Evolution and transmission dynamics of wild poliovirus in Pakistan and Afghanistan (2012-2023)

Abstract

Despite concerted global vaccination efforts, wild poliovirus remains endemic in two countries in 2024, Pakistan and Afghanistan. This study uses phylogeographic analysis of poliovirus genetic and epidemiological data from clinical and wastewater surveillance to identify the causes of poliovirus persistence and routes of spread over the last decade (2012 to 2023). Poliovirus genetic diversity declined after 2020, with one of two major genetic clusters dying out, and recent detections are now closely related genetically. High-risk and hard-to-access regions have sustained polio transmission over the past decade, even when interrupted elsewhere. Karachi, one of the most densely populated cities globally, has acted as a hub for the amplification and spread of poliovirus to other regions, many of which we show to be dead-end for onwards transmission despite frequent virus detection. Phylogenetic analysis has long been central to the polio surveillance network, and advancing the approaches used can provide critical epidemiological insights to accelerate eradication efforts.

Fig. 1. Reported cases of acute flaccid paralysis (AFP).

A Reported AFP cases in Afghanistan and Pakistan aggregated in 3-month periods between January 2005 and August 2023. Gray strips show even years. The black arrow on panel A shows the sampling time of the first genetic sequence included in this analysis. B Map showing the 16 regions used for the phylogeographic analysis, with cities of over 10 million inhabitants plotted as white points and labeled. Disputed territory is shown with dotted lines. The geodata used is obtained from the World Health Organization. The boundaries and names shown, and the designations used on the map do not imply the expression of any opinion whatsoever on the part of the authors or the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

Fig. 2. Phylogenetic analysis.

A Dated consensus phylogenetic tree reconstructed from WPV1 sequences from stool of AFP cases and ES samples collected between January 2012 and August 2023. The vertical orange line indicates the time of the first sequence in the database. Branches and internal nodes are colored by their inferred location, and tips, by their known location. The two lineages of poliovirus in the region, which were responsible for the 2019–2020 outbreak, are labelled A and B, with the numbered clusters inside of lineage B supporting all transmission seen in 2023. B Lineages through time (LTT) plot inferred from all available sequences. C Effective viral population size (Ne) inferred from genetic sequences generated from stool samples from AFP cases. Blue shaded regions on panels B and C show 95% CrIs around the mean estimate shown in black. Vertical gray stripes represent even years.

Fig. 3. Estimated viral movements across regions.

A, B Bayes factor supported estimates of the number of movements between the regions across the full time period. Panel A shows the number of importations into each region and B the number of exportations from each region. 95% CrIs for each estimate are shown with black error bars. The values used to generate these bars are shown in Supplementary Table S2. Inferred movement events between regions during the C 2013–2014 and D 2019–2020 outbreak periods based on the reconstruction of most likely ancestral regions. Links between regions are colored according to the exporting region. C and D are scaled to show the relative number of movement events between regions in each outbreak period, with regions in the north of each country plotted at the top and regions in the south plotted at the bottom. A matrix representation of the number of movements between regions is provided in Supplementary Fig. S9. Colors are mapped to regions in Fig. 1B.

Fig. 4. Analysis of local transmission lineages.

A Flowchart showing the process of generating and classifying local transmission lineages (LTLs). B Classification of LTLs by region over the time period covered by the data. These plots show median numbers of lineages in each group over time over a posterior sample of 300 phylogenies. 95% CrIs for these estimates are shown in Supplementary Fig. S4. The black vertical lines are one year prior to the end of the dataset, after which we can’t be sure of lineage classifications due to data censoring.