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. 2020 Aug 28;15(8):e0237560.
doi: 10.1371/journal.pone.0237560. eCollection 2020.

HIV-1 phylodynamic analysis among people who inject drugs in Pakistan correlates with trends in illicit opioid trade

François Cholette  1   2 , Jeffrey Joy  3   4   5 , Yann Pelcat  6 , Laura H Thompson  2 , Richard Pilon  1 , John Ho  1 , Rupert Capina  1 , Chris Archibald  7 , James F Blanchard  8 , Faran Emmanuel  8 , Tahira Reza  9 , Nosheen Dar  10 , Richard Harrigan  4 , John Kim  1 , Paul Sandstrom  1   11
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HIV-1 phylodynamic analysis among people who inject drugs in Pakistan correlates with trends in illicit opioid trade

François Cholette et al. PLoS One. .

Abstract

Pakistan is considered by the World Health Organization to currently have a "concentrated" HIV-1 epidemic due to a rapid rise in infections among people who inject drugs (PWID). Prevalence among the country's nearly 105,000 PWID is estimated to be 37.8% but has been shown to be higher in several large urban centers. A lack of public health resources, the common use of professional injectors and unsafe injection practices are believed to have fueled the outbreak. Here we evaluate the molecular characteristics of HIV-1 sequences (n = 290) from PWID in several Pakistani cities to examine transmission dynamics and the association between rates of HIV-1 transmission with regards to regional trends in opioid trafficking. Tip-to-tip (patristic) distance based phylogenetic cluster inferences and BEAST2 Bayesian phylodynamic analyses of time-stamped data were performed on HIV-1 pol sequences generated from dried blood spots collected from 1,453 PWID as part of a cross-sectional survey conducted in Pakistan during 2014/2015. Overall, subtype A1 strains were dominant (75.2%) followed by CRF02_AG (14.1%), recombinants/unassigned (7.2%), CRF35_AD (2.1%), G (1.0%) and C (0.3%). Nearly three quarters of the PWID HIV-1 sequences belonged to one of five distinct phylogenetic clusters. Just below half (44.4%) of individuals in the largest cluster (n = 118) did seek help injecting from professional injectors which was previously identified as a strong correlate of HIV-1 infection. Spikes in estimated HIV-1 effective population sizes coincided with increases in opium poppy cultivation in Afghanistan, Pakistan's western neighbor. Structured coalescent analysis was undertaken in order to investigate the spatial relationship of HIV-1 transmission among the various cities under study. In general terms, our analysis placed the city of Larkana at the center of the PWID HIV-1 epidemic in Pakistan which is consistent with previous epidemiological data.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Geographic HIV-1 subtype distribution among people who inject drugs in Pakistan.
“Recomb” refers to HIV-1 sequences that were unsuccessfully subtyped (i.e. labelled as recombinant and/or unassigned) by the automated subtyping tools. This map was created using ESRI ArcMap software version 10.5., using open source data from the Global Administrative Areas version 2.8 (https://gadm.org/data.html).
Fig 2
Fig 2. Maximum likelihood phylogenetic tree for HIV-1 pol sequences (n = 561).
A) Viral strain sequences from people who inject drugs in Pakistan are annotated according to city of origin: Karachi (blue, n = 109 [19.4%]), Peshawar (orange, n = 94 [16.7%]), Hyderabad (purple, n = 42 [7.5%]), Larkana (green, n = 25 [4.5%]) and Quetta (red, n = 20 [3.6%]) while branches representing background sequences (n = 271 [48.3%]) were left black. Monophyletic clusters identified by Cluster Picker are highlighted by light grey bars. B) Sub-tree from principal maximum likelihood phylogenetic tree from HIV-1 pol sequences used for cluster analysis presenting HIV-1 subtype CRF35_AD sequences from people who inject drugs in Pakistan. The numbers on the branches represent the percentage of maximum likelihood ultra-fast bootstrap samples (100,000 replicates) where the node is supported by a value of ≥ 90%. Branches are annotated according to city or country of origin: Karachi (blue, n = 7 [20.0%]), Peshawar (orange, n = 1 [2.9%]), Hyderabad (purple, n = 1 [2.9%]), Quetta (red, n = 1 [2.9%]), Afghanistan (black, n = 10 [28.6%]), and grey (Iran, n = 15 [42.8%]).
Fig 3
Fig 3. Phylogenetic clusters inferred using tip-to-tip (patristic) distance between sequences measured on phylogenetic trees.
Viral strain sequences from people who inject drugs in Pakistan are annotated according to city of origin: Karachi (blue), Peshawar (orange), Hyderabad (purple), Larkana (green) and Quetta (red).
Fig 4
Fig 4. Effective population size estimates of HIV-1 among people who inject drugs in Pakistan.
The median effective population size is shown by the solid blue line, with the 95% highest and lowest posterior densities represented by the area shaded in blue. The timeframe dates back to the early 1980’s but estimates up to 1994 only are displayed for legibility. Opium poppy cultivation in Afghanistan, according to estimates by the United Nations Office on Drugs and Crime [12], is represented by light orange bars.
Fig 5
Fig 5. Spatial dispersion of HIV-1 subtype A1 among people who inject drugs in Pakistan.
Arrows between cities represent the number of HIV-1 migration events inferred using a MCMC structured coalescent approach with MultiTypeTree as implemented in BEAST2. Arrow colors reflect the number of HIV-1 migration events between cities according to the legend at the bottom right corner. This map was created using ESRI ArcMap software version 10.5., using open source data from the Global Administrative Areas version 2.8 (https://gadm.org/data.html).
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