Biomedical subjects

Tetyana I Vasylyeva

Publications and source records attributed to Tetyana I Vasylyeva.

3 recordsLinked to original sources

PubMed2026

Detection and genomic characterization of a travel-associated ECSA lineage chikungunya virus infection in Mexico.

BACKGROUND: In 2013, chikungunya virus (CHIKV), a re-emerging Aedes-borne virus, was introduced into the Americas. This led to synchronous epidemics across the region associated mainly with the Asian lineage, which eventually subsided. Resurgent outbreaks have been recorded since, principally in South America, largely driven by the East-Central-South-African (ECSA) lineage. In 2025, more than 300,000 CHIKV suspected cases were reported in Brazil and Cuba. CASE SUMMARY: In November 2025, a healthy adult male traveling from Cuba arrived in Merida, Mexico, and shortly after presented febrile symptoms consistent with an arboviral infection. CHIKV infection was diagnosed by RT-qPCR. Though the infection was mild, the patient developed a rash on the abdomen and neck that persisted for up to a month, with further inflammation of the joints of the left leg. Phylogenetic analysis of the viral genome indicated placement within the ECSA lineage, clustering with other contemporaneous virus genomes sampled from Brazil that belong to a recently described clade II within the country, in which viral genomes from Cuba also cluster. CONCLUSION: We identify a travel-associated ECSA lineage CHIKV case in Mexico. This viral lineage has not previously been detected in the country. This finding highlights the risk for subsequent local transmission and is consistent with reports of the presence of this lineage in Cuba. Ten years since the last CHIKV epidemic in Mexico, strengthened surveillance is required to anticipate potential local outbreaks within the region.

ECSA↗

PubMed2025

VANTAGE: van-based real-time HIV sequencing for transmission mapping and drug resistance profiling in war-affected Ukraine.

We deployed the VANTAGE (VAN for Transmissible Agent Genomic Epidemiology) mobile system in Lviv, Ukraine, demonstrating end-to-end sequencing of dried blood spot samples within a clinic van usually serving de-occupied and frontline regions. HIV-1 pol sequences were obtained from 50% of samples, all subtype A6. Median time to 100× coverage was 38 min. Phylogenetic analysis revealed a local transmission cluster including a displaced person and the non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance mutation E138A, supporting real-time HIV genomic surveillance in humanitarian crises.

Humans↗

PubMed2025

Parallel algorithms for phylogenetic inference under a structured coalescent approximation.

While advances in molecular epidemiology and computational modeling have enhanced our capacity to track pathogen evolution, the accurate reconstruction of spatiotemporal transmission dynamics remains essential for developing epidemic preparedness frameworks and implementing outbreak response measures. Structured coalescent models offer a phylogeographic framework by restricting lineage coalescence events to geographically proximate host populations. Although the Bayesian structured coalescent approximation (BASTA) provides a tractable approach, contemporary phylogeographic analyses involving dozens of geographic localities and hundreds to thousands of viral genomes substantially exceed the computational capacity of existing implementations. The BASTA likelihood scales cubically with deme count and quadratically with sequence count due to matrix exponentiation and pairwise coalescent probability calculations. Here, we introduce a comprehensive algorithmic restructuring of the structured coalescent likelihood that eliminates redundancies, optimizes memory access, and exposes parallelization opportunities. Our approach reorganizes computations along three dimensions: (i) independent calculation of deme-transition probability matrices across time intervals; (ii) simultaneous evaluation of partial likelihood vectors within temporal slices; and (iii) concurrent aggregation of coalescent probabilities. Algorithmic restructuring cuts average coalescent likelihood computation by 7-8 fold, and parallelization further boosts performance to 10-26 fold, enabling joint phylogeographic analyses of dengue virus across 10 South American countries and H5N1 avian influenza across 20 Eurasian regions to finish in a fraction of prior time. This computational efficiency also enables comparison between backward-in-time structured coalescent approximations and forward-in-time phylogeographic methods, revealing that the former provides appropriately conservative posterior estimates, particularly at intermediate phylogenetic depths. We integrate our implementation into the popular BEAST X and BEAGLE software packages, with an accompanying interface in BEAUti X to easily set up the analyses, providing researchers with an accessible and scalable tool for real-time phylogeographic surveillance of rapidly evolving pathogens.

Journal Article↗