Factors, enablers and challenges for COVID-19 vaccine development.

The COVID-19 pandemic triggered a sense of vulnerability and urgency that led to concerted actions by governments, funders, regulators and industry to overcome traditional challenges for the development of vaccine candidates and to reach authorisation. Unprecedented financial investments, massive demand, accelerated clinical development and regulatory reviews were among the key factors that contributed to accelerating the development and approval of COVID-19 vaccines. The rapid development of COVID-19 vaccines benefited of previous scientific innovations such as mRNA and recombinant vectors and proteins. This has created a new era of vaccinology, with powerful platform technologies and a new model for vaccine development. These lessons learnt highlight the need of strong leadership, to bring together governments, global health organisations, manufacturers, scientists, private sector, civil society and philanthropy, to generate innovative, fair and equitable access mechanisms to COVID-19 vaccines for populations worldwide and to build a more efficient and effective vaccine ecosystem to prepare for other pandemics that may emerge. With a longer-term view, new vaccines must be developed with incentives to build expertise for manufacturing that can be leveraged for low/middle-income countries and other markets to ensure equity in innovation, access and delivery. The creation of vaccine manufacturing hubs with appropriate and sustained training, in particular in Africa, is certainly the way of the future to a new public health era to safeguard the health and economic security of the continent and guarantee vaccine security and access, with however the need for such capacity to be sustained in the interpandemic period.

IoMT Meets Machine Learning: From Edge to Cloud Chronic Diseases Diagnosis System.

In conventional healthcare, real-time monitoring of patient records and information mining for timely diagnosis of chronic diseases under certain health conditions is a crucial process. Chronic diseases, if not diagnosed in time, may result in patients' death. In modern medical and healthcare systems, Internet of Things (IoT) driven ecosystems use autonomous sensors to sense and track patients' medical conditions and suggest appropriate actions. In this paper, a novel IoT and machine learning (ML)-based hybrid approach is proposed that considers multiple perspectives for early detection and monitoring of 6 different chronic diseases such as COVID-19, pneumonia, diabetes, heart disease, brain tumor, and Alzheimer's. The results from multiple ML models are compared for accuracy, precision, recall, F1 score, and area under the curve (AUC) as a performance measure. The proposed approach is validated in the cloud-based environment using benchmark and real-world datasets. The statistical analyses on the datasets using ANOVA tests show that the accuracy results of different classifiers are significantly different. This will help the healthcare sector and doctors in the early diagnosis of chronic diseases.

Tweeting for Health Using Real-time Mining and Artificial Intelligence-Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter.

BACKGROUND: Digital misinformation, primarily on social media, has led to harmful and costly beliefs in the general population. Notably, these beliefs have resulted in public health crises to the detriment of governments worldwide and their citizens. However, public health officials need access to a comprehensive system capable of mining and analyzing large volumes of social media data in real time. OBJECTIVE: This study aimed to design and develop a big data pipeline and ecosystem (UbiLab Misinformation Analysis System [U-MAS]) to identify and analyze false or misleading information disseminated via social media on a certain topic or set of related topics. METHODS: U-MAS is a platform-independent ecosystem developed in Python that leverages the Twitter V2 application programming interface and the Elastic Stack. The U-MAS expert system has 5 major components: data extraction framework, latent Dirichlet allocation (LDA) topic model, sentiment analyzer, misinformation classification model, and Elastic Cloud deployment (indexing of data and visualizations). The data extraction framework queries the data through the Twitter V2 application programming interface, with queries identified by public health experts. The LDA topic model, sentiment analyzer, and misinformation classification model are independently trained using a small, expert-validated subset of the extracted data. These models are then incorporated into U-MAS to analyze and classify the remaining data. Finally, the analyzed data are loaded into an index in the Elastic Cloud deployment and can then be presented on dashboards with advanced visualizations and analytics pertinent to infodemiology and infoveillance analysis. RESULTS: U-MAS performed efficiently and accurately. Independent investigators have successfully used the system to extract significant insights into a fluoride-related health misinformation use case (2016 to 2021). The system is currently used for a vaccine hesitancy use case (2007 to 2022) and a heat wave-related illnesses use case (2011 to 2022). Each component in the system for the fluoride misinformation use case performed as expected. The data extraction framework handles large amounts of data within short periods. The LDA topic models achieved relatively high coherence values (0.54), and the predicted topics were accurate and befitting to the data. The sentiment analyzer performed at a correlation coefficient of 0.72 but could be improved in further iterations. The misinformation classifier attained a satisfactory correlation coefficient of 0.82 against expert-validated data. Moreover, the output dashboard and analytics hosted on the Elastic Cloud deployment are intuitive for researchers without a technical background and comprehensive in their visualization and analytics capabilities. In fact, the investigators of the fluoride misinformation use case have successfully used the system to extract interesting and important insights into public health, which have been published separately. CONCLUSIONS: The novel U-MAS pipeline has the potential to detect and analyze misleading information related to a particular topic or set of related topics.

