Identification and quantification of pathogenic helminth eggs using a digital image system

Occurrence of parasites in waters used for crops irrigation and vegetables from the Savannah of Bogotá, Colombia

The World Health Organization (WHO) has established as a criterion of parasitological quality for irrigation water, ≤ 1 helminth egg/liter, which guarantees the safety in agricultural products. In this study, the presence of parasites in surface water used for irrigation of crops (n = 96) and vegetables (celery and lettuce) (n = 120), from the Former La Ramada irrigation district, was evaluated using conventional and molecular parasitological methods. Our findings showed contamination of irrigation systems in the study area with domestic wastewater, demonstrated by the presence of Ancylostomatidae eggs, Ascaris spp., Hymenolepis spp., Trichuris spp., Capillaria spp., Giardia spp. cysts, and oocysts of Toxoplasma gondii and Cryptosporidium spp. A prevalence of 33% and 23.3% was calculated for helminths and protozoa, respectively in vegetables, representing a possible risk to human and animal health in relation to these parasites. These findings show the need for continuous monitoring of the water quality used for crop irrigation, as well as the safety of food, taking into account the values established in national and international regulations.

A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization

Diagnosis of soil-transmitted helminth (STH) and schistosome infections relies largely on conventional microscopy which has limited sensitivity, requires highly trained personnel and is error-prone. Rapid advances in miniaturization of optical systems, sensors and processors have enhanced research and development of digital and automated microscopes suitable for the detection of these diseases in resource-limited settings. While some studies have reported proof-of-principle results, others have evaluated the performance of working prototypes in field settings. The extensive commercialization of these innovative devices has, however, not yet been achieved. This review provides an overview of recent publications (2010–2022) on innovative field applicable optical devices which can be used for the diagnosis of STH and schistosome infections. Using an adapted technology readiness level (TRL) scale taking into account the WHO target product profile (TPP) for these diseases, the developmental stages of the devices were ranked to determine the readiness for practical applications in field settings. From the reviewed 18 articles, 19 innovative optical devices were identified and ranked. Almost all of the devices (85%) were ranked with a TRL score below 8 indicating that, most of the devices are not ready for commercialization and field use. The potential limitations of these innovative devices were discussed. We believe that the outcome of this review can guide the end-to-end development of automated digital microscopes aligned with the WHO TPP for the diagnosis of STH and schistosome infections in resource-limited settings.

Microalgae-based wastewater treatment - Microalgae-bacteria consortia, multi-omics approaches and algal stress response

Sustainable environmental management is one of the important aspects of sustainable development goals. Increasing amounts of wastewaters (WW) from exponential economic growth is a major challenge, and conventional treatment methods entail a huge carbon footprint in terms of energy use and GHG emissions. Microalgae-based WW treatment is a potential candidate for sustainable WW treatment. The nutrients which are otherwise unutilized in the conventional processes are recovered in the beneficial microalgal biomass. This review presents comprehensive information regarding the potential of microalgae as sustainable bioremediation agents. Microalgae-bacterial consortia play a critical role in synergistic nutrient removal, supported by the complex nutritional and metabolite exchange between microalgae and the associated bacteria. Design of effective microalgae-bacteria consortia either by screening or by recent technologies such as synthetic biology approaches are highly required for efficient WW treatment. Furthermore, this review discusses the crucial research gap in microalgal WW treatment - the application of a multi-omics platform for understanding microalgal response towards WW conditions and the design of effective microalgal or microalgae-bacteria consortia based on genetic information. While metagenomics helps in the identification and monitoring of the microbial community throughout the treatment process, transcriptomics, proteomics and metabolomics aid in studying the algal cellular response towards the nutrients and pollutants in WW. It has been established that the integration of microalgal processes into conventional WW treatment systems is feasible. In this direction, future research directions for microalgal WW treatment emphasize the need for identifying the niche in WW treatment, while highlighting the pilot sale plants in existence. Microalgae-based WW treatment could be a potential phase in the waste hierarchy of circular economy and sustainability, considering WWs are a rich secondary source of finite resources such as nitrogen and phosphorus.

Comparison of Human Intestinal Parasite Ova Segmentation Using Machine Learning and Deep Learning Techniques

Helminthiasis disease is one of the most serious health problems in the world and frequently occurs in children, especially in unhygienic conditions. The manual diagnosis method is time consuming and challenging, especially when there are a large number of samples. An automated system is acknowledged as a quick and easy technique to assess helminth sample images by offering direct visibility on the computer monitor without the requirement for examination under a microscope. Thus, this paper aims to compare the human intestinal parasite ova segmentation performance between machine learning segmentation and deep learning segmentation. Four types of helminth ova are tested, which are Ascaris Lumbricoides Ova (ALO), Enterobious Vermicularis Ova (EVO), Hookworm Ova (HWO), and Trichuris Trichiura Ova (TTO). In this paper, fuzzy c-Mean (FCM) segmentation technique is used in machine learning segmentation, while convolutional neural network (CNN) segmentation technique is used for deep learning. The performance of segmentation algorithms based on FCM and CNN segmentation techniques is investigated and compared to select the best segmentation procedure for helminth ova detection. The results reveal that the accuracy obtained for each helminth species is in the range of 97% to 100% for both techniques. However, IoU analysis showed that CNN based on ResNet technique performed better than FCM for ALO, EVO, and TTO with values of 75.80%, 55.48%, and 77.06%, respectively. Therefore, segmentation through deep learning is more suitable for segmenting the human intestinal parasite ova.

