Abstract
Over the past three decades, a notable rise in the occurrence of enteric protozoan pathogens, especially Giardia and Cryptosporidium spp., in drinking water sources has been observed. This rise could be attributed not only to an actual increase in water contamination but also to improvements in detection methods. These waterborne pathogens have played a pivotal role in disease outbreaks and the overall escalation of disease rates in both developed and developing nations worldwide. Consequently, the control of waterborne diseases has become a vital component of public health policies and a primary objective of drinking water treatment plants (DWTPs). Limited studies applied real-time PCR (qPCR) and/or immunofluorescence assay (IFA) for monitoring Giardia and Cryptosporidium spp., particularly in developing countries like Egypt. Water samples from two conventional drinking water treatment plants and two compact units (CUs) were analyzed using both IFA and qPCR methods to detect Giardia and Cryptosporidium. Using qPCR and IFA, the conventional DWTPs showed complete removal of Giardia and Cryptosporidium, whereas Mansheyat Alqanater and Niklah CUs achieved only partial removal. Specifically, Cryptosporidium gene copies removal rates were 33.33% and 60% for Mansheyat Alqanater and Niklah CUs, respectively. Niklah CU also removed 50% of Giardia gene copies, but no Giardia gene copies were removed by Mansheyat Alqanater CU. Using IFA, both Mansheyat Alqanater and Niklah CUs showed a similar removal rate of 50% for Giardia cysts. Additionally, Niklah CU achieved a 50% removal of Cryptosporidium oocysts, whereas Mansheyat Alqanater CU did not show any removal of Cryptosporidium oocysts. Conventional DWTPs were more effective than CUs in removing enteric protozoa. The contamination of drinking water by enteric pathogenic protozoa remains a significant issue globally, leading to increased disease rates. Infectious disease surveillance in drinking water is an important epidemiological tool to monitor the health of a population.