Operational intricacies of sequencing-based surveillance in developing countries
Editorial

Operational intricacies of sequencing-based surveillance in developing countries

Jimmy T. Efird1,2

1VA Cooperative Studies Program Coordinating Center, Boston, MA, USA; 2Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

Correspondence to: Jimmy T. Efird. Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA. Email: jte38@case.edu.

Comment on: Hu X, Zhou W, Zhang L, et al. Implementing sequencing-based surveillance in developing countries: findings from a pilot rollout for hepatitis A in China. Ann Transl Med 2021;9:1119.


Submitted Jun 18, 2021. Accepted for publication Sep 16, 2022.

doi: 10.21037/atm-21-3145


The recent COVID-19 pandemic highlights the concept of a sentinel event as an important implement for the prevention and analysis of the root causes of an emerging virus. As noted by Hu and colleagues in their manuscript on “Implementing sequencing-based surveillance in developing countries: findings from a pilot rollout for hepatitis A in China”, the efficiency of a traceback investigation for a common-source exposure is facilitated by identifying identical sequence patterns and overlapping epidemiologic characteristics. The complexities of a viral outbreak vis-à-vis early detection and management are compounded by geography and temporal trends (time/space), with sequencing-based surveillance revealing the virologic links among sporadic cases—thus advancing the ability to detect and mitigate undesirable effects by weeks to months. To this extent, sequence-based surveillance provides direct and indirect clues about the rate of viral progression, aids the understanding of transmission routes, and informs therapeutic implications downstream to the evolving nature (variants) of the virus. For example, the previously unknown betacoronavirus, now known as 2019-nCoV (a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily), was detected by unbiased sequencing of human airway epithelial cells in samples from patients with pneumonia (1). Sequencing also was instrumental in identifying the mutation of a surface spike protein that mediates SARS-CoV-2 entry into cells (2). Comparable sequencing of hepatitis A virus (Picornaviridae family) has played a pivotal role in improving preparedness and rapid response in recent outbreaks (3).

The cross-species emergence of viruses from animal vectors to humans reflect their genetic diversity, recombination activity, as well as other factors including climate change and proximity of new construction to native species habitats (e.g., zoonotic transmission, ecological and environmental mechanisms). The constant antigenic modification of viruses and potential for human harm merit the implementation and refinement of sequencing-based surveillance program utilizing next-generation technology (4). In the post COVID-19 context, wherein influenza has largely remained dormant during the pandemic, the emergence of new strains poses a public health concern, especially among younger age groups who have not developed natural immunity to influenza during this void. Unfortunately, many underdeveloped regions of the world do not have the bioinformatics capabilities and trained personnel to readily analyze virus genomic data. The need for well-developed sequencing efforts further coincides with the increasing use of antiviral agents and the information derived about antiviral resistance or reduced susceptibility (e.g., neuraminidase and matrix gene segments) (5). Over the past decade, increased access to open-source genetic databases and advanced bioinformatic tools has in part eased the transition to sequencing-based surveillance (6).

There are many lessons to be learned about the operational intricacies of sequencing-based surveillance in developing countries, as illustrated in this pilot rollout for hepatitis A in China. The authors are to be applauded for their informative manuscript.


Acknowledgments

Funding: None.


Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Translational Medicine. The article did not undergo external peer review.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (https://atm.amegroups.com/article/view/10.21037/atm-21-3145/coif). JTE serves as an unpaid editorial board member of Annals of Translational Medicine from October 2020 to September 2022. The author has no other conflicts of interest to declare.

Ethical Statement: The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


References

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  2. Shang J, Wan Y, Luo C, et al. Cell entry mechanisms of SARS-CoV-2. Proc Natl Acad Sci U S A 2020;117:11727-34. [Crossref] [PubMed]
  3. Enkirch T, Severi E, Vennema H, et al. Improving preparedness to respond to cross-border hepatitis A outbreaks in the European Union/European Economic Area: towards comparable sequencing of hepatitis A virus. Euro Surveill 2019;24:1800397. [Crossref] [PubMed]
  4. Borges V, Pinheiro M, Pechirra P, et al. INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance. Genome Med 2018;10:46. [Crossref] [PubMed]
  5. WHO. Next-generation sequencing of influenza viruses: general information for national influenza centres. Geneva: World Health Organization, 2020.
  6. Cortes A, Dendrou CA, Motyer A, et al. Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank. Nat Genet 2017;49:1311-8. [Crossref] [PubMed]
Cite this article as: Efird JT. Operational intricacies of sequencing-based surveillance in developing countries. Ann Transl Med 2022;10(19):1043. doi: 10.21037/atm-21-3145

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