Looking back into the Hepatitis C Virus epidemic dynamics from Unnao, India through phylogenetic approach

Viral hepatitis is a major public health challenge. Hepatitis C Virus (HCV) infection causes the progressive liver damage. A surprisingly high number of individuals tested positive for HCV infection during the Unnao Human Immunodeficiency Virus (HIV) outbreak investigation in 2017-2018 (more than 90% of the people living with HIV were from the Premganj township and Chakmeerapur village of the district in the northern State of Uttar Pradesh). This particular outbreak was attributed to the unsafe use of syringe & needles while seeking treatment, rendering it as an iatrogenic transmission. Earlier investigation towards, phylogenetic characterization revealed the shared ancestry for HCV sequences from the reported outbreak. In this investigation using the HCV sequences reported earlier (n = 67) we have analyzed the transmission linkages and evolutionary dynamics of this HCV outbreak using phylogenetic methods. In current analysis, time-scaled phylogenies indicated that most clusters initiated during 2015-2016. Transmission dynamics highlighted that the outbreak was experiencing an exponential phase during 2016-2017, where reproductive number was observed to be beyond documented values for HCV. Phylogeography revealed that source of the virus was Chakmeerapur and the effective population of Premganj was double the size of that in Chakmeerapur. In summary, we provide the snapshot of epidemic dynamics for HCV outbreak attributed to iatrogenic transmission.

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Publication Details

Journal
PLoS ONE
Published
2025-01-16
DOI
https://doi.org/10.1371/journal.pone.0317705
Citations
1
Primary Topic
Hepatitis C virus research
Type
article
Field-Weighted Citation Impact
1.32
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article

Looking back into the Hepatitis C Virus epidemic dynamics from Unnao, India through phylogenetic approach

Ajit Patil, Pallavi Vidhate, Sandip Patil, Amrita Rao et al.
1 citations
PLoS ONE
Hepatitis C virus research
1.32
article

Looking back into the Hepatitis C Virus epidemic dynamics from Unnao, India through phylogenetic approach

Ajit Patil, Pallavi Vidhate, Sandip Patil, Amrita Rao, Samiran Panda, Swarali Kurle
article en
1 citations

Abstract

Viral hepatitis is a major public health challenge. Hepatitis C Virus (HCV) infection causes the progressive liver damage. A surprisingly high number of individuals tested positive for HCV infection during the Unnao Human Immunodeficiency Virus (HIV) outbreak investigation in 2017-2018 (more than 90% of the people living with HIV were from the Premganj township and Chakmeerapur village of the district in the northern State of Uttar Pradesh). This particular outbreak was attributed to the unsafe use of syringe & needles while seeking treatment, rendering it as an iatrogenic transmission. Earlier investigation towards, phylogenetic characterization revealed the shared ancestry for HCV sequences from the reported outbreak. In this investigation using the HCV sequences reported earlier (n = 67) we have analyzed the transmission linkages and evolutionary dynamics of this HCV outbreak using phylogenetic methods. In current analysis, time-scaled phylogenies indicated that most clusters initiated during 2015-2016. Transmission dynamics highlighted that the outbreak was experiencing an exponential phase during 2016-2017, where reproductive number was observed to be beyond documented values for HCV. Phylogeography revealed that source of the virus was Chakmeerapur and the effective population of Premganj was double the size of that in Chakmeerapur. In summary, we provide the snapshot of epidemic dynamics for HCV outbreak attributed to iatrogenic transmission.

PLoS ONEVol. 20(1)
Indian Council of Medical Research (IN), National AIDS Research Institute (IN), ICMR-National Institute of Virology (IN)
Openalex Percentile: Top 25%
Hepatitis C virus research
1.32
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Looking back into the Hepatitis C Virus epidemic dynamics from Unnao, India through phylogenetic approach — Ajit Patil, Pallavi Vidhate, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS