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Abstract

Genomic surveillance is vital for detecting outbreaks and understanding the epidemiology and transmission of bacterial strains, yet it is not integrated into many national antimicrobial resistance (AMR) surveillance programmes. Key factors are that few scientists in the public health sector are trained in bacterial genomics, and the diverse sequencing platforms and bioinformatic tools make it challenging to generate reproducible outputs. In Kenya, these gaps were addressed by training public health scientists to conduct genomic surveillance on isolates from the national AMR surveillance repository and produce harmonized reports. The 2-week training combined theory and laboratory and bioinformatic experiences with isolates from the surveillance repository. Whole-genome sequences generated on Illumina and Nanopore sequencers were analysed using publicly available bioinformatic tools, and a harmonized report was generated using the HAMRonization tool. Pre- and post-training tests and self-assessments were used to assess the effectiveness of the training. Thirteen scientists were trained and generated data on the isolates, summarizing the AMR genes present consistently with the reported phenotypes and identifying the plasmid replicons that could transmit antibiotic resistance. Ninety per cent of the participants demonstrated an overall improvement in their post-training test scores, with an average increase of 14 %. Critical challenges were experienced in delayed delivery of equipment and supplies, power fluctuations and internet connections that were inadequate for bioinformatic analysis. Despite this, the training built the knowledge and skills to implement bacterial genomic surveillance. More advanced and immersive training experiences and building supporting infrastructure would solidify these gains to produce tangible public health outcomes.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2023-08-30
2024-05-01
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References

  1. World Health Organization Antimicrobial resistance: global report on surveillance. World Health Organization; 2014 https://apps.who.int/iris/handle/10665/112642 accessed 7 April 2021
  2. Government of Kenya National Action Plan on Prevention and Containment of Antimicrobial Resistance. Government of Kenya; 2017
  3. National Antimicrobial Resistance Surveillance Strategy 2018–2022. Gov Kenya; 2018
  4. Antimicrobial Resistance Surveillance Report – Human Health January 2019 – August 2021. Ministry of Health Kenya; 2021
  5. Global Antimicrobial Resistance and Use Surveillance System (GLASS). n.d https://www.who.int/publications-detail-redirect/9789240027336 accessed 7 December 2022
  6. Mboowa G, Sserwadda I, Aruhomukama D. Genomics and bioinformatics capacity in Africa: no continent is left behind. Genome 2021; 64:503–513 [View Article] [PubMed]
    [Google Scholar]
  7. H3Africa: a tipping point for a revolution in bioinformatics, genomics and health research in Africa | Source Code for Biology and Medicine | Full Text. n.d https://scfbm.biomedcentral.com/articles/10.1186/1751-0473-9-10 accessed 11 June 2023
  8. Shaffer JG, Mather FJ, Wele M, Li J, Tangara CO et al. Expanding research capacity in sub-Saharan Africa through informatics, bioinformatics, and data science training programs in Mali. Front Genet 2019; 10:331 [View Article] [PubMed]
    [Google Scholar]
  9. Karikari TK. Bioinformatics in Africa: the rise of ghana?. PLoS Comput Biol 2015; 11:e1004308 [View Article] [PubMed]
    [Google Scholar]
  10. Adedokun BO, Olopade CO, Olopade OI. Building local capacity for genomics research in Africa: recommendations from analysis of publications in Sub-Saharan Africa from 2004 to 2013. Glob Health Action 2016; 9:31026 [View Article] [PubMed]
    [Google Scholar]
  11. Ellington MJ, Heinz E, Wailan AM, Dorman MJ, de Goffau M et al. Contrasting patterns of longitudinal population dynamics and antimicrobial resistance mechanisms in two priority bacterial pathogens over 7 years in a single center. Genome Biol 2019; 20:184 [View Article] [PubMed]
    [Google Scholar]
  12. Henson SP, Boinett CJ, Ellington MJ, Kagia N, Mwarumba S et al. Molecular epidemiology of Klebsiella pneumoniae invasive infections over a decade at Kilifi County Hospital in Kenya. Int J Med Microbiol 2017; 307:422–429 [View Article] [PubMed]
    [Google Scholar]
  13. Musila L, Kyany’a C, Maybank R, Stam J, Oundo V et al. Detection of diverse carbapenem and multidrug resistance genes and high-risk strain types among carbapenem non-susceptible clinical isolates of target gram-negative bacteria in Kenya. PLoS One 2021; 16:e0246937 [View Article] [PubMed]
    [Google Scholar]
  14. Kyany’a C, Musila L. Colistin resistance gene mcr-8 in a high-risk sequence type 15 Klebsiella pneumoniae isolate from Kenya. Microbiol Resour Announc 2020; 9:e00783-20 [View Article] [PubMed]
    [Google Scholar]
  15. Muraya A, Kyany’a C, Kiyaga S, Smith HJ, Kibet C et al. Antimicrobial resistance and virulence characteristics of Klebsiella pneumoniae isolates in Kenya by whole-genome sequencing. Pathogens 2022; 11:545 [View Article]
    [Google Scholar]
  16. Kariuki S, Onsare RS. Epidemiology and genomics of invasive nontyphoidal Salmonella infections in Kenya. Clin Infect Dis 2015; 61 Suppl 4:S317–24 [View Article] [PubMed]
    [Google Scholar]
  17. Kariuki S, Dyson ZA, Mbae C, Ngetich R, Kavai SM et al. Multiple introductions of multidrug-resistant typhoid associated with acute infection and asymptomatic carriage, Kenya. Elife 2021; 10:e67852 [View Article] [PubMed]
    [Google Scholar]
  18. Kyany’a C, Nyasinga J, Matano D, Oundo V, Wacira S et al. Phenotypic and genotypic characterization of clinical Staphylococcus aureus isolates from Kenya. BMC Microbiol 2019; 19:245 [View Article] [PubMed]
    [Google Scholar]
  19. Kiyaga S, Kyany’a C, Muraya AW, Smith HJ, Mills EG et al. Genetic diversity, distribution, and genomic characterization of antibiotic resistance and virulence of clinical Pseudomonas aeruginosa strains in Kenya. Front Microbiol 2022; 13:835403 [View Article] [PubMed]
    [Google Scholar]
  20. Cehovin A, Harrison OB, Lewis SB, Ward PN, Ngetsa C et al. Identification of novel Neisseria gonorrhoeae lineages harboring resistance plasmids in Coastal Kenya. J Infect Dis 2018; 218:801–808 [View Article] [PubMed]
    [Google Scholar]
  21. Kivata MW, Mbuchi M, Eyase FL, Bulimo WD, Kyanya CK et al. gyrA and parC mutations in fluoroquinolone-resistant Neisseria gonorrhoeae isolates from Kenya. BMC Microbiol 2019; 19:76 [View Article] [PubMed]
    [Google Scholar]
  22. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517–D525 [View Article] [PubMed]
    [Google Scholar]
  23. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother 2020; 75:3491–3500 [View Article] [PubMed]
    [Google Scholar]
  24. Feldgarden M, Brover V, Haft DH, Prasad AB, Slotta DJ et al. Validating the AMRFinder tool and resistance gene database by using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrob Agents Chemother 2019; 63:e00483-19 [View Article] [PubMed]
    [Google Scholar]
  25. Ferdinand AS, Kelaher M, Lane CR, da Silva AG, Sherry NL et al. An implementation science approach to evaluating pathogen whole genome sequencing in public health. Genome Med 2021; 13:121 [View Article] [PubMed]
    [Google Scholar]
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