Cryptosporidium and Giardia in surface water and drinking water: Animal sources and towards the use of a machine-learning approach as a tool for predicting contamination

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing

BACKGROUND

Amebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method in laboratories involves the microscopy of stool samples. However, this approach can sometimes result in the misinterpretation of amebiasis as other gastroenteritis (GE) conditions. The goal of the work is to produce a machine learning (ML) model that uses laboratory findings and demographic information to automatically predict amebiasis.

METHOD

Data extracted from Jordanian electronic medical records (EMR) between 2020 and 2022 comprised 763 amebic cases and 314 nonamebic cases. Patient demographics, clinical signs, microscopic diagnoses, and leukocyte counts were used to train eight decision tree algorithms and compare their accuracy of predictions. Feature ranking and correlation methods were implemented to enhance the accuracy of classifying amebiasis from other conditions.

RESULTS

The primary dependent variables distinguishing amebiasis include the percentage of neutrophils, mucus presence, and the counts of red blood cells (RBCs) and white blood cells (WBCs) in stool samples. Prediction accuracy and precision ranged from 92% to 94.6% when employing decision tree classifiers including decision tree (DT), random forest (RF), XGBoost, AdaBoost, and gradient boosting (GB). However, the optimized RF model demonstrated an area under the curve (AUC) of 98% for detecting amebiasis from laboratory data, utilizing only 300 estimators with a max depth of 20. This study highlights that amebiasis is a significant health concern in Jordan, responsible for 17.22% of all gastroenteritis episodes in this study. Male sex and age were associated with higher incidence of amebiasis (P = 0.014), with over 25% of cases occurring in infants and toddlers.

CONCLUSIONS

The application of ML to EMR can accurately predict amebiasis. This finding significantly contributes to the emerging use of ML as a decision support system in parasitic disease diagnosis.

Cryptosporidium Species Infections Detected from Fecal Samples of Animal and Human Hosts in South Africa: Systematic Review and Meta-Analysis

This study presents a systematic review and meta-analysis approach of Cryptosporidium species prevalence studies in animal and human hosts published between 1980 and 2020 in South Africa. Extensive searches were conducted on three electronic databases including PubMed, ScienceDirect and Google Scholar. The findings indicated an overall pooled prevalence estimate (PPE) of Cryptosporidium spp. infections in animals and humans at 21.5% and 18.1%, respectively. The PCR-RFLP appeared to be the most sensitive diagnostic method with a PPE of 77.8% for the detection of Cryptosporidium spp. infections followed by ELISA (66.7%); LAMP (45.4%); PCR (25.3%); qPCR (20.7%); microscopy (10.1%); IFAT (8.4%); and RDT (7.9%). In animal hosts, C. parvum had the highest PPE of 3.7%, followed by C. andersoni (1.5%), C. ubiquitum (1.4%) and C. bovis (1.0%), while in humans, C. parvum also had the highest PPE of 18.3% followed by C. meleagridis at 0.4%. The data generated in this study indicated that Cryptosporidium spp. infections were highly prevalent in both animals and humans in South Africa, especially in the KwaZulu-Natal and North West provinces. However, we further observed that there was a lack of prevalence studies for both animals and humans in some of the provinces. This study highlights the necessity for a "One Health" strategic approach promoting public hygiene, animal husbandry and regular screening for Cryptosporidium spp. infections in both animals and humans.

Food and Waterborne Cryptosporidiosis from a One Health Perspective: A Comprehensive Review

A sharp rise in the global population and improved lifestyles has led to questions about the quality of both food and water. Among protozoan parasites, Cryptosporidium is of great importance in this regard. Hence, Cryptosporidium's associated risk factors, its unique characteristics compared to other protozoan parasites, its zoonotic transmission, and associated economic losses in the public health and livestock sectors need to be focused on from a One Health perspective, including collaboration by experts from all three sectors. Cryptosporidium, being the fifth largest food threat, and the second largest cause of mortality in children under five years of age, is of great significance. The contamination of vegetables, fresh fruits, juices, unpasteurized raw milk, uncooked meat, and fish by Cryptosporidium oocysts occurs through infected food handlers, sewage-based contamination, agricultural effluents, infected animal manure being used as biofertilizer, etc., leading to severe foodborne outbreaks. The only Food and Drug Administration (FDA)-approved drug, Nitazoxanide (NTZ), provides inconsistent results in all groups of patients, and currently, there is no vaccine against it. The prime concerns of this review are to provide a deep insight into the Cryptosporidium's global burden, associated water- and foodborne outbreaks, and some future perspectives in an attempt to effectively manage this protozoal disease. A thorough literature search was performed to organize the most relevant, latest, and quantified data, justifying the title. The estimation of its true burden, strategies to break the transmission pathways and life cycle of Cryptosporidium, and the search for vaccine targets through genome editing technology represent some future research perspectives.

