286 papers
Epidemiology is the study of how diseases spread through populations and what factors influence their patterns. Rather than focusing on individual patients, this field examines broader trends to identify outbreaks, track transmission, and guide public health decisions. By analyzing data on infection rates and risk factors, researchers work to prevent future health crises and protect communities worldwide.
On Gist.Science, we process every new preprint in this category directly from medRxiv to make these critical findings instantly accessible. For each study, we provide both a plain-language explanation for general readers and a detailed technical summary for specialists. This dual approach ensures that vital insights into disease dynamics are understood clearly and quickly by everyone who needs them.
Explore the latest research below to see how scientists are currently mapping disease trends and developing strategies to safeguard global health.
This UK Biobank study demonstrates that a comprehensive five-domain behavioral exposome derived from accelerometry—encompassing movement volume, inactivity fragmentation, and circadian rhythms—is significantly associated with incident solid cancer risk, with nocturnal light exposure showing a specific novel link to pancreatic cancer.
By integrating viral load and contact survey data into a mathematical model, this study reveals that individual variation in contact rates, rather than viral shedding, is the primary driver of SARS-CoV-2 transmission heterogeneity, and demonstrates that frequent or pre-event rapid testing can effectively curb superspreading events.
This 2023 cross-sectional study in Wolaita Zone, Ethiopia, found that 84.9% of ART patients engaged in family-based HIV index case testing, a rate significantly influenced by urban residence, longer ART duration, status disclosure, family discussions, and professional counseling, though still falling short of the national 95% target.
This large-scale Australian population-based cohort study of over 5 million singletons found no strong evidence that children conceived via medically assisted reproduction have an elevated overall risk of childhood cancer compared to naturally conceived children, although some specific cancer subtypes showed unadjusted incidence increases that disappeared after controlling for confounders.
This study developed and validated the Hypertension Population Risk Tool (HTNPoRT), a high-performing, sex-specific diagnostic algorithm using readily available self-reported data to effectively screen individuals and guide population-level hypertension prevention strategies in Canada.
This systematic review and meta-analysis of 82 studies across 17 sub-Saharan African countries demonstrates that the implementation of Option B+ policies significantly improved both HIV care uptake (by 8%) and retention rates (by 46%) among pregnant and postpartum women, although retention levels remain insufficient to meet UNAIDS 95-95-95 targets.
This paper proposes a causal framework, including specific estimands and a target trial protocol, to rigorously quantify the effects of treatment delays on cancer outcomes using observational data, thereby addressing methodological challenges like indication bias to inform better healthcare policy.
This paper employs an evolutionary epidemiological model to estimate that thousands of undetected human avian influenza infections occur annually with an infection fatality ratio of approximately 0.32%, highlighting the critical need to prevent animal-to-human spillovers to mitigate severe individual outcomes and delay future pandemics.
This cross-sectional study of 587 workers in Salvador, Brazil, reveals that precarious employment conditions, particularly informal work and job insecurity, are significantly associated with a higher prevalence of common mental disorders, with specific risk factors varying by employment type, gender, and income level.
By integrating wastewater and clinical genomics across metropolitan and hospital catchments in Valencia, this study demonstrates that while wastewater surveillance effectively tracks dominant SARS-CoV-2 lineages and can detect emerging mutations like S:V445P missed by clinical sampling, its ability to capture fine-scale diversity and hospitalization-linked mutations varies by location, necessitating integration with large-scale clinical GWAS and interaction networks to prioritize evolutionarily significant variants.