Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making.
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ABSTRACT:
SUBMITTER: Nichols JD
PROVIDER: S-EPMC8241114 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSeveral theories in autism posit that common aspects of the autism phenotype may be manifestations of an underlying differentiation in predictive abilities. The present study investigates this hypothesis in the context of strategic decision making in autistic participants compared to a control group.MethodAutistic individuals (43 adults, 35 male) and a comparison group (42 adults, 35 male) of age and gender matched individuals, played a modified version of the prisoner's dilemma (PD) task where they were asked, if capable, to predict their opponents' move. The predictive performance of the two groups was assessed.ResultsOverall, participants in the autism group had a significantly lower number of correct predictions. Moreover, autistic participants stated, significantly more frequently than the comparison group, that they were unable to make a prediction. When attempting a prediction however, the success ratio did not differ between the two groups.ConclusionsThese findings indicate that there is a difference in prediction performance between the two groups. Although our task design does not allow us to identify whether this difference is due to difficulty to form a prediction or a reluctance in registering one, these findings could justify a role for prediction in strategic decision making during the PD task.
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Project description:When making decisions in groups, the outcome of one's decision often depends on the decisions of others, and there is a tradeoff between short-term incentives for an individual and long-term incentives for the groups. Yet, little is known about the neurocomputational mechanisms at play when weighing different utilities during repeated social interactions. Here, using model-based fMRI and Public-good-games, we find that the ventromedial prefrontal cortex encodes immediate expected rewards as individual utility while the lateral frontopolar cortex encodes group utility (i.e., pending rewards of alternative strategies beneficial for the group). When it is required to change one's strategy, these brain regions exhibited changes in functional interactions with brain regions engaged in switching strategies. Moreover, the anterior cingulate cortex and the temporoparietal junction updated beliefs about the decision of others during interactions. Together, our findings provide a neurocomputational account of how the brain dynamically computes effective strategies to make adaptive collective decisions.
| S-EPMC6872737 | biostudies-literature
Project description:Pronouns are extraordinarily common in daily language yet little is known about the neural mechanisms that support decisions about pronoun reference. We propose a large-scale neural network for resolving pronoun reference that consists of two components. First, a core language network in peri-Sylvian cortex supports syntactic and semantic resources for interpreting pronoun meaning in sentences. Second, a frontal-parietal network that supports strategic decision-making is recruited to support probabilistic and risk-related components of resolving a pronoun's referent. In an fMRI study of healthy young adults, we observed activation of left inferior frontal and superior temporal cortex, consistent with a language network. We also observed activation of brain regions not associated with traditional language areas. By manipulating the context of the pronoun, we were able to demonstrate recruitment of dorsolateral prefrontal cortex during probabilistic evaluation of a pronoun's reference, and orbital frontal activation when a pronoun must adopt a risky referent. Together, these findings are consistent with a two-component model for resolving a pronoun's reference that includes neuroanatomic regions supporting core linguistic and decision-making mechanisms.
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Project description:Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers. Highlights Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19. Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies. Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.
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Project description:Pollinator declines have prompted efforts to assess how land-use change affects insect pollinators and pollination services in agricultural landscapes. Yet many tools to measure insect pollination services require substantial landscape-scale data and technical expertise. In expert workshops, 3 straightforward methods (desk-based method, field survey, and empirical manipulation with exclusion experiments) for rapid insect pollination assessment at site scale were developed to provide an adaptable framework that is accessible to nonspecialist with limited resources. These methods were designed for TESSA (Toolkit for Ecosystem Service Site-Based Assessment) and allow comparative assessment of pollination services at a site of conservation interest and in its most plausible alternative state (e.g., converted to agricultural land). We applied the methods at a nature reserve in the United Kingdom to estimate the value of insect pollination services provided by the reserve. The economic value of pollination services provided by the reserve ranged from US$6163 to US$11,546/year. The conversion of the reserve to arable land would provide no insect pollination services and a net annual benefit from insect-pollinated crop production of approximately $1542/year (US$24∙ha-1 ∙year-1 ). The methods had wide applicability and were readily adapted to different insect-pollinated crops: rape (Brassica napus) and beans (Vicia faba) crops. All methods were rapidly employed under a low budget. The relatively less robust methods that required fewer resources yielded higher estimates of annual insect pollination benefit.
