Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes

  1. Megan E Carey  Is a corresponding author
  2. Zoe A Dyson
  3. Danielle J Ingle
  4. Afreenish Amir
  5. Mabel K Aworh
  6. Marie Anne Chattaway
  7. Ka Lip Chew
  8. John A Crump
  9. Nicholas A Feasey
  10. Benjamin P Howden
  11. Karen H Keddy
  12. Mailis Maes
  13. Christopher M Parry
  14. Sandra Van Puyvelde
  15. Hattie E Webb
  16. Ayorinde Oluwatobiloba Afolayan
  17. Anna P Alexander
  18. Shalini Anandan
  19. Jason R Andrews
  20. Philip M Ashton
  21. Buddha Basnyat
  22. Ashish Bavdekar
  23. Isaac I Bogoch
  24. John D Clemens
  25. Kesia Esther da Silva
  26. Anuradha De
  27. Joep de Ligt
  28. Paula Lucia Diaz Guevara
  29. Christiane Dolecek
  30. Shanta Dutta
  31. Marthie M Ehlers
  32. Louise Francois Watkins
  33. Denise O Garrett
  34. Gauri Godbole
  35. Melita A Gordon
  36. Andrew R Greenhill
  37. Chelsey Griffin
  38. Madhu Gupta
  39. Rene S Hendriksen
  40. Robert S Heyderman
  41. Yogesh Hooda
  42. Juan Carlos Hormazabal
  43. Odion O Ikhimiukor
  44. Junaid Iqbal
  45. Jobin John Jacob
  46. Claire Jenkins
  47. Dasaratha Ramaiah Jinka
  48. Jacob John
  49. Gagandeep Kang
  50. Abdoulie Kanteh
  51. Arti Kapil
  52. Abhilasha Karkey
  53. Samuel Kariuki
  54. Robert A Kingsley
  55. Roshine Mary Koshy
  56. AC Lauer
  57. Myron M Levine
  58. Ravikumar Kadahalli Lingegowda
  59. Stephen P Luby
  60. Grant Austin Mackenzie
  61. Tapfumanei Mashe
  62. Chisomo Msefula
  63. Ankur Mutreja
  64. Geetha Nagaraj
  65. Savitha Nagaraj
  66. Satheesh Nair
  67. Take K Naseri
  68. Susana Nimarota-Brown
  69. Elisabeth Njamkepo
  70. Iruka N Okeke
  71. Sulochana Putli Bai Perumal
  72. Andrew J Pollard
  73. Agila Kumari Pragasam
  74. Firdausi Qadri
  75. Farah N Qamar
  76. Sadia Isfat Ara Rahman
  77. Savitra Devi Rambocus
  78. David A Rasko
  79. Pallab Ray
  80. Roy Robins-Browne
  81. Temsunaro Rongsen-Chandola
  82. Jean Pierre Rutanga
  83. Samir K Saha
  84. Senjuti Saha
  85. Karnika Saigal
  86. Mohammad Saiful Islam Sajib
  87. Jessica C Seidman
  88. Jivan Shakya
  89. Varun Shamanna
  90. Jayanthi Shastri
  91. Rajeev Shrestha
  92. Sonia Sia
  93. Michael J Sikorski
  94. Ashita Singh
  95. Anthony M Smith
  96. Kaitlin A Tagg
  97. Dipesh Tamrakar
  98. Arif Mohammed Tanmoy
  99. Maria Thomas
  100. Mathew S Thomas
  101. Robert Thomsen
  102. Nicholas R Thomson
  103. Siaosi Tupua
  104. Krista Vaidya
  105. Mary Valcanis
  106. Balaji Veeraraghavan
  107. François-Xavier Weill
  108. Jackie Wright
  109. Gordon Dougan
  110. Silvia Argimón
  111. Jacqueline A Keane
  112. David M Aanensen
  113. Stephen Baker
  114. Kathryn E Holt
  115. Global Typhoid Genomics Consortium Group Authorship
  1. Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, United Kingdom
  2. Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, United Kingdom
  3. IAVI, Chelsea & Westminster Hospital, United Kingdom
  4. Department of Infectious Diseases, Central Clinical School, Monash University, Australia
  5. Wellcome Sanger Institute, Wellcome Genome Campus, United Kingdom
  6. Department of Microbiology and Immunology at the Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Australia
  7. National Institute of Health, Pakistan
  8. Nigeria Field Epidemiology and Laboratory Training Programme, Nigeria
  9. College of Veterinary Medicine, North Carolina State University, United States
  10. United Kingdom Health Security Agency, United Kingdom
  11. National University Hospital, Singapore
  12. Centre for International Health, University of Otago, New Zealand
  13. Department of Clinical Sciences, Liverpool School of Tropical Medicine, United Kingdom
  14. Malawi-Liverpool Wellcome Programme, Kamuzu University of Health Sciences, Malawi
  15. Centre for Pathogen Genomics, Department of Microbiology and Immunology, University of Melbourne at Doherty Institute for Infection and Immunity, Australia
  16. Microbiological Diagnostic Unit Public Health Laboratory, The University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Australia
  17. Independent consultant, South Africa
  18. University of Antwerp, Belgium
  19. Centers for Disease Control and Prevention, United States
  20. Global Health Research Unit (GHRU) for the Genomic Surveillance of Antimicrobial Resistance, Faculty of Pharmacy, University of Ibadan, Nigeria
  21. Lady Willingdon Hospital, India
  22. Department of Clinical Microbiology, Christian Medical College, India