Newspaper Coverage and Framing of Bats, and Their Impact on Readership Engagement.

The media is a valuable pathway for transforming people's attitudes towards conservation issues. Understanding how bats are framed in the media is hence essential for bat conservation, particularly considering the recent fearmongering and misinformation about the risks posed by bats. We reviewed bat-related articles published online no later than 2019 (before the recent COVID19 pandemic), in 15 newspapers from the five most populated countries in Western Europe. We examined the extent to which bats were presented as a threat to human health and the assumed general attitudes towards bats that such articles supported. We quantified press coverage on bat conservation values and evaluated whether the country and political stance had any information bias. Finally, we assessed their terminology and, for the first time, modelled the active response from the readership based on the number of online comments. Out of 1095 articles sampled, 17% focused on bats and diseases, 53% on a range of ecological and conservation topics, and 30% only mention bats anecdotally. While most of the ecological articles did not present bats as a threat (97%), most articles focusing on diseases did so (80%). Ecosystem services were mentioned on very few occasions in both types (< 30%), and references to the economic benefits they provide were meagre (< 4%). Disease-related concepts were recurrent, and those articles that framed bats as a threat were the ones that garnered the highest number of comments. Therefore, we encourage the media to play a more proactive role in reinforcing positive conservation messaging by presenting the myriad ways in which bats contribute to safeguarding human well-being and ecosystem functioning.

Material flow analysis-based assessment of polypropylene-fiber-containing microplastics released from disposable masks: Characterizing distribution in the environmental media.

With the upsurge in the use of disposable masks during the coronavirus disease pandemic, improper disposal of discarded masks and their negative impact on the environment have emerged as major issues. Improperly disposed of masks release various pollutants, particularly microplastic (MP) fibers, which can harm both terrestrial and aquatic ecosystems by interfering with the nutrient cycling, plant growth, and the health and reproductive success of organisms. This study assesses the environmental distribution of polypropylene (PP)-containing MPs, generated from disposable masks, using material flow analysis (MFA). The system flowchart is designed based on the processing efficiency of various compartments in the MFA model. The highest amount of MPs (99.7 %) is found in the landfill and soil compartments. A scenario analysis reveals that waste incineration significantly reduces the amount of MP transferred to landfills. Therefore, considering cogeneration and gradually increasing the incineration treatment rate are crucial to manage the processing load of waste incineration plants and minimize the negative impact of MPs on the environment. The findings provide insights into the potential environmental exposure associated with the improper disposal of waste masks and indicate strategies for sustainable mask disposal and management.

Ecosystem degradation and the spread of Covid-19.

The linkages between the emergence of zoonotic diseases and ecosystem degradation have been widely acknowledged by the scientific community and policy makers. In this paper we investigate the relationship between human overexploitation of natural resources, represented by the Human Appropriation of Net Primary Production Index (HANPP) and the spread of Covid-19 cases during the first pandemic wave in 730 regions of 63 countries worldwide. Using a Bayesian estimation technique, we highlight the significant role of HANPP as a driver of Covid-19 diffusion, besides confirming the well-known impact of population size and the effects of other socio-economic variables. We believe that these findings could be relevant for policy makers in their effort towards a more sustainable intensive agriculture and responsible urbanisation.