Cutting edge technology for wastewater treatment using smart nanomaterials: recent trends and futuristic advancements

Water is a vital component of our existence. Many human activities, such as improper waste disposal from households, industries, hospitals, and synthetic processes, are major contributors to the contamination of water streams. It is the responsibility of every individual to safeguard water resources and reduce pollution. Among the various available wastewater treatment (WWT) methods, smart nanomaterials stand out for their effectiveness in pollutant removal through absorption and adsorption. This paper examines the application of valuable smart nanomaterials in treating wastewater. Various nanomaterials, including cellulose nanocrystals (CNC), cellulose nanofibrils (CNF), nanoadsorbents, nanometals, nanofilters, nanocatalysts, carbon nanotubes (CNTs), nanosilver, nanotitanium dioxide, magnetic nanoparticles, nanozero-valent metallic nanoparticles, nanocomposites, nanofibers, and quantum dots, are identified as promising candidates for WWT. These smart nanomaterials efficiently eliminate toxic substances, microplastics, nanoplastics, and polythene particulates from wastewater. Additionally, the paper discusses comparative studies on the purification efficiency of nanoscience technology versus conventional methods.

Machine learning and explainable artificial intelligence for the prevention of waterborne cryptosporidiosis and giardiosis

Cryptosporidium and Giardia are important parasitic protozoa due to their zoonotic potential and impact on human health, and have often caused waterborne outbreaks of disease. Detection of (oo)cysts in water matrices is challenging and extremely costly, thus only few countries have legislated for regular monitoring of drinking water for their presence. Several attempts have been made trying to investigate the association between the presence of such (oo)cysts in waters with other biotic or abiotic factors, with inconclusive findings. In this regard, the aim of this study was the development of an holistic approach leveraging Machine Learning (ML) and eXplainable Artificial Intelligence (XAI) techniques, in order to provide empirical evidence related to the presence and prediction of Cryptosporidium oocysts and Giardia cysts in water samples. To meet this objective, we initially modelled the complex relationship between Cryptosporidium and Giardia (oo)cysts and a set of parasitological, microbiological, physicochemical and meteorological parameters via a model-agnostic meta-learner algorithm that provides flexibility regarding the selection of the ML model executing the fitting task. Based on this generic approach, a set of four well-known ML candidates were, empirically, evaluated in terms of their predictive capabilities. Then, the best-performed algorithms, were further examined through XAI techniques for gaining meaningful insights related to the explainability and interpretability of the derived solutions. The findings reveal that the Random Forest achieves the highest prediction performance when the objective is the prediction of both contamination and contamination intensity with Cryptosporidium oocysts in a given water sample, with meteorological/physicochemical and microbiological markers being informative, respectively. For the prediction of contamination with Giardia, the eXtreme Gradient Boosting with physicochemical parameters was the most efficient algorithm, while, the Support Vector Regression that takes into consideration both microbiological and meteorological markers was more efficient for evaluating the contamination intensity with cysts. The results of the study designate that the adoption of ML and XAI approaches can be considered as a valuable tool for unveiling the complicated correlation of the presence and contamination intensity with these zoonotic parasites that could constitute, in turn, a basis for the development of monitoring platforms and early warning systems for the prevention of waterborne disease outbreaks.

Domesticated animal reservoirs of Cryptosporidium and Giardia in agricultural farms in Laguna and Quezon provinces, Philippines

Cryptosporidium and Giardia are recognized as significant etiological agents of diarrheal outbreaks in humans as these parasites may be transmitted through the ingestion of water and food contaminated with feces of human or animal origin. However, surveillance studies on the role of animal reservoirs in the transmission of Cryptosporidium and Giardia are deemed insufficient and the complete dimension of the problem contributing to contamination in an agricultural setting is unknown. This study aimed to assess the presence of Cryptosporidium and Giardia in domesticated animals from selected farms in the agricultural provinces of Laguna and Quezon in Southern Luzon, Philippines. Using immunofluorescence assay, an overall 85.7% incidence of protozoan infection was recorded among the animals (N = 161). Of these, 77.0 and 73.9% were positive for Cryptosporidium and Giardia, respectively. Highest incidence (95.83%) of Cryptosporidium was documented in swine and the highest incidence (89.47%) of Giardia was observed in ruminants. Analyses revealed significant differences in the incidence of the protozoan parasites among animals with different containment status, water source, age group, and sex. On the other hand, farm workers' knowledge on parasite transmission was negatively correlated (p = 0.001) to parasite incidence. With the scarcity of data about Cryptosporidium and Giardia in farm-raised animals in the Philippines, the information obtained from this study will be vital for protozoan source tracking and further control interventions against Cryptosporidium and Giardia infections.

