SARS-CoV-2 Introductions into Lao PDR Revealed by Genomic Surveillance, 2021–2024

  1. Siribun Panapruksachat
  2. Cécile Troupin
  3. Manila Souksavanh
  4. Chantisa Keeratipusana
  5. Manivanh Vongsouvath
  6. Susath Vongphachanh
  7. Malavanh Vongsouvath
  8. Koukeo Phommasone
  9. Somphavanh Somlor
  10. Matthew T. Robinson
  11. Thanat Chookajorn
  12. Theerarat Kochakarn
  13. Nicholas PJ Day
  14. Mayfong Mayxay
  15. Andrew G. Letizia
  16. Audrey Dubot-Pérès
  17. Elizabeth A Ashley
  18. Philippe Buchy
  19. Phonepadith Xangsayarath
  20. Elizabeth M. Batty

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Abstract

We used 2492 whole genome sequences from Laos to investigate the molecular epidemiology of SARS-CoV-2 from 2021 through 2024, covering the major waves of COVID-19 disease in Laos including time periods of travel restrictions and after relaxation of travel across international borders. We identify successive waves of COVID-19 caused by shifts in the dominant lineage, beginning with the Alpha variant in April 2021 and continuing through the Delta and Omicron variants. We quantify a shift from a small number of viral introductions responsible for widespread transmission in early waves to a larger number of introductions for each variant after travel restrictions were lifted, and identify potential routes of introduction into the country. Our study underscores the importance of genomic surveillance to public health responses to characterize viral transmission dynamics during pandemics.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/20257242.

    Major Issues

    1. The sample set combines routine hospital screening, contact investigations, air-passenger screening, and a case-based surveillance study. These are very different sampling streams, and they are not evenly distributed across provinces or time. Vientiane Capital and Vientiane Province account for 57.71% of samples, while some provinces have very few or no samples. The authors should provide a clearer table of samples by month, province, source type, lab, Ct threshold, and variant. This would help readers judge whether inferred introductions reflect true epidemiology or sampling intensity.

    2. The authors appropriately acknowledge this, but the results still present specific inferred origins such as the UK, USA, China, Thailand, and Vietnam in a way that may appear more certain than the data allow. Because countries such as the UK, USA, Germany, and China are heavily represented in global datasets, inferred origin may reflect where related genomes were sequenced rather than where the virus actually entered Laos from. The authors should soften causal language, report uncertainty more prominently, and consider sensitivity analyses using downsampled global trees or regional rather than country-level origin categories.

    3. The manuscript reports 443 introductions, including 100 during lockdown and 343 after lockdown, but readers need more detail on how matUtils classified introductions, how polytomies were handled, and how identical or near-identical genomes from multiple countries were interpreted. A supplementary table listing each inferred introduction, lineage, date, province, descendant cluster size, inferred origin, and uncertainty would greatly improve reproducibility.

    4. The change from few introductions with large clusters to many introductions with smaller clusters may reflect real travel changes, but it may also reflect changes in testing intensity, sequencing effort, population immunity, variant biology, public database completeness, and retrospective sequencing delays. The authors should avoid attributing this shift too strongly to travel restrictions alone unless additional normalization or sensitivity analyses are added.

    5. LOMWRU and IPL used different Ct cutoffs, primer schemes, sequencing workflows, basecalling approaches, and consensus pipelines. This is understandable operationally, but the manuscript should clarify whether these differences affected genome completeness, lineage assignment, failure rates, or detection of particular variants. A short comparison by lab and time period would strengthen confidence in the combined dataset.

    6. The manuscript suggests that genomic sequencing can help evaluate border-control measures, but the available metadata cannot distinguish infections detected in quarantine from undetected community introductions, nor direct importation from transmission through unsampled third countries. The discussion should frame these findings as suggestive rather than as a direct evaluation of border policy effectiveness.

    7. The data availability statement provides sequence access information, but the manuscript should also provide analysis code, the exact UShER tree version/hash, PastML settings, matUtils commands, pango-collapse configuration, and processed introduction tables. This is especially important because introduction inference is sensitive to tree version and background sampling.

    Minor Issues

    1. The methods state that the dataset was categorized relative to the "implementation of the lockdown on May 9, 2022," but elsewhere May 9, 2022 is described as the date when all travel restrictions were lifted. This should be corrected for clarity.

    2. The sentence "Individual lineages were grouped into the Variants of Concern and Variants of pango-collapse v0.8.2" appears grammatically incomplete. It likely needs revision.

    3. Table 1 should clarify what is included under "Other variant," and the missing location for first detection should be completed if available.

    4. The Mu row lists "06/2021" without a day, while other rows give full dates. Use a consistent date format or explain missing day-level metadata.

    5. The term "Vientiane region" should be defined clearly when combining Vientiane Capital and Vientiane Province.

    6. Figures with phylogenetic trees are informative but dense. Larger labels, clearer legends, or zoomed inset panels for key introductions would improve readability.

    7. Figure 6 would benefit from confidence intervals or uncertainty indicators for introduction proportions, since the denominators differ strongly by province and period.

    8. The manuscript should distinguish more consistently between "probable origin," "closest sampled relative," and "true source of introduction."

    9. The introduction includes a military-readiness framing that feels abrupt relative to the public-health genomic surveillance focus. It could be moved to the discussion or reframed more broadly.

    1. The discussion already acknowledges sampling bias well, but some of those caveats should also appear earlier in the results when country-origin findings are first presented.

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. Version published to 10.64898/2026.04.09.26349480 on medRxiv