Rice Coronavirus Research

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Works related to coronaviruses that are authored by members of the Rice community.

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Fear of missing out and depressive symptoms during the COVID-19 pandemic
(Wiley, 2023) LeRoy, Angie S.; Lai, Vincent D.; Tsay-Jones, Arya; Fagundes, Christopher P.
During the early stages of the COVID-19 pandemic, governments issued public health safety measures (e.g., “stay-at-home” ordinances), leaving many people “missing out” on integral social aspects of their own lives. The fear of missing out, popularly shortened as, “FoMO,” is a felt sense of unease one experiences when they perceive they may be missing out on rewarding and/or enjoyable experiences. Among 76 participants (ages M = 69.36, SD = 5.34), who were at risk for hospitalization or death if infected with COVID-19, we found that FoMO was associated with depressive symptoms at Time 1, even when controlling for perceived stress, loneliness, and fear of COVID-19. However, FoMO did not predict future depressive symptoms, about 1 week later, when controlling for Time 1 depressive symptoms. These findings provide further evidence that FoMO is associated with depressive symptoms in a short period of time even when accounting for other powerful social factors such as loneliness. Future research should explore the potential causal relationships between FoMO and depression, especially those that may establish temporal precedence.
A Recombinant Protein XBB.1.5 RBD/Alum/CpG Vaccine Elicits High Neutralizing Antibody Titers against Omicron Subvariants of SARS-CoV-2
(MDPI, 2023) Thimmiraju, Syamala Rani; Adhikari, Rakesh; Villar, Maria Jose; Lee, Jungsoon; Liu, Zhuyun; Kundu, Rakhi; Chen, Yi-Lin; Sharma, Suman; Ghei, Karm; Keegan, Brian; Versteeg, Leroy; Gillespie, Portia M.; Ciciriello, Allan; Islam, Nelufa Y.; Poveda, Cristina; Uzcategui, Nestor; Chen, Wen-Hsiang; Kimata, Jason T.; Zhan, Bin; Strych, Ulrich; Bottazzi, Maria Elena; Hotez, Peter J.; Pollet, Jeroen
(1) Background: We previously reported the development of a recombinant protein SARS-CoV-2 vaccine, consisting of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, adjuvanted with aluminum hydroxide (alum) and CpG oligonucleotides. In mice and non-human primates, our wild-type (WT) RBD vaccine induced high neutralizing antibody titers against the WT isolate of the virus, and, with partners in India and Indonesia, it was later developed into two closely resembling human vaccines, Corbevax and Indovac. Here, we describe the development and characterization of a next-generation vaccine adapted to the recently emerging XBB variants of SARS-CoV-2. (2) Methods: We conducted preclinical studies in mice using a novel yeast-produced SARS-CoV-2 XBB.1.5 RBD subunit vaccine candidate formulated with alum and CpG. We examined the neutralization profile of sera obtained from mice vaccinated twice intramuscularly at a 21-day interval with the XBB.1.5-based RBD vaccine, against WT, Beta, Delta, BA.4, BQ.1.1, BA.2.75.2, XBB.1.16, XBB.1.5, and EG.5.1 SARS-CoV-2 pseudoviruses. (3) Results: The XBB.1.5 RBD/CpG/alum vaccine elicited a robust antibody response in mice. Furthermore, the serum from vaccinated mice demonstrated potent neutralization against the XBB.1.5 pseudovirus as well as several other Omicron pseudoviruses. However, regardless of the high antibody cross-reactivity with ELISA, the anti-XBB.1.5 RBD antigen serum showed low neutralizing titers against the WT and Delta virus variants. (4) Conclusions: Whereas we observed modest cross-neutralization against Omicron subvariants with the sera from mice vaccinated with the WT RBD/CpG/Alum vaccine or with the BA.4/5-based vaccine, the sera raised against the XBB.1.5 RBD showed robust cross-neutralization. These findings underscore the imminent opportunity for an updated vaccine formulation utilizing the XBB.1.5 RBD antigen.
Public Health Interventions Guided by Houston’s Wastewater Surveillance Program During the COVID-19 Pandemic
(Sage, 2023) Hopkins, Loren; Ensor, Katherine B.; Stadler, Lauren; Johnson, Catherine D.; Schneider, Rebecca; Domakonda, Kaavya; McCarthy, James J.; Septimus, Edward J.; Persse, David; Williams, Stephen L.
