Table 6.

Applications of microbial subtyping in low-resource settings.

Approaches applied	Microorganisms attributed	Dominant sources identified		Countries	References
		Reservoirs (subtyping evidence)	Vehicles
Microbial subtyping—MLST*	NTS*	Humans (NTS genotypes from human & animals did not overlap)	–#	The Gambia	(231)
Microbial subtyping—PFGE*+ AMR* profiles + plasmid typing		Humans (different PFGE patterns of NTS genomic DNA from human & poultry; 64.2% of NTS from human were resistant to antibiotics vs. all NTS from livestock and environment were susceptible)	–%	Kenya	(232)
		Humans (65.6% matching of NTS between people of contacts and index cases based on AMR profiles, and plasmid typing; matched PFGE patterns between index cases and people of contacts. 1.7% matching between NTS from environment sources and index cases)	–%		(233)
Microbial subtyping—PFGE*		Wildlife (Other than one wild species, all PFGE patterns of isolates from these animals were matched to an established pattern of human)	–#	South Africa	(234)
Microbial subtyping—PFGE*+ phage typing		Poultry (NTS isolates from poultry and humans owned the same phage type and their PFGE patterns were clustered)	–#	Burkina Faso	(235)

^* MLST, multi-locus sequence typing; PFGE, pulsed-field gel electrophoresis; NTS, non-typhoidal Salmonella; AMR, antimicrobial resistance.

^% Environmental samples for source attribution were taken from this study to investigate potential vehicles, but no NTS were isolated from these samples or attribution patterns between isolates from the environment and humans were different.

^#This study conducted source attribution only at the reservoir level and environmental samples were not taken.