A new diagnostic approach to fast-track and increase the accessibility of gastrointestinal nematode identification from faeces: FECPAKG2 egg nemabiome metabarcoding

Effective gastrointestinal nematode (GIN) management in livestock industries is becoming increasingly difficult due to the rise of anthelmintic resistance and changes in the temporal and geographical distribution of major GINs. Underpinning the response to these challenges is the need for a fast-tracked diagnostic identification technique, making it easier for livestock producers to make informed GIN management decisions. The traditional 'gold-standard' approach, larval culture followed by morphological differentiation, is laborious and potentially inaccurate. We developed a new diagnostic approach to identify GINs that integrates a remote-location digital faecal egg count platform, FECPAK^G2, with internal transcribed spacer 2 (ITS2) nemabiome metabarcoding. The technique involves a quick and simple protocol to harvest concentrated strongyle eggs from the FECPAK^G2 cassette utilising a repurposed pipette tip, followed by DNA isolation and Illumina next generation amplicon sequencing. The GIN compositions and alpha diversity generated by our FECPAK^G2 egg nemabiome metabarcoding approach was not significantly different to traditional morphological larval differentiation and nemabiome metabarcoding of larval and faecal samples. We demonstrated that storing FECPAK^G2 harvested eggs in either DNA isolation lysis buffer or 80% ethanol (v/v) had no impact on GIN identification outcomes for at least 60 days; enabling the transport of biological samples from their remote origins to a molecular diagnostic facility for nemabiome metabarcoding, in the absence of a cold chain. We discovered that sustained GIN egg embryonation in the lysis buffer storage solution lead to higher yields of DNA compared with ethanol-stored GIN eggs or faeces with GIN eggs. Taking advantage of an already well-established platform such as FECPAK^G2, and providing the livestock producers that use it with the option to identify GINs in their samples and contribute to large-scale GIN distribution and/or anthelmintic resistance surveys, is an important future direction for the FECPAK^G2 egg nemabiome metabarcoding approach.

Diagnostic tools for the detection of taeniid eggs in different environmental matrices: A systematic review

The cestode family Taeniidae consists of the genera Echinococcus and Taenia, both of which include zoonotic tapeworms of serious public health importance. Various environmental matrices have been identified from which parasite transmission to animals and humans can occur, and many techniques for detecting taeniid eggs in different environments have been developed. However, the majority lack appropriate validation, and standardized egg isolation procedures are absent. This hampers interstudy comparisons and poses a challenge for future researchers when deciding which technique to implement for assessing taeniid egg contamination in a particular matrix. Therefore, the aim of this systematic review was to present an overview of the detection methods for taeniid eggs in the environment, to discuss and compare them, and to provide recommendations for future studies. In total, 1814 publications were retrieved from scientific databases, and, ultimately, data were systematically reviewed from 90 papers. The results provide an overview of numerous diagnostic tests for taeniid egg detection in (or on) water, food, soil, insects, objects, and air. These tools could be categorized as either conventional (light microscopy), molecular, or immunodetection tools. The relatively cheap microscopy techniques often lack sensitivity and are unable to identify a taeniid egg at the genus level. Nevertheless, several records ascribed a genus, or even species, to taeniid eggs that had been detected by light microscopy. Molecular and immunodetection tools offer better specificity, but still rely on the preceding egg recovery steps that also affect overall sensitivity. Finally, the majority of the methods lacked any attempt at performance evaluation and standardization, especially at the earlier stages of the analysis (e.g., sampling strategy, storage conditions, egg recovery), and viability was rarely addressed. As such, our review highlights the need for standardized, validated detection tools, that not only assess the extent of environmental contamination, but also the egg genus or species, and address viability.

•

The cestode family Taeniidae contains species of serious public health importance.

•

Parasite transmission may occur from several environmental matrices.

•

Many methods for environmental detection of taeniid eggs have been developed.

•

These often lack standardization, performance evaluation, and viability assessment.

Automated Diagnostics: Advances in the Diagnosis of Intestinal Parasitic Infections in Humans and Animals

The increasingly close proximity between people and animals is of great concern for public health, given the risk of exposure to infectious diseases transmitted through animals, which are carriers of more than 60 zoonotic agents. These diseases, which are included in the list of Neglected Tropical Diseases, cause losses in countries with tropical and subtropical climates, and in regions with temperate climates. Indeed, they affect more than a billion people around the world, a large proportion of which are infected by one or more parasitic helminths, causing annual losses of billions of dollars. Several studies are being conducted in search for differentiated, more sensitive diagnostics with fewer errors. These studies, which involve the automated examination of intestinal parasites, still face challenges that must be overcome in order to ensure the proper identification of parasites. This includes a protocol that allows for elimination of most of the debris in samples, satisfactory staining of parasite structures, and a robust image database. Our objective here is therefore to offer a critical description of the techniques currently in use for the automated diagnosis of intestinal parasites in fecal samples, as well as advances in these techniques.

Helminth egg analysis platform (HEAP): An opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures

BACKGROUND

Millions of people throughout the world suffer from parasite infections. Traditionally, technicians use manual eye inspection of microscopic specimens to perform a parasite examination. However, manual operations have limitations that hinder the ability to obtain precise egg counts and cause inefficient identification of infected parasites on co-infections. The technician requirements for handling a large number of microscopic examinations in countries that have limited medical resources are substantial. We developed the helminth egg analysis platform (HEAP) as a user-friendly microscopic helminth eggs identification and quantification platform to assist medical technicians during parasite infection examination.

METHODS

Multiple deep learning strategies including SSD (Single Shot MultiBox Detector), U-net, and Faster R-CNN (Faster Region-based Convolutional Neural Network) are integrated to identify the same specimen allowing users to choose the best predictions. An image binning and egg-in-edge algorithm based on pixel density detection was developed to increase the performance. Computers with different operation systems can be gathered to lower the computation time using our easy-to-deploy software architecture.

RESULTS

A user-friendly interface is provided to substantially increase the efficiency of manual validation. To adapt to low-cost computers, we architected a distributed computing structure with high flexibilities.

