User agency–based versus machine agency–based misinformation interventions: The effects of commenting and AI fact-checking labeling on attitudes toward the COVID-19 vaccination

This study aimed to examine the effects of commenting on a Facebook misinformation post by comparing a user agency–based intervention and machine agency–based intervention in the form of artificial intelligence (AI) fact-checking labeling on attitudes toward the COVID-19 vaccination. We found that both interventions were effective at promoting positive attitudes toward vaccination compared to the misinformation-only condition. However, the intervention effects manifested differently depending on participants' residential locations, such that the commenting intervention emerged as a promising tool for suburban participants. The effectiveness of the AI fact-checking labeling intervention was pronounced for urban populations. Neither of the fact-checking interventions showed salient effects with the rural population. These findings suggest that although user agency- and machine agency–based interventions might have potential against misinformation, these interventions should be developed in a more sophisticated way to address the unequal effects among populations in different geographic locations. [ FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Social Media as Risk-Attenuation and Misinformation-Amplification Station: How Social Media Interaction Affects Misperceptions about COVID-19.

This study addresses how social media interaction affects misperceptions about COVID-19 via risk perceptions thereof and whether political orientation moderates the relationship. Using original two-wave panel survey data (N = 679), this study reveals that social media interaction increases misperception directly, as well as indirectly by reducing the extent of risk perception. The extent of risk perception is found to be a negative predictor of misperception. The deleterious role of social media interaction on misperception is pronounced across groups of conservatives and liberals, but in different ways. Although the effects of social media interaction on the level of misperception are observed in both conservatives and liberals, this relationship is particularly salient among conservatives. Furthermore, whereas conservatives consistently show low levels of risk perception toward COVID-19 regardless of how much they interact with others on social media, the more liberals interact on social media, the less likely they are to perceive COVID-19-related risks. The findings expand our understanding of the role of interaction behaviors on social media in forming risk perceptions and misperceptions on the politicized COVID-19 pandemic.

Communication Expressed on the COVID-19 Subreddit in the Midst of a Global Pandemic.

The manner in which scientific information related to the COVID-19 pandemic has been shared and discussed in similar venues has, to date, been largely neglected. Considering the role that such discourse plays in knowledge sharing and knowledge production, it is essential to understand such communication processes as they relate to global health crises like the COVID-19 pandemic. The current study examines communication expressed by participants in the r/COVID19 subreddit, a community that facilitates scientific discussion of the ongoing coronavirus pandemic. A computational content analysis was performed to identify the primary themes of users' communication on r/COVID19, while stepwise segmented regression was used to assess identify longitudinal changes in the volume of user contributions. Findings showed that while conversations were centered on scientific conversations, they were catalyzed by sociological and political developments rather than scientific breakthroughs. Future studies should examine the effects of pandemic-related communities on lurkers, the effects of visibility on scientific and medical contributions, and the implications of pseudonymity and ambiguous credentials in a community addressing a volatile health and scientific topic.

Bacterial Co-Infection and Empirical Antibacterial Therapy in Patients With COVID-19.

