Whole-genome sequencing surveillance of Siberian tick-borne encephalitis virus (TBEV) identifies an additional lineage in Kyrgyzstan.

Tick-borne encephalitis virus (TBEV) is the most prevalent tick-borne viral disease in Europe and Asia. There are three main subtypes of the virus: European, Siberian, and Far Eastern, each of which having distinctive ecology, clinical presentation, and geographic distribution. In recent years, other TBEV subtypes have been described, namely the Himalayan and Baikalian subtypes.

Challenges and lessons learned in recruiting participants for school-based disease prevention programs during COVID-19.

Schools provide an ideal setting for delivery of disease prevention programs due to the ability to deliver health education and counseling, including health behavior interventions, to large numbers of students. However, the remote and hybrid learning models that arose during the coronavirus (COVID-19) pandemic created obstacles to these efforts. In this article, we provide insights on collaborating with schools to deliver disease prevention programming during the height of the COVID-19 pandemic, and in subsequent years.

Changes in Skin Cancer-Related Behaviors, Distress, and Beliefs in Response to Receipt of Low- to Moderate-Penetrance Genetic Test Results for Skin Cancer Risk.

Little is known about the impact of low- to moderate-penetrance genetic testing for skin cancer, which is a promising approach to skin cancer prevention. To address this deficit, we conducted an analysis comparing changes in skin cancer-related behaviors, distress, and beliefs measured at a baseline and twice after the receipt of skin cancer precision prevention materials containing risk feedback (higher or average risk) among 568 non-Hispanic White (NHW) and 463 Hispanic participants. Regression analyses identified decreased average weekend hours in the sun (β = -0.

Serodynamics: A primer and synthetic review of methods for epidemiological inference using serological data.

We present a review and primer of methods to understand epidemiological dynamics and identify past exposures from serological data, referred to as serodynamics. We discuss processing and interpreting serological data prior to fitting serodynamical models, and review approaches for estimating epidemiological trends and past exposures, ranging from serocatalytic models applied to binary serostatus data, to more complex models incorporating quantitative antibody measurements and immunological understanding. Although these methods are seemingly disparate, we demonstrate how they are derived within a common mathematical framework.