CONCLUSIONS

HEAP serves not only as a prediction service provider but also as a parasitic egg database of microscopic helminth egg image collection, labeling data and pretrained models. All images and labeling resources are free and accessible at http://heap.cgu.edu.tw. HEAP can also be an ideal education and training resource for helminth egg examination.

Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection

Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a decreased sensitivity in low transmission settings and it is labour intensive. Visual reading of Kato-Katz preparations requires the samples to be analyzed in a short period of time since its preparation. Digitizing the samples could provide a solution which allows to store the samples in a digital database and perform remote analysis. Artificial intelligence (AI) methods based on digitized samples can support diagnosis by performing an objective and automatic quantification of disease infection. In this work, we propose an end-to-end pipeline for microscopy image digitization and automatic analysis of digitized images of STH. Our solution includes (a) a digitization system based on a mobile app that digitizes microscope samples using a 3D printed microscope adapter, (b) a telemedicine platform for remote analysis and labelling, and (c) novel deep learning algorithms for automatic assessment and quantification of parasitological infections by STH. The deep learning algorithm has been trained and tested on 51 slides of stool samples containing 949 Trichuris spp. eggs from 6 different subjects. The algorithm evaluation was performed using a cross-validation strategy, obtaining a mean precision of 98.44% and a mean recall of 80.94%. The results also proved the potential of generalization capability of the method at identifying different types of helminth eggs. Additionally, the AI-assisted quantification of STH based on digitized samples has been compared to the one performed using conventional microscopy, showing a good agreement between measurements. In conclusion, this work has presented a comprehensive pipeline using smartphone-assisted microscopy. It is integrated with a telemedicine platform for automatic image analysis and quantification of STH infection using AI models.

Diagnostic Techniques for Soil-Transmitted Helminths - Recent Advances

Soil-transmitted helminth (STH) infections (hookworms, Trichuris, Ascaris) and Strongyloides spp. are associated with a substantial global burden and high morbidity. Sensitive and specific methods for diagnosis of these infections are essential for mapping the burden in communities, accurate assessment of infection levels, to guide interventions and monitoring the success of STH control programs. Despite considerable progress to control STH over several decades, we are still far from identifying a fully adequate diagnostic test. Conventional microscopy-based methods such as direct Kato–Katz smear or mounts after stool centrifugation/flotation-based concentration techniques have been the mainstay of diagnosis, especially in resource-poor countries where these infections abound. However, recently, these are being adapted to closed, easy to perform, digital formats, thereby improving the sensitivity as well as applicability in a remote, resource-limited setting. The use of image analysis systems to identify and quantify helminth eggs, with potential adaptation to smartphones, is also promising. Antibody detection tests have a limited role mostly in the case of Strongyloides hyperinfection. Coproantigen detection tests have been developed and used in veterinary practice for detection of STH, but these have not been evaluated for use in humans. More sensitive molecular diagnostics, including assays developed with new bioinformatic tools and techniques such as polymerase chain reaction (PCR), quantitative PCR (qPCR) and loop-mediated amplification assay, can help in the clear and precise assessment of STH burden during elimination phase and are of immense value for diagnosis in areas with low endemicity and in travelers to endemic regions. Moreover, the molecular techniques will help detect new species that may emerge. Sample preservation and efficient DNA extraction are critical and significantly affect the efficiency of molecular diagnostic tests. In addition to the diagnosis of clinical or asymptomatic infection in humans, detection of STH eggs in environmental samples is imperative to boost STH control efforts. Overall the diagnostic performance, cost-effectiveness, ease of performance, rapidity and in-field applicability of any test should be considered when choosing from the various diagnostic assays in areas with different endemicity, in addition to striving towards the development of novel technologies and optimization of existing methods.

Photo-assisted electrochemical advanced oxidation processes for the disinfection of aqueous solutions: A review

Disinfection is usually the final step in water treatment and its effectiveness is of paramount importance in ensuring public health. Chlorination, ultraviolet (UV) irradiation and ozone (O3) are currently the most common methods for water disinfection; however, the generation of toxic by-products and the non-remnant effect of UV and O3 still constitute major drawbacks. Photo-assisted electrochemical advanced oxidation processes (EAOPs) on the other hand, appear as a potentially effective option for water disinfection. In these processes, the synergism between electrochemically produced active species and photo-generated radicals, improve their performance when compared with the corresponding separate processes and with other physical or chemical approaches. In photo-assisted EAOPs the inactivation of pathogens takes place by means of mechanisms that occur at different distances from the anode, that is: (i) directly at the electrode's surface (direct oxidation), (ii) at the anode's vicinity by means of electrochemically generated hydroxyl radical species (quasi-direct), (iii) or at the bulk solution (away from the electrode surface) by photo-electrogenerated active species (indirect oxidation). This review addresses state of the art reports concerning the inactivation of pathogens in water by means of photo-assisted EAOPs such as photo-electrocatalytic process, photo-assisted electrochemical oxidation, photo-electrocoagulation and cathodic processes. By focusing on the oxidation mechanism, it was found that while quasi-direct oxidation is the preponderant inactivation mechanism, the photo-electrocatalytic process using semiconductor materials is the most studied method as revealed by numerous reports in the literature. Advantages, disadvantages, trends and perspectives for water disinfection in photo-assisted EAOPs are also analyzed in this work.

