228 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 study demonstrates that the nationwide expansion of *Helicobacter pylori* eradication therapy in Japan since 2013 has already contributed to a 10.4% reduction in gastric cancer deaths by 2021, preventing an estimated 1,427 deaths through a counterfactual analysis framework that accounts for the disease's long natural history.
This population-based cohort study in England provides evidence that live shingles vaccination in adults aged 70 and over is associated with significantly reduced rates of all-cause death, all-cause hospitalization, and infection-related hospitalization, suggesting potential non-specific beneficial effects beyond the vaccine's target disease.
This study analyzes spatio-temporal HPV vaccination data from 2019 to 2024 in Malawi, revealing that coverage for both doses remains significantly below WHO targets with notable regional disparities and a counterintuitive negative association with urbanization, thereby highlighting the urgent need for decentralized, targeted interventions to accelerate cervical cancer elimination.
Using data from the CORDELIA-Catalunya Study, this research demonstrates through both multivariable regression and Mendelian randomization that higher leisure-time physical activity is causally associated with more favorable lifelong BMI trajectories and a reduced risk of obesity, with protective effects observed in both sexes but being stronger in men.
This study demonstrates that while trachoma transmission exhibits significant sub-district spatial heterogeneity in higher-prevalence areas, this heterogeneity diminishes as populations approach elimination, suggesting that district-level data remains sufficient for guiding surveillance and intervention decisions in the final stages of the disease's eradication.
By integrating serological data with a mechanistic model to correct for significant underreporting caused by fluctuating testing capacities and eligibility rules during the Omicron wave in Newfoundland and Labrador, researchers quantified the true infection burden and demonstrated that school closures and strict alert levels effectively reduced SARS-CoV-2 transmission, a conclusion unattainable through reported case data alone.
This study presents an enhanced, data-driven approach for modeling COVID-19 dynamics in Thuringia, Germany, by refining the globally discovered SINDy model through local coefficient optimization and neural network augmentation to accurately capture the effects of vaccination and public health interventions.
By integrating sensitive wastewater genomic surveillance with clinical whole-genome sequencing during South Africa's 2024–25 measles outbreak, researchers successfully uncovered previously undetected interprovincial transmission links and demonstrated that this combined approach significantly enhances the resolution and scalability of measles virus monitoring for global elimination efforts.
This cross-sectional study of 436 women living with HIV in Kinshasa reveals a 47.25% prevalence of high-risk oncogenic HPV infection, which is significantly associated with advanced HIV clinical stage, high viral loads, and shorter duration of antiretroviral therapy, highlighting the urgent need to integrate systematic HPV screening into HIV care programs.
This population-based study demonstrates that a joint model linking PSA dynamics, retesting patterns, and prostate cancer diagnosis provides more accurate risk estimates and corrects for informative observation bias compared to traditional isolated analyses.