Society

Using machine learning, the authors reveal that stable background conditions explain most variation in armed conflict risk worldwide. Positive temperature deviations and precipitation extremes also increase the risk of conflict onset and incidence.

Continued monitoring of SARS-CoV-2 at the population level is important for identifying at-risk groups. Here the authors analyse data from a serological surveillance platform in San Francisco and find considerable variation in infection and vaccination history by race/ethnicity and socioeconomic status.

Prompting people to consider accuracy can improve the quality of news they share online. Here, using an internal meta-analysis, the authors show that this effect is replicable and generalizes across headlines, types of accuracy prompt, and various participant characteristics.