EMA-amplicon-based sequencing informs risk assessment analysis of water treatment systems.

Illumina amplicon-based sequencing was coupled with ethidium monoazide bromide (EMA) pre-treatment to monitor the total viable bacterial community and subsequently identify and prioritise the target organisms for the health risk assessment of the untreated rainwater and rainwater treated using large-volume batch solar reactor prototypes installed in an informal settlement and rural farming community. Taxonomic assignments indicated that Legionella and Pseudomonas were the most frequently detected genera containing opportunistic bacterial pathogens in the untreated and treated rainwater at both sites. Additionally, Mycobacterium, Clostridium sensu stricto and Escherichia/Shigella displayed high (≥80%) detection frequencies in the untreated and/or treated rainwater samples at one or both sites. Numerous exposure scenarios (e.g. drinking, cleaning) were subsequently investigated and the health risk of using untreated and solar reactor treated rainwater in developing countries was quantified based on the presence of L. pneumophila, P. aeruginosa and E. coli. The solar reactor prototypes were able to reduce the health risk associated with E. coli and P. aeruginosa to below the 1 × 10−4 annual benchmark limit for all the non-potable uses of rainwater within the target communities (exception of showering for E. coli). However, the risk associated with intentional drinking of untreated or treated rainwater exceeded the benchmark limit (E. coli and P. aeruginosa). Additionally, while the solar reactor treatment reduced the risk associated with garden hosing and showering based on the presence of L. pneumophila, the risk estimates for both activities still exceeded the annual benchmark limit. The large-volume batch solar reactor prototypes were thus able to reduce the risk posed by the target bacteria for non-potable activities rainwater is commonly used for in water scarce regions of sub-Saharan Africa. This study highlights the need to assess water treatment systems in field trials using QMRA.