BACKGROUND: The rate and composition of bacterial co-infection in patients with coronavirus disease 2019 (COVID-19) were evaluated when microbiological testing was conducted on the majority of patients. We also evaluated whether the use of empirical antibacterials was associated with mortality. METHODS: In this retrospective study, all of the adult patients with COVID-19 hospitalized in a single tertiary hospital in South Korea between February 2020 and December 2021 were included. Bacterial co-infection was assessed by sputum cultures, blood cultures, and molecular testing, including polymerase chain reaction sputum testing and urinary antigen tests. Mortality was compared between patients who received empirical antibacterials and those who did not. RESULTS: Of the 367 adult patients admitted during the study period, 300 (81.7%) had sputum culture results and were included in the analysis. Of these 300 patients, 127 (42.3%) had a history of antibiotic exposure. The co-infection rate within 48 hours was 8.3% (25/300): 6.4% (11/173) of patients without prior antibiotic exposure and 11% (14/127) of patients with prior antibacterial exposure. The co-infected bacteria were different according to antibacterial exposure before admission, and multi-drug resistant pathogens were detected exclusively in the antibacterial exposed group. Among the patients without positive results for the microbiological tests, empirical antibacterials were used in 33.3% of cases (100/300). Empirical antibacterial therapy was not significantly related to the 30-day mortality or in-hospital mortality rates in the study cohort before or after the propensity score-matching. CONCLUSION: In this study including only patients underwent microbiological testing, bacterial co-infection was not frequent, and the co-infected organisms varied depending on previous antibacterial exposures. Given the rarity of co-infection and the lack of potential benefits, empiric antibacterial use in COVID-19 should be an important target of antibiotic stewardship.

Immunogenicity against the Omicron Variant after mRNA-Based COVID-19 Booster Vaccination in Medical Students Who Received Two Primary Doses of the mRNA-1273 Vaccine.

We evaluated the immune response against the Omicron variant after mRNA-based COVID-19 booster vaccination in medical students. We prospectively enrolled medical students who received two primary doses of the mRNA-1273 vaccine. The neutralizing response and the SARS-CoV-2-specific T-cell response was evaluated. A total of 56 serum samples were obtained before booster vaccination. Nineteen students (33.9%) developed COVID-19 two months after booster vaccination. Of 56 students, 35 students (12 infected and 23 uninfected) were available for blood sampling four months after booster vaccination. In comparison with uninfected students, infected students showed a significantly higher level of SARS-CoV-2-specific IgG (5.23 AU/mL vs. 5.12 AU/mL, p < 0.001) and rate of neutralizing response (96.22% vs. 27.18%, p < 0.001) four months after booster vaccination. There was no significant difference in the SARS-CoV-2-specific T-cell response. Among 23 infection-naive students, the neutralizing response was significantly higher in those who received the mRNA-1273 booster than in those who received the BNT162b2 booster (69.07% vs. 26.43%, p = 0.02). In our study, booster vaccination with mRNA-1273 instead of BNT162b2 was significantly associated with a higher neutralizing response.

Telehealth uptake among middle-aged and older Americans during COVID-19: chronic conditions, social media communication, and race/ethnicity.

OBJECTIVES: This study investigated whether and to what extent constructs of the protection motivation theory of health (PMT)-threat appraisal (perceived vulnerability/severity) and coping appraisal (response efficacy and self-efficacy)-are related to telehealth engagement during the COVID-19 pandemic, and how these associations differ by race/ethnicity among middle-aged and older Americans. METHODS: Data were from the 2020 Health and Retirement Study. Multivariable ordinary least-squares regression analyses were computed adjusting for health and sociodemographic factors. RESULTS: Some PMT constructs are useful in understanding telehealth uptake. Perceived vulnerability/severity, particularly comorbidity (b = 0.13, 95% confidence interval (CI) [0.11, 0.15], p < 0.001), and response efficacy, particularly participation in communication via social media (b = 0.24, 95% CI [0.21, 0.27], p < 0.001), were significantly and positively associated with higher telehealth uptake during the COVID-19 pandemic among middle-aged and older Americans. Non-Hispanic Black adults were more likely to engage in telehealth during the pandemic than their non-Hispanic White counterparts (b = 0.20, 95% CI [0.12, 0.28], p < 0.001). Multiple moderation analyses revealed the significant association between comorbidity and telehealth uptake was similar across racial/ethnic groups, whereas the significant association between social media communication and telehealth uptake varied by race/ethnicity. Specifically, the association was significantly less pronounced for Hispanic adults (b = -0.11, 95% CI [-0.19, -0.04], p < 0.01) and non-Hispanic Asian/other races adults (b = -0.13, 95% CI [-0.26, -0.01], p < 0.05) than it was for their non-Hispanic White counterparts. CONCLUSION: Results suggest the potential of using social media and telehealth to narrow health disparities, particularly serving as a bridge for members of underserved communities to telehealth uptake.

