Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England.

Mathematical modelling has played an important role in offering informed advice during the COVID-19 pandemic. In England, a cross government and academia collaboration generated medium-term projections (MTPs) of possible epidemic trajectories over the future 4-6 weeks from a collection of epidemiological models. In this article, we outline this collaborative modelling approach and evaluate the accuracy of the combined and individual model projections against the data over the period November 2021-December 2022 when various Omicron subvariants were spreading across England. Using a number of statistical methods, we quantify the predictive performance of the model projections for both the combined and individual MTPs, by evaluating the point and probabilistic accuracy. Our results illustrate that the combined MTPs, produced from an ensemble of heterogeneous epidemiological models, were a closer fit to the data than the individual models during the periods of epidemic growth or decline, with the 90% confidence intervals widest around the epidemic peaks. We also show that the combined MTPs increase the robustness and reduce the biases associated with a single model projection. Learning from our experience of ensemble modelling during the COVID-19 epidemic, our findings highlight the importance of developing cross-institutional multi-model infectious disease hubs for future outbreak control.

Triggering social interactions: chimpanzees respond to imitation by a humanoid robot and request responses from it.

Even the most rudimentary social cues may evoke affiliative responses in humans and promote social communication and cohesion. The present work tested whether such cues of an agent may also promote communicative interactions in a nonhuman primate species, by examining interaction-promoting behaviours in chimpanzees. Here, chimpanzees were tested during interactions with an interactive humanoid robot, which showed simple bodily movements and sent out calls. The results revealed that chimpanzees exhibited two types of interaction-promoting behaviours during relaxed or playful contexts. First, the chimpanzees showed prolonged active interest when they were imitated by the robot. Second, the subjects requested 'social' responses from the robot, i.e. by showing play invitations and offering toys or other objects. This study thus provides evidence that even rudimentary cues of a robotic agent may promote social interactions in chimpanzees, like in humans. Such simple and frequent social interactions most likely provided a foundation for sophisticated forms of affiliative communication to emerge.