Fungal infections are underestimated threats that affect over 1 billion people, andCandidaspp.,Cryptococcusspp., andAspergillusspp. are the 3 most fatal fungi. The treatment of these infections is performed with a limited arsenal of antifungal drugs, and the class of the azoles is the most used. Although these drugs present low toxicity for the host, there is an emergence of therapeutic failure due to azole resistance. Drug resistance normally develops in patients undergoing azole long-term therapy, when the fungus in contact with the drug can adapt and survive. Conversely, several reports have been showing that resistant isolates are also recovered from patients with no prior history of azole therapy, suggesting that other routes might be driving antifungal resistance. Intriguingly, antifungal resistance also happens in the environment since resistant strains have been isolated from plant materials, soil, decomposing matter, and compost, where important human fungal pathogens live. As the resistant fungi can be isolated from the environment, in places where agrochemicals are extensively used in agriculture and wood industry, the hypothesis that fungicides could be driving and selecting resistance mechanism in nature, before the contact of the fungus with the host, has gained more attention. The effects of fungicide exposure on fungal resistance have been extensively studied inAspergillus fumigatusand less investigated in other human fungal pathogens. Here, we discuss not only classic and recent studies showing that environmental azole exposure selects cross-resistance to medical azoles inA.fumigatus, but also how this phenomenon affectsCandidaandCryptococcus, other 2 important human fungal pathogens found in the environment. We also examine data showing that fungicide exposure can select relevant changes in the morphophysiology and virulence of those pathogens, suggesting that its effect goes beyond the cross-resistance.

A quantitative microbial risk assessment model for estimating infection risks arising from consuming crops eaten raw that have been irrigated with effluents from stabilization ponds was constructed. A log-normal probability distribution function was fitted to a large database from a comprehensive monitoring of an experimental pond system to account for variability in Escherichia coli concentration in irrigation water. Crop contamination levels were estimated using predictive models derived from field experiments involving the irrigation of several crops with different effluent qualities. Data on daily intake of salad crops were obtained from a national survey in Brazil. Ten thousand-trial Monte Carlo simulations were used to estimate human health risks associated with the use of wastewater for irrigating low- and high-growing crops. The use of effluents containing 103–104E. coli per 100 ml resulted in median rotavirus infection risk of approximately 10−3 and 10−4 pppy when irrigating, respectively, low- and high-growing crops; the corresponding 95th percentile risk estimates were around 10−2 in both scenarios. Sensitivity analyses revealed that variations in effluent quality, in the assumed ratios of pathogens to E. coli, and in the reduction of pathogens between harvest and consumption had great impact upon risk estimates.

A set of experiments were conducted in Brazil in a pilot-scale waste stabilization pond (WSP) system (a four-maturation-pond series) treating an upflow anaerobic sludge blanket (UASB) reactor effluent. Over a year and a half the pond series was monitored under two flow rate conditions, hence also different hydraulic retention times and surface loading rates. On-site and laboratory trials were carried out to assess: (i) ammonia losses by volatilization using acrylic capture chambers placed at the surface of the ponds; (ii) organic nitrogen sedimentation rates using metal buckets placed at the bottom of the ponds for collecting settled particulate matter; (iii) nitrogen removal by algal uptake based on the nitrogen content of the suspended particulate matter in samples from the ponds' water column. In addition, nitrification and denitrification rates were measured in laboratory-based experiments using pond water and sediment samples. The pond system achieved high nitrogen removal (69% total nitrogen and 92% ammonia removal). The average total nitrogen removal rates varied from 10,098 to 3,849 g N/ha·d in the first and the last ponds, respectively, with the following fractions associated with the various removal pathways: (i) 23.5–45.6% sedimentation of organic nitrogen; (ii) 13.1–27.8% algal uptake; (iii) 1.2–3.1% ammonia volatilization; and (iv) 0.15–0.34% nitrification-denitrification.

This paper presents the results of an experiment on salad crop irrigation with waste stabilisation pond effluents, conducted in Southeast Brazil. Over about 18 months several trials were carried out using different effluent qualities to irrigate lettuce, kale, arugula, spinach, and green pepper. Equations for predicting the bacterial quality of irrigated crops (E.coli per gram) based on the irrigation water quality (E.coli per 100 mL) were derived for low and high growing crops. The quantitative microbial risk analysis (QMRA) technique, using pathogen-ingestion scenarios based on these field data and on official statistics of vegetables consumption in Brazil, was used to estimate infection risks arising from the consumption of wastewater irrigated crops. It is inferred that irrigation with effluents complying with the WHO guidelines for unrestricted irrigation should result in salad crops acceptable for consumption.