Overcoming the gender bias in ecology and evolution: is the double-anonymized peer review an effective pathway over time?

Male researchers dominate scientific production in science, technology, engineering, and mathematics (STEM). However, potential mechanisms to avoid this gender imbalance remain poorly explored in STEM, including ecology and evolution areas. In the last decades, changes in the peer-review process towards double-anonymized (DA) have increased among ecology and evolution (EcoEvo) journals. Using comprehensive data on articles from 18 selected EcoEvo journals with an impact factor >1, we tested the effect of the DA peer-review process in female-leading (i.e., first and senior authors) articles. We tested whether the representation of female-leading authors differs between double and single-anonymized (SA) peer-reviewed journals. Also, we tested if the adoption of the DA by previous SA journals has increased the representativeness of female-leading authors over time. We found that publications led by female authors did not differ between DA and SA journals. Moreover, female-leading articles did not increase after changes from SA to DA peer-review. Tackling female underrepresentation in science is a complex task requiring many interventions. Still, our results highlight that adopting the DA peer-review system alone could be insufficient in fostering gender equality in EcoEvo scientific publications. Ecologists and evolutionists understand how diversity is important to ecosystems' resilience in facing environmental changes. The question remaining is: why is it so difficult to promote and keep this "diversity" in addition to equity and inclusion in the academic environment? We thus argue that all scientists, mentors, and research centers must be engaged in promoting solutions to gender bias by fostering diversity, inclusion, and affirmative measures.

The Development of a Chatbot Technology to Disseminate Post-COVID-19 Information: Descriptive Implementation Study.

BACKGROUND: Post-COVID-19, or long COVID, has now affected millions of individuals, resulting in fatigue, neurocognitive symptoms, and an impact on daily life. The uncertainty of knowledge around this condition, including its overall prevalence, pathophysiology, and management, along with the growing numbers of affected individuals, has created an essential need for information and disease management. This has become even more critical in a time of abundant online misinformation and potential misleading of patients and health care professionals. OBJECTIVE: The RAFAEL platform is an ecosystem created to address the information about and management of post-COVID-19, integrating online information, webinars, and chatbot technology to answer a large number of individuals in a time- and resource-limited setting. This paper describes the development and deployment of the RAFAEL platform and chatbot in addressing post-COVID-19 in children and adults. METHODS: The RAFAEL study took place in Geneva, Switzerland. The RAFAEL platform and chatbot were made available online, and all users were considered participants of this study. The development phase started in December 2020 and included developing the concept, the backend, and the frontend, as well as beta testing. The specific strategy behind the RAFAEL chatbot balanced an accessible interactive approach with medical safety, aiming to relay correct and verified information for the management of post-COVID-19. Development was followed by deployment with the establishment of partnerships and communication strategies in the French-speaking world. The use of the chatbot and the answers provided were continuously monitored by community moderators and health care professionals, creating a safe fallback for users. RESULTS: To date, the RAFAEL chatbot has had 30,488 interactions, with an 79.6% (6417/8061) matching rate and a 73.2% (n=1795) positive feedback rate out of the 2451 users who provided feedback. Overall, 5807 unique users interacted with the chatbot, with 5.1 interactions per user, on average, and 8061 stories triggered. The use of the RAFAEL chatbot and platform was additionally driven by the monthly thematic webinars as well as communication campaigns, with an average of 250 participants at each webinar. User queries included questions about post-COVID-19 symptoms (n=5612, 69.2%), of which fatigue was the most predominant query (n=1255, 22.4%) in symptoms-related stories. Additional queries included questions about consultations (n=598, 7.4%), treatment (n=527, 6.5%), and general information (n=510, 6.3%). CONCLUSIONS: The RAFAEL chatbot is, to the best of our knowledge, the first chatbot developed to address post-COVID-19 in children and adults. Its innovation lies in the use of a scalable tool to disseminate verified information in a time- and resource-limited environment. Additionally, the use of machine learning could help professionals gain knowledge about a new condition, while concomitantly addressing patients' concerns. Lessons learned from the RAFAEL chatbot will further encourage a participative approach to learning and could potentially be applied to other chronic conditions.