Prevalence and assemblage identified of Giardia duodenalis in zoo and farmed Asiatic black bears (Ursus thibetanus) from the Heilongjiang and Fujian Provinces of China

Captive and free-living wildlife serve as significant hosts for Giardia duodenalis. Asiatic black bears, valued for their economic and medicinal importance, are extensively farmed in China and also prevalent in zoos. However, studies on G. duodenalis in these animals in China are limited. Here, 218 feces samples of Asiatic black bears were collected: 36 from a zoo in Heilongjiang Province, and 182 from a farm in Fujian Province. Nested PCR of the SSU rRNA gene, followed by sequencing, was employed to determine the frequency and assemblage distribution of G. duodenalis. Positive samples underwent further analysis through multilocus genotyping (MLG) by amplifying the genes for glutamate dehydrogenase (gdh), β-giardin (bg), and triosephosphate isomerase (tpi). Of the 218 samples, G. duodenalis was detected in 22 cases at the SSU rRNA gene locus, including three from Heilongjiang and 19 from Fujian. Three assemblages were identified: A (n = 1), B (n = 16), and E (n = 2) in Fujian; and B (n = 3) in Heilongjiang. Out of the 22 positive samples, 20, 19, and 9 were effectively amplified and sequenced across the tpi, gdh, and bg loci, respectively. Seven samples were genotyped successfully at all three loci, identifying MLG-B1 (n = 1), MLG-B2 (n = 1), and MLG-B3 (n = 1), MLG-B4 (n = 1), MLG-B5 (n = 2), and MLG-B6 (n = 1) as the six assemblage B MLGs. This study marks the first documentation of G. duodenalis in Asiatic black bears in captivity in Fujian and Heilongjiang. The identification of zoonotic assemblages A and B, along with E, underscores potential public health concerns.

Assessment of pathogenic protozoa in a drinking water treatment plant with UV treatment

Controlling drinking water treatment processes is essential to address water contamination and the adaptability of certain pathogenic protozoa. Sometimes, standard treatment methods and chlorine disinfection may prove insufficient in eliminating pathogenic protozoa. However, ultraviolet (UV) radiation has proved to be more effective than chlorine. This study aims to characterize the eukaryotic community of a drinking water treatment plant that applies a final UV disinfection treatment, focusing on pathogenic protozoa. Fifty water samples (raw water, before and after UV treatment) were evaluated to comply with regulation parameters and identify relevant protozoa. Despite physicochemical and microbiological parameters meeting the regulation, some potentially pathogenic protozoa, such as Blastocystis or Cryptosporidium, were still detected in very low relative abundances in treated water. It was found for the first time in Spain the pathogenic amoebae Naegleria fowleri in one river water, which was not found after the treatment. Moreover, Blastocystis subtypes ST1-ST6 were detected in this study in raw, before and after UV water samples. Blastocystis was only found in 2 two samples after UV treatment, with a very low abundance (≤0.02%). Obtained results demonstrate the effectiveness of water treatment in reducing the prevalence of pathogenic protozoa.

Investigating the relationship between extreme weather and cryptosporidiosis and giardiasis in Colorado: A multi-decade study using distributed-lag nonlinear models

Environmentally-mediated protozoan diseases like cryptosporidiosis and giardiasis are likely to be highly impacted by extreme weather, as climate-related conditions like temperature and precipitation have been linked to their survival, distribution, and overall transmission success. Our aim was to investigate the relationship between extreme temperature and precipitation and cryptosporidiosis and giardiasis infection using monthly weather data and case reports from Colorado counties over a twenty-one year period. Data on reportable diseases and weather among Colorado counties were collected using the Colorado Electronic Disease Reporting System (CEDRS) and the Daily Surface Weather and Climatological Summaries (Daymet) Version 3 dataset, respectively. We used a conditional Poisson distributed-lag nonlinear modeling approach to estimate the lagged association (between 0 and 12-months) between relative temperature and precipitation extremes and the risk of cryptosporidiosis and giardiasis infection in Colorado counties between 1997 and 2017, relative to the risk found at average values of temperature and precipitation for a given county and month. We found distinctly different patterns in the associations between temperature extremes and cryptosporidiosis, versus temperature extremes and giardiasis. When maximum or minimum temperatures were high (90th percentile) or very high (95th percentile), we found a significant increase in cryptosporidiosis risk, but a significant decrease in giardiasis risk, relative to risk at the county and calendar-month mean. Conversely, we found very similar relationships between precipitation extremes and both cryptosporidiosis and giardiasis, which highlighted the prominent role of long-term (>8 months) lags. Our study presents novel insights on the influence that extreme temperature and precipitation can have on parasitic disease transmission in real-world settings. Additionally, we present preliminary evidence that the standard lag periods that are typically used in epidemiological studies to assess the impacts of extreme weather on cryptosporidiosis and giardiasis may not be capturing the entire relevant period.

