Clinical Research Directory

Clinical Time and Temporal Dynamics Study (CLIN-TIME)

TH-CLINICAL-TIME is a prospective, longitudinal observational study evaluating how changes in clinical measurements over time may help researchers better understand patient health trajectories and clinically meaningful outcomes. The study will examine patterns such as changes from an individual's baseline, rate of change, persistence of abnormalities, variability, recurrence, and recovery following clinical events. Data may include routinely collected clinical measurements, physiologic observations, laboratory results, cardiac measurements, imaging-derived measurements, patient-reported information, and remote or digital health data when available and permitted by the study protocol. The study will investigate whether these temporal patterns provide additional information beyond individual measurements taken at a single point in time. The planned study horizon extends from 2026 through 2076, while individual participant follow-up will occur according to the approved study schedule, consent, and applicable requirements.

Improving Disease Prevention Strategies by Integrating Socio-spatial Characterization of Human Mobility

In contrast to the trend expected based on existing prediction models, dengue incidence was historically low during the pandemic mobility restrictions of 2020-2021 in most dengue endemic countries. This highlights that current transmission models do not correctly take human mobility into account. Within a pilot-study in Cienfuegos, South-Central Cuba, we will characterise the epidemiological spread and distribution of dengue outbreaks (2012-2025) in districts repeatedly involved in previous dengue outbreaks as initiating, case-concentrating or transmission sustaining areas. This will be linked with fine-grained mobility data and socio-spatial characterizations of commuting flows and population hubs where people are concentrated during day-time (time when transmission happens). This information, together with entomological and environmental risk-data, will be used to i) improve the accuracy of mathematical dengue models, ii) better understand the transmission process and iii) inform and improve the design of disease control strategies. The project will contribute to much-needed evidence-based guidance for public health actors on improved prevention strategies of epidemics dispersion and where and when to implement control measures.

Bern, Get Ready (BEready) Cohort Study for Pandemic Preparedness

The BEready project aims to find out how people in the Canton of Bern can be helped to be more prepared for the next pandemic. BEready wants to understand how infections spread among people as well as between people and animals. BEready wants to find out how social and environmental factors can influence the transmission or catching of infectious diseases. BEready wants to better understand how households and their pets in the Canton of Bern were and continue to be affected by the coronavirus disease 2019 (COVID-19).