Decision-makers in developing communities
often lack credible data
to inform decisions related to water, sanitation, and hygiene. Quantitative
microbial risk assessment (QMRA), which quantifies pathogen-related
health risks across exposure routes, can be informative; however,
the utility of QMRA for decision-making is often undermined by data
gaps. This work integrates QMRA, uncertainty and sensitivity analyses,
and household surveys in Bwaise, Kampala (Uganda) to characterize
the implications of censored data management, identify sources of
uncertainty, and incorporate risk perceptions to improve the suitability
of QMRA for informal settlements or similar settings. In Bwaise, drinking
water, hand rinse, and soil samples were collected from 45 households
and supplemented with data from 844 surveys. Quantified pathogen (adenovirus, Campylobacter jejuni, and Shigella spp./EIEC) concentrations were used with QMRA to model infection
risks from exposure through drinking water, hand-to-mouth contact,
and soil ingestion. Health risks were most sensitive to pathogen data,
hand-to-mouth contact frequency, and dose–response models (particularly C. jejuni). When managing censored data, results
from upper limits of detection, half of limits of detection, and uniform
distributions returned similar results, which deviated from lower
limits of detection and maximum likelihood estimation imputation approaches.
Finally, risk perceptions (e.g., it is unsafe to drink directly from
a water source) were identified to inform risk management.