Prevalence and molecular characterization of Giardia duodenalis in companion dogs, domestic livestock and wildlife in the Jordan Basin, Israel

Giardiasis is a small intestinal disease caused by the zoonotic parasite, Giardia duodenalis. This study presents the molecular findings of G. duodenalis infection in companion dogs, domestic livestock and wildlife in the Northern Jordan Basin, Israel. Identification of G. duodenalis was accomplished by nested PCR (nPCR) targeting the 18S rRNA gene. Samples were collected from water (five samples from four sources of which one was recycled water), as well as feces from wolves (Canis lupus) (n = 34), jackals (Canis aureus) (n = 24), wild boars (Sus scrofa) (n = 40), cattle (Bos taurus) (n = 40), dogs (Canis lupus familiaris) (n = 37) and nutria (Mayocastor coypus) (n = 100). All positive samples were sequenced and a phylogenetic tree was drawn using the Bayesian Inference (BI) algorithm. Differences in G. duodenalis prevalence between the different hosts were analyzed by Pearson's chi-square (p < 0.05). Of the total 275 fecal samples, 36 were positive for G. duodenalis (13%). Frequency rates among different animal species was highest in wolves (32.3%), whilst rates in wild boars (22.5%), dogs (16.2%), cattle (12.5%) and jackals (4.2%), were observed to be significantly lower (p < 0.001). Three out of 5 recycled water (RW) samples were G. duodenalis positive. Three clusters with high posterior probabilities (PP) were found in the BI: Cluster 1: samples from wolves, wild boars, water and cattle together with database sequences of assemblages A, B and F, Cluster 2: samples from dogs, nutria and a jackal with sequences from assemblage D and Cluster 3: samples from cattle, wild boars, wolves and dogs with sequences from assemblage C and D. We suggest that wolves serve as reservoirs of G. duodenalis in this region. The finding of Giardia in RW suggests that this vehicle may further contaminate crops intended for human consumption as this water source is used for agricultural irrigation.

Microbiological hazard identification in river waters used for recreational activities

Pathogenic bacteria, viruses, and parasites can cause waterborne disease outbreaks. The study of coastal water quality contributes to identifying potential risks to human health and to improving water management practices. The Río de la Plata River, a wide estuary in South America, is used for recreational activities, as a water source for consumption and as a site for sewage discharges. In the present study, as the first step of a quantitative microbial risk assessment of the coastal water quality of this river, a descriptive study was performed to identify the microbial pathogens prevalent in its waters and in the sewage discharged into the river. Two sites, representing two different potential risk scenarios, were chosen: a heavily polluted beach and an apparently safe beach. Conductivity and fecal contamination indicators including enterococci, Escherichia coli, F + RNA bacteriophages, and human polyomaviruses showed high levels. Regarding enterococci, differences between sites were significant (p-values <0.001). 93.3% and 56.5% of the apparently safe beach exceeded the recreational water limits for E. coli and enterococci. Regarding pathogens, diarrheagenic E. coli, Salmonella, and noroviruses were detected with different frequencies between sites. The parasites Cryptosporidium spp. and Giardia duodenalis were frequently detected in both sites. The results regarding viral, bacterial, and parasitic pathogens, even without correlation with conventional indicators, showed the importance of monitoring a variety of microorganisms to determine water quality more reliably and accurately, and to facilitate further studies of health risk assessment. The taxonomic description of microbial pathogens in river waters allow identifying the microorganisms that infect the population living on its shores but also pathogens not previously reported by the clinical surveillance system.

Cryptosporidium and agriculture: A review

Cryptosporidiosis is a significant contributor to global foodborne and waterborne disease burden. It is a widespread cause of diarrheal diseases that affect humans and animals worldwide. Agricultural environments can become a source of contamination with Cryptosporidium species through faecal material derived from humans and animals. This review aims to report the main findings of scientific research on Cryptosporidium species related to various agricultural sectors, and highlights the risks of cryptosporidiosis in agricultural production, the contamination sources, the importance of animal production in transmission, and the role of farmed animals as hosts of the parasites. Agricultural contamination sources can cause water pollution in groundwater and different surface waters used for drinking, recreational purposes, and irrigation. The application of contaminated manure, faecal sludge management, and irrigation with inadequately treated water are the main concerns associated with foodborne and waterborne cryptosporidiosis related to agricultural activities. The review emphasizes the public health implications of agriculture concerning the transmission risk of Cryptosporidium parasites and the urgent need for a new concept in the agriculture sector. Furthermore, the findings of this review provide valuable information for developing appropriate measures and monitoring strategies to minimize the risk of infection.