Multifunctional Filter Membranes Based on Self-Assembled Core-Shell Biodegradable Nanofibers for Persistent Electrostatic Filtration through the Triboelectric Effect.

The massive production of polymer-based respiratory masks during the COVID-19 pandemic has rekindled the issue of environmental pollution from nonrecyclable plastic waste. To mitigate this problem, conventional filters should be redesigned with improved filtration performance over the entire operational life while also being naturally degradable at the end. Herein, we developed a functional and biodegradable polymeric filter membrane consisting of a polybutylene adipate terephthalate (PBAT) matrix blended with cetyltrimethylammonium bromide (CTAB) and montmorillonite (MMT) clay, whose surface properties have been modified through cation exchange reactions for good miscibility with PBAT in an organic solvent. Particularly, the spontaneous evolution of a partial core-shell structure (i.e., PBAT core encased by CTAB-MMT shell) during the electrospinning process amplified the triboelectric effect as well as the antibacterial/antiviral activity that was not observed in naive PBAT. Unlike the conventional face mask filter that relies on the electrostatic adsorption mechanism, which deteriorates over time and/or due to external environmental factors, the PBAT@CTAB-MMT nanofiber membrane (NFM)-based filter continuously retains electrostatic charges on the surface due to the triboelectric effect of CTAB-MMT. As a result, the PBAT@CTAB-MMT NFM-based filter showed high filtration efficiencies (98.3%, PM0.3) even at a low differential pressure of 40 Pa or less over its lifetime. Altogether, we not only propose an effective and practical solution to improve the performance of filter membranes while minimizing their environmental footprint but also provide valuable insight into the synergetic functionalities of organic-inorganic hybrid materials for applications beyond filter membranes.

Application of machine learning for multi-community COVID-19 outbreak predictions with wastewater surveillance.

The potential of wastewater-based epidemiology (WBE) as a surveillance and early warning tool for the COVID-19 outbreak has been demonstrated. For areas with limited testing capacity, wastewater surveillance can provide information on the disease dynamic at a community level. A predictive model is a key to generating quantitative estimates of the infected population. Modeling longitudinal wastewater data can be challenging as biomarkers in wastewater are susceptible to variations caused by multiple factors associated with the wastewater matrix and the sewersheds characteristics. As WBE is an emerging trend, the model should be able to address the uncertainties of wastewater from different sewersheds. We proposed exploiting machine learning and deep learning techniques, which are supported by the growing WBE data. In this article, we reviewed the existing predictive models, among which the emerging machine learning/deep learning models showed great potential. However, most models are built for individual sewersheds with few features extracted from the wastewater. To fulfill the research gap, we compared different time-series and non-time-series models for their short-term predictive performance of COVID-19 cases in 9 diverse sewersheds. The time-series models, long short-term memory (LSTM) and Prophet, outcompeted the non-time-series models. Besides viral (SARS-CoV-2) loads and location identity, domain-specific features like biochemical parameters of wastewater, geographical parameters of the sewersheds, and some socioeconomic parameters of the communities can contribute to the models. With proper feature engineering and hyperparameter tuning, we believe machine learning models like LSTM can be a feasible solution for the COVID-19 trend prediction via WBE. Overall, this is a proof-of-concept study on the application of machine learning in COVID-19 WBE. Future studies are needed to deploy and maintain the model in more real-world applications.

Clinical epidemiological applicability of real-time polymerase chain reaction for COVID-19.