  23. Division of Infectious Diseases and Geographic Medicine, Stanford University, United States
  24. Malawi-Liverpool Wellcome Programme, Malawi
  25. Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, United Kingdom
  26. Oxford University Clinical Research Unit Nepal, Nepal
  27. KEM Hospital Research Centre, India
  28. Department of Medicine, Division of Infectious Diseases, University of Toronto, Canada
  29. International Vaccine Institute, Republic of Korea
  30. International Centre for Diarrhoeal Disease Research, Bangladesh
  31. UCLA Fielding School of Public Health, United States
  32. Korea University, Republic of Korea
  33. Topiwala National Medical College, India
  34. ESR, Institute of Environmental Science and Research Ltd., Porirua, New Zealand
  35. Grupo de Microbiologia, Instituto Nacional de Salud, Colombia
  36. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, United Kingdom
  37. Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Thailand
  38. ICMR - National Institute of Cholera & Enteric Diseases, India
  39. Department of Medical Microbiology, Faculty of Health Sciences, University of Pretoria, South Africa
  40. Department of Medical Microbiology, Tshwane Academic Division, National Health Laboratory Service, South Africa
  41. Sabin Vaccine Institute, United States
  42. Federation University Australia, Australia
  43. Papua New Guinea Institute of Medical Research, Papua New Guinea
  44. Post Graduate Institute of Medical Education and Research, India
  45. Technical University of Denmark, Denmark
  46. Research Department of Infection, Division of Infection and Immunity, University College London, United Kingdom
  47. Child Health Research Foundation, Bangladesh
  48. Bacteriologia, Subdepartamento de Enfermedades Infecciosas, Departamento de Laboratorio Biomedico, Instituto de Salud Publica de Chile (ISP), Chile
  49. Department of Pediatrics and Child Health, Aga Khan University, Pakistan
  50. Rural Development Trust Hospital, India
  51. Department of Community Health, Christian Medical College, India
  52. Medical Research Council Unit The Gambia at London School Hygiene & Tropical Medicine, Gambia
  53. All India Institute of Medical Sciences, India
  54. Centre for Microbiology Research, Kenya Medical Research Institute, Kenya
  55. Quadram Institute Bioscience, United Kingdom
  56. Makunda Christian Hospital, India
  57. Center for Vaccine Development and Global Health (CVD), University of Maryland School of Medicine, Baltimore, Maryland, USA, United States
  58. Central Research Laboratory, Kempegowda Institute of Medical Sciences, India
  59. National Microbiology Reference Laboratory, Zimbabwe
  60. World Health Organization, Zimbabwe
  61. Kamuzu University of Health Sciences, Malawi
  62. Saint Johns Medical College and Hospital, India
  63. Ministry of Health, Government of Samoa, Samoa
  64. Institut Pasteur, Université Paris Cité, France
  65. Kanchi Kamakoti CHILDS Trust Hospital, India
  66. Oxford Vaccine Group, Department of Paediatrics, University of Oxford, United Kingdom
  67. The NIHR Oxford Biomedical Research Centre, United Kingdom
  68. Department of Microbiology and Immunology, University of Maryland School of Medicine, United States
  69. Institute for Genome Sciences, University of Maryland School of Medicine, United States
  70. Murdoch Children’s Research Institute, Royal Children’s Hospital, Australia
  71. Centre for Health Research and Development, Society for Applied Studies, India
  72. University of Rwanda, College of Science and Technology, Rwanda
  73. Chacha Nehru Bal Chikitsalaya, India
  74. Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, United Kingdom
  75. Dhulikhel Hospital, Nepal
  76. Institute for Research in Science and Technology, Nepal
  77. Kasturba Hospital for Infectious Diseases, India
  78. Center for Infectious Disease Research & Surveillance, Dhulikhel Hospital, Kathmandu University Hospital, Nepal
  79. Research Institute for Tropical Medicine, Department of Health, Philippines
  80. Chinchpada Christian Hospital, India
  81. Centre for Enteric Diseases, National Institute for Communicable Diseases, South Africa
  82. Christian Medical College, Ludhiana, India
  83. Duncan Hospital, India
  84. University of California Davis, United States
  85. Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, United Kingdom
7 figures, 3 tables and 10 additional files