Application of Dendrimers for Treating Parasitic Diseases

Despite advances in medical knowledge, parasitic diseases remain a significant global health burden and their pharmacological treatment is often hampered by drug toxicity. Therefore, drug delivery systems may provide useful advantages when used in combination with conventional therapeutic compounds. Dendrimers are three-dimensional polymeric structures, characterized by a central core, branches and terminal functional groups. These nanostructures are known for their defined structure, great water solubility, biocompatibility and high encapsulation ability against a wide range of molecules. Furthermore, the high ratio between terminal groups and molecular volume render them a hopeful vector for drug delivery. These nanostructures offer several advantages compared to conventional drugs for the treatment of parasitic infection. Dendrimers deliver drugs to target sites with reduced dosage, solving side effects that occur with accepted marketed drugs. In recent years, extensive progress has been made towards the use of dendrimers for therapeutic, prophylactic and diagnostic purposes for the management of parasitic infections. The present review highlights the potential of several dendrimers in the management of parasitic diseases.

The Control of Zoonotic Soil-Transmitted Helminthoses Using Saprophytic Fungi

Soil-transmitted helminths (STHs) are parasites transmitted through contact with soil contaminated with their infective eggs/larvae. People are infected by exposure to human-specific species or animal species (zoonotic agents). Fecal samples containing eggs of Ascaris suum or Lemurostrongylus sp. were sprayed with spores of the soil saprophytic filamentous fungi Clonostachys rosea (CR) and Trichoderma atrobrunneum (TA). The antagonistic effect was assessed by estimating the viability of eggs and their developmental rate. Compared to the controls (unexposed to fungi), the viability of the eggs of A. suum was halved in CR and decreased by two thirds in TA, while the viability of the eggs of Lemurostrongylus sp. was reduced by one quarter and one third in CR and TA treatments, respectively. The Soil Contamination Index (SCI), defined as the viable eggs that attained the infective stage, reached the highest percentages for A. suum in the controls after four weeks (66%), with 21% in CL and 11% in TA. For Lemurostrongylus sp., the values were 80%, 49%, and 41% for control, CR and TA treatments, respectively. We concluded that spreading spores of C. rosea or T. atrobrunneum directly onto the feces of animal species represents a sustainable approach under a One Health context to potentially reduce the risk of zoonotic STHs in humans.

Helminth Egg Automatic Detector (HEAD): Improvements in development for digital identification and quantification of Helminth eggs and its application online

Conventional analytical techniques for evaluating Helminth eggs are based on different steps to concentrate them in a pellet for direct observation and quantification under a light microscope, which can generate under-counts or over-counts and be time consuming. To enhance this process, a new approach via automatic identification was implemented in which various image processing detectors were developed and incorporated into a Helminth Egg Automatic Detector (HEAD) system. This allowed the identification and quantification of pathogenic eggs of global medical importance. More than 2.6 billion people are currently affected and infected, and this results in approximately 80,000 child deaths each year. As a result, since 1980 the World Health Organization (WHO) has implemented guidelines, regulations and criteria for the control of the health risk. After the initial release of the analytical technique, two improvements were developed in the detector: first, a texture verification process that reduced the number of false positive results; and second, the establishment of the optimal thresholds for each species. In addition, the software was made available on a free platform. After performing an internal statistical verification of the system, testing with internationally recognized parasitology laboratories was carried out, Subsequently, the HEAD System is capable of identifying and quantifying different species of Helminth eggs in different environmental samples: wastewater, sludge, biosolids, excreta and soil, with in-service sensitivity and specificity values for the open library for machine learning TensorFlow (TF) model of 96.82% and 97.96% respectively. The current iteration uses AutoML Vision (a computer platform for the automatization of machine learning models, making it easier to train, optimize and export results to cloud applications or devices). It represents a useful and cheap tool that could be utilized by environmental monitoring facilities and laboratories around the world.•The HEAD Software will significantly reduce the costs associated with the detection and quantification of helminth eggs to a high level of accuracy.•It represents a tool, not only for microbiologists and researchers, but also for various agencies involved in sanitation, such as environmental regulation agencies, which currently require highly trained technicians.•The simplicity of the device contributes to the control the contamination of water, soil, and crops, even in poor and isolated communities.

Helminth Egg Automatic Detector (HEAD): Improvements in development for digital identification and quantification of helminth eggs and their application online

Helminths are parasitic worms that constitute a major public health problem. Conventional analytical techniques to evaluate helminth eggs in environmental samples rely on different steps, namely sedimentation, filtration, centrifugation, and flotation, to separate the eggs from a variety of particles and concentrate them in a pellet for direct observation under an optical microscope. To improve this process, a new approach was implemented in which various image processing algorithms were developed and implemented by a Helminth Egg Automatic Detector (HEAD). This allowed identification and quantification of pathogenic helminth eggs of global medical importance and it was found to be useful for relatively clean wastewater samples. After the initial version, two improvements were developed: first, a texture verification process that reduced the number of false positive results; and second, the establishment of the optimal thresholds (morphology and texture) for each helminth egg species. This second implementation, which was found to improve on the results of the former, was developed with the objective of using free software as a platform for the system. This does not require the purchase of a license, unlike the previous version that required a Mathworks® license to run. After an internal statistical verification of the system was carried out, trials in internationally recognized microbiology laboratories were performed with the aim of reinforcing software training and developing a web-based system able to receive images and perform the analysis throughout a web service. Once completed, these improvements represented a useful and cheap tool that could be used by environmental monitoring facilities and laboratories throughout the world; this tool is capable of identifying and quantifying different species of helminth eggs in otherwise difficult environmental samples: wastewater, soil, biosolids, excreta, and sludge, with a sensitivity and specificity for the TensorFlow (TF) model in the web service values of 96.82% and 97.96% respectively. Additionally, in the case of Ascaris, it may even differentiate between fertile and non-fertile eggs.