OBJECTIVES: Real-time polymerase chain reaction is currently used as a confirmatory test for coronavirus disease 2019 (COVID-19). The test results are interpreted as positive, negative, or inconclusive, and are used only for a qualitative classification of patients. However, the test results can be quantitated using threshold count (Ct) values to determine the amount of virus present in the sample. Therefore, this study investigated the diagnostic usefulness of Ct results through various quantitative analyzes, along with an analysis of clinical and epidemiological characteristics. METHODS: Clinical and epidemiological data from 4,642 COVID-19 patients in April 2021 were analyzed, including the Ct values of the RNA-dependent RNA polymerase (RdRp), envelope (E), and nucleocapsid (N) genes. Clinical and epidemiological data (sex, age, underlying diseases, and early symptoms) were collected through a structured questionnaire. A correlation analysis was used to examine the relationships between variables. RESULTS: All 3 genes showed statistically significant relationships with symptoms and severity levels. The Ct values of the RdRp gene decreased as the severity of the patients increased. Moreover, statistical significance was observed for the presence of underlying diseases and dyspnea. CONCLUSION: Ct values were found to be related to patients' clinical and epidemiological characteristics. In particular, since these factors are closely related to symptoms and severity, Ct values can be used as primary data for predicting patients' disease prognosis despite the limitations of this method. Conducting follow-up studies to validate this approach might enable using the data from this study to establish policies for preventing COVID-19 infection and spread.

Socioeconomic status correlations with confirmed COVID-19 cases and SARS-CoV-2 wastewater concentrations in small-medium sized communities.

Over two years into the COVID-19 pandemic, it is apparent that some populations across the world are more susceptible than others to SARS-CoV-2 infection and spread. Understanding how populations with varying demographic patterns are impacted by COVID-19 may highlight which factors are most important in targeting to combat global suffering. The first objective of this study was to investigate the association of various socioeconomic status (SES) parameters and confirmed COVID-19 cases in the state of Ohio, USA. This study examines the largest and capital city of Ohio (Columbus) and various small-medium-sized communities. The second objective was to determine the relationship between SES parameters and community-level SARS-CoV-2 concentrations using municipal wastewater samples from each city's respective wastewater treatment plants from August 2020 to January 2021. SES parameters include population size, median income, poverty, race/ethnicity, education, health care access, types of COVID-19 testing sites, and social vulnerability index. Statistical analysis results show that confirmed (normalized and/or non-normalized) COVID-19 cases were negatively associated with White percentage and registered hospitals, and positively associated with registered physicians and various COVID-19 testing sites. Wastewater viral concentrations were negatively associated with poverty, and positively associated with median income, community health centers, and onsite rapid testing locations. Additional analyses conclude that population is a significant factor in determining COVID-19 cases and SARS-CoV-2 wastewater concentrations. Results indicate that community healthcare parameters relate to a negative health outcome (COVID-19) and that demographic parameters can be associated with community-level SARS-CoV-2 wastewater concentrations. As the first study that examines the association between socioeconomic parameters and SARS-CoV-2 wastewater concentrations as well as confirmed COVID-19 cases, it is apparent that social determinants have an impact in determining the health burden of small-medium sized Ohioan cities. This study design and innovative approach are scalable and applicable for endemic and pandemic surveillance across the world.

Associations between living arrangement and sexual and gender minority stressors among university students since the start of the COVID-19 pandemic.

OBJECTIVE: To examine the associations between COVID-19-related living arrangements and sexual and gender minority (SGM)-related stressors (ie, identity concealment and familial rejection). PARTICIPANTS: N = 478 SGM university students (Mage = 22 years, SD = 4.00). METHODS: SGM university students were surveyed cross-sectionally between May and August 2020 regarding SGM-related stressors and living arrangements since the start of COVID-19. RESULTS: Approximately half (48.7%) of the sample reported a living rearrangement to their parents' home due to COVID-19. Living rearrangement to parents' homes was associated with an increased degree of identity concealment (ß [95% C.I.] = 0.62 [0.10, 1.15]; p = .020) and familial rejection (ß [95% C.I.] = 1.56 [0.72, 2.41]; p < .001) since the start of COVID-19 compared to stably living without parents (34.3%). Stably living with parents (17.0%) was not associated with increased degree of SGM-related stressors compared to experiencing a living rearrangement. CONCLUSIONS: Stakeholders must consider the unique identity-related vulnerabilities of SGM students living with parents and who experience living rearrangements due to COVID-19.