Fate of Cryptosporidium and Giardia through conventional and compact drinking water treatment plants

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.

Occurrence of Cryptosporidium oocysts in commercial oysters in southern Thailand

The enteric parasite Cryptosporidium is spread through the fecal-oral pathway, most commonly by the consumption of contaminated water but also through food. Because eating raw or barely cooked shellfish might put consumers at risk for cryptosporidiosis, identifying the parasite in oysters is important for public health. A total of 240 oysters, collected from two shellfish aquaculture sites in Thailand's Gulf coast, Nakhon Si Thammarat and Surat Thani, were tested for the presence of Cryptosporidium. Escherichia coli, enterococci, and thermotolerant coliform total levels were measured to assess seawater quality in the shellfish production regions. Oocysts of Cryptosporidium spp. were detected in 13.8% of the samples processed by immunofluorescence analyses. The detection of Cryptosporidium spp. oocysts in oysters obtained from Surat Thani (17.5%) was higher than in those obtained from Nakhon Si Thammarat (9.2%). The difference in detection of positive samples obtained from Nakhon Si Thammarat and those obtained from Surat Thani may be attributed to the effects of physical, ecological, and anthropogenic conditions, resulting in an increased level of marine water contamination by Cryptosporidium spp. oocysts. These findings demonstrate that native commercial oysters obtained from Thailand's southern Gulf coast contained Cryptosporidium spp. oocysts which might serve as a source of human infection. Consequently, these findings pose a serious public health concern and suggest that more quality control measures need to be implemented by the oyster aquaculture business to ensure the safety of seafood.

First report of Giardia duodenalis in pet rabbits in Brazil

Giardia duodenalis is a flagellate protozoan that multiplies in the small intestine of a wide variety of hosts, animals and humans. It has a worldwide distribution, however it is considered a neglected disease by the World Health Organization (WHO). Nowadays, rabbits are being chosen as pets, especially by children. There are already reports of the occurrence of G. duodenalis in rabbits from other countries, but research has not been carried out in Brazil yet. Thus, the objective of our work was to verify the occurrence and molecularly characterize G. duodenalis that affect pet rabbits, through the polymerase chain reaction (PCR) in the northwest region of the state of São Paulo, Brazil. Fecal samples from 100 rabbits were collected, which later underwent a process of DNA extraction and amplification by nested-PCR (nPCR), using the SSU rRNA gene, and β-giardin (bg), glutamate dehydrogenase (gdh) and triosephosphate isomerase (tpi) to determine the assemblage. A questionnaire was answered by the owners with information about gender, age, deworming, diarrhea, water source, food, place of residence and contact with other animals. From those samples, 40 were positive for G. duodenalis. Good quality of the SSU rRNA gene by nPCR were obtained from two samples. For the first time, we report the occurrence of G. duodenalis assemblage A on pet rabbits in Brazil.

Nowcasting of fecal coliform presence using an artificial neural network

At least 2 billion people worldwide use drinking water sources that are contaminated with feces, causing waterborne diseases; poor sanitation, poor hygiene, and unsafe drinking water result in a daily death rate of more than 800 children under 5 years of age from diarrheal diseases. This study shows the feasibility of a novel method to nowcast fecal coliforms' (FC) presence in drinking water sources by applying a multilayer perceptron artificial neuron network (MLP-ANN) model. The model gives a binary answer for FC presence or absence in drinking water sources using a minimum of water quality and geographical parameters, which can be monitored in real-time as predictors with low-cost and in-situ equipment. Using 51,400 samples to train, validate and test the model with temperature, pH, electrical conductivity, turbidity, dissolved oxygen, and total dissolved solids (TDS) as water-quality inputs and the water source type and location (as districts in India) as geographical inputs. The model achieved a total accuracy of 92.8% and a sensitivity of 98.2%, meaning that most FC-contaminated samples were classified correctly. In addition, precision reached 93.1%, meaning that most FC-contamination classifications were actually contaminated. The MLP-ANN performed better than the Linear Regression and K-Nearest Neighbors models, with lower accuracies of 90.2% and 91.0%, respectively. The MLP-ANN model could characterize the water quality geospatially, learn from the parameters whether the water is contaminated by FC, and predict with high accuracy on new testing data. This method can be used as a part of a sensor for FC monitoring and management in water, reducing the time gaps between routine lab testing and thus improving drinking water quality and addressing the SDG 6 targets.