Inactivation of helminth eggs in an electro-Fenton reactor: Towards full electrochemical disinfection of human waste using activated carbon

The disinfection of helminth eggs and Escherichia coli contaminated aqueous solutions, was studied using an electro-Fenton reactor equipped with a polarized activated carbon (AC) packed bed and two chambers loaded with cation exchange resins. Experiments using different arrangements and operation conditions, revealed that effective elimination of Escherichia coli takes place in all electrochemical disinfection tests. For the more resistant helminth eggs however, adsorption, electro-oxidation and electro-Fenton experiments showed retention within the reactor and pathogen inactivation values of 0, 16, and 25%, respectively. Using helminth eggs concentration data in different sections of the reactor, optical microscopy analysis and an exploratory computer simulation, differences in the disinfection performance were explained and new recirculation and flow direction and polarization switching operation schemes were defined. The corresponding experiments revealed that the effective coupling between adsorption and electro-Fenton phenomena, all along the AC packed bed compartment, results in 100% inactivation of helminth eggs.

A historical review of the techniques of recovery of parasites for their detection in human stools

Since the early 20th century, the detection of intestinal parasites has improved with the development of several techniques for parasitic structures recovery and identification, which differ in sensitivity, specificity, practicality, cost, and infrastructure demand. This study aims to review, in chronological order, the stool examination techniques and discuss their advantages, limitations, and perspectives, and to provide professionals and specialists in this field with data that lays a foundation for critical analysis on the use of such procedures. The concentration procedures that constitute the main techniques applied in routine research and in parasitological kits are a) spontaneous sedimentation; b) centrifugation-sedimentation with formalin-ethyl acetate; and c) flotation with zinc sulfate solution. While selecting a technique, one should consider the purpose of its application and the technical-operational, biological, and physicochemical factors inherent in the procedures used in stool processing, which may restrict its use. These intrinsic limitations may have undergone procedural changes driven by scientific and technological development and by development of alternative methods, which now contribute to the improvement of diagnostic accuracy.

Real-time detection and identification of nematode eggs genus and species through optical imaging

Nematode eggs are pervasive pathogens that infect billions of people and livestock every year. Adult parasitic nematode worms can be distinguished based on their size and morphology. However, their eggs, particularly their species Ascaris lumbricoides and Ascaris suum cannot be identified from each other. Identifying eggs of helminths from wastewater and sludge is important from a public health perspective to minimize the spread of Ascaris infections. Numerous methods exist for nematode identification, from a morphological-based approach to high throughput sequencing technology. However, these techniques are not consistent and often laborious and time-consuming. In this study, we demonstrate that non-invasive real-time identification of eggs is possible based on their intrinsic fluorescence. Using confocal microscopy, we investigate the autofluorescence properties of five species of nematode eggs and observe clear differences between genus and for the first time their species in sludge samples. This non-invasive imaging technique could lead to better understanding of these species and may assist in early control of diseases.

Automated Diagnosis of Canine Gastrointestinal Parasites Using Image Analysis

Because canine intestinal parasites are considered cosmopolitan, they carry significant zoonotic potential to public health. These etiological agents are routinely diagnosed using microscopic examination commonly used because of its low cost, simple execution, and direct evidence. However, there are reports in the literature on the poor performance of this test due to low to moderate sensitivity resulting from frequent errors, procedures and interpretation. Therefore, to improve the diagnostic efficiency of microscopic examination in veterinary medicine, we developed and evaluated a unique new protocol. This system was tested in a study involving four genera of highly prevalent canine intestinal parasites in an endemic region in São Paulo state, Brazil. Fecal samples from 104 animals were collected for this research. The new protocol had a significantly higher (p < 0.0001) number of positive cases on image data, including parasites and impurities, and was elaborate to test them with the TF-GII/Dog technique, with a moderate agreement and Kappa index of 0.7636. We concluded that the new Prototic Coproparasitological Test for Dogs (PC-Test Dog) allowed a better visualization of the parasitic structures and showed a favorable result for the diagnosis of intestinal parasites in dogs.

Sources of environmental contamination with Toxocara spp.: An omnipresent parasite

Embryonated Toxocara eggs in the environment are considered to be the most important source of human toxocariasis. These eggs, however, are also a source of infection for the definitive and paratenic hosts. Most available literature focuses on Toxocara canis in dogs, or other canids. There are, however, other Toxocara species with their accompanying definitive hosts. Results from studies that modelled patent infections in dogs, cats and foxes show that although dogs are a very important source for environmental contamination with Toxocara eggs, other sources cannot be ignored. For a good understanding of the relative contributions of different definitive hosts to environmental contamination with Toxocara eggs, computational models should be built and fed with data from different fields of expertise as is discussed in this paper.

Quick incubation process to determine inactivation of Ascaris and Toxocara eggs

Helminth eggs are among the most important biological contaminants in environmental engineering. They pose a significant health risk associated with poor sanitation, the use of contaminated water for irrigation, and the disposal of excreta or sludge to land. Helminths are parasitic worms transmitted to humans via their eggs, which is the infective stage of their life cycle. They are therefore relevant to public health and environmental fields due to their low infectious dose, their persistence in the environment (up to several years), and their high resistance to conventional disinfection processes. The evaluation of the efficiency of any process of inactivation, through the determination of the viability of these parasites, is fundamental, but the traditional incubation technique requires 20 days to determine both the viability and the infectivity of nematode eggs. However, the present study found that, using an inactivation process at a temperature of 60 °C for 1 hour and incubation at 28 °C and 34 °C, the absence of division of the nucleus of eggs of species from two genera, Ascaris lumbricoides and Toxocara canis, showed them to be inactivated following only 48 hours of incubation. Similar inactivation results were observed using an automatic system as long as the eggs were inactivated. The minimum time required to evaluate the inactivation of nematode eggs through the incubation technique was 48 hours.