Wastewater surveillance of SARS-CoV-2 in dormitories as a part of comprehensive university campus COVID-19 monitoring.

Wastewater-based epidemiology is an effective tool for monitoring infectious disease spread or illicit drug use within communities. At the Ohio State University, we conducted a SARS-CoV-2 wastewater surveillance program in the 2020-2021 academic year and compared results with the university-required weekly COVID-19 saliva testing to monitor COVID-19 infection prevalence in the on-campus residential communities. The objectives of the study were to rapidly track trends in the wastewater SARS-CoV-2 gene concentrations, analyze the relationship between case numbers and wastewater signals when adjusted using human fecal viral indicator concentrations (PMMoV, crAssphage) in wastewater, and investigate the relationship of the SARS-CoV-2 gene concentrations with wastewater parameters. SARS-CoV-2 nucleocapsid and envelope (N1, N2, and E) gene concentrations, determined with reverse transcription droplet digital PCR, were used to track SARS-CoV-2 viral loads in dormitory wastewater once a week at 6 sampling sites across the campus during the fall semester in 2020. During the following spring semester, research was focused on SARS-CoV2 N2 gene concentrations at 5 sites sampled twice a week. Spearman correlations both with and without adjusting using human fecal viral indicators showed a significant correlation (p < 0.05) between human COVID-19 positive case counts and wastewater SARS-CoV-2 gene concentrations. Spearman correlations showed significant relationships between N1 gene concentrations and both TSS and turbidity, and between E gene concentrations and both pH and turbidity. These results suggest that wastewater signal increases with the census of infected individuals, in which the majority are asymptomatic, with a statistically significant (p-value <0.05) temporal correlation. The study design can be utilized as a platform for rapid trend tracking of SARS-CoV-2 variants and other diseases circulating in various communities.

Violacein-embedded nanofiber filters with antiviral and antibacterial activities.

Most respiratory masks are made of fabrics, which only capture the infectious virus carriers into the matrix. However, these contagious viruses stay active for a long duration (∼7 days) within the fabric matrix possibly inducing post-contact transmissions. Moreover, conventional masks are vulnerable to bacterial growth with prolonged exposure to exhaled breaths. Herein, we combined violacein, a naturally-occurring antimicrobial agent, with porous nanofiber membranes to develop a series of functional filters that autonomously sterilizes viruses and bacteria. The violacein-embedded membrane inactivates viruses within 4 h (99.532 % reduction for influenza and 99.999 % for human coronavirus) and bacteria within 2 h (75.5 % reduction). Besides, its nanofiber structure physically filters out the nanoscale (<0.8 µm) and micron-scale (0.8 µm - 3 µm) particulates, providing high filtration efficiencies (99.7 % and 100 % for PM 1.0 and PM 10, respectively) with long-term stability (for 25 days). In addition, violacein provides additional UV-resistant property, which protects the skin from sunlight. The violacein-embedded membrane not only proved the sterile efficacy of microbe extracted pigments for biomedical products but also provided insights to advance the personal protective equipment (PPE) to fight against contagious pathogens.

Identification of MicroRNAs as Potential Blood-Based Biomarkers for Diagnosis and Therapeutic Monitoring of Active Tuberculosis.