Giardia duodenalis Styles, 1902 Prevalence in Cattle (Bos taurus Linnaeus, 1758) in Europe: A Systematic Review

Giardia duodenalis Styles, 1902 is an infectious agent which can cause enteritic disease in cattle (Bos taurus Linnaeus, 1758) worldwide. As a zoonotic protozoan, it is important to acknowledge Giardia prevalence and assemblages found in cattle and risk factors associated with the Giardia infection in herds. This systematic review aims to estimate the prevalence of G. duodenalis and its assemblages in cattle and to identify the risk factors associated with Giardia infection in cattle in Europe. A systematic review was performed according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to collect information from published studies in Europe. A total of 1414 studies were identified and 17 relevant studies were included in this review. Mean Giardia prevalence in cattle in Europe was 35.1%, with the highest prevalence found in neonatal animals (39.6%), but mean heard prevalence was 67.0%. Mixed infections of Giardia assemblages A and E were found most frequently (55.6%), while assemblages A and B were found more frequently in animals under 24 months old. Risk factors, such as deep litter with run-out, prolonged calf contact with the dam, and seasonality, such as winter and spring, were found to be potential risk factors for Giardia presence in the herds.

Performance of sewage treatment technologies for the removal of Cryptosporidium sp. and Giardia sp.: Toward water circularity

Cryptosporidium sp. and Giardia sp. are parasites that cause diseases in the population. Most of parasite diseases regarding the consumption of drinking water polluted with sewage are caused by Cryptosporidium sp. or Giardia sp. it is because of the incomplete disinfection of the wastewater treatment. Therefore, in this work the removal or inactivation efficiency of different treatment technologies presented by around 40 scientific studies was evaluated, with a view to water circularity. For Cryptosporidium sp., we conclude that the most efficient secondary technologies are aerobic technologies, which remove between 0.00 and 2.17 log units (Ulog), with activated sludge presenting the greatest efficiency, and that the tertiary technologies with the greatest removal are those that use ultrasound, which reach removal values of 3.17 Ulog. In the case of Giardia sp., the secondary technologies with the greatest removal are anaerobic technologies, with values between 0.00 and 3.80 Ulog, and the tertiary technologies with the greatest removal are those that combine filtration with UV or a chemical disinfection agent. Despite the removal values obtained, the greatest concern remains detecting and quantifying the infectious forms of both parasites in effluents; therefore, although the technologies perform adequately, discharge effluents must be monitored with more sensitive techniques, above all aiming for circularity of the treated water in a context of the water scarcity that affects some parts of the world.

Detection of Cryptosporidium spp. and Giardia spp. in Environmental Water Samples: A Journey into the Past and New Perspectives

Among the major issues linked with producing safe water for consumption is the presence of the parasitic protozoa Cryptosporidium spp. and Giardia spp. Since they are both responsible for gastrointestinal illnesses that can be waterborne, their monitoring is crucial, especially in water sources feeding treatment plants. Although their discovery was made in the early 1900s and even before, it was only in 1999 that the U.S. Environmental Protection Agency (EPA) published a standardized protocol for the detection of these parasites, modified and named today the U.S. EPA 1623.1 Method. It involves the flow-through filtration of a large volume of the water of interest, the elution of the biological material retained on the filter, the purification of the (oo)cysts, and the detection by immunofluorescence of the target parasites. Since the 1990s, several molecular-biology-based techniques were also developed to detect Cryptosporidium and Giardia cells from environmental or clinical samples. The application of U.S. EPA 1623.1 as well as numerous biomolecular methods are reviewed in this article, and their advantages and disadvantages are discussed guiding the readers, such as graduate students, researchers, drinking water managers, epidemiologists, and public health specialists, through the ever-expanding number of techniques available in the literature for the detection of Cryptosporidium spp. and Giardia spp. in water.

Association of Common Zoonotic Pathogens With Concentrated Animal Feeding Operations

Animal farming has intensified significantly in recent decades, with the emergence of concentrated animal feeding operations (CAFOs) in industrialized nations. The congregation of susceptible animals in CAFOs can lead to heavy environmental contamination with pathogens, promoting the emergence of hyper-transmissible, and virulent pathogens. As a result, CAFOs have been associated with emergence of highly pathogenic avian influenza viruses, hepatitis E virus, Escherichia coli O157:H7, Streptococcus suis, livestock-associated methicillin-resistant Staphylococcus aureus, and Cryptosporidium parvum in farm animals. This has led to increased transmission of zoonotic pathogens in humans and changes in disease patterns in general communities. They are exemplified by the common occurrence of outbreaks of illnesses through direct and indirect contact with farm animals, and wide occurrence of similar serotypes or subtypes in both humans and farm animals in industrialized nations. Therefore, control measures should be developed to slow down the dispersal of zoonotic pathogens associated with CAFOs and prevent the emergence of new pathogens of epidemic and pandemic potential.