Viability determination of Ascaris ova in raw wastewater: a comparative evaluation of culture-based, BacLight Live/Dead staining and PMA-qPCR methods

Accurate evaluation of viable Ascaris ova in wastewater is the key to mitigating Ascaris reinfections in endemic regions. In this study, the viability of Ascaris ova in raw wastewater was determined using three different detection methods: culture-based, BacLight Live/Dead staining and propidium monoazide-quantitative polymerase chain reaction (PMA-qPCR). Furthermore, comparative assessment of viability utilising the aforementioned detection methods was performed using seeded experiments in wastewater. The percentage of viability was: culture-based (82%), BacLight Live/Dead staining (87%) and PMA-qPCR (85%) respectively. Despite the fact that no statistical difference was shown in the viability determination among the three methods, PMA-qPCR-based viability determination would be preferable over the other two methods for evaluating potential public health risks with A. suum ova due to its accuracy, being least subjective and its rapid reaction time.

Kankanet: An artificial neural network-based object detection smartphone application and mobile microscope as a point-of-care diagnostic aid for soil-transmitted helminthiases

Background

Endemic areas for soil-transmitted helminthiases often lack the tools and trained personnel necessary for point-of-care diagnosis. This study pilots the use of smartphone microscopy and an artificial neural network-based (ANN) object detection application named Kankanet to address those two needs.

Methodology/Principal findings

A smartphone was equipped with a USB Video Class (UVC) microscope attachment and Kankanet, which was trained to recognize eggs of Ascaris lumbricoides, Trichuris trichiura, and hookworm using a dataset of 2,078 images. It was evaluated for interpretive accuracy based on 185 new images. Fecal samples were processed using Kato-Katz (KK), spontaneous sedimentation technique in tube (SSTT), and Merthiolate-Iodine-Formaldehyde (MIF) techniques. UVC imaging and ANN interpretation of these slides was compared to parasitologist interpretation of standard microscopy.Relative to a gold standard defined as any positive result from parasitologist reading of KK, SSTT, and MIF preparations through standard microscopy, parasitologists reading UVC imaging of SSTT achieved a comparable sensitivity (82.9%) and specificity (97.1%) in A. lumbricoides to standard KK interpretation (97.0% sensitivity, 96.0% specificity). The UVC could not accurately image T. trichiura or hookworm. Though Kankanet interpretation was not quite as sensitive as parasitologist interpretation, it still achieved high sensitivity for A. lumbricoides and hookworm (69.6% and 71.4%, respectively). Kankanet showed high sensitivity for T. trichiura in microscope images (100.0%), but low in UVC images (50.0%).

Conclusions/Significance

The UVC achieved comparable sensitivity to standard microscopy with only A. lumbricoides. With further improvement of image resolution and magnification, UVC shows promise as a point-of-care imaging tool. In addition to smartphone microscopy, ANN-based object detection can be developed as a diagnostic aid. Though trained with a limited dataset, Kankanet accurately interprets both standard microscope and low-quality UVC images. Kankanet may achieve sensitivity comparable to parasitologists with continued expansion of the image database and improvement of machine learning technology.

For rainforest-enshrouded rural villages of Madagascar, soil-transmitted helminthiases are more the rule than the exception. However, the microscopy equipment and lab technicians needed for diagnosis are a distance of several days’ hike away. We piloted a solution for these communities by leveraging resources the villages already had: a traveling team of local health care workers, and their personal Android smartphones. We demonstrated that an inexpensive, commercially available microscope attachment for smartphones could rival the sensitivity and specificity of a regular microscope using standard field fecal sample processing techniques. We also developed an artificial neural network-based object detection Android application, called Kankanet, based on open-source programming libraries. Kankanet was used to detect eggs of the three most common soil-transmitted helminths: Ascaris lumbricoides, Trichuris trichiura, and hookworm. We found Kankanet to be moderately sensitive and highly specific for both standard microscope images and low-quality smartphone microscope images. This proof-of-concept study demonstrates the diagnostic capabilities of artificial neural network-based object detection systems. Since the programming frameworks used were all open-source and user-friendly even for computer science laymen, artificial neural network-based object detection shows strong potential for development of low-cost, high-impact diagnostic aids essential to health care and field research in resource-limited communities.

Pathogens, faecal indicators and human-specific microbial source-tracking markers in sewage

The objective of this review is to assess the current state of knowledge of pathogens, general faecal indicators and human-specific microbial source tracking markers in sewage. Most of the microbes present in sewage are from the microbiota of the human gut, including pathogens. Bacteria and viruses are the most abundant groups of microbes in the human gut microbiota. Most reports on this topic show that raw sewage microbiological profiles reflect the human gut microbiota. Human and animal faeces share many commensal microbes as well as pathogens. Faecal-orally transmitted pathogens constitute a serious public health problem that can be minimized through sanitation. Assessing both the sanitation processes and the contribution of sewage to the faecal contamination of water bodies requires knowledge of the content of pathogens in sewage, microbes indicating general faecal contamination and microbes that are only present in human faecal remains, which are known as the human-specific microbial source-tracking (MST) markers. Detection of pathogens would be the ideal option for managing sanitation and determining the microbiological quality of waters contaminated by sewage; but at present, this is neither practical nor feasible in routine testing. Traditionally, faecal indicator bacteria have been used as surrogate indicators of general faecal residues. However, in many water management circumstances, it becomes necessary to detect both the origin of faecal contamination, for which MST is paramount, and live micro-organisms, for which molecular methods are not suitable. The presence and concentrations of pathogens, general faecal indicators and human-specific MST markers most frequently reported in different areas of the world are summarized in this review.

