Volume 97, Issue 4
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645



Lack of adequate sanitation results in fecal contamination of the environment and poses a risk of disease transmission via multiple exposure pathways. To better understand how eight different sources contribute to overall exposure to fecal contamination, we quantified exposure through multiple pathways for children under 5 years old in four high-density, low-income, urban neighborhoods in Accra, Ghana. We collected more than 500 hours of structured observation of behaviors of 156 children, 800 household surveys, and 1,855 environmental samples. Data were analyzed using Bayesian models, estimating the environmental and behavioral factors associated with exposure to fecal contamination. These estimates were applied in exposure models simulating sequences of behaviors and transfers of fecal indicators. This approach allows us to identify the contribution of any sources of fecal contamination in the environment to child exposure and use dynamic fecal microbe transfer networks to track fecal indicators from the environment to oral ingestion. The contributions of different sources to exposure were categorized into four types (high/low by dose and frequency), as a basis for ranking pathways by the potential to reduce exposure. Although we observed variation in estimated exposure (10–10 CFU/day for ) between different age groups and neighborhoods, the greatest contribution was consistently from food (contributing > 99.9% to total exposure). Hands played a pivotal role in fecal microbe transfer, linking environmental sources to oral ingestion. The fecal microbe transfer network constructed here provides a systematic approach to study the complex interaction between contaminated environment and human behavior on exposure to fecal contamination.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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  1. Cohen Hubal EA, Sheldon LS, Burke JM, McCurdy TR, Berry MR, Rigas ML, Zartarian GV, Freeman NC, , 2000. Children’s exposure assessment: a review of factors influencing children’s exposure, and the data available to characterize and assess that exposure. Environ Health Perspect 188: 475486.[Crossref] [Google Scholar]
  2. Pickering AJ, Julian TR, Marks SJ, Mattioli MC, Boehm AB, Schwab KJ, Davis J, , 2012. Fecal contamination and diarrheal pathogens on surfaces and in soils among Tanzanian households with and without improved sanitation. Environ Sci Technol 46: 57365743.[Crossref] [Google Scholar]
  3. Liu L, ., 2012. Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000. Lancet 379: 21512161.[Crossref] [Google Scholar]
  4. Moe CL, Rheingans RD, , 2006. Global challenges in water, sanitation and health. J Water Health 4: 4157. [Google Scholar]
  5. Arnold BF, ., 2013. Cluster-randomised controlled trials of individual and combined water, sanitation, hygiene and nutritional interventions in rural Bangladesh and Kenya: the wash benefits study design and rationale. BMJ Open 3: e003476.[Crossref] [Google Scholar]
  6. Fewtrell L, Kaufmann RB, Kay D, Enanoria W, Haller L, Colford JMJ, , 2005. Water, sanitation, and hygiene interventions to reduce diarrhoea in less developed countries: a systematic review and meta-analysis. Lancet Infect Dis 5: 4252.[Crossref] [Google Scholar]
  7. Briscoe J, , 1984. Intervention studies and the definition of dominant transmission routes. Am J Epidemiol 120: 449455.[Crossref] [Google Scholar]
  8. Robb K, Null C, Teunis PFM, Yakubu H, Armah G, Moe CL, , 2017. Assessment of fecal exposure pathways in low-income urban neighborhoods in Accra, Ghana: rationale, design, methods and key findings of the SaniPath Study. Am J Trop Med Hyg 97: 10221034. [Google Scholar]
  9. Humphrey JH, Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team., , 2015. The sanitation hygiene infant nutrition efficacy (shine) trial: rationale, design, and methods. Clin Infect Dis 61: S685S702.[Crossref] [Google Scholar]
  10. Ngure FM, Reid BM, Humphrey JH, Mbuya MN, Pelto G, Stoltzfus RJ, , 2014. Water, sanitation, and hygiene (wash), environmental enteropathy, nutrition, and early child development: making the links. Ann N Y Acad Sci 1308: 118128.[Crossref] [Google Scholar]
  11. Haas CN, Rose JB, Gerba CP, , 2014. Quantitative Microbial Risk Assessment, 2nd edition. New York, NY: Wiley. ISBN 978-1-118-14529-6.
