Volume 4 Issue 7, July 2020

The scientific community’s response to COVID-19 has resulted in a large volume of research moving through the publication pipeline at extraordinary speed, with a median time from receipt to acceptance of 6 days for journal articles. Although the nature of this emergency warrants accelerated publishing, measures are required to safeguard the integrity of scientific evidence.

Selfless motivations for charitable giving are often represented as being superior to selfish ones. But, we argue, evidence from the behavioural sciences suggests that such a ‘hierarchy of charity’ may stand in the way of what ultimately matters: generating the most impactful giving overall.

Although disease dynamics of prey are influenced by predator behaviour, little is known about the potential effects of wide-ranging post-industrial hunters. Mysterud et al. describe the movement behaviour of Norwegian hunters using more than 165,000 hunting records from 2001–2017, showing that hunters migrate to and from areas of high prey density, potentially moving pathogens into previously unaffected areas.

Stroke can lead to debilitating consequences, including loss of language. An important goal of stroke research is to use machine learning to predict outcomes and response to therapy. A new study compares different approaches to predicting post-stroke outcomes and highlights the need for systematic optimization and validation to ultimately translate scientific insights to clinical settings.

Thirty-two experts propose ten considerations for managing the de-escalation of COVID-19 containment measures while still maintaining public adherence to social and physical distancing.

Hunter movements have implications for how to control emerging wildlife diseases. In northern Europe, hunter residential densities are more closely linked to human than prey density, hunters are largely migratory, and they aggregate with increasing regional prey densities.

Jachimowicz et al. find that increased income inequality increases financial hardship particularly for individuals with low income, in part by weakening the community buffer that could otherwise offer support.

Using data from more than 370,000 individuals on the HEXACO-100 personality measure, Jose Espinoza and colleagues find that five profiles of the HEXACO-PI-R traits replicate robustly across multiple independent samples, and across age and gender.

Halai et al. report a systematic comparison of machine learning algorithms that predict the speech impairments of aphasia patients from brain scans, identifying which algorithms and types of neuroimaging data improve predictions of behavioural outcomes.

Pierson et al. compiled and analysed a dataset detailing nearly 100 million traffic stops conducted across the United States, finding evidence of persistent racial bias against black and Hispanic drivers in police stops and search decisions.

Lopez and Rodo explore post-lockdown scenarios by using a stochastic modified SEIR model, showing that lockdowns should last at least 60 days to avoid a second wave of infection. Social distancing, increasing awareness and personal protective behaviours could replace lockdowns.

The COVID-19 Government Response Event Dataset (CoronaNet v.1.0) compiles real time, publicly available (https://coronanet-project.org) data on policy announcements made in response to the COVID-19 pandemic across the world.