Figures

Figure 1 with 4 supplements
Global genotype prevalence estimates.

Based on assumed acute cases isolated from untargeted sampling frames from 2010 onwards, with known country of origin (total N=9478 genomes). (a) Genotype prevalence by world region, 2010–2020. Countries contributing data are shaded in beige, and are grouped by regions as defined by the UN statistics division. (b) Annual genotype prevalence for countries with ≥50 genomes where typhoid is endemic. In both plots, colours indicate prevalence of Typhi genotypes, as per inset legend. Genotypes not exceeding 20% frequency in at least one country are aggregated as ‘other’. Full data on regional and national genotype prevalences, including raw counts, proportions, and 95% confidence intervals, are given in Supplementary files 5 and 6, respectively.

Figure 1—figure supplement 1
Genome size pre- and post-filtering, stratified by detection of an IncHI1 plasmid replicon marker.

(a) All assemblies examined (n=13,000). (b) Assemblies of genomes included in the analysis (n=12,965), inclusion criterion being size between 4.5 and 5.5 Mbp.

Figure 1—figure supplement 2
Annual breakdown of genotypes per world region, 2010–2020, for regions with ≥20 representative genomes.

Bars show genotype prevalence rates observed per annum, coloured as per inset legend. Genotypes present at ≥20% frequency in any country are indicated separately, rare genotypes are aggregated as ‘other’. Full data, including raw counts, proportions, and 95% confidence intervals, are available in Supplementary file 5.

Figure 1—figure supplement 3
Annual breakdown of genotypes per country, for countries with <50 representative genomes between 2010 and 2020.

(Note plots for countries with ≥50 genomes are shown in Figure 1b, full data including raw counts, proportions, and 95% confidence intervals, are in Supplementary file 6). Bars show genotype prevalence rates observed per annum, coloured as per inset legend. Genotypes present at ≥20% frequency in any country are indicated separately, rare genotypes are aggregated as ‘other’.

Figure 1—figure supplement 4
Phylogenetic tree showing relationships amongst genotype 2.3.2 genomes.

The tree is a core-genome distance-based neighbour-joining tree generated from assemblies using Pathogenwatch, including n=164 genotype 2.3.2 genomes, outgroup rooted using a diverse set of genomes from Ingle et al., 2021 (n=115 genomes from 16 genotypes). Tips are coloured by world region, according to inset legend; triangles indicate genomes harbouring QRDR mutations resulting in predicted non-susceptibility to ciprofloxacin (CipNS). Clades representing putative local clonal expansions are shaded.

Figure 2 with 5 supplements
Prevalence of key antimicrobial resistance (AMR) genotype profiles by country.

For all countries with ≥50 representative genomes (untargeted, assumed acute cases) from 2010 to 2020, where typhoid is endemic. Percentage resistance values are printed for each country/drug combination, and are coloured by categorical ranges to reflect escalating levels of concern for empirical antimicrobial use: (i) 0: no resistance detected; (ii) >0 and ≤2%: resistance present but rare; (iii) 2–10%: emerging resistance; (iv) 10–50%: resistance common; (v) >50%: established resistance. Annual rates underlying these summary rates are shown in Figure 3 and Supplementary file 8. Full data including counts and confidence intervals are included in Supplementary file 8. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant; AziR, azithromycin resistant. Countries are grouped by geographical region.

