Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2024
Identifying the unknown: Application of molecular epidemiology tools to identify clustering and HIV transmission routes in Poland.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Horecki Marcin, Serwin Karol, Cielniak Iwona, Siwak Ewa, Jasik Monika Bociąga, Kalinowska-Nowak Anna, Rozpłochowski Błażej, Aksak-Wąs Bogusz, Witak-Jędra Magdalena, Szymczak Aleksandra, Szetela Bartosz, Mularska Elżbieta, Witor Adam, Jakubowski Paweł, Hlebowicz Maria, Olczak Anita, Łojewski Władysław, Jabłonowska Elżbieta, Mielczak Kaja, Ząbek Piotr, Parczewski Miłosz, Lübke Nadine, Obermeyer Martin, Urbańska Anna, Karasińska-Cieślak Malwina
Аннотация
BACKGROUND: Understanding the dynamics of HIV-1 transmission is essential for developing effective screening and intervention strategies. Viral genetic sequences provide valuable information that can be used to infer the history and patterns of viral transmission.
PURPOSE: Our study explores the structure and dynamics of HIV transmissions in Poland from 1999 to 2022 to elucidate key patterns related with national epidemics.
METHODS: To understand the temporal dynamics of transmission routes we examined HIV pol sequence data from 5705 Polish PWH. The HIV-TRAnsmission Cluster Engine (HIV-TRACE) was utilized to identify potential links between different risk groups and putative links to individuals with unreported transmission risk.
RESULTS: Our analyses generated 503 clusters, containing 3942 individuals, and identified 13,917 putative links. Approximately 69.1 % of the sequences formed clusters. In the dataset 32.2 % of individuals were reported MSM transmission route, 7.9 % by heterosexual, and 5.6 % by PWID transmissions. The transmission route was unknown for 54.2 % of patients. Putative transmissions from MSM to all other groups revealed that 45.1 % of links lead to people with unregistered transmission mode. For heterosexual patients, 40.2 % of connections were directed to patients lacking information on infection routes and 30.5 % to MSM individuals. Our analysis unveiled that 45.1 % of cases with unreported transmission routes may be identified as MSM, while 3.5 % might be potential non-disclosed MSM.
CONCLUSIONS: Genetic linkages can provide valuable insights into the transmission dynamics among individuals, even in cases where transmission risk information is missing or unreported. The observed association between MSM and unreported cases highlights the potential of molecular epidemiology to complete missing patient data.
PURPOSE: Our study explores the structure and dynamics of HIV transmissions in Poland from 1999 to 2022 to elucidate key patterns related with national epidemics.
METHODS: To understand the temporal dynamics of transmission routes we examined HIV pol sequence data from 5705 Polish PWH. The HIV-TRAnsmission Cluster Engine (HIV-TRACE) was utilized to identify potential links between different risk groups and putative links to individuals with unreported transmission risk.
RESULTS: Our analyses generated 503 clusters, containing 3942 individuals, and identified 13,917 putative links. Approximately 69.1 % of the sequences formed clusters. In the dataset 32.2 % of individuals were reported MSM transmission route, 7.9 % by heterosexual, and 5.6 % by PWID transmissions. The transmission route was unknown for 54.2 % of patients. Putative transmissions from MSM to all other groups revealed that 45.1 % of links lead to people with unregistered transmission mode. For heterosexual patients, 40.2 % of connections were directed to patients lacking information on infection routes and 30.5 % to MSM individuals. Our analysis unveiled that 45.1 % of cases with unreported transmission routes may be identified as MSM, while 3.5 % might be potential non-disclosed MSM.
CONCLUSIONS: Genetic linkages can provide valuable insights into the transmission dynamics among individuals, even in cases where transmission risk information is missing or unreported. The observed association between MSM and unreported cases highlights the potential of molecular epidemiology to complete missing patient data.