The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NOX, NO₂, O₃, PM₁₀, PM₂.₅, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM₂.₅, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM₂.₅, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

To date, carbapenem-resistant Enterobacteriaceae have been found predominantly in clinical settings worldwide. Raoultella belongs to the Enterobacteriaceae family which can cause hospital-acquired infections, and carbapenem-resistant Raoultella spp. (CRR) is sporadically reported in the environment. We investigated the distribution and underlying resistance mechanisms of CRR in a wastewater treatment plant (WWTP) from eastern China between January 2018 and February 2019. A total of 17 CRR were isolated from 324 environmental samples, including Raoultella ornithinolytica (n = 15) and Raoultella planticola (n = 2). The detection of CRR was more frequent in the water inlet compared to anaerobic tank, aerobic tank, sludge thickener, activated sludge, mud cake storage area, and water outlet, and CRR was detected in mud cake stacking area. All CRR were resistant to imipenem, meropenem, ampicillin, piperacillin-tazobactam, cefotaxime, ceftazidime, trimethoprim-sulfamethoxazole and fosfomycin. Four different carbapenemase genes were identified, including blaKPC₋₂ (n = 13), blaNDM₋₁ (n = 8), blaNDM₋₅ (n = 1), blaIMP₋₄ (n = 1). Interestingly, isolated R. ornithinolytica from the WWTP were closely related to those reported from human samples in China. Plasmid analysis indicated that IncFII(Yp), IncP6, and IncU mediated blaKPC₋₂ spread, IncX3 and IncN2 mediated blaNDM spread in the environment. The core structure of the Tn3-ISKpn27-blaKPC₋₂-ISKpn6, ISAba125-blaNDM-bleMBL-trpF-dsbD were identified. The study provides evidence that Raoultella spp. may spread alarming carbapenem resistance in the environment and, therefore, the continuous surveillance for carbapenem resistance in the WWTP should be conducted, especially sludge.

Wastewater-based epidemiology (WBE) has emerged as a valuable approach for forecasting disease outbreaks in developed countries with a centralized sewage infrastructure. On the other hand, due to the absence of well-defined and systematic sewage networks, WBE is challenging to implement in developing countries like Bangladesh where most people live in rural areas. Identification of appropriate locations for rural Hotspot Based Sampling (HBS) and urban Drain Based Sampling (DBS) are critical to enable WBE based monitoring system. We investigated the best sampling locations from both urban and rural areas in Bangladesh after evaluating the sanitation infrastructure for forecasting COVID-19 prevalence. A total of 168 wastewater samples were collected from 14 districts of Bangladesh during each of the two peak pandemic seasons. RT-qPCR commercial kits were used to target ORF1ab and N genes. The presence of SARS-CoV-2 genetic materials was found in 98% (165/168) and 95% (160/168) wastewater samples in the first and second round sampling, respectively. Although wastewater effluents from both the marketplace and isolation center drains were found with the highest amount of genetic materials according to the mixed model, quantifiable SARS-CoV-2 RNAs were also identified in the other four sampling sites. Hence, wastewater samples of the marketplace in rural areas and isolation centers in urban areas can be considered the appropriate sampling sites to detect contagion hotspots. This is the first complete study to detect SARS-CoV-2 genetic components in wastewater samples collected from rural and urban areas for monitoring the COVID-19 pandemic. The results based on the study revealed a correlation between viral copy numbers in wastewater samples and SARS-CoV-2 positive cases reported by the Directorate General of Health Services (DGHS) as part of the national surveillance program for COVID-19 prevention. The findings of this study will help in setting strategies and guidelines for the selection of appropriate sampling sites, which will facilitate in development of comprehensive wastewater-based epidemiological systems for surveillance of rural and urban areas of low-income countries with inadequate sewage infrastructure.

Antimicrobial resistance (AMR) is a serious problem for public and animal health, and also for the environment. Monitoring and reporting the occurrence of AMR determinants and bacteria with the potential to disseminate is a priority for health surveillance programs around the world and critical to the One Health concept. Wildlife is a reservoir of AMR, and human activities can strongly influence their resistome.The main goal of this work was to study the resistome of wild boar faecal microbiome, one of the most important game species in Europe using metagenomic and culturing approaches. The most abundant genes identified by the high-throughput qPCR array encode mobile genetic elements, including integrons, which can promote the dissemination of AMR determinants. A diverse set of genes (n = 62) conferring resistance to several classes of antibiotics (ARGs), some of them included in the WHO list of critically important antimicrobials were also detected. The most abundant ARGs confer resistance to tetracyclines and aminoglycosides. The phenotypic resistance of E. coli and Enterococcus spp. were also investigated, and together supported the metagenomic results.As the wild boar is an omnivorous animal, it can be a disseminator of AMR bacteria and ARGs to livestock, humans, and the environment. This study supports that wild boar can be a key sentinel species in ecosystems surveillance and should be included in National Action Plans to fight AMR, adopting a One Health approach.

Monitoring beach plastic contamination across space and time is necessary for understanding its sources and ecological effects, and for guiding mitigation. This is logistically and financially challenging, especially for microplastics. Citizen science represents an option for sampling accessible sites to support long term monitoring, but challenges persist around data validation. Here we test a simple citizen science methodology to monitor visible microplastic contamination on sandy beaches using a standard quadrat unit (50 cm × 50 cm x 5 cm depth) sieved to 1 mm, to support the analysis of microplastic on two islands within the marine protected area of the Galápagos Archipelago, Ecuador (San Cristóbal and Santa Cruz islands). High school and university students undertook supervised sampling of two beaches in 2019–2020 collecting over 7000 particles. A sub-sample of the suspected microplastics collected (n = 2,213, ∼30% total) were analysed using FTIR spectrometry, confirming 93% of particles >1 mm visually identified by students were microplastics or rubber, validating this method as a crowd-sourced indicator for microplastic contamination. These data provide important insights into the plastic contamination of Galápagos, revealing plastic abundances of 0–2524 particles m⁻² over the two beaches (the highest reported in Galápagos). Strong accumulation gradients were measured parallel to the waterline at Punta Pitt (San Cristobal island) and perpendicular to the waterline at Tortuga Bay (Santa Cruz island), where four-fold higher concentrations were recorded at the sea turtle nesting habitat on the back-beach dune. No significant seasonal trends were measured during one year. These results demonstrate the value of citizen science in filling spatiotemporal knowledge gaps of beach contamination to support intervention design and conservation.