  12. Marks HM, Coleman ME, Lin CTJ, Roberts T, , 1998. Topics in microbial risk assessment: dynamic flow tree process. Risk Anal 18: 309328.[Crossref] [Google Scholar]
  13. Teunis PFM, Nagelkerke NJD, Haas CN, , 1999. Dose response models for infectious gastroenteritis. Risk Anal 19: 12511260. [Google Scholar]
  14. Gibbons CL, Burden of Communicable diseases in Europe (BCoDE) consortium., , 2014. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health 14: 147.[Crossref] [Google Scholar]
  15. Teunis PFM, Reese HE, Null C, Yakubu H, Moe CL, , 2016. Quantifying contact with the environment: behaviors of young children in Accra, Ghana. Am J Trop Med Hyg 94: 920931.[Crossref] [Google Scholar]
  16. Cohen Hubal EA, Suggs JC, Nishioka MG, Ivancic WA, , 2005. Characterizing residue transfer efficiencies using a fluorescent imaging technique. J Expo Anal Environ Epidemiol 15: 261270.[Crossref] [Google Scholar]
  17. R Core Team, 2013. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. Available at: http://www.R-project.org/. ISBN 3-900051-07-0. Accessed December 19, 2014.
  18. Haas CN, , 1996. How to average microbial densities to characterize risk. Water Res 30: 10361038.[Crossref] [Google Scholar]
  19. Peprah D, Baker KK, Moe C, Robb K, Wellington N, Yakubu H, Null C, , 2015. Public toilets and their customers in low-income Accra, Ghana. Environ Urban 27: 589604.[Crossref] [Google Scholar]
  20. Kumar GS, Kar SS, Jain A, , 2011. Health and environmental sanitation in India: issues for prioritizing control strategies. Indian J Occup Environ Med 15: 9396.[Crossref] [Google Scholar]
  21. Parascandola M, Weed DL, , 2001. Causation in epidemiology. J Epidemiol Community Health 55: 905912.[Crossref] [Google Scholar]
  22. Ghana Statistical Service Ghana Health Service ICF Macro, , , 2009. Ghana Demographic and Health Survey, 2008. Accra, Ghana: GSS, GHS, and ICF Macro.
  23. Arifeen S, Black RE, Antelman G, Baqui A, Caulfield L, Becker S, , 2001. Exclusive breastfeeding reduces acute respiratory infection and diarrhea deaths among infants in Dhaka slums. Pediatrics 108: E67.[Crossref] [Google Scholar]
  24. Ochoa TJ, ., 2009. Age-related susceptibility to infection with diarrheagenic Escherichia coli among infants from Periurban areas in Lima, Peru. Nephrol Dial Transplant 49: 16941702. [Google Scholar]
  25. Institute of Statistical, Social and Economic Research, 2011. Multiple Indicator Cluster Survey in 5 High Densely Populated Localities, 2010–2011. Final Report. Accra, Ghana: ISSER.
  26. Genser B, Strina A, Teles CA, Prado MS, Barreto ML, , 2006. Risk factors for childhood diarrhea incidence: dynamic analysis of a longitudinal study. Epidemiology 17: 658667.[Crossref] [Google Scholar]
  27. Genser B, Strina A, dos Santos LA, Teles CA, Prado MS, Cairncross S, Barreto ML, , 2008. Impact of a city-wide sanitation intervention in a large urban centre on social, environmental and behavioural determinants of childhood diarrhoea: analysis of two cohort studies. Int J Epidemiol 37: 831840.[Crossref] [Google Scholar]
  28. Pickering AJ, ., 2010. Hands, water, and health: fecal contamination in Tanzanian communities with improved, non-networked water supplies. Environ Sci Technol 44: 32673272.[Crossref] [Google Scholar]
  29. FAO/WHO, 2006. FAO/WHO Guidance to Governments on the Application of HACCP in Small and/or Less Developed Food Businesses. Available at: http://apps.who.int/iris/bitstream/10665/43598/1/9789241595032_eng.pdf?ua=1. Accessed December 19, 2014.