COVID-19 pharmaceuticals in aquatic matrices: The threatening effects over cyanobacteria and microalgae.

Water contamination by pharmaceuticals is a global concern due to their potential negative effects on aquatic ecosystems and human health. This study examined the presence of three repositioned drugs used for COVID-19 treatment: azithromycin (AZI), ivermectin (IVE) and hydroxychloroquine (HCQ) in water samples collected from three urban rivers in Curitiba, Brazil, during August and September 2020. We conducted a risk assessment and evaluated the individual (0, 2, 4, 20, 100 and 200 µg.L-1) and combined (mix of the drugs at 2 µg.L-1) effects of the antimicrobials on the cyanobacterium Synechococcus elongatus and microalga Chlorella vulgaris. The liquid chromatography coupled to mass spectrometry results showed that AZI and IVE were present in all collected samples, while HCQ occurred in 78 % of them. In all the studied sites, the concentrations found of AZI (up to 2.85 µg.L-1) and HCQ (up to 2.97 µg.L-1) represent environmental risks for the studied species, while IVE (up to 3.2 µg.L-1) was a risk only for Chlorella vulgaris. The hazard quotients (HQ) indices demonstrated that the microalga was less sensitive to the drugs than the cyanobacteria. HCQ and IVE had the highest values of HQ for the cyanobacteria and microalga, respectively, being the most toxic drugs for each species. Interactive effects of drugs were observed on growth, photosynthesis and antioxidant activity. The treatment with AZI + IVE resulted in cyanobacteria death, while exposure to the mixture of all three drugs led to decreased growth and photosynthesis in the cells. On the other hand, no effect on growth was observed for C. vulgaris, although photosynthesis has been negatively affected by all treatments. The use of AZI, IVE and HCQ for COVID-19 treatment may have generated surface water contamination, which could increased their potential ecotoxicological effects. This raises the need to further investigation into their effects on aquatic ecosystems.

Plastic or plastic-free life: From formation to removal.

Microplastics (MPs) and nanoplastics (NPs) have caused global environmental concerns due to their ubiquitous existence in our surrounding environment and the potential threats posed to the ecosystem and human health. This review aims to extend current knowledge on the formation and degradation of MPs and NPs. The paper presents the potential sources of MPs and NPs including plastic containers, textiles, cosmetics, personal care products, COVID-19 wastes, and other plastic products. Once in the natural environment, the fragmentation and degradation of plastic wastes are thought to be initiated by physical, chemical, and biological factors. The corresponding degradation mechanism will be presented in the present review. Given the plastic life and environment, humans are inevitably exposed to MPs and NPs through ingestion, inhalation, and dermal contact. The potential risks MPs/NPs pose to humans will be also discussed in our study. Currently, the relevance of MP/NP exposure to human health outcomes is still controversial and not yet fully understood. Deciphering the translocation and degradation of plastics in the human body will be helpful to reveal their potential organotoxicity. In this case, available approaches to alleviate MP/NP pollution and advanced strategies to reduce MP/NP toxicity in humans are recommended to build a plastic-free life.

WHO's Community-Centered Epidemic and Pandemic Information Platform: Hive.

Each epidemic and pandemic is accompanied by an infodemic. The infodemic during the COVID-19 pandemic was unprecedented. Accessing accurate information was difficult and misinformation harmed the pandemic response, the health of individuals and trust in science, governments and societies. WHO is building a community-centered information platform, the Hive, to deliver on the vision of ensuring that all people everywhere have access to the right information, at the right time, in the right format in order to make decisions to protect their health and the health of others. The platform provides access to credible information, a safe space for knowledge-sharing, discussion, and collaborating with others, and a forum to crowdsource solutions to problems. The platform is equipped with many collaboration features, including instant chats, event management, and data analytics tools to generate insights. The Hive platform is an innovative minimum viable product (MVP) that seeks to leverage the complex information ecosystem and the invaluable role communities play to share and access trustworthy health information during epidemics and pandemics.

Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research.

Research increasingly relies on interrogating large-scale data resources. The NIH National Heart, Lung, and Blood Institute developed the NHLBI BioData CatalystⓇ (BDC), a community-driven ecosystem where researchers, including bench and clinical scientists, statisticians, and algorithm developers, find, access, share, store, and compute on large-scale datasets. This ecosystem provides secure, cloud-based workspaces, user authentication and authorization, search, tools and workflows, applications, and new innovative features to address community needs, including exploratory data analysis, genomic and imaging tools, tools for reproducibility, and improved interoperability with other NIH data science platforms. BDC offers straightforward access to large-scale datasets and computational resources that support precision medicine for heart, lung, blood, and sleep conditions, leveraging separately developed and managed platforms to maximize flexibility based on researcher needs, expertise, and backgrounds. Through the NHLBI BioData Catalyst Fellows Program, BDC facilitates scientific discoveries and technological advances. BDC also facilitated accelerated research on the coronavirus disease-2019 (COVID-19) pandemic.

Influence of COVID-19 lockdown on river water quality and assessment of environmental health in an industrialized belt of southern Western Ghats, India.

The COVID-19 pandemic and sudden lockdown have severely hampered the country's economic growth and socio-cultural activities while imparting a positive effect on the overall fitness of the environment especially air and water resources. Increased urbanization and rapid industrialization have led to rising pollution and deterioration of rivers and associated sectors such as agriculture, domestic and commercial needs. However, various available studies in different parts of the country indicate that the COVID-19 pandemic has changed the entire ecosystem. But it is noted that studies are lacking in the southern Western Ghats region of India. Therefore, the present study attempts to investigate how the continuous lockdowns affect the River Water Quality (RWQ) during lockdown (October 2020) and post-lockdown (January 2021) periods in the lower catchments (Eloor-Edayar industrialized belt) of Periyar river, Kerala state, South India. A total of thirty samples (15 samples each) were analyzed based on drinking water quality, irrigational suitability, and multivariate statistical methods to evaluate the physical and chemical status of RWQ. The results of the Water Quality Index (WQI) for assessing the drinking water suitability showed a total of 93% of samples in the excellent and good category during the lockdown, while only 47% of samples were found fit for drinking during the post-lockdown period. Irrigational suitability indices like Mg hazard, KR, PI, SAR, and Wilcox diagram revealed lockdown period samples as more suitable for irrigational activities compared to post-lockdown samples with site-specific changes. Spearman rank correlation analysis indicated EC and TDS with a strong positive correlation to Ca2+, Mg2+, Na+, K+, TH, SO42-, and Cl- during both periods as well as strong positive correlations within the alkaline earth elements (Ca2+ and Mg 2+) and alkalis (Na+ and K+). Three significant components were extracted from principal component analysis (PCA), explaining 88.89% and 96.03% of the total variance for lockdown and post-lockdown periods, respectively. Variables like DO, BOD, Ca2+, NO3-, and Cl- remained in the same component loading during both periods elucidating their natural origin in the basin. The results of health risk assessment based on US EPA represented hazard quotient and hazard index values below the acceptable limit signifying no potential noncarcinogenic risk via oral exposure except As, suggesting children as more vulnerable to the negative effects than adults. Furthermore, this study also shows rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for deriving appropriate plans for the restoration of river health from anthropogenic stress.

Global face mask pollution: threats to the environment and wildlife, and potential solutions.