Figure 2—figure supplement 1
Prevalence of key antimicrobial resistance (AMR) genotype profiles by world region, for non-targeted samples, 2010–2020.

Percentage resistance values are printed for each region/drug combination, and are coloured by categorical ranges to reflect escalating levels of concern for empirical antimicrobial use: (i) 0: no resistance detected; (ii) >0 and ≤2%: resistance present but rare; (iii) 2–10%: emerging resistance; (iv) 10–50%: resistance common; (v) >50%: established resistance. Full data including counts and confidence intervals are in Supplementary file 7. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant; AziR, azithromycin resistant.

Figure 2—figure supplement 2
Antimicrobial resistance (AMR) prevalence for non-targeted samples, 2010–2020.

Data are shown only for countries with N≥20 isolates (others are coloured grey). Countries are coloured by the prevalence of resistance per country, as per the inset legend. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant; AziR, azithromycin resistant.

Figure 2—figure supplement 3
Annual genotype prevalence amongst multidrug-resistant (MDR) and ciprofloxacin non-susceptible (CipNS) genomes.

For countries with ≥50 representative genomes between 2010 and 2020 and endemic typhoid. Genotypes for (a) MDR and (b) CipNS genomes are coloured according to the inset legends; sensitive genomes of all genotypes are aggregated and coloured grey.

Figure 2—figure supplement 4
Distribution of fluoroquinolone resistance determinants by genotype.

For selected countries discussed in text. Node size indicates total number of isolates for a given combination of genotype (row) and determinant (column); nodes are coloured to indicate the frequency of the determinant within that genotype. Wt = wildtype; that is, no quinolone resistance determining mutations was detected in gyrA or parC and no plasmid-borne quinolone resistance (qnr) genes were detected.

Figure 2—figure supplement 5
Ciprofloxacin-resistant genotypes identified.

Rows show all n=24 unique combinations of Typhi genotype, quinolone-resistance determining region (QRDR) mutations (in gyrA, gyrB, parC, see Methods) and acquired plasmid-mediated quinolone resistance (PMQR) genes (qnrB, qnrD, qnrS) identified in genomes that are predicted to result in ciprofloxacin resistance (presence of ≥1 QRDR mutation+≥1 PMQR gene, or presence of ≥3 QRDR mutations).

Figure 3 with 2 supplements
Annual prevalence of key antimicrobial resistance (AMR) profiles.

For countries with ≥3 years with ≥10 representative genomes (untargeted, assumed acute cases) from 2000 to 2020. Data are shown only for country/year combinations with N≥5 isolates. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant.

Figure 3—figure supplement 1
Annual prevalence of key antimicrobial resistance (AMR) profiles.

For countries with ≥3 years with ≥10 representative genomes (untargeted, assumed acute cases) from 2000 to 2020 and endemic typhoid. Data are shown only for country/year combinations with N≥5 isolates. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant; AziR, azithromycin resistant.

Figure 3—figure supplement 2
Trends in annual frequency of multidrug-resistant (MDR) genomes and proportion of MDR explained by IncHI1 plasmids.

For countries with endemic typhoid and ≥5% MDR prevalence between 2000 and 2020.

Phylogenetic tree showing position of 2015 Rwalpindi isolate, Rwp1-PK1, in context with other genomes from Pakistan.

Core-genome distance-based neighbour-joining tree generated in Pathogenwatch, using all genomes from Klemm et al., 2018 (the first genomic characterisation of the extensively drug-resistant [XDR] outbreak clade, including outbreak strains and local context strains from Sindh Province in 2016–2017) and Rasheed et al., 2020 (genomic report of XDR outbreak strains from Lahore in 2019). Tree tips are coloured by genotype, according to inset legend; the 2015 strain Rwp1-PK1 is labelled in the tree and indicated with a triangle. Year of isolation and presence of antimicrobial resistance (AMR) determinants are indicated in the heatmap, according to inset legend.

Distribution of azithromycin resistance-associated acrB mutations detected in Typhi genomes.

(a) Temporal distribution of acrB mutants. (b) Distribution of acrB mutants by genotype and mutation. The first acrB mutant appeared in Samoa in 2007. Other mutants have appeared independently across a range of genetic backgrounds, largely in South Asian countries, but remain at low prevalence levels overall (see Figure 2). Country of origin is coloured as per inset label.

