Cost-utility analysis of opportunistic and systematic diabetic retinopathy screening strategies from the perspective of the Brazilian Public Healthcare System

Objective: To perform a cost-utility analysis of diabetic retinopathy (DR) screening strategies from the perspective of the Brazilian Public Healthcare System. Methods: A model-based economic evaluation was performed to estimate the incremental costs per quality-adjusted life-year (QALY) gained between three DR screening strategies: (1) the opportunistic ophthalmology referral-based (usual practice), (2) the systematic ophthalmology referral-based, and (3) the systematic teleophthalmology-based. The target population included individuals with type 2 diabetes (T2D) aged 40 years, without retinopathy, followed over a 40-year time horizon. A Markov model was developed with five health states and a 1-year cycle. Model parameters were based on literature and country databases. One-way and probabilistic sensitivity analyses were performed to assess model parameters’ uncertainty. WHO willingness-to-pay (WHO-WTP) thresholds were used as reference (i.e. one and three times the Brazilian per capita Gross Domestic Product of R$32747 in 2018). Results: Compared to usual practice, the systematic teleophthalmology-based screening was associated with an incremental cost of R$21445/QALY gained ($9792/QALY gained). The systematic ophthalmology referral-based screening was more expensive (incremental costs = R$4) and less effective (incremental QALY = −0.012) compared to the systematic teleophthalmology-based screening. The probability of systematic teleophthalmology-based screening being cost-effective compared to usual practice was 0.46 and 0.67 at the minimum and the maximum WHO-WTP thresholds, respectively. Conclusion: Systematic teleophthalmology-based DR screening for the Brazilian population with T2D would be considered very cost effective compared to the opportunistic ophthalmology referral-based screening according to the WHO-WTP threshold. However, there is still a considerable amount of uncertainty around the results

The psychological science accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data