Navigating Data Uncertainty and Modeling Assumptions in Quantitative Microbial Risk Assessment in an Informal Settlement in Kampala, Uganda

Diana M. Byrne, Kerry A. Hamilton, Stephanie A. Houser, Muwonge Mubasira, David Katende, Hannah A.C. Lohman, John T. Trimmer, Noble Banadda, Assata Zerai, Jeremy S. Guest

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish
Pages (from-to)5463-5474
Number of pages12
JournalEnvironmental Science and Technology
Issue number8
StatePublished - Apr 20 2021

Bibliographical note

Funding Information:
First, the authors would like to thank everyone from Bwaise who participated in this research. Additionally, this work was made possible by Community Integrated Development Initiatives and the Uganda Rural Community Support Foundation (Kampala, Uganda). The authors thank the students from the Department of Agricultural and Biological Engineering at Makerere University who assisted with survey data collection and also Eugene Manda (Makerere University) for the assistance with laboratory work. They wish her a wonderful retirement! Instrumentation for qPCR was provided by the Roy J. Carver Biotechnology Center. This research was funded by the Social and Behavioral Sciences Initiative and Campus Research Board, both supported by the Office of the Vice Chancellor for Research and Innovation, UIUC. D.M.B. and H.A.C.L. were supported by the National Science Foundation Graduate Research Fellowship Program. J.T.T. was supported by the Illinois Distinguished Fellowship at UIUC.

Publisher Copyright:
© 2021 American Chemical Society. All rights reserved.

ASJC Scopus subject areas

  • Chemistry (all)
  • Environmental Chemistry


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