Comprehensive evaluation of stool-based diagnostic methods and benzimidazole resistance markers to assess drug efficacy and detect the emergence of anthelmintic resistance: A Starworms study protocol

Background

To work towards reaching the WHO goal of eliminating soil-transmitted helminth (STH) infections as a public health problem, the total number of children receiving anthelmintic drugs has strongly increased over the past few years. However, as drug pressure levels rise, the development of anthelmintic drug resistance (AR) is more and more likely to appear. Currently, any global surveillance system to monitor drug efficacy and the emergence of possible AR is lacking. Consequently, it remains unclear to what extent the efficacy of drugs may have dropped and whether AR is already present. The overall aim of this study is to recommend the best diagnostic methods to monitor drug efficacy and molecular markers to assess the emergence of AR in STH control programs.

Methods

A series of drug efficacy trials will be performed in four STH endemic countries with varying drug pressure (Ethiopia and Brazil: low drug pressure, Lao PDR: moderate drug pressure and Tanzania: high drug pressure). These trials are designed to assess the efficacy of a single oral dose of 400 mg albendazole (ALB) against STH infections in school-aged children (SAC) by microscopic (duplicate Kato-Katz thick smear, Mini-FLOTAC and FECPAK^G2) and molecular stool-based diagnostic methods (quantitative PCR (qPCR)). Data will be collected on the cost of the materials used, as well as the time required to prepare and examine stool samples for the different diagnostic methods. Following qPCR, DNA samples will also be submitted for pyrosequencing to assess the presence and prevalence of single nucleotide polymorphisms (SNPs) in the β-tubulin gene. These SNPs are known to be linked to AR in animal STHs.

Discussion

The results obtained by these trials will provide robust evidence regarding the cost-efficiency and diagnostic performance of the different stool-based diagnostic methods for the assessment of drug efficacy in control programs. The assessment of associations between the frequency of SNPs in the β-tubulin gene and the history of drug pressure and drug efficacy will allow the validation of these SNPs as a marker for AR in human STHs.

Trial registration

The trial was retrospectively registered the 7^th of March 2018 on Clinicaltrials.gov (ID: NCT03465488).

Soil-transmitted helminths (STHs) affect 1.4 billion people worldwide and cause significant morbidity when the intensity of infection is high. Currently, these infections are controlled in school-aged children by preventive chemotherapy with the benzimidazole drugs albendazole (ALB) or mebendazole (MEB). However, for the success of these control programs, it is essential to keep track of the efficacy of these drugs and to screen parasite populations for a possible rise of anthelmintic resistance (AR). In this light, a series of trials will be performed to assess the efficacy of ALB treatment against STH in four endemic countries with varying drug pressure. Both microscopic and molecular stool-based diagnostic methods will be used to evaluate drug efficacy. DNA samples will also be analysed for the presence and prevalence of mutations in a gene that was previously linked to AR in animal STHs. The results of these trials will provide evidence on the efficacy of ALB, help select the optimal diagnostic method to assess drug efficacy and provide information regarding the usefulness of genetic markers for AR detection in human STHs.

Modification and optimization of the FECPAKG2 protocol for the detection and quantification of soil-transmitted helminth eggs in human stool

BACKGROUND

Standard diagnosis of human soil-transmitted helminth (STH) infections is based on the microscopic detection of helminth eggs in stool and supports programmatic decision making in control programs. However, the current standard diagnostic techniques still show a number of limitations. Recently, the FECPAKG2 method was developed to detect helminth infections and asses drug efficacy in sheep or cattle. It includes a device that takes digital images of helminth eggs that have been concentrated into one microscopic field of view and stores these images online for future evaluation. The goal of this study was to introduce a standard operating procedure (SOP) for the detection and quantification of human STH eggs using the FECPAKG2 and to optimize 2 crucial steps of the protocol, namely the sedimentation step (aimed at separating sinking eggs from floating debris) and the accumulation step (aimed at concentrating the eggs by flotation).

METHODOLOGY/PRINCIPAL FINDINGS

A total of 55 stool samples from naturally infected children were used from 4 different geographical areas (Ethiopia, Laos, Tanzania and Brazil). The results showed that Trichuris eggs generally moved slower than eggs of the other two STH species during both sedimentation in water in the FECPAKG2 sedimenter as during accumulation in flotation solution in the FECPAKG2 cassettes. The highest number of eggs were present in the slurry of the sedimenter after overnight sedimentation (Ascaris: 95.7%, Trichuris: 89.8% and hookworm: 94.2% of the eggs). A minimum of 24 minutes were needed to ensure the accumulation of at least 80% of the eggs from all three STH species in the FECPAKG2 cassette (Ascaris: 96.1%; Trichuris: 88.2% and hookworm: 87.6%).

CONCLUSIONS/SIGNIFICANCE

This study introduces for the first time a SOP for the FECPAKG2 method. Different aspects of the method for diagnosing human STH infections were optimized. Our study forms the basis for a thorough and objective evaluation of the system as a diagnostic tool that could be implemented in STH control programs.

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium

Background: Microscopy remains the gold standard in the diagnosis of neglected tropical diseases. As resource limited, rural areas often lack laboratory equipment and trained personnel, new diagnostic techniques are needed. Low-cost, point-of-care imaging devices show potential in the diagnosis of these diseases. Novel, digital image analysis algorithms can be utilized to automate sample analysis.

Objective: Evaluation of the imaging performance of a miniature digital microscopy scanner for the diagnosis of soil-transmitted helminths and Schistosoma haematobium, and training of a deep learning-based image analysis algorithm for automated detection of soil-transmitted helminths in the captured images.

Methods: A total of 13 iodine-stained stool samples containing Ascaris lumbricoides, Trichuris trichiura and hookworm eggs and 4 urine samples containing Schistosoma haematobium were digitized using a reference whole slide-scanner and the mobile microscopy scanner. Parasites in the images were identified by visual examination and by analysis with a deep learning-based image analysis algorithm in the stool samples. Results were compared between the digital and visual analysis of the images showing helminth eggs.