Early diagnosis increases the treatment success rate for active tuberculosis (ATB) and decreases mortality. MicroRNAs (miRNAs) have been studied as blood-based markers of several infectious diseases. We performed miRNA profiling to identify differentially expressed (DE) miRNAs using whole blood samples from 10 healthy controls (HCs), 15 subjects with latent tuberculosis infection (LTBI), and 12 patients with ATB, and investigated the expression of the top six miRNAs at diagnosis and over the treatment period in addition to performing miRNA-target gene network and gene ontology analyses. miRNA profiling identified 84 DE miRNAs in patients with ATB, including 80 upregulated and four downregulated miRNAs. Receiver operating characteristic curves of the top six miRNAs exhibited excellent distinguishing efficiency with an area under curve (AUC) value > 0.85. Among them, miR-199a-3p and miR-6886-3p can differentiate between ATB and LTBI. Anti-TB treatment restored the levels of miR-199b-3p, miR-199a-3p, miR-16-5p, and miR-374c-5p to HC levels. Furthermore, 108 predicted target genes were related to the regulation of cellular amide metabolism, intrinsic apoptotic signaling, translation, transforming growth factor beta receptor signaling, and cysteine-type endopeptidase activity. The DE miRNAs identified herein are potential biomarkers for diagnosis and therapeutic monitoring in ATB.

Potential environmental and health risk when returning to normal amidst COVID-19 vaccination.

Due to the SARS-CoV-2 pandemic and restricted occupancy in work and school settings, there is a heightened risk for Legionella infection. An increase of stagnation in water pipe systems with limited water usage stimulates biofilm build-up, further facilitating Legionella proliferation. Individuals can inhale infected water aerosols and develop Legionellosis that can progress into mild flu-like symptoms or severe pneumonia. While SARS-CoV-2 vaccinations have been introduced globally, there is a concern for bacterial coinfections as individuals resume normal activities. Even with new SARS-CoV-2 variants circulating, Legionella persists as a public health threat as vulnerable communities' restrictions fluctuate. Proper water monitoring and management are critical while reopening communities. This article features Legionella characteristics and novel case reports amidst the pandemic. This article encourages greater awareness for building managers to minimize water stagnancy by disinfecting water distribution systems and promotes healthcare professionals to properly diagnose other illnesses during the ongoing pandemic to reduce morbidity and mortality.

Convergent use of phosphatidic acid for hepatitis C virus and SARS-CoV-2 replication organelle formation.

Double membrane vesicles (DMVs) serve as replication organelles of plus-strand RNA viruses such as hepatitis C virus (HCV) and SARS-CoV-2. Viral DMVs are morphologically analogous to DMVs formed during autophagy, but lipids driving their biogenesis are largely unknown. Here we show that production of the lipid phosphatidic acid (PA) by acylglycerolphosphate acyltransferase (AGPAT) 1 and 2 in the ER is important for DMV biogenesis in viral replication and autophagy. Using DMVs in HCV-replicating cells as model, we found that AGPATs are recruited to and critically contribute to HCV and SARS-CoV-2 replication and proper DMV formation. An intracellular PA sensor accumulated at viral DMV formation sites, consistent with elevated levels of PA in fractions of purified DMVs analyzed by lipidomics. Apart from AGPATs, PA is generated by alternative pathways and their pharmacological inhibition also impaired HCV and SARS-CoV-2 replication as well as formation of autophagosome-like DMVs. These data identify PA as host cell lipid involved in proper replication organelle formation by HCV and SARS-CoV-2, two phylogenetically disparate viruses causing very different diseases, i.e. chronic liver disease and COVID-19, respectively. Host-targeting therapy aiming at PA synthesis pathways might be suitable to attenuate replication of these viruses.

Contribution of autophagy machinery factors to HCV and SARS-CoV-2 replication organelle formation.