Face masks are an indispensable low-cost public healthcare necessity for containing viral transmission. After the coronavirus disease (COVID-19) became a pandemic, there was an unprecedented demand for, and subsequent increase in face mask production and use, leading to global ecological challenges, including excessive resource consumption and significant environmental pollution. Here, we review the global demand volume for face masks and the associated energy consumption and pollution potential throughout their life cycle. First, the production and distribution processes consume petroleum-based raw materials and other energy sources and release greenhouse gases. Second, most methods of mask waste disposal result in secondary microplastic pollution and the release of toxic gases and organic substances. Third, face masks discarded in outdoor environments represent a new plastic pollutant and pose significant challenges to the environment and wildlife in various ecosystems. Therefore, the long-term impacts on environmental and wildlife health aspects related to the production, use, and disposal of face masks should be considered and urgently investigated. Here, we propose five reasonable countermeasures to alleviate these global-scale ecological crises induced by mask use during and following the COVID-19 pandemic era: increasing public awareness; improving mask waste management; innovating waste disposal methods; developing biodegradable masks; and formulating relevant policies and regulations. Implementation of these measures will help address the pollution caused by face masks.

Impact of microfiber pollution on aquatic biota: A critical analysis of effects and preventive measures.

The widespread use of Personal protective equipments (PPEs) by the healthcare professionals and public due to Corona Virus Disease (COVID-19) pandemic has become a new source for MFs pollution. Mismanaged plastic wastes and random dispose of used surgical face mask end up in large aquatic bodies via small waterways and waste water treatment plants (WWTPs). Microplastics/Microfibres (MPs/MFs) have recently been reported in a variety of aquatic and terrestrial ecosystems, including water, deep sea sediments, air and soil. Natural components like UV radiation and temperature play a major role in weathering of surgical masks. High loads of MPs/MFs emitted into the aquatic environment are easily consumed by organism's habitat in such ecosystem by disrupting the food chain and causing chronic health problems in the organisms including humans. The aim of this review article is to shed light on these issues and compile the most recent information available regarding the deterioration of surgical face masks in the environment as well as other contaminants and their presence in various environments, particularly with regard to methods that make use of exposure models, biomarkers of exposure, and their limitations. Along with this, the study focuses on identifying gaps in current understanding and highlighting prospective research directions. The literature on surgical face mask pollution and its effects on the biological and physiological systems of various organisms and ecosystems is critically analysed in this review. It also raises awareness of how to properly dispose of used surgical face masks and other PPEs.

A novel circular approach to analyze the challenges associated with micro-nano plastics and their sustainable remediation techniques.

The mismanagement of consumer-discarded plastic waste (CDPW) has raised global environmental concerns about climate change. The COVID-19 outbreak has generated ∼1.6 million tons of plastic waste per day in the form of personal protective equipment (masks, gloves, face shields, and sanitizer bottles). These plastic wastes are either combustible or openly dumped in aquatic and terrestrial environments. Open dumping upsurges emerging contaminants like micro-nano plastics (MNPs) that directly enter the ecosystem and cause severe impacts on flora and fauna. Therefore, it has become an utmost priority to determine sustainable technologies that can degrade or treat MNPs from the environment. The present review assesses the sources and impacts of MNPs, various challenges, and issues associated with their remediation techniques. Accordingly, a novel sustainable circular model is recommended to increase the degradation efficiency of MNPs using biochemical and biological methods. It is also concluded that the proposed model does not only overcome environmental issues but also provides a sustainable secondary resource to meet the sustainable development goals (SDGs).

Wastewater monitoring can anchor global disease surveillance systems.

To inform the development of global wastewater monitoring systems, we surveyed programmes in 43 countries. Most programmes monitored predominantly urban populations. In high-income countries (HICs), composite sampling at centralised treatment plants was most common, whereas grab sampling from surface waters, open drains, and pit latrines was more typical in low-income and middle-income countries (LMICs). Almost all programmes analysed samples in-country, with an average processing time of 2·3 days in HICs and 4·5 days in LMICs. Whereas 59% of HICs regularly monitored wastewater for SARS-CoV-2 variants, only 13% of LMICs did so. Most programmes share their wastewater data internally, with partnering organisations, but not publicly. Our findings show the richness of the existing wastewater monitoring ecosystem. With additional leadership, funding, and implementation frameworks, thousands of individual wastewater initiatives can coalesce into an integrated, sustainable network for disease surveillance-one that minimises the risk of overlooking future global health threats.