Results: Parasite identification by visual analysis of digital slides captured with the mobile microscope was feasible for all analyzed parasites. Although the spatial resolution of the reference slide-scanner is higher, the resolution of the mobile microscope is sufficient for reliable identification and classification of all parasites studied. Digital image analysis of stool sample images captured with the mobile microscope showed high sensitivity for detection of all helminths studied (range of sensitivity = 83.3–100%) in the test set (n = 217) of manually labeled helminth eggs.

Conclusions: In this proof-of-concept study, the imaging performance of a mobile, digital microscope was sufficient for visual detection of soil-transmitted helminths and Schistosoma haematobium. Furthermore, we show that deep learning-based image analysis can be utilized for the automated detection and classification of helminths in the captured images.

Development of a Field Laboratory for Monitoring of Fecal-Sludge Treatment Plants

In urban humanitarian-aid operations, safe treatment of fecal sludge is highly important. While currently field-deployable fecal-sludge treatment plants are being developed, field-ready analytical equipment for process-control and public health monitoring is missing. Within the Microbial Sludge Quality project, a field laboratory was developed. A minimum set of parameters for the considered processes was developed through literature research. The analytical methods were tested on their field applicability and, if necessary, modified. The following methods were modified for field use: bacteriological analysis (sample homogenization and counting), chemical oxygen demand (sample digestion), volatile fatty acid–alkalinity titration (redesigned test setup), total solids (redesigned test setup), and ammonia determination (redesigned test setup). For bacteriological analysis, chemical oxygen demand, and total solids the modifications lead to highly comparable analytical results. The results obtained by the field methodology for volatile fatty acid–alkalinity titration and ammonia determination were sufficient for field-process monitoring; however, they did not correlate as well. To enable rapid startup of the laboratory during humanitarian-aid missions, it was developed to include analytical and support equipment. The usage of the developed laboratory should allow close-in-time process monitoring and public-health assessments of fecal-sludge treatment plants.

Recent Advances in the Diagnosis and Detection of Opisthorchis viverrini Sensu Lato in Human and Intermediate Hosts for Use in Control and Elimination Programs

Opisthorchiasis is a neglected tropical disease, caused by infection with the fish-borne trematode Opisthorchis viverrini sensu lato that afflicts more than 10million people in Southeast Asia, including Thailand, Lao PDR, Vietnam and Cambodia. The disease is characterized by a chronic infection that induces hepatobiliary inflammation, especially periductal fibrosis, which can be detected by ultrasonography. This chronic inflammation eventually leads to cholangiocarcinoma (CCA), a usually fatal bile duct cancer that develops in approximately 1% of O. viverrini-infected individuals. In Thailand alone, CCA kills up to 20,000 people every year and is therefore of substantial public health importance. Its socioeconomic impacts on impoverished families and communities are considerable. To reduce O. viverrini-associated morbidity and CCA, the primary intervention measures focus on opisthorchiasis control and elimination. Accurate diagnoses of O. viverrini infection, in both mammalian, snail and fish intermediate hosts, are important for achieving these goals. Despite extensive efforts over several decades to find sensitive and specific diagnostics for opisthorchiasis, a simple and robust diagnostic method is still required. Here we review earlier and current developments in the search for new diagnostics for opisthorchiasis, with practical applications in the research laboratory, the clinic and the field. Of the methods currently available, the urine antigen assay shows considerable potential for the diagnosis and screening of opisthorchiasis. Nevertheless, these new assays require validation, determination of their cost-effectiveness when applied for mass screening in an endemic setting in support of policy decisions for national public health programs aimed at the control and elimination of opisthorchiasis.

Detection and quantification of soil-transmitted helminths in environmental samples: A review of current state-of-the-art and future perspectives

It is estimated that over a billion people are infected with soil-transmitted helminths (STHs) globally with majority occurring in tropical and subtropical regions of the world. The roundworm (Ascaris lumbricoides), whipworm (Trichuris trichiura), and hookworms (Ancylostoma duodenale and Necator americanus) are the main species infecting people. These infections are mostly gained through exposure to faecally contaminated water, soil or contaminated food and with an increase in the risk of infections due to wastewater and sludge reuse in agriculture. Different methods have been developed for the detection and quantification of STHs eggs in environmental samples. However, there is a lack of a universally accepted technique which creates a challenge for comparative assessments of helminths egg concentrations both in different samples matrices as well as between locations. This review presents a comparison of reported methodologies for the detection of STHs eggs, an assessment of the relative performance of available detection methods and a discussion of new emerging techniques that could be applied for detection and quantification. It is based on a literature search using PubMed and Science Direct considering all geographical locations. Original research articles were selected based on their methodology and results sections. Methods reported in these articles were grouped into conventional, molecular and emerging techniques, the main steps in each method were then compared and discussed. The inclusion of a dissociation step aimed at detaching helminth eggs from particulate matter was found to improve the recovery of eggs. Additionally the selection and application of flotation solutions that take into account the relative densities of the eggs of different species of STHs also results in higher egg recovery. Generally the use of conventional methods was shown to be laborious and time consuming and prone to human error. The alternate use of nucleic acid-based techniques has improved the sensitivity of detection and made species specific identification possible. However, these nucleic acid based methods are expensive and less suitable in regions with limited resources and skill. The loop mediated isothermal amplification method shows promise for application in these settings due to its simplicity and use of basic equipment. In addition, the development of imaging soft-ware for the detection and quantification of STHs shows promise to further reduce human error associated with the analysis of environmental samples. It may be concluded that there is a need to comparatively assess the performance of different methods to determine their applicability in different settings as well as for use with different sample matrices (wastewater, sludge, compost, soil, vegetables etc.).