The social and humanitarian impacts of overshooting the Paris Agreement’s aspirational goal of a 1.5 degrees Celsius rise in global mean temperature remain largely unknown, despite robust knowledge of physical climate impacts. Andrew Kruczkiewicz and colleagues outline five factors that policymakers and planners should take into account when considering the human impacts of climate overshoot.

Researchers at the University of Tokyo developed an experimental method to induce a strong physiological response linked to psychological pressure by making participants aim for a streak of success in a task. Their findings suggest this approach reproduces pressurelike conditions in a laboratory setting more effectively than traditional methods, affording easier access to the study of this state. That in turn could open up research into how pressure influences human performance in physical and intellectual tasks.

Researchers at the University of Waterloo have developed a machine learning approach that could help public health officials anticipate disease outbreaks by analyzing vaccine skepticism on social media. Using the mathematical concept of tipping points, the team showed that online misinformation spreads much like a contagion and can signal heightened outbreak risk well before illness appears. Their model, tested on posts from California ahead of a 2014 measles outbreak, detected early warning patterns that traditional tweet-counting methods missed. This work supports Waterloo’s efforts to strengthen evidence-based decision-making and rebuild public trust in science, and the model could eventually be adapted across platforms like TikTok and Instagram to help identify communities nearing a critical shift in vaccination sentiment.

As cities around the world grapple with escalating mental health challenges, researchers from The University of Hong Kong (HKU) have pinpointed the ideal levels of urban greenness that maximise psychological well-being. Published in Nature Cities, HKU’s latest study synthesises four decades of global evidence to demonstrate a curvilinear—inverted-U—dose-response relationship, challenging the long-held assumption “greener is always better.”

A new study co-authored by University of Notre Dame researcher Helge-Johannes Marahrens shows that analyzing social media posts can help experts predict when people will move during crises, supporting faster and more effective humanitarian aid delivery. Marahrens, assistant professor of computational social science in Notre Dame’s Keough School of Global Affairs, said that this research highlights how powerful computational tools can help address major global challenges to human dignity.