Animal Waste, Water Quality and Human Health

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GIARDIASISRose et al. (1991) fitted the “simple exponential model” to infections exhibited byvolunteers in studies reported by Rendtorff (1954) and Rendtorff & Holt (1954),using the exponential dose response model in which Pr infection =1– e −rd where d isagain the average dose given to each group of volunteers and r is the probability thata single Giardia cyst could cause infection. They obtained r = 0.01982. Thereforethe ID 50 = –ln(½)/r = 0.693/r ≈ 35.CRYPTOSPORIDIOSISComparative risk analysis 393Clinical trials for infectivity of oocysts of Cryptosporidium parvum were done as partof a set of three studies in the Medical School of the University of Texas. 9 Individualanalyses for each set have generally indicated that the appropriate dose-response curveis the single-parameter “simple exponential model”. But a meta-analysis has identifieddifferent infectivity levels when fitting a number of candidate curves to each trial’sdataset, such that the differences depend on the particular isolate used and on themethod of “passaging” the Cryptosporidium in the laboratory (Teunis et al. 2002a,2002b). Having regard to all these studies USEPA (2003), in developing its “LongTerm 2 Enhanced Surface Water Treatment Rule” for drinking water, concluded thatthe dose-response function (for infection, cf. illness) should indeed be of “simpleexponential” form, with a particular value of its single parameter (r = 0.09). Thisgives rise to ID 50 ≈ 8. However, two further studies have since been reported. 10Teunis (2009) has interpreted all five studies together, together with a sixth, 11 andthis (omitting the infectious TU502 Crypto. hominis data, because it has a humansource) leads to a conclusion that on average the ID 50 for Cryptosporidium can betaken as approximately the same as is inferred for Giardia (i.e., about 35).PATHOGENS IN ANIMAL EXCRETAThe following material has been particularly guided by information presented by Solleret al. (2010) and USEPA (2010), along with some other published literature. Chapter 3of this text gives further detailed information.Tables A10.1–A10.5 present summaries of studies of prevalence and concentrationof the five pathogens considered in this chapter, each including the four animal groups91011These studies were conducted for the TAMU, Iowa and ICP isolates (Okhuysen et al. 1999).The Moredun Crypto. parvum isolate (Okhuysen et al. 2002) and the TU502 Crypto. hominis isolate(Chappell et al. 2006).The 16W (Crypto. parvum) isolate.
394Animal Waste, Water Quality and Human HealthTable A10.1 Campylobacter.Reference Prevalence (%) Concentration NotesCattleBerry et al. (2007) 2.2–14.9 – Beef cattle feedlotsBesser et al. (2005) 1.6–62.2 – Beef cattle feedlotsBrown et al. (2004) 36 – Rural Cheshire, UKDevane et al. (2005) 97.8 – New Zealand dairy cattle (all positive for C.jejuni)Hakkinen & Hänninen (2009) 49.7 – Substantial differences between herdsHutchison et al. (2004/5) 12.8 320 cfu/g (g.m.) Fresh composite farm manure, UK. max. =1.5 × 10 5 cfu/gKwan et al. (2008) 35.9 – Five NW England farms, prevalence range =26.4% (winter) to 50.8% (summer)McAllister et al. (2005) 30–47 – Cows (Ontario, Canada)41.7 – Calves (British Columbia, Canada)McAllister et al. (2005) 41.7 – CanadaMoriarty et al. (2008) – 430 cfu/g (med.) New Zealand: Concentration range15–1.8 × 10 7 cfu/gStanley et al. (1998a) – 610 MPN/g (ave.) UK beef cattle at slaughter– 69.9 MPN/g (ave.) UK cows– 33,000 MPN/g (ave.) UK calvesSwineDorner et al. (2004) 45.9, 79.7 – Canadian sows and gilts (females, not yetmated)Hutchison et al. (2004/5) 13.5 310 cfu/g (g.m.) Fresh composite farm manure, UK. max. =1.5 × 10 4 cfu/g(Continued)
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Emerging Issues in Water and Infect
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3Zoonotic waterborne pathogen loads
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Zoonotic waterborne pathogen loads
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the cause of a variety of food- and
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4Zoonotic waterbornepathogens in li
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Zoonotic waterborne pathogens in li
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controlling E. coli-associated diar
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5Transport of microbial pollution i
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Transport of microbial pollution in
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7ExposureWill Robertson and Gordon
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Exposure 259main components influen
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Exposure 261rainfall events (Atherh
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Exposure 263contact activities, the
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Exposure 265Table 7.1 Notable studi
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Exposure 267Table 7.2 Notable studi
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Exposure 269water than zoonotic pat
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Exposure 2711999). As suggested by
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Exposure 273leptospirosis is primar
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are severely underreported. As with
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Exposure 277duodenalis in surface w
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Exposure 279Keeley, A. and Faulkner
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Exposure 281Schultz-Fademrecht, C.,
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IndexAgricultural runoff, 122, 168,
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Index 463Biogas, 137-139, 291Bio-se
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Index 465Critical control points, 1
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Index 467290-291, 293, 295, 300, 30
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Index 469Hazard detection, 285Hazar
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Index 471pathogens, 2, 4-14, 17-21,
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Index 473Probiotics, 132-133Protozo
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Index 475Molecular, 16, 19, 22, 27,
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