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Project description:Workplace programmes to test staff for asymptomatic COVID-19 infection have become common, but raise a number of ethical challenges. In this article, we report the findings of a consultation that informed the development of an ethical framework for organisational decision-making about such programmes. We conducted a mixed-method consultation - a survey and semi-structured interviews during November-December 2020 in a UK case study organisation that had introduced asymptomatic testing for all staff working on-site in its buildings. Analysis of closed-ended survey data was conducted descriptively. An analysis approach based on the Framework Method was used for the open-ended survey responses and interview data. The analyses were then integrated to facilitate systematic analysis across themes. Inferences were based on the integrated findings and combined with other inputs (literature review, ethical analysis, legal and public health guidance, expert discussions) to develop an ethical framework. The consultation involved 61 staff members from the case study organisation (50 survey respondents and 11 interview participants). There was strong support for the asymptomatic testing programme: 90% of the survey respondents viewed it as helpful or very helpful. Open-ended survey responses and interviews gave insight into participants' concerns, including those relating to goal drift, risk of false negatives, and potential negative impacts for household members and people whose roles lacked contractual and financial stability. Integration of the consultation findings and the other inputs identified the importance of a whole-system approach with appropriate support for the key control measure of isolation following positive tests. The need to build trust in the testing programme, for example through effective communication from leaders, was also emphasised. The consultation, together with other inputs, informed an ethical framework intended to support employers. The framework may support organisational decision-making in areas ranging from design and operation of the programme through to choices about participation. The framework is likely to benefit from further consultation and refinement in new settings.
| S-EPMC9476340 | biostudies-literature
Project description:Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.
| S-EPMC3213208 | biostudies-literature
Project description:Visitors can play an important role in the spread of infections. Here, we incorporate an epidemic model into a game theoretical framework to investigate the effects of travel strategies on infection control. Potential visitors must decide whether to travel to a destination that is at risk of infectious disease outbreaks. We compare the individually optimal (Nash equilibrium) strategy to the group optimal strategy that maximizes the overall population utility. Economic epidemiological models often find that individual and group optimal strategies are very different. By contrast, we find perfect agreement between individual and group optimal strategies across a wide parameter regime. For more limited regimes where disagreement does occur, the disagreement is (i) generally very extreme; (ii) highly sensitive to small changes in infection transmissibility and visitor costs/benefits; and (iii) can manifest either in a higher travel volume for individual optimal than group optimal strategies, or vice versa. The simulations show qualitative agreement with the 2003 severe acute respiratory syndrome (SARS) outbreak in Beijing, China. We conclude that a conflict between individual and group optimal visitor travel strategies during outbreaks may not generally be a problem, although extreme differences could emerge suddenly under certain changes in economic and epidemiological conditions.
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Project description:Deciding the best action in social settings requires decision-makers to consider their and others' preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior across individuals in strategic situations. While prosocial, moral, and emotional factors have been intensively investigated to explain this diversity, neuro-cognitive determinants of strategic decision-making and their relation with intelligence remain mostly unknown. This study presents a new model of the process of strategic decision-making in repeated interactions, first providing a precise measure of the environment's complexity, and then analyzing how this complexity affects subjects' performance and neural response. The results confirm the theoretical predictions of the model. The frequency of deviations from optimal behavior is explained by a combination of higher complexity of the strategic environment and cognitive skills of the individuals. Brain response correlates with strategic complexity, but only in the subgroups with higher cognitive skills. Furthermore, neural effects were only observed in a fronto-parietal network typically involved in single-agent tasks (the Multiple Demand Network), thus suggesting that neural processes dealing with cognitively demanding individual tasks also have a central role in interactive decision-making. Our findings contribute to understanding how cognitive factors shape strategic decision-making and may provide the neural pathway of the reported association between strategic sophistication and fluid intelligence.
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Project description:In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021.
| S-EPMC7833949 | biostudies-literature