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Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. [ABSTRACT FROM AUTHOR]

Water-borne pathogens such as Cryptosporidium pose a significant human health risk and catchments provide the first critical pollution ‘barrier’ in mitigating risk in drinking water supply. In this paper we apply an adaptive management framework to mitigating Cryptosporidium risk in source water using a case study of the Myponga catchment in South Australia. Firstly, we evaluated the effectiveness of past water quality management programs in relation to the adoption of practices by landholders using a socio-economic survey of land use and management in the catchment. The impact of past management on the mitigation of Cryptosporidium risk in source water was also evaluated based on analysis of water quality monitoring data. Quantitative risk assessment was used in planning the next round of management in the adaptive cycle. Specifically, a pathogen budget model was used to identify the major remaining sources of Cryptosporidium in the catchment and estimate the mitigation impact of 30 alternative catchment management scenarios. Survey results show that earlier programs have resulted in the comprehensive adoption of best management practices by dairy farmers including exclusion of stock from watercourses and effluent management from 2000 to 2007. Whilst median Cryptosporidium concentrations in source water have decreased since 2004 they remain above target levels and put pressure on other barriers to mitigate risk, particularly the treatment plant. Non-dairy calves were identified as the major remaining source of Cryptosporidium in the Myponga catchment. The restriction of watercourse access of non-dairy calves could achieve a further reduction in Cryptosporidium export to the Myponga reservoir of around 90% from current levels. The adaptive management framework applied in this study was useful in guiding learning from past management, and in analysing, planning and refocussing the next round of catchment management strategies to achieve water quality targets. [Copyright &y& Elsevier]

Background: To determine the prevalence of enteric infections in Aboriginal children aged 0-2 years using conventional and molecular diagnostic techniques and to explore associations between the presence of pathogens and child growth.Methods: Cross-sectional analysis of Aboriginal children (n = 62) residing in a remote community in Northern Australia, conducted from July 24th - October 30th 2017. Stool samples were analysed for organisms by microscopy (directly in the field and following fixation and storage in sodium-acetate formalin), and by qualitative PCR for viruses, bacteria and parasites and serology for Strongyloides-specific IgG. Child growth (height and weight) was measured and z scores calculated according to WHO growth standards.Results: Nearly 60% of children had evidence for at least one enteric pathogen in their stool (37/62). The highest burden of infection was with adenovirus/sapovirus (22.9%), followed by astrovirus (9.8%) and Cryptosporidium hominis/parvum (8.2%). Non-pathogenic organisms were detected in 22.5% of children. Ten percent of children had diarrhea at the time of stool collection. Infection with two or more pathogens was negatively associated with height for age z scores (- 1.34, 95% CI - 2.61 to - 0.07), as was carriage of the non-pathogen Blastocystis hominis (- 2.05, 95% CI - 3.55 to - 0.54).Conclusions: Infants and toddlers living in this remote Northern Australian Aboriginal community had a high burden of enteric pathogens and non-pathogens. The association between carriage of pathogens/non-pathogens with impaired child growth in the critical first 1000 days of life has implications for healthy child growth and development and warrants further investigation. These findings have relevance for many other First Nations Communities that face many of the same challenges with regard to poverty, infections, and malnutrition. [ABSTRACT FROM AUTHOR]

Cryptosporidiosis causes gastroenteritis and is transmitted to humans via contaminated water and food, and contact with infected animals and people. We analyse long-term cryptosporidiosis patterns across Australia (2001–2012) and review published Australian studies and jurisdictional health bulletins to identify high risk populations and potential risk factors for disease. Using national data on reported cryptosporidiosis, the average annual rate of reported illness was 12.8 cases per 100 000 population, with cycles of high and low reporting years. Reports of illness peak in summer, similar to other infectious gastrointestinal diseases. States with high livestock densities like New South Wales and Queensland also record a spring peak in illnesses. Children aged less than four years have the highest rates of disease, along with adult females. Rates of reported cryptosporidiosis are highest in the warmer, remote regions and in Aboriginal and Torres Strait Islander populations. Our review of 34 published studies and seven health department reports on cryptosporidiosis in Australia highlights a lack of long term, non-outbreak studies in these regions and populations, with an emphasis on outbreaks and risk factors in urban areas. The high disease rates in remote, tropical and subtropical areas and in Aboriginal and Torres Strait Islander populations underscore the need to develop interventions that target the sources of infection, seasonal exposures and risk factors for cryptosporidiosis in these settings. Spatial epidemiology can provide an evidence base to identify priorities for intervention to prevent and control cryptosporidiosis in high risk populations. [ABSTRACT FROM AUTHOR]