Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset.

The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014-2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems.

Publishing data to support the fight against human vector-borne diseases.

Vector-borne diseases are responsible for more than 17% of human cases of infectious diseases. In most situations, effective control of debilitating and deadly vector-bone diseases (VBDs), such as malaria, dengue, chikungunya, yellow fever, Zika and Chagas requires up-to-date, robust and comprehensive information on the presence, diversity, ecology, bionomics and geographic spread of the organisms that carry and transmit the infectious agents. Huge gaps exist in the information related to these vectors, creating an essential need for campaigns to mobilise and share data. The publication of data papers is an effective tool for overcoming this challenge. These peer-reviewed articles provide scholarly credit for researchers whose vital work of assembling and publishing well-described, properly-formatted datasets often fails to receive appropriate recognition. To address this, GigaScience's sister journal GigaByte partnered with the Global Biodiversity Information Facility (GBIF) to publish a series of data papers, with support from the Special Programme for Research and Training in Tropical Diseases (TDR), hosted by the World Health Organisation (WHO). Here we outline the initial results of this targeted approach to sharing data and describe its importance for controlling VBDs and improving public health.

Evaluation of the integration of P recovery, polyhydroxyalkanoate production and short cut nitrogen removal in a mainstream wastewater treatment process.

Wastewater treatment systems are nowadays evolving into systems where energy and resources are recovered from wastewater. This work presents the long term operation of a demo-scale pilot plant (7.8 m3) with a novel configuration named as mainstream SCEPPHAR (ShortCut Enhanced Phosphorus and polyhydroxyalkanoate (PHA) Recovery) and based on two sequencing batch reactors (R1-HET and R2-AUT). This is the first report of an implementation at demo scale and under relevant operational conditions of the simultaneous integration of shortcut nitrification, P recovery and production of sludge with a higher PHA content than conventional activated sludge. An operating period under full nitrification mode achieved successful removal efficiencies for total N, P and CODT (86 ± 12%, 93 ± 9% and 79 ± 6%). In the following period, nitrite shortcut (with undetectable activity of nitrite oxidising bacteria) was achieved by implementing automatic control of the aerobic phase length in R2-AUT using ammonium measurement and operating at a lower sludge retention time. Similar N, P and CODT removal efficiencies to the full nitrification period were obtained. P-recovery from the anaerobic supernatant of R1-HET was achieved in a separate precipitator by increasing pH and dosing MgCl2, recovering an average value of 45% of the P in the influent as struvite precipitate, with a peak up to 63%. These values are much higher than the typical values of sidestream P-recovery (12%). Regarding PHA, a percentage in the biomass in the range 6.9-9.2% (gPHA·g-1TSS) was obtained.

Multi-criteria analyses of wastewater treatment bio-processes under an uncertainty and a multiplicity of steady states.

This paper presents a multi-criteria evaluation methodology for determining the operating strategies for bio-chemical, wastewater treatment plants based on a model analysis under an uncertainty that can present multiple steady states. The method is based on Monte Carlo (MC) simulations and the expected utility theory in order to deal with the analysis of choices among risky operating strategies with multi-dimensional outcomes. The motivation is given by a case study using an anaerobic digestion model (ADM) adapted for multiple co-substrates. It is shown how the multi-criteria analyses' computational complexity can be reduced within an approximation based on Gaussian-process regression and how a reliability map can be built for a bio-process model under uncertainty and multiplicity. In our uncertainty-analyses case study, the reliability map shows the probability of a biogas-production collapse for a given set of substrates mixture input loads.