1. Baseline molecular markers of AQ and SP in Sub-Saharan Africa
Burkina Faso: IRSS
Chad: CSSI
Gambia: MRC
Guinea: UGANC
Mali: MRTC
Nigeria: JEDIMA
Niger: CERMES
Jean Bosco OUEDRAOGO
IRSS-DRO, Bobo-Dioulasso

2. Overview Background Samples and methods Prevalence of AQ markers
Prevalence of SP markers
Summary

3. Objectives
Measure the prevalence of molecular markers associated with resistance to SP and AQ before SMC in the community
in children under 5yrs
in older age groups too old for SMC
Importance of standardised methods of sampling, DNA extraction
Importance of adequate sample size
Measure the change in the prevalence of these markers at intervals (2-3 years) in SMC areas
Measure protective efficacy of SMC treatments (using case control studies)

4. Background:Molecular markers of AQSP
C72S
K76T
M74I
N75E
pfcrt
CVMNK
CVIET
SVMNT AQ
pfmdr1
N86Y
F184Y
D1246Y
NFD
NYD
YYY
N51I
C59R
S108N
pfdhfr
VCS
IRN (Triple) SP
I431V
S436A
A631S/T
A581G
K540E
A437G
pfdhps SK
GE (Double)

5. Sampling locations for molecular marker surveys
Community surveys in 2015 in areas that had not started SMC (except Gambia which had started SMC in 2014)
Representative sampling of two age groups after the end of the transmission season:
<5years
10-30 years
Household surveys in villages selected with PPS
2000 individuals in each age group
Total target sample size of 28,000
Powered to detect odds ratio of 2.5 in each country and an odds ratio of 1.4 in pooled analysis

6. Why Monitoring efficacy of SMC drugs?
provide reassurance about efficacy after 2yrs SMC
establish baseline for future monitoring
monitor factors that may limit selection for resistance:
avoid missed months
adherence to daily doses
diagnosis by RDT + prompt treatment of breakthrough cases
withdrawal of ASAQ from SMC areas
avoid under-dosing: dosing by age; exclusion of children >5yrs

7. Monitoring of molecular markers of resistance
finger-prick samples -> dried blood spots on filter paper
detection PCR on all samples
Pfdhps 437,540; Pfdhfr 108,59,51; PfCRT 76T; PfMDR1-86Y on positive samples
analyses in London using standardised methods

8. Molecular marker survey sites
Case-control studies 250 cases+controls in each site
Molecular marker survey sites

9. Methods DNA extraction using robotic platform
Pfcrt genotyping using real-time PCR using Hydrolysis probes
CVMNK, CVIET, SVMNT
Direct sequencing
Pfmdr1 (86 and 184) and 1246
Dhfr ( 51, 59 and 108)
Dhps (431, 436, 437, 540,581 and 613)

10. Samples Total samples Extracted Tested Positive Sequenced 30268 15,337
3118 (20.3%)
2324

11. Samples by country Country Total samples Extracted Tested Positive
Sequenced
Nigeria
4009
2880
713 (24.8%)
713
Guinea
3977
2880
627 (21.8%)
576
Niger
4470
2880
813 (28.2%)
480
Mali
4400
2880
768 (26.7%)
480
Chad
4392
1728
(6.8%) 96
Gambia
4460
2304 61
(2.60%)
Burkina Faso
4560
1440
960
110
(11.5%)

12. Prevalence of Pfcrt in Sub-Saharan Africa
NIGER
4 samples (0.14%), all from Niger, carried pfmdr1_YY but only one had CVMNK/CVIET

13. Baseline Prevalence of dhfr Mutations

14. Baseline Prevalence of dhps Mutations

15. Example: Baseline Prevalence of Molecular Markers in Niger
Key findings:
Low frequency of pfcrt_cviet (11%) and pfmdr1_YY (1%) were observed.
Low frequency of quadruple mutation (53%) were found.
Low frequency (0.2 %) of mutations associated with SP (triple_dhfr + double_dhps) were found
but none of these carried the AQ resistance (pfcrt_civet + pfmdr1_YY) haplotypes.

16. Summary
Large scale survey in 7 countries before scale-up of SMC, showed low frequencies of mutations associated with SP resistance, and no samples with AQ resistant genotypes
Prevalence of AQ markers reflects the drug combinations most used for first line malaria treatment in recent years
The results are consistent with the high clinical efficacy observed in case control studies in Gambia, Mali and Senegal
Repeat surveys in the same locations using the same sampling methods will be done at the end of the 2017 transmission season, to assess effects after 2 years of SMC at scale

17. Timings, intrepretation, and longer-term monitoring
mid 2016 – results from baseline available
mid 2018 – results from post SMC survey available
Evidence for loss of efficacy will be if:
Increased frequency of markers
Reduced efficacy or shortened duration of efficacy from case-control studies
Reduced impact in sentinel surveillance
Longer-term monitoring:
Regional coordination,
Methods standardisation,
Finance

18. Ceesay Serign Jawo
Kalifa Bojang
Jane Achan
Jean Bosco Ouedraogo
Issaka Zongo
Ogboi Sonny Johnbull
Tony Eloike
Abdoulaye Diallo
Jean Louis Ndiaye
Maman Laminou Ibrahim
Abdoulaye Djimde
Alassane Dicko
Issaka Sagara
Aliou Traore
Jean-Pierre Gami
Hamit Kessely BOURKOU
Kadidja Gamougam
Kovana Marcel Loua
Fassou Rene
Funder
Corinne Merle
Colin Sutherland Julian Muwanguzi Johanna Nader Leslie Choi Inke Lubis Ryan Henrici
Paul Milligan
Paul Snell
Matthew Cairns
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