Since the start of the COVID-19 pandemic, wastewater surveillance has emerged as a powerful tool used by public health authorities to track SARS-CoV-2 infections in communities. In May 2020, the Houston Health Department began working with a coalition of municipal and academic partners to develop a wastewater monitoring and reporting system for the city of Houston, Texas. Data collected from the system are integrated with other COVID-19 surveillance data and communicated through different channels to local authorities and the general public. This information is used to shape policies and inform actions to mitigate and prevent the spread of COVID-19 at municipal, institutional, and individual levels. Based on the success of this monitoring and reporting system to drive public health protection efforts, the wastewater surveillance program is likely to become a standard part of the public health toolkit for responding to infectious diseases and, potentially, other disease-causing outbreaks.
A rapid, low-cost, and highly sensitive SARS-CoV-2 diagnostic based on whole-genome sequencing
(Public Library of Science, 2023) Adastra, Per A.; Durand, Neva C.; Mitra, Namita; Pulido, Saul Godinez; Mahajan, Ragini; Blackburn, Alyssa; Colaric, Zane L.; Theisen, Joshua W. M.; Weisz, David; Dudchenko, Olga; Gnirke, Andreas; Rao, Suhas S. P.; Kaur, Parwinder; Aiden, Erez Lieberman; Aiden, Aviva Presser; Center for Theoretical Biological Physics
Early detection of SARS-CoV-2 infection is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset. Here, we introduce a low-cost, high-throughput method for diagnosing and studying SARS-CoV-2 infection. Dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), this method amplifies the entirety of the SARS-CoV-2 genome. This contrasts with typical RT-PCR-based diagnostic tests, which amplify only a few loci. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https://artic.network/) with short-read DNA sequencing and de novo genome assembly. Using this method, we can reliably (>95% accuracy) detect SARS-CoV-2 at a concentration of 84 genome equivalents per milliliter (GE/mL). The vast majority of diagnostic methods meeting our analytical criteria that are currently authorized for use by the United States Food and Drug Administration with the Coronavirus Disease 2019 (COVID-19) Emergency Use Authorization require higher concentrations of the virus to achieve this degree of sensitivity and specificity. In addition, we can reliably assemble the SARS-CoV-2 genome in the sample, often with no gaps and perfect accuracy given sufficient viral load. The genotypic data in these genome assemblies enable the more effective analysis of disease spread than is possible with an ordinary binary diagnostic. These data can also help identify vaccine and drug targets. Finally, we show that the diagnoses obtained using POLAR of positive and negative clinical nasal mid-turbinate swab samples 100% match those obtained in a clinical diagnostic lab using the Center for Disease Control’s 2019-Novel Coronavirus test. Using POLAR, a single person can manually process 192 samples over an 8-hour experiment at the cost of ~$36 per patient (as of December 7th, 2022), enabling a 24-hour turnaround with sequencing and data analysis time. We anticipate that further testing and refinement will allow greater sensitivity using this approach.