Deactivation of Caenorhabditis elegans nematodes in drinking water by PMS/UV-C: efficiency and mechanisms

The occurrence and infestations of chlorine-resistant invertebrates in drinking water distributions have attracted concerns on water quality in China, making effective deactivation imperative. This study presents a novel strategy for nematode (Caenorhabditis elegans) deactivation using peroxymonosulfate (PMS)/UV-C. The results indicated that 100% deactivation efficiency was obtained under optimal conditions. An acidic pH and 0.25 mg/L Fe(II) were beneficial to the PMS/UV-C-triggered deactivation of nematodes. A mechanism study demonstrated that [Formula: see text] was activated by UV-C to produce ·OH and [Formula: see text], which resulted in oxidative stress and stimulated the occurrence of cell apoptosis, leading to nematode deactivation. The results reveal PMS/UV-C as an alternative to chlorination in water treatment plants (WTP) or an emergency application when chlorine-resistant invertebrates breed in a second-supply water tank is a promising strategy for disinfection. This approach possessed the advantages of avoiding the production of chlorine disinfection by-products (DBP) and greater efficacy of nematode deactivation. This work will provide ideas for on-going research efforts into chlorine-resistant invertebrate deactivation and eventually achieve the direct drinking of municipal tap water.

Uranium uptake from wastewater by the novel MnxTi1-xOy composite materials: Performance and mechanism

The novel Mn_xTi_1-xO_y composite materials with different mole ratios (Mn to Ti = 3:7, 5:5 and 7:3) were prepared to remove uranium species from wastewater. These composite materials were characterized by various techniques, such as thermogravimetric analysis (TG), X-ray diffraction (XRD), Fourier transformed infrared (FT-IR) and scanning electron microscopy (SEM). It was found that the chitosan in Mn_xTi_1-x-Chi were completely removed after calcination at 650 °C and Mn_xTi_1-xO_y composites possessed uniform distribution of the porous structure as well as plentiful hydroxyl-containing groups. Moreover, the as-prepared Mn_xTi_1-xO_y composite materials were applied to remove uranium from solution to evaluate the adsorption performance. It was found that the Mn_0.5Ti_0.5O_y possessed relatively excellent uptake performance for uranium comparing with the Mn_0.3Ti_0.7O_y and Mn_0.7Ti_0.3O_y and its maximum uptake capacity and efficiency reach 695.2 mg/g and 98.6% (pH = 4, m/V = 0.1 g/L, T = 298 K), respectively, which were much superior than most of reported materials based on titanium oxide or manganese oxide. Besides, the uranium uptake on Mn_0.5Ti_0.5O_y was independent on ionic strength and it had considerable reusability, which might be the necessary condition for Mn_0.5Ti_0.5O_y to be applied in uranium uptake from uranium-containing wastewater. As a candidate adsorbent, Mn_0.5Ti_0.5O_y possessed a high potentiality to remove uranium from wastewater.

The risk factors for intestinal Giardia spp infection: Global systematic review and meta-analysis and meta-regression

Parasitic infections are a public health concern as they can cause aggression, growth retardation, weight loss, anemia, and other health problems. In this study, a systematic review and meta-analysis were performed to find an association between the probable social-environmental risk factors including lack of safe drinking water, no hand washing, sex, age, no access to education, no access to toilet, and Giardia spp infection. We conducted literature research among international databases including Scopus, PubMed, Web of Science and Cochrane from1 January 1995 to March 15, 2020, including 23 articles with 102 studies while the odds ratio (OR) was calculated using 2 × 2 tables or extracted. The pooled effect size with 95% confidence intervals (CIs) was estimated using a random or fixed-effects model. The results show a significant association between intestinal Giardia spp infection risk and lack of safe drinking water (OR: 1.14; 95%CI: 1.02-1.25); no access to toilet (OR: 1.22; 95%CI: 1.07-1.37); and age (2-10 vs 10-30 year) (OR: 1.42; 95%CI: 1.09-1.78). An insignificant association was observed between intestinal Giardia spp infection risk and age (<2 vs 2-10 year) (OR: 0.89; 95%CI: 0.75-1.02); no access to education (OR: 1.10; 95%CI: 0.80-1.40); Sex (male vs female) (OR: 1.04; 95%CI: 0.74-1.34); and no handwashing (OR: 1.18; 95%CI: 0.87-1.49). The results of meta-regression also indicate that intestinal Giardia spp infection has decreased over time (C= -0.024, p-value = 0.03) significantly, and also by growth of human development index (HDI) (C= - 0.42, p-value = 0.29) insignificantly. Improvement of personal hygiene, sanitation and raising public awareness can be effective in reducing Giardia spp infections.