Figure 6 with 2 supplements
Annual genotype and antimicrobial resistance (AMR) frequencies by isolating lab, for South Asian countries with multiple data sources.

Labs shown are those with ≥20 isolates; and years shown for each lab are those with N≥5 isolates from that year. (a) Bars are coloured to indicate annual genotype prevalence, as per inset legend. (b) Lines indicate annual frequencies of key AMR profiles, coloured by isolating laboratory as per inset legend. MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant. See Supplementary file 9 for three-letter laboratory code master list.

Figure 6—figure supplement 1
Genotype prevalence estimated from different data sources, for South Asian countries.

For source laboratories with N≥20 isolates. Lines show 95% confidence interval for each proportion (prevalence) estimate; solid circles highlight the pooled point estimate for national prevalence in each country. Lines are coloured by country as per the inset legend. See Supplementary file 9 for three-letter laboratory code master list.

Figure 6—figure supplement 2
Antimicrobial resistance (AMR) prevalence estimated from different sources, for South Asian countries.

For source laboratories with N≥20 isolates from which to estimate prevalence. Lines show 95% confidence interval for each proportion (prevalence) estimate; solid circles highlight the pooled point estimate for national prevalence in each country. Lines are coloured by country as per the inset legend. See Supplementary file 9 for three-letter laboratory code master list.

Genotype and antimicrobial resistance (AMR) prevalence rates estimated for Nigeria from different data sources.

Data are shown only for source labs with N≥10 isolates from which to estimate prevalence. (a) Genotype prevalence and (b) AMR prevalence, using all available isolates per lab, 2010–2020. Lines show 95% confidence interval for each proportion (prevalence) estimate. Red indicates estimates based on data from individual labs, black indicates pooled estimates (i.e. from all labs), as per inset legend. (c) Annual genotype frequencies. Bars are coloured by genotype as per inset legend. Lab abbreviations are shown in y-axis labels for panels (a–b). MDR, multidrug resistant; XDR, extensively drug resistant; CipNS, ciprofloxacin non-susceptible; CipR, ciprofloxacin resistant; CefR, ceftriaxone resistant; AziR, azithromycin resistant. See Supplementary file 9 for three-letter laboratory code master list.

Tables

Table 1
Summary of published studies and other data sources.

Details of research studies and public health laboratory data aggregated in this study.

Published studiesPubMed ID or DOI (citation as per reference list)Total genomes*Representative cases 2010–2020Travel associated
11677608 (Parkhill et al., 2001)100
12644504 (Deng et al., 2003)100
18660809 (Holt et al., 2008)400
25392358 (Hendriksen et al., 2015a)2200
25428145 (Hendriksen et al., 2015b)200
25961941 (Wong et al., 2015)1736733248
26411565 (Baker et al., 2015)3000
26974227 (Pham Thanh et al., 2016a)77770
27069781 (Ashton et al., 2016)489432356
27331909 (Pham Thanh et al., 2016b)110
27657909 (Wong et al., 2016b)1281110
27703135 (Wong et al., 2016a)994343
28060810 (Dyson et al., 2017)4400
28280021 (Rodrigues et al., 2017)300
28705963 (Kong et al., 2017)200
28931025 (Kuijpers et al., 2017)64590
29051234 (Gul et al., 2017)100
29136410 (Phoba et al., 2017)100
29216342 (Day et al., 2018)543
29255729 (Matono et al., 2017)10700
29463654 (Klemm et al., 2018)10000
29616895 (Djeghout et al., 2018)100
29684021 (Britto et al., 2018)1921690
30425150 (Tanmoy et al., 2018)53600
30504848 (Park et al., 2018)2492090
30236166 (Burnsed et al., 2018)3000
31225619 (Oo et al., 2019)39390
31513580 (Ingle et al., 2019)1079991
31730615 (Hooda et al., 2019)1200
31872221 (Sah et al., 2019)200
31665304 (Britto et al., 2020)94940
32003431 (Pragasam et al., 2020)19400
32106221 (Rahman et al., 2020)2021470
32119918 (Chirico et al., 2020)100
32217683 (Tagg et al., 2020)500
32253142 (Liu et al., 2021)100
32732230 (Hao et al., 2020)100
32883020 (Rasheed et al., 2020)27270
33079054 (Maes et al., 2020)770
33085725 (Thanh Duy et al., 2020)11600
33347558 (Mashe et al., 2021)2900
34223059 (Duy et al., 2020)400
33496224 (Octavia et al., 2021)151512
33515460 (Carey et al., 2021)66660
33593966 (Sajib et al., 2021)80800
33651791 (Shin et al., 2021)800
33704480 (Nair et al., 2021)585858
33965548 (Jacob et al., 2021)200
34370659 (Chattaway et al., 2021)631604584
34463736 (Gauld et al., 2022)2622620
34515028 (Kariuki et al., 2021)136880
34529660 (Guevara et al., 2021)7700
34543095 (Ingle et al., 2021)116116107
34626469 (Argimón et al., 2021b)92920
34812716 (Kanteh et al., 2021)16140
35344544 (Dyson et al., 2022)4100
35750070 (da Silva et al., 2022)340233900
35767580 (Maes et al., 2022)203900
35999186 (Lagrada et al., 2022)1901900
36026470 (Ikhimiukor et al., 2022a)22140
36094088 (Sikorski et al., 2022)2021741
37327220 (Rutanga et al., 2023)51260
37339282 (Smith et al., 2023)28128113
DOI: 10.1101/2022.09.01.506167 (Thilliez et al., 2022)5700
DOI: 10.1101/2022.10.03.510628 (Carey et al., 2022)46300
DOI: 10.1101/2023.03.27.23287794 (Ashton et al., 2023)20200
DOI: 10.1101/2023.03.11.23286741 (Dyson et al., 2023)7327070
Previously unpublished public health laboratory data
France (Institut Pasteur)232317
New Zealand (ESR)999752
USA (CDC)889850712
Total13,00095082297
  1. *

