A comprehensive, open-source data model for wastewater-based epidemiology.

The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data are highly dependent on context and are difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.

A critical review of the data pipeline: how wastewater system operation flows from data to intelligence.

Faced with an unprecedented amount of data coming from evermore ubiquitous sensors, the wastewater treatment community has been hard at work to develop new monitoring systems, models and controllers to bridge the gap between current practice and data-driven, smart water systems. For additional sensor data and models to have an appreciable impact, however, they must be relevant enough to be looked at by busy water professionals; be clear enough to be understood; be reliable enough to be believed and be convincing enough to be acted upon. Failure to attain any one of those aspects can be a fatal blow to the adoption of even the most promising new measurement technology. This review paper examines the state-of-the-art in the transformation of raw data into actionable insight, specifically for water resource recovery facility (WRRF) operation. Sources of difficulties found along the way are pinpointed, while also exploring possible paths towards improving the value of collected data for all stakeholders, i.e., all personnel that have a stake in the good and efficient operation of a WRRF.

Cross-country analysis of faecal sludge dewatering.

Dewatering of faecal sludge (FS) is indispensable for adequate FS management. However, comprehensive knowledge is lacking on FS dewatering performance. This study compared the dewatering performance of FS from different countries and onsite sanitation technologies, to assess influential characteristics on dewatering, and to compare dewatering performance of FS with wastewater sludge. We collected 73 FS samples from septic tanks, lined pit latrines, unlined pit latrines and johkasou tanks in Uganda, Vietnam and Japan, and 18 samples of wastewater sludge in Switzerland. Capillary suction time (CST) and total solids (TS) of centrifuged sludge (%TSfinal) were determined as metrics of dewatering rate and dewaterability, respectively, together with relevant sludge characteristics. Data were analysed by bootstrapping comparison of median results of each sample category and by bootstrapping multiple regression analysis to quantify the relative importance of sludge characteristics on dewatering performance. Results showed that the dewatering rate was significantly different between FS from different technologies, whereas dewaterability was significantly different within the same technology. FS had a significantly lower dewatering rate than wastewater sludge. In contrast, FS dewaterability was greater than wastewater sludge. However, this could be attributed to higher concentrations of sand in FS. Electrochemical properties such as NH4-N and surface charge had the strongest correlation to dewatering rate, and solid properties such as sand content and total volatile solids to dewaterability. The results identify potential characteristics that could explain and predict the high variability of FS dewatering performance that is observed in the field.