Laboratory of Parasitology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, B-9820, Merelbeke, Belgium; Laboratory of Infectious and Parasitic Diseases, Veterinary Research Institute, Hellenic Agricultural Organization - DEMETER, 57001, Thermi, Thessaloniki, Greece.
Laboratory of Parasitology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, B-9820, Merelbeke, Belgium.
Environ Pollut. 2020 Sep;264:114766. doi: 10.1016/j.envpol.2020.114766. Epub 2020 May 11.
Cryptosporidium and Giardia are important parasites due to their zoonotic potential and impact on human health, often causing waterborne outbreaks of disease. Detection of (oo)cysts in water matrices is challenging and few countries have legislated water monitoring for their presence. The aim of this study was to investigate the presence and origin of these parasites in different water sources in Northern Greece and identify interactions between biotic/abiotic factors in order to develop risk-assessment models. During a 2-year period, using a longitudinal, repeated sampling approach, 12 locations in 4 rivers, irrigation canals, and a water production company, were monitored for Cryptosporidium and Giardia, using standard methods. Furthermore, 254 faecal samples from animals were collected from 15 cattle and 12 sheep farms located near the water sampling points and screened for both parasites, in order to estimate their potential contribution to water contamination. River water samples were frequently contaminated with Cryptosporidium (47.1%) and Giardia (66.2%), with higher contamination rates during winter and spring. During a 5-month period, (oo)cysts were detected in drinking-water (<1/litre). Animals on all farms were infected by both parasites, with 16.7% of calves and 17.2% of lambs excreting Cryptosporidium oocysts and 41.3% of calves and 43.1% of lambs excreting Giardia cysts. The most prevalent species identified in both water and animal samples were C. parvum and G. duodenalis assemblage AII. The presence of G. duodenalis assemblage AII in drinking water and C. parvum IIaA15G2R1 in surface water highlights the potential risk of waterborne infection. No correlation was found between (oo)cyst counts and faecal-indicator bacteria. Machine-learning models that can predict contamination intensity with Cryptosporidium (75% accuracy) and Giardia (69% accuracy), combining biological, physicochemical and meteorological factors, were developed. Although these prediction accuracies may be insufficient for public health purposes, they could be useful for augmenting and informing risk-based sampling plans.
隐孢子虫和贾第鞭毛虫是重要的寄生虫，因为它们具有动物源性和对人类健康的影响，经常导致水源性疾病爆发。在水基质中检测（oo）囊壳具有挑战性，并且很少有国家立法监测其存在。本研究旨在调查希腊北部不同水源中这些寄生虫的存在和来源，并确定生物/非生物因素之间的相互作用，以开发风险评估模型。
在为期两年的时间里，使用纵向、重复采样方法，对 4 条河流、灌溉渠和一家水生产公司的 12 个地点进行了隐孢子虫和贾第鞭毛虫监测，使用标准方法。此外，从靠近水采样点的 15 个牛场和 12 个绵羊场采集了 254 份动物粪便样本，用于筛查这两种寄生虫，以估计它们对水污染的潜在贡献。
河流水样经常受到隐孢子虫（47.1%）和贾第鞭毛虫（66.2%）的污染，冬季和春季污染率较高。在 5 个月的时间里，饮用水中（<1/升）检测到（oo）囊壳。所有农场的动物都感染了这两种寄生虫，16.7%的犊牛和 17.2%的羔羊排出隐孢子虫卵囊，41.3%的犊牛和 43.1%的羔羊排出贾第鞭毛虫囊。在水和动物样本中鉴定出的最常见的物种是小隐孢子虫和贝氏隐孢子虫 AII 组合。饮用水中存在贝氏隐孢子虫 AII 和地表水中存在小隐孢子虫 IIaA15G2R1 突出了水源性感染的潜在风险。（oo）囊壳计数与粪便指示细菌之间没有相关性。
结合生物、物理化学和气象因素，开发了可以预测隐孢子虫（75%准确率）和贾第鞭毛虫（69%准确率）污染强度的机器学习模型。尽管这些预测准确率可能不足以用于公共卫生目的，但它们可能有助于补充和告知基于风险的采样计划。