    Genomes associated with assumed acute typhoid cases, isolated from 2010 onwards from non-targeted sampling frames; this is the subset of data used to generate genotype prevalence distributions shown in Figures 13.

  2. Genomes recorded as travel-associated and with known travel to a specific country in this region, associated with assumed acute typhoid isolated from 2010 onwards from non-targeted sampling frames.

Table 2
Summary of genomes by region.
RegionTotal genomes*Representative cases 2010–2020Travel (%) amongst representative cases 2010–2020
Australia and NZ57570 (0%)
Caribbean202020 (100%)
Central America103100100 (100%)
Eastern Africa110683049 (5.9%)
Eastern Asia1233 (100%)
Eastern Europe311 (100%)
Melanesia2323730 (81.1%)
Micronesia411 (100%)
Middle Africa59216 (28.6%)
Northern Africa4166 (100%)
Northern America1671402 (1.4%)
Northern Europe1091050 (0%)
Polynesia32426245 (17.2%)
South America3671055 (4.8%)
South-eastern Asia114058472 (12.3%)
Southern Africa3172862 (0.7%)
Southern Asia823166231878 (28.4%)
Southern Europe1066 (100%)
Western Africa38426734 (12.7%)
Western Asia472121 (100%)
Western Europe733 (100%)
Unknown22500
Total1296594782284 (24.1%)
  1. *

    Genomes associated with assumed acute typhoid cases, isolated from 2010 onwards from non-targeted sampling frames; this is the subset of data used to generate genotype prevalence distributions shown in Figures 13.

  2. Genomes recorded as travel-associated and with known travel to a specific country in this region, associated with assumed acute typhoid isolated from 2010 onwards from non-targeted sampling frames. Countries were assigned to world regions based on the United Nations (UN) Statistics Division standard M49.