Personal protective equipment-derived pollution during Covid-19 era: A critical review of ecotoxicology impacts, intervention strategies, and future challenges.

During the COVID-19 pandemic, people used personal protective equipment (PPE) to lessen the spread of the virus. The release of microplastics (MPs) from discarded PPE is a new threat to the long-term health of the environment and poses challenges that are not yet clear. PPE-derived MPs have been found in multi-environmental compartments, e.g., water, sediments, air, and soil across the Bay of Bengal (BoB). As COVID-19 spreads, healthcare facilities use more plastic PPE, polluting aquatic ecosystems. Excessive PPE use releases MPs into the ecosystem, which aquatic organisms ingest, distressing the food chain and possibly causing ongoing health problems in humans. Thus, post-COVID-19 sustainability depends on proper intervention strategies for PPE waste, which have received scholarly interest. Although many studies have investigated PPE-induced MPs pollution in the BoB countries (e.g., India, Bangladesh, Sri Lanka, and Myanmar), the ecotoxicity impacts, intervention strategies, and future challenges of PPE-derived waste have largely gone unnoticed. Our study presents a critical literature review covering the ecotoxicity impacts, intervention strategies, and future challenges across the BoB countries (e.g., India (162,034.45 tons), Bangladesh (67,996 tons), Sri Lanka (35,707.95 tons), and Myanmar (22,593.5 tons). The ecotoxicity impacts of PPE-derived MPs on human health and other environmental compartments are critically addressed. The review's findings infer a gap in the 5R (Reduce, Reuse, Recycle, Redesign, and Restructure) Strategy's implementation in the BoB coastal regions, hindering the achievement of UN SDG-12. Despite widespread research advancements in the BoB, many questions about PPE-derived MPs pollution from the perspective of the COVID-19 era still need to be answered. In response to the post-COVID-19 environmental remediation concerns, this study highlights the present research gaps and suggests new research directions considering the current MPs' research advancements on COVID-related PPE waste. Finally, the review suggests a framework for proper intervention strategies for reducing and monitoring PPE-derived MPs pollution in the BoB countries.

COVID-19 Lockdown Pandemic Period Effects in Highly Impacted Aquatic Ecosystems.

Human activities severely affect aquatic ecosystems: the lockdown restrictions due to SARS-CoV-2 (COVID-19) have proved that reducing anthropogenic activities can positively influence the environment and mitigate atmospheric pollution. In addition, studies on aquatic ecosystems have highlighted the decrease in suspended matter and pollutant concentrations associated with reduced marine transport and industrial activities. We evaluated the effects of the reduction of anthropogenic activities in highly impacted water ecosystems. Three of the sampling sites were on the Tiber River's lower stretch close to the urban area of Rome (Italy), and the other two were transitional waters located in the southern Latium region coastal area. These sampling sites have been studied by our research group for at least 20 years. The present study involved analysis of chemical and physicochemical parameters, biological communities, and land use. Microbiological fecal indicators and Salmonella spp. were also analyzed. There were two sampling campaigns, the first one in May 2020 (ID II) at the end of lockdown measures, and the second one a year later, in June 2021 (ID III). The data were compared with our old data, collected from 2002 to 2015 (ID I), to evaluate the potential effects of the restrictive measures. Biotic communities were dominated by pollution-tolerant taxa, indicating eutrophication and organic pollution. Furthermore, the high concentrations of microbiological indicators was mainly due to sewage from the urban area. The results of the research indicated no significant changes from past years (ID I) to 2020 (ID II) and 2021 (ID III). In conclusion, the restrictions adopted in Italy during the pandemic period were not sufficient to mitigate the heavy pressure of urbanization and agriculture that have long affected the studied aquatic ecosystems. Environ Toxicol Chem 2023;42:966-977. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.