  30. FAO/WHO, 2006. Food Safety Risk Analysis. A Guide for National Food Safety Authorities. Available at: http://www.fao.org/docrep/012/a0822e/a0822e.pdf. Accessed December 19, 2014.
  31. Westrell T, Schönning C, Stenstrøm TA, Ashbolt NJ, , 2004. QMRA (quantitative microbial risk assessment) and HACCP (hazard analysis and critical control points) for management of pathogens in wastewater and sewage sludge treatment and reuse. Water Sci Technol 50: 2330. [Google Scholar]
  32. Mbuya MNN, Humphrey JH, , 2015. Preventing environmental enteric dysfunction through improved water, sanitation and hygiene: an opportunity for stunting reduction in developing countries. Matern Child Nutr 12: 106120.[Crossref] [Google Scholar]
  33. Cairncross S, Valdmanis V, , 2006. Water supply, sanitation, and hygiene promotion. Jamison DT, Breman JG, Measham AR, Alleyne G, Claeson M, Evans DB, Jha P, Mills A, Musgrove P, eds., Disease Control Priorities in Developing Countries, 2nd edition, chap. 41. Washington, DC: World Bank.
  34. Moe CL, Sobsey MD, Samsa GP, Mesolo V, , 1991. Bacterial indicators of risk of diarrhoeal disease from drinking-water in the Philippines. Bull World Health Organ 69: 305317. [Google Scholar]
  35. Haas CN, , 1983. Estimation of risk due to low doses of microorganisms: a comparison of alternative methodologies. Am J Epidemiol 118: 573582.[Crossref] [Google Scholar]
  36. Haas CN, Thayyar-Madabusi A, Rose JB, Gerba CP, , 2000. Development of a dose-response relationship for Escherichia coli o157:h7. Int J Food Microbiol 56: 23.[Crossref] [Google Scholar]
  37. Teunis PFM, Havelaar AH, , 2000. The Beta Poisson dose-response model is not a single-hit model. Risk Anal 20: 513520.[Crossref] [Google Scholar]
  38. Teunis PFM, Takumi K, Shinagawa K, , 2004. Dose response for infection by Escherichia coli O157:H7 from outbreak data. Risk Anal 24: 401407.[Crossref] [Google Scholar]
  39. Havelaar AH, Swart AN, , 2014. Impact of acquired immunity and dose-dependent probability of illness on quantitative microbial risk assessment. Risk Anal 34: 18071819.[Crossref] [Google Scholar]
  40. Drechsel P, Keraita B, , 2014. Irrigated Urban Vegetable Production in Ghana: Characteristics, Benefits and Risk Mitigation, 2nd edition. Colombo, Sri Lanka: International Water Management Institute (IWMI).
  41. Ghana Statistical Service, 2012. 2010 Population & Housing Census. Accra, Ghana: Ghana Statistical Service.
  42. Strande L, Ronteltap M, Brdjanovic D, (eds.), 2014. Faecal Sludge Management (FSM) Book - Systems Approach for Implementation and Operation. London, United Kingdom: IWA Publishing. ISBN 9781780404738.
  43. Keraita B, Konradsen F, Dreschel P, , 2010. Farm-Based Measures for Reducing Microbiological Health Risks for Consumers from Informal Wastewater-Irrigated Agriculture. Sri Lanka: International Water Management Institute.
  44. Mensah P, Yeboah-Manu D, Owusu-Darko K, Ablordey A, , 2002. Street foods in Accra, Ghana: how safe are they? Bull World Health Organ 80: 546554. [Google Scholar]
  45. Machdar E, van der Steen NP, Raschid-Sally L, Lens PNL, , 2013. Application of quantitative microbial risk assessment to analyze the public health risk from poor drinking water quality in a low income area in Accra, Ghana. Sci Total Environ 449: 134142.[Crossref] [Google Scholar]
  46. Labite H, Lunani I, van der Steen P, Vairavamoorthy K, Drechsel P, Lens P, , 2010. Quantitative microbial risk analysis to evaluate health effects of interventions in the urban water system of Accra, Ghana. J Water Health 8: 417430.[Crossref] [Google Scholar]

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  • Received : 19 May 2016
  • Accepted : 21 Jun 2017
  • Published online : 21 Aug 2017

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