Table 3
Extended spectrum beta-lactamase (ESBL) genes detected in Typhi genomes.
GenotypeESBL3GCRCountry of originnYearsOther plasmid/AMR markers
2.5.1CTX-M-15YDRC Phoba et al., 201712015IncY; blaTEM-1, dfrA7, sul1
(gyrA-S83F)
3CTX-M-15YPhilippines Lagrada et al., 202212013
SHV-12YPhilippines Hendriksen et al., 2015a; Lagrada et al., 202222007IncHI2A*; blaTEM-1, dfrA18, tetA(D)
3.3CTX-M-15YUK12012(gyrA-S83F)
3.3.2CTX-M-15YBangladesh Djeghout et al., 2018; Tanmoy et al., 201822000IncI1*; blaTEM-1
3.5CTX-M-12YColombia Guevara et al., 202112012IncL, IncFIB(pHCM2); blaTEM-1, sul1
4.3.1CTX-M-15YIndia Sah et al., 201912019IncY*; qnrS, blaTEM-1, dfrA14, sul2,
(gyrA-S83Y)
Y/NPakistan da Silva et al., 2022; Klemm et al., 201822018IncY ; qnrS, blaTEM-1, sul2, catA1, dfrA7, sul1, tetA(A); (gyrA-S83F)
4.3.1.1CTX-M-15NPakistan da Silva et al., 202212016IncY; qnrS, blaTEM-1, sul2, catA1, dfrA7, sul1, tetA(A); (gyrA-S83F)
4.3.1.1.P1CTX-M-15YIndia Klemm et al., 2018; Nair et al., 202112019IncY*qnrS, blaTEM-1, sul2, catA1, dfrA7, sul1
(gyrA-S83F)
YMexico https://wwwn.cdc.gov/narmsnow/12019
YPakistan Klemm et al., 2018; Munir et al., 2016; Rasheed et al., 20206562015–20
YUSA https://wwwn.cdc.gov/narmsnow/12019
CTX-M-55YPakistan Nair et al., 202112018
4.3.1.2CTX-M-15YIraq Nair et al., 202122019IncY; (gyrA-S83F)
4.3.1.2.1SHV-12YIndia Argimón et al., 2021a; Chattaway et al., 2021; Ingle et al., 2021; Jacob et al., 2021182015–20IncX3*; qnrB
(gyrA-S83F, gyrA-D87N, parC-S80I)
  1. ‘Other plasmid/AMR markers’ column includes: (i) plasmid replicons (Inc types) identified in the genome (in bold); (ii) other acquired AMR genes; (iii) chromosomal AMR mutations (in brackets). n.a. indicates susceptibility data not available.

  2. *

    indicates this plasmid is the reported location of the ESBL gene in the genome assembly.

  3. n=31 4.3.1.1 .P1 isolates from Pakistan lacked plasmid replicons.

  4. the ESBL 4.3.1. isolate from Klemm et al., 2018, was phenotypically third-generation cephalosporin resistant (3GCR), but the one from da Silva et al., 2022, was phenotypically 3GC sensitive.

Additional files

Supplementary file 1

Details of local ethical approvals provided for studies that were unpublished at the time of contributing data to this consortium project.

Most data are now published, and the citations for the original studies are provided here. National surveillance programs in Chile (Maes et al., 2022), Colombia (Guevara et al., 2021), France, New Zealand, and Nigeria (Ikhimiukor et al., 2022b) were exempt from local ethical approvals as these countries allow sharing of non-identifiable pathogen sequence data for surveillance purposes. The US CDC Internal Review Board confirmed their approval was not required for use in this project (#NCEZID-ARLT-10/20/21-fa687).

https://cdn.elifesciences.org/articles/85867/elife-85867-supp1-v1.zip
Supplementary file 2

Line list of 13,000 genomes included in the study.

https://cdn.elifesciences.org/articles/85867/elife-85867-supp2-v1.zip
Supplementary file 3

Source information recorded for genomes included in the study.

^Indicates cases included in the definition of ‘assumed acute illness’.

https://cdn.elifesciences.org/articles/85867/elife-85867-supp3-v1.zip
Supplementary file 4

Summary of genomes by country.

https://cdn.elifesciences.org/articles/85867/elife-85867-supp4-v1.zip
Supplementary file 5

Genotype frequencies per region (N, %, 95% confidence interval; annual and aggregated, 2010–2020).

https://cdn.elifesciences.org/articles/85867/elife-85867-supp5-v1.zip
Supplementary file 6

Genotype frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020).

https://cdn.elifesciences.org/articles/85867/elife-85867-supp6-v1.zip
Supplementary file 7

Antimicrobial resistance (AMR) frequencies per region (N, %, 95% confidence interval; aggregated 2010–2020).

https://cdn.elifesciences.org/articles/85867/elife-85867-supp7-v1.zip
Supplementary file 8

Antimicrobial resistance (AMR) frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020).

https://cdn.elifesciences.org/articles/85867/elife-85867-supp8-v1.zip
Supplementary file 9

Laboratory code master list.

