Stefanos Alexander Limnaios

Mr. Stefanos Alexander Limnaios

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
6 January 2022 in Viruses
Verified
Journal Article
Open access
PDF file
SLStefanos Alexander Limnaios
Stefanos Alexander Limnaios
Evangelia KostakiEvangelia Kostaki
Evangelia Kostaki
GAGeorgios Adamis
Georgios Adamis
MAMyrto Astriti
Myrto Astriti
MCMaria Chini
Maria Chini
Dimitrios ParaskevisDimitrios Paraskevis
Dimitrios Paraskevis
Our aim was to estimate the date of the origin and the transmission rates of the major local clusters of subtypes A1 and B in Greece. Phylodynamic analyses were conducted in 14 subtype A1 and 31 subtype B clusters. The earliest dates of origin for subtypes A1 and B were in 1982.6 and in 1985.5, respectively. The transmission rate for the subtype A1 clusters ranged between 7.54 and 39.61 infections/100 person years (IQR: 9.39, 15.88), and for subtype B clusters between 4.42 and 36.44 infections/100 person years (IQR: 7.38, 15.04). Statistical analysis revealed that the average difference in the transmission rate between the PWID and the MSM clusters was 6.73 (95% CI: 0.86 to 12.60; p = 0.026). Our study provides evidence that the date of introduction of subtype A1 in Greece was the earliest in Europe. Transmission rates were significantly higher for PWID than MSM clusters due to the conditions that gave rise to an extensive PWID HIV-1 outbreak ten years ago in Athens, Greece. Transmission rate can be considered as a valuable measure for public health since it provides a proxy of the rate of epidemic growth within a cluster and, therefore, it can be useful for targeted HIV prevention programs.

11 December 2020 in medRxiv
Verified
Preprint
Open access
PDF file
Evangelia KostakiEvangelia Kostaki
Evangelia Kostaki
SLStefanos Alexander Limnaios
Stefanos Alexander Limnaios
Sotirios RoussosSotirios Roussos
Sotirios Roussos
MPMina Psichogiou
Mina Psichogiou
Georgios NikolopoulosGeorgios Nikolopoulos
Georgios Nikolopoulos
Dimitrios ParaskevisDimitrios Paraskevis
Dimitrios Paraskevis
Improving HIV diagnosis, access to care and effective antiretroviral treatment provides our global strategy to reduce HIV incidence. To reach this goal we need to increase our knowledge about local epidemics. HIV infection dates would be an important information towards this goal, but they are largely unknown. To date, methods to estimate the dates of HIV infection are based mainly on laboratory or molecular methods. Our aim was to validate molecular clock inferred infection dates that were estimated by analysing sequences from 145 people living with HIV (PLHIV) with known transmission dates (clinically estimated infection dates). All HIV sequences were obtained by Sanger sequencing and were previously found to belong to well-established molecular transmission clusters (MTCs). Our analysis showed that the molecular clock inferred infection dates were correlated with the clinically estimated ones (Spearman’s Correlation coefficient = 0.93, p<0.001) and that there was an agreement between them (Lin’s concordance correlation coefficient = 0.92, p<0.001). For most cases (61.4%), the molecular clock inferred preceded the clinically estimated infection dates. The median difference between clinically and molecularly estimated dates of infection was of 0.18 (IQR: -0.21, 0.89) years. The lowest differences were identified in people who inject drugs of our study population. Our study shows that the estimated time to more recent common ancestor (t MRCA ) of nodes within clusters provides a reliable approximation of HIV infections for PLHIV infected within MTCs. Next-generation sequencing data and molecular clock estimates based on heterochronous sequences provide, probably, more reliable methods for inferring infection dates. However, since these data are not available in most of the HIV clinical laboratories, our approach, under specific conditions, can provide a reliable estimation of HIV infection dates and can be used for HIV public health interventions.