Epidemiology and Strain Variation of Cryptosporidium

Chalmers, Rachel M.; Casemore, D.P.

doi:10.1007/1-4020-7878-1_3

Cited by 2 publications

(2 citation statements)

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“…Cryptosporidium hominis, C. parvum are the two most frequently identified species in cryptosporidiosis cases in developed countries, representing over 90% of the cases (Bouzid et al, 2013). Cryptosporidium hominis is largely restricted to human hosts, and therefore has low zoonotic potential (Chalmers and Casemore, 2004). Cryptosporidium parvum has been detected in both animals (wild and livestock) and humans, and is a major pathogen in calves (Bouzid et al, 2013, Hashim et al, 2006.…”

Section: Taxonomymentioning

confidence: 99%

“…Cryptosporidium parvum has been detected in both animals (wild and livestock) and humans, and is a major pathogen in calves (Bouzid et al, 2013, Hashim et al, 2006. Cryptosporidium felis, and C. canis are most commonly associated with feline and canine hosts, respectively (Chalmers and Casemore, 2004). Cryptosporidium meleagridis is associated with avian hosts including turkeys, parrots and chickens but also has been associated with a small number (<1%) of human cases of cryptosporidiosis (Chappell et al, 2011).…”

Section: Taxonomymentioning

confidence: 99%

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Taking the ‘poo’ out of ‘pool’: participatory systems modelling as a decision-support tool for even the messiest public environmental health problems

Currie¹

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It is widely recognised that environmental health services and interventions operate in dynamically complex systems. Environmental health researchers and practitioners work to solve complex problems yet continue to favour methods that eschew the concept of complexity. Conventional quantitative risk assessment methods used in environmental health, while valuable, are often based on studies that examine the effects of individual environmental hazards in isolation. They do not examine a system that leads to adverse environmental health outcomes, such as disease outbreaks. In this research, I explored the applicability of participatory system dynamic modelling as a means of assisting environmental health decision-makers in the management of dynamically complex infectious diseases. Using cryptosporidiosis in South East Queensland as a case study, I applied system dynamic modelling techniques to explore the population-level drivers of Cryptosporidium transmission in the study area, with a particular focus on the role of public aquatic facilities (i.e. public swimming pools). This research was conducted in three stages. This first involved an extensive review of the literature on complexity and environmental health service delivery, decision-making for complex environmental health problems, and system dynamic modelling. This review highlighted current challenges environmental health decision-makers face when developing policies and interventions and identified ways in which system dynamic models can assist in overcoming some of these.

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