Positive-strand RNA viruses replicate in close association with rearranged intracellular membranes. For hepatitis C virus (HCV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), these rearrangements comprise endoplasmic reticulum (ER)-derived double membrane vesicles (DMVs) serving as RNA replication sites. Cellular factors involved in DMV biogenesis are poorly defined. Here, we show that despite structural similarity of viral DMVs with autophagosomes, conventional macroautophagy is dispensable for HCV and SARS-CoV-2 replication. However, both viruses exploit factors involved in autophagosome formation, most notably class III phosphatidylinositol 3-kinase (PI3K). As revealed with a biosensor, PI3K is activated in cells infected with either virus to produce phosphatidylinositol 3-phosphate (PI3P) while kinase complex inhibition or depletion profoundly reduces replication and viral DMV formation. The PI3P-binding protein DFCP1, recruited to omegasomes in early steps of autophagosome formation, participates in replication and DMV formation of both viruses. These results indicate that phylogenetically unrelated HCV and SARS-CoV-2 exploit similar components of the autophagy machinery to create their replication organelles.

Detection of SARS-CoV-2 in urban stormwater: An environmental reservoir and potential interface between human and animal sources.

While wastewater has been found to harbor SARS-CoV-2, the persistence of SARSCoV-2 in stormwater and potential transmission is poorly understood. It is plausible that the virus is detectable in stormwater samples where human-originated fecal contamination may have occurred from sources like sanitary sewer overflows, leaky wastewater pipes, and non-human animal waste. Because of these potential contamination pathways, it is possible that stormwater could serve as an environmental reservoir and transmission pathway for SARS-CoV-2. The objectives of this study are: 1) determine whether the presence of SARS-CoV-2 could be detected in stormwater via RT-ddPCR (reverse transcription-digital droplet PCR); 2) quantify human-specific fecal contamination using microbial source tracking; and 3) examine whether rainfall characteristics influence virus concentrations. To accomplish these objectives, we investigated whether SARS-CoV-2 could be detected from 10 storm sewer outfalls each draining a single, dominant land use in Columbus, Xenia, and Springboro, Ohio. Of the 25 samples collected in 2020, at minimum one SARS-CoV-2 target gene (N2 [US-CDC and CN-CDC], and E) was detected in 22 samples (88%). A single significant correlation (p = 0.001), between antecedent dry period and the USCDC N2 gene, was found between target gene concentrations and rainfall characteristics. Grouped by city, two significant relationships emerged showing cities had different levels of the SARS-CoV-2 E gene. Given the differences in scale, the county-level COVID-19 confirmed cases COVID-19 rates were not significantly correlated with stormwater outfall-scale SARS-CoV-2 gene concentrations. Countywide COVID-19 data did not accurately portray neighborhood-scale confirmed COVID-19 case rates. Potential hazards may arise when human fecal contamination is present in stormwater and facilitates future investigation on the threat of viral outbreaks via surfaces waters where fecal contamination may have occurred. Future studies should investigate whether humans are able to contract SARS-CoV-2 from surface waters and the factors that may affect viral longevity and transmission.

Integrative Imaging Reveals SARS-CoV-2-Induced Reshaping of Subcellular Morphologies.

Pathogenesis induced by SARS-CoV-2 is thought to result from both an inflammation-dominated cytokine response and virus-induced cell perturbation causing cell death. Here, we employ an integrative imaging analysis to determine morphological organelle alterations induced in SARS-CoV-2-infected human lung epithelial cells. We report 3D electron microscopy reconstructions of whole cells and subcellular compartments, revealing extensive fragmentation of the Golgi apparatus, alteration of the mitochondrial network and recruitment of peroxisomes to viral replication organelles formed by clusters of double-membrane vesicles (DMVs). These are tethered to the endoplasmic reticulum, providing insights into DMV biogenesis and spatial coordination of SARS-CoV-2 replication. Live cell imaging combined with an infection sensor reveals profound remodeling of cytoskeleton elements. Pharmacological inhibition of their dynamics suppresses SARS-CoV-2 replication. We thus report insights into virus-induced cytopathic effects and provide alongside a comprehensive publicly available repository of 3D datasets of SARS-CoV-2-infected cells for download and smooth online visualization.