A probabilistic epidemiological model for infectious diseases: The case of COVID-19 at global-level

This study has developed a probabilistic epidemiological model a few weeks after the World Health Organization declared COVID-19 a pandemic (based on the little data available at that time). The aim was to assess relative risks for future scenarios and evaluate the effectiveness of different management actions for 1 year ahead. We quantified, categorized, and ranked the risks for scenarios such as business as usual, and moderate and strong mitigation. We estimated that, in the absence of interventions, COVID-19 would have a 100% risk of explosion (i.e., more than 25% infections in the world population) and 34% (2.6 billion) of the world population would have been infected until the end of simulation. We analyzed the suitability of model scenarios by comparing actual values against estimated values for the first 6 weeks of the simulation period. The results proved to be more suitable with a business-as-usual scenario in Asia and moderate mitigation in the other continents. If everything went on like this, we would have 55% risk of explosion and 22% (1.7 billion) of the world population would have been infected. Strong mitigation actions in all continents could reduce these numbers to, 7% and 3% (223 million), respectively. Although the results were based on the data available in March 2020, both the model and probabilistic approach proved to be practicable and could be a basis for risk assessment in future pandemic episodes with unknown virus, especially in the early stages, when data and literature are scarce.     

Do colored cells in risk matrices affect decision-making and risk perception? Insights from randomized controlled studies

Risk matrices communicate the likelihood and potential impact of risks and are often used to inform decision-making around risk mitigations. The merits and demerits of risk matrices in general have been discussed extensively, yet little attention has been paid to the potential influence of color in risk matrices on their users. We draw from fuzzy-trace theory and hypothesize that when color is present, individuals are likely to place greater value on reducing risks that cross color boundaries (i.e., the boundary-crossing effect), leading to sub-optimal decision making. In two randomized controlled studies, employing forced-choice and willingness-to-pay measures to investigate the boundary-crossing effect in two different color formats for risk matrices, we find preliminary evidence to support our hypotheses that color can influence decision making. The evidence also suggests that the boundary-crossing effect is only present in, or is stronger for, higher numeracy individuals. We therefore recommend that designers should consider avoiding color in risk matrices, particularly in situations where these are likely to be used by highly numerate individuals, if the communication goal is to inform in an unbiased way.     

Adolescents' Retributive and Restorative Orientations in Response to Intergroup Harms in Schools

This mixed-methods study examined how adolescents understand and evaluate different ways to address intergroup harms in schools. In individual interviews, 77 adolescents (M age = 16.49 years; 39 girls, 38 boys) in Bogotá, Colombia, responded to hypothetical vignettes wherein a rival group at school engaged in a transgression against their group. Adolescents reported that students who were harmed should and would talk to school authorities, but also noted they would likely retaliate. In terms of teacher-sanctioned responses to harm, youth endorsed compensation most strongly, followed by apologies, and rated suspension least positively. Youths' explanations for their endorsement of different disciplinary practices reflected varied concerns, including their perceptions of how justice is best achieved and how restoration could be attained.     

Evidence in Norwegian child protection interventions – Analysing cases of familial violence

How is expert evidence used in care order proceedings when children are considered for foster care placement because of familial violence? What are important factors and how do the decision-makers use and evaluate evidence from specialists and experts? In this in-depth analysis of 104 published care order decisions from the Norwegian County Boards, I investigate how decision-makers use and evaluate evidence from expert witnesses to determine whether a care order may be granted. The analysis shows that the evidence largely revolves around social functioning, care context and topics about how parents and children relate to each other. Led by the law, the decision-makers use this evidence to determine whether the child's situation is harmful, whether support services are viable and whether a care order is in the child's best interests. I find that decision-makers draw unevenly on evidence with regards to these legal requirements, and that the use predominantly defers to expert authority. However, there is also evidence of independent reasoning, where deferral to the epistemic authority of the experts is weakened. This is shown through evaluative and critical assessments and scrutiny of the disciplinary evidence.     

DO PRICES TRANSMIT RATIONALLY EXPECTED INFORMATION?

A simple model with asymmetric information, in which inventory holders or traders submit demand curves to an auctioneer, has a unique partially revealing equilibrium. We wonder whether the agents can plausibly coordinate on this equilibrium through “eductive” reasoning relying on common knowledge. The analysis stresses the role of two effects, sensitivity and amplification, whose product should be small enough. The property is obtained whenever the equilibrium excess demand is steep enough, i.e., when the search for information does not distort demand too much. Neither the influence of the number of informed agents nor that of noise trading are monotonic. Real‐time learning has strikingly different features. (JEL: D82, D84)