The industrial sector plays a significant role in global economic growth. However, it also produces polluting effluents that must be treated to prevent environmental damage and ensure the quality of life for future generations is not compromised. Various physical, chemical, and biological methods have been employed to treat industrial effluents. Filamentous fungi, in particular, have garnered attention as effective bioremediation agents due to their ability to produce enzymes capable of degrading recalcitrant compounds, and adsorb different pollutant molecules. The novelty of the work reported herein lies in its comprehensive assessment of the research surrounding the use of white- and brown-rot fungi for removing phenolic compounds from industrial effluents. This study employs a systematic review coupled with scientometric analysis to provide insights into the evolution of this technology over time. It scrutinizes geographical distribution, identifies research gaps and trends, and highlights the most studied fungal species and their applications. A systematic review of 464 publications from 1945 to 2023 assessed the use of these fungi in removing phenolic compounds from industrial effluents. White-rot fungi were predominant (96.3%), notably Phanerochaete chrysosporium, Pleurotus ostreatus, Trametes versicolor, and Lentinula edodes. The cultures employing free cells (64.15%) stand out over those using immobilized cells, just like cultures with isolated fungi regarding systems with microbial consortia. Geographically, Italy, Spain, Greece, India, and Brazil emerged as the most prominent countries in publications related to this area during the evaluated period.

The industrial sector plays a crucial role in driving global economic growth by creating employ-ment opportunities, generating local income, and significantly contributing to each country's Gross Domestic Product (GDP). However, the manufacturing industry is responsible for produc-ing a substantial amount of polluting effluents, which can harm the environment and compromise the life quality of future generations if not appropriately treated. Various methods, including physical, chemical, and biological processes, have been employed in the treatment of industrial ef-fluents. Filamentous fungi, in particular, have garnered attention as effective bioremediation agents due to their ability to produce enzymes capable of degrading recalcitrant compounds and adsorb different pollutant molecules. This study aimed to assess the collective body of research on using white and brown rot fungi to remove phenolic compounds from industrial effluents. The research employed a systematic review, incorporating scientometric analysis, with the primary goal of constructing a comprehensive overview of the evolution of this technology over time. The analysis also aimed to scrutinize its geographical distribution and identify gaps and trends within these research inquiries. Data for the study were obtained from the Web of Science (WoS) data-base using specific search terms (("white rot fung*" OR "brown rot fung*") AND (phenol* OR phenoloxidase OR "polyphenol oxidase*") AND (wastewater OR effluent* OR bioremediation)). The time frame considered ranged from 1945 to 2023, resulting in 464 publications. After refine-ment, 109 studies were selected for further analysis, focusing on using filamentous fungi in the bi-oremediation of industrial effluents. The findings revealed that white rot fungi were the most studied in industrial effluent remediation processes, accounting for 96.3% of the studies assessed, followed by brown rot fungi at 2.7%. Filamentous fungi demonstrate significant potential for treating industrial effluents due to their high capacity to degrade phenolic compounds, especially in wastewater from olive mills, paper production industries, and distilleries. Among the investi-gated species, Phanerochaete chrysosporium, Pleurotus ostreatus, Trametes versicolor, and Lentinula edodes have been the most extensively researched for this application. Notably, cultures with free cells (64.15%) stood out compared to cultures with immobilized cells, and cultures with isolated fungi surpassed microbial consortia. Geographically, Italy, Spain, Greece, India, and Brazil emerged as the most prominent countries in publications related to this area during the evaluated period.

Wastewater‐based epidemiology (WBE) has been widely applied for SARS‐CoV‐2 surveillance. Yet, operational parameters such as influent flow rate and sewer system characteristics may reflect underlying hydraulic variability relevant to detection performance, raising questions about the representativeness of results from small and medium‐sized plants. We conducted a systematic meta‐analysis of 10 published studies assessing SARS‐CoV‐2 RNA detection across wastewater treatment plants of different sizes and flow ranges. Data were extracted into 2 × 2 tables and analyzed in R using the meta and metafor packages. Odds ratios (ORs) were pooled with Mantel–Haenszel random‐effects models and DerSimonian–Laird τ ² estimation. Subgroup analyses compared studies from developed versus emerging economies, meta‐regression tested population size as a moderator, and publication bias was evaluated with funnel plots and Egger's test. The overall pooled OR was 2.08 (95% CI: 0.99–4.37, p = 0.053; I ² = 82.3%), indicating a non‐significant trend toward higher detection at higher flow rates. Subgroup analyses showed similar pooled effects across developed and emerging economies, though heterogeneity was lower in emerging settings. Meta‐regression revealed no significant association between population size and detection (slope = 0.29, p = 0.52). Funnel plots were relatively symmetric, and Egger's test did not indicate significant publication bias ( p = 0.169). Overall, these findings suggest that influent flow rate is not significantly associated with the probability of SARS‐CoV‐2 detection in WBE studies, supporting the inclusion of small and medium‐sized treatment plants in surveillance networks. At the same time, the concentration of studies in high‐income countries highlights inequities in the global WBE literature and in site deployment, with vulnerable populations often underrepresented. Expanding WBE infrastructure in underserved regions is necessary to ensure equitable and representative surveillance capacity.