Occurrence of Cryptosporidium and Giardia in surface water supply from 2016 to 2020 in South Brazil

The objectives of this research are to evaluate Giardia and Cryptosporidium contamination in surface water supply in Rio Grande do Sul (RS) State in South Brazil in the years 2016 to 2020, assess seasonality, and to infer the population that may have been exposed to these protozoa through drinking water based on drinking water treatment efficiency. Data were obtained through the drinking water surveillance national information system. From 204 DWT plants in the state, 66 have been analyzed for protozoa. A total of 2304 analyses of protozoa in raw water were evaluated, of which 223 had both Giardia spp. cysts and/or Cryptosporidium spp. oocysts in concentrations that varied from 0.1 to 21.5/L. A total of 2,712,125 people from 48 cities were at risk of having the presence of pathogenic protozoa in their drinking water. The probability of finding these protozoa was higher in winter. Giardia cysts were more likely to be found in a period without rain, suggesting that sewage was the main source of contamination. It is concluded that the springs of Rio Grande do Sul are impacted and the circulation of pathogenic protozoa through the territory is endemic with a probable source of contamination to sewage and livestock activity.

Cryptosporidium spp. and Giardia spp. (oo)cysts as target-organisms in sanitation and environmental monitoring: A review in microscopy-based viability assays

Cysts and (oo)cysts are the infective forms of parasitic protozoa, as Giardia and Cryptosporidium, which are widespread and associated to worldwide waterborne diseases outbreaks. These microorganisms pose a challenge to public health, as they are resistant to conventional disinfection methods, which make them important parameters when evaluating inactivation efficiency. However, when (oo)cysts are targets, it is challenging to infer inactivation efficacy, as it may require infectivity tests that are not often an option for laboratory routine analysis. In this scene, (oo)cyst viability based on induced excystation, membrane integrity and enzyme activity evaluated by dye inclusion and/or exclusion, as well as fluorescence reduction consist on microscopy-based techniques that may be options to estimate inactivation in the environmental context. This scoping review presents applications, advantages and limitations of these methodologies for viability assessment, in order to shed light on the (oo)cyst viability topic and provide insight strategies for choosing protocols in the environmental and sanitation field, in laboratory applications and novel research.

Pre-ozonation of surface water: An effective water treatment process to reduce the risk of infection by Giardia in drinking water

Giardia is a protozoan parasite of primary concern for the drinking water industry. High contact times are required for Giardia inactivation by chlorination, while ozonation may be effective at much lower Ct products. In this study, we have assessed the occurrence of Giardia cysts in raw water, and in chlorinated or ozonated water from a drinking water treatment plant (DWTP) in Brazil, over a 16-month period. Moreover, we analyzed the effects of primary disinfection on cysts, and calculated the infection risk caused by the occurrence of Giardia cysts in raw water, chlorinated or ozonated water. Furthermore, we assessed the correlation of Giardia cysts with indicator bacteria in raw water. Data referring to concentration of Giardia cysts in raw water showed adherence to a gamma distribution at a significance level α = 0.05. The detection frequency and the mean concentration of Giardia cysts were higher in raw water (86.6%, 26 cysts∙L^-1), than in chlorinated (46.1%, 15.7 cysts·L^-1) or ozonated water (43.5%, 11.1 cysts·L^-1). Overall, Giardia non-viable cysts were detected more frequently in ozonated water (80%) than in chlorinated water (68.2%) or raw water (37.7%). Ozonation and chlorination resulted, respectively, in ≈27.5- and ≈13- fold reduction of Giardia infection risk, when compared to the risk calculated for raw water. Total coliform and Escherichia coli proved to be suitable surrogates to predict the occurrence of Giardia cysts in raw surface water, however, the indicator bacteria may not be suitable surrogates to predict the disinfection of Giardia cysts, as no correlation was found between indicator bacteria and Giardia cysts in treated water. To our knowledge, this is the first study reporting the efficacy of chlorine and ozone at Ct products actually applied at a full-scale drinking water treatment plant against Giardia cysts naturally occurring in the source water, i.e. real situation. Ozonation has proven more efficient than chlorination against Giardia cysts in surface water. Escherichia coli proved to be suitable surrogate to predict Giardia cysts in raw surface water.