◽  
Long Term Effects ◽  
Short Term ◽  
Privileged Status ◽  
Error Learning ◽  
Learning From Others

Social learning underpins our species’ extraordinary success. Learning through observation has been investigated in several species but learning from advice – where information is intentionally broadcast – is less understood. We used a pre-registered, online experiment (N=1492) combined with computational modelling to examine learning through observation and advice. Participants were more likely to immediately follow advice than to copy an observed choice but this was dependent upon trust in the adviser: highly paranoid participants were less likely to follow advice in the short-term. Reinforcement learning modelling revealed two distinct patterns regarding the long-term effects of social information: some individuals relied fully on social information whereas others reverted to trial-and-error learning. This variation may affect prevalence and fidelity of socially-transmitted information. Our results highlight the privileged status of advice relative to observation and how assimilation of intentionally-broadcasted information is affected by trust in others.

scholarly journals Trusting and learning from others: immediate and long-term effects of learning from observation and advice

2021 ◽  
Vol 288 (1961) ◽  
Author(s):  
Uri Hertz ◽  
Vaughan Bell ◽  
Nichola Raihani
Keyword(s):  
Reinforcement Learning ◽  
Social Information ◽  
Computational Modelling ◽  
Trial And Error ◽  
Long Term Effects ◽  
Short Term ◽  
Privileged Status ◽  
Error Learning ◽  
Learning From Others

Social learning underpins our species's extraordinary success. Learning through observation has been investigated in several species, but learning from advice—where information is intentionally broadcast—is less understood. We used a pre-registered, online experiment ( n = 1492) combined with computational modelling to examine learning through observation and advice. Participants were more likely to immediately follow advice than to copy an observed choice, but this was dependent upon trust in the adviser: highly paranoid participants were less likely to follow advice in the short term. Reinforcement learning modelling revealed two distinct patterns regarding the long-term effects of social information: some individuals relied fully on social information, whereas others reverted to trial-and-error learning. This variation may affect the prevalence and fidelity of socially transmitted information. Our results highlight the privileged status of advice relative to observation and how the assimilation of intentionally broadcast information is affected by trust in others.

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