Three letter laboratory codes assigned by the consortium.

https://cdn.elifesciences.org/articles/85867/elife-85867-supp9-v1.zip
MDAR checklist
https://cdn.elifesciences.org/articles/85867/elife-85867-mdarchecklist1-v1.pdf

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  1. Megan E Carey
  2. Zoe A Dyson
  3. Danielle J Ingle
  4. Afreenish Amir
  5. Mabel K Aworh
  6. Marie Anne Chattaway
  7. Ka Lip Chew
  8. John A Crump
  9. Nicholas A Feasey
  10. Benjamin P Howden
  11. Karen H Keddy
  12. Mailis Maes
  13. Christopher M Parry
  14. Sandra Van Puyvelde
  15. Hattie E Webb
  16. Ayorinde Oluwatobiloba Afolayan
  17. Anna P Alexander
  18. Shalini Anandan
  19. Jason R Andrews
  20. Philip M Ashton
  21. Buddha Basnyat
  22. Ashish Bavdekar
  23. Isaac I Bogoch
  24. John D Clemens
  25. Kesia Esther da Silva
  26. Anuradha De
  27. Joep de Ligt
  28. Paula Lucia Diaz Guevara
  29. Christiane Dolecek
  30. Shanta Dutta
  31. Marthie M Ehlers
  32. Louise Francois Watkins
  33. Denise O Garrett
  34. Gauri Godbole
  35. Melita A Gordon
  36. Andrew R Greenhill
  37. Chelsey Griffin
  38. Madhu Gupta
  39. Rene S Hendriksen
  40. Robert S Heyderman
  41. Yogesh Hooda
  42. Juan Carlos Hormazabal
  43. Odion O Ikhimiukor
  44. Junaid Iqbal
  45. Jobin John Jacob
  46. Claire Jenkins
  47. Dasaratha Ramaiah Jinka
  48. Jacob John
  49. Gagandeep Kang
  50. Abdoulie Kanteh
  51. Arti Kapil
  52. Abhilasha Karkey
  53. Samuel Kariuki
  54. Robert A Kingsley
  55. Roshine Mary Koshy
  56. AC Lauer
  57. Myron M Levine
  58. Ravikumar Kadahalli Lingegowda
  59. Stephen P Luby
  60. Grant Austin Mackenzie
  61. Tapfumanei Mashe
  62. Chisomo Msefula
  63. Ankur Mutreja
  64. Geetha Nagaraj
  65. Savitha Nagaraj
  66. Satheesh Nair
  67. Take K Naseri
  68. Susana Nimarota-Brown
  69. Elisabeth Njamkepo
  70. Iruka N Okeke
  71. Sulochana Putli Bai Perumal
  72. Andrew J Pollard
  73. Agila Kumari Pragasam
  74. Firdausi Qadri
  75. Farah N Qamar
  76. Sadia Isfat Ara Rahman
  77. Savitra Devi Rambocus
  78. David A Rasko
  79. Pallab Ray
  80. Roy Robins-Browne
  81. Temsunaro Rongsen-Chandola
  82. Jean Pierre Rutanga
  83. Samir K Saha
  84. Senjuti Saha
  85. Karnika Saigal
  86. Mohammad Saiful Islam Sajib
  87. Jessica C Seidman
  88. Jivan Shakya
  89. Varun Shamanna
  90. Jayanthi Shastri
  91. Rajeev Shrestha
  92. Sonia Sia
  93. Michael J Sikorski
  94. Ashita Singh
  95. Anthony M Smith
  96. Kaitlin A Tagg
  97. Dipesh Tamrakar
  98. Arif Mohammed Tanmoy
  99. Maria Thomas
  100. Mathew S Thomas
  101. Robert Thomsen
  102. Nicholas R Thomson
  103. Siaosi Tupua
  104. Krista Vaidya
  105. Mary Valcanis
  106. Balaji Veeraraghavan
  107. François-Xavier Weill
  108. Jackie Wright
  109. Gordon Dougan
  110. Silvia Argimón
  111. Jacqueline A Keane
  112. David M Aanensen
  113. Stephen Baker
  114. Kathryn E Holt
  115. Global Typhoid Genomics Consortium Group Authorship
(2023)
Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes
eLife 12:e85867.
https://doi.org/10.7554/eLife.85867