Future vaccination strategies in pneumococcal disease should target specific bacterial serotypes for different host age groups.

Severe COVID-19 is characterised by a plasma proteomic biomarker signature, indicating innate immune activation, leucocyte–endothelial interactions, and epithelial injury.

A simple model provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Deep learning on fundus images provides a non-invasive, short time-scale biological aging clock that successfully identifies aging genes validated in a fly model.

Among children in low-resource settings, diverse enteropathogens share common, population-level antibody dynamics, which creates a new opportunity to estimate transmission through serologic surveillance.

Sequence changes in the pneumococcal genome explain most of the variability in duration of asymptomatic carriage with serotype, antibiotic resistance and prophage accounting for the largest effects.

Single-cell RNA sequencing highlights the influence of host–pathogen interactions and stochasticity on transcriptional and phenotypic variance in lymphoblastoid cell lines derived from Epstein–Barr virus-infected primary B cells.

Modeling weighted transfer ratios enable statistical analysis of maternal–infant transfer at a more general level and can indicate whether any transfer is persistent, transient, or originates from alternate sources.

Structural differences in adolescent brains associated with binge drinking might be preceding the onset of such behavior, suggesting a reevaluation of studies of the effects of alcohol on the adolescent brain.

The COVID-19 pandemic has clearly demonstrated the need for a global system to monitor the dynamics of susceptibility and immunity, as well as infection, during epidemics and pandemics.