Stratification of Pediatric COVID-19 Cases Using Inflammatory Biomarker Profiling and Machine Learning
(MDPI, 2023) Subramanian, Devika; Vittala, Aadith; Chen, Xinpu; Julien, Christopher; Acosta, Sebastian; Rusin, Craig; Allen, Carl; Rider, Nicholas; Starosolski, Zbigniew; Annapragada, Ananth; Devaraj, Sridevi
While pediatric COVID-19 is rarely severe, a small fraction of children infected with SARS-CoV-2 go on to develop multisystem inflammatory syndrome (MIS-C), with substantial morbidity. An objective method with high specificity and high sensitivity to identify current or imminent MIS-C in children infected with SARS-CoV-2 is highly desirable. The aim was to learn about an interpretable novel cytokine/chemokine assay panel providing such an objective classification. This retrospective study was conducted on four groups of pediatric patients seen at multiple sites of Texas Children’s Hospital, Houston, TX who consented to provide blood samples to our COVID-19 Biorepository. Standard laboratory markers of inflammation and a novel cytokine/chemokine array were measured in blood samples of all patients. Group 1 consisted of 72 COVID-19, 70 MIS-C and 63 uninfected control patients seen between May 2020 and January 2021 and predominantly infected with pre-alpha variants. Group 2 consisted of 29 COVID-19 and 43 MIS-C patients seen between January and May 2021 infected predominantly with the alpha variant. Group 3 consisted of 30 COVID-19 and 32 MIS-C patients seen between August and October 2021 infected with alpha and/or delta variants. Group 4 consisted of 20 COVID-19 and 46 MIS-C patients seen between October 2021 andJanuary 2022 infected with delta and/or omicron variants. Group 1 was used to train an L1-regularized logistic regression model which was tested using five-fold cross validation, and then separately validated against the remaining naïve groups. The area under receiver operating curve (AUROC) and F1-score were used to quantify the performance of the cytokine/chemokine assay-based classifier. Standard laboratory markers predict MIS-C with a five-fold cross-validated AUROC of 0.86 ± 0.05 and an F1 score of 0.78 ± 0.07, while the cytokine/chemokine panel predicted MIS-C with a five-fold cross-validated AUROC of 0.95 ± 0.02 and an F1 score of 0.91 ± 0.04, with only sixteen of the forty-five cytokines/chemokines sufficient to achieve this performance. Tested on Group 2 the cytokine/chemokine panel yielded AUROC = 0.98 and F1 = 0.93, on Group 3 it yielded AUROC = 0.89 and F1 = 0.89, and on Group 4 AUROC = 0.99 and F1 = 0.97. Adding standard laboratory markers to the cytokine/chemokine panel did not improve performance. A top-10 subset of these 16 cytokines achieves equivalent performance on the validation data sets. Our findings demonstrate that a sixteen-cytokine/chemokine panel as well as the top ten subset provides a highly sensitive, and specific method to identify MIS-C in patients infected with SARS-CoV-2 of all the major variants identified to date.
Mechanisms of SARS-CoV-2-induced Encephalopathy and Encephalitis in COVID-19 Cases
(Sage, 2023) Vengalil, Aaron; Nizamutdinov, Damir; Su, Matthew; Huang, Jason H.
The SARS-CoV-2 virus caused an unprecedented pandemic around the globe, infecting 36.5 million people and causing the death of over 1 million in the United States of America alone. COVID-19 patients demonstrated respiratory symptoms, cardiovascular complications, and neurologic symptoms, which in most severe cases included encephalopathy and encephalitis. Hypoxia and the uncontrolled proliferation of cytokines are commonly recognized to cause encephalopathy, while the retrograde trans-synaptic spread of the virus is thought to cause encephalitis in SARS-CoV-2-induced pathogenesis. Although recent research revealed some mechanisms explaining the development of neurologic symptoms, it still remains unclear whether interactions between these mechanisms exist. This review focuses on the discussion and analysis of previously reported hypotheses of SARS-CoV-2-induced encephalopathy and encephalitis and looks into possible overlaps between the pathogenesis of both neurological outcomes of the disease. Promising therapeutic approaches to prevent and treat SARS-CoV-2-induced neurological complications are also covered. More studies are needed to further investigate the dominant mechanism of pathogenesis for developing more effective preventative measures in COVID-19 cases with the neurologic presentation.
Balancing economic and epidemiological interventions in the early stages of pathogen emergence
(AAAS, 2023) Dobson, Andy; Ricci, Cristiano; Boucekkine, Raouf; Gozzi, Fausto; Fabbri, Giorgio; Loch-Temzelides, Ted; Pascual, Mercedes; Baker Institute for Public Policy
The global pandemic of COVID-19 has underlined the need for more coordinated responses to emergent pathogens. These responses need to balance epidemic control in ways that concomitantly minimize hospitalizations and economic damages. We develop a hybrid economic-epidemiological modeling framework that allows us to examine the interaction between economic and health impacts over the first period of pathogen emergence when lockdown, testing, and isolation are the only means of containing the epidemic. This operational mathematical setting allows us to determine the optimal policy interventions under a variety of scenarios that might prevail in the first period of a large-scale epidemic outbreak. Combining testing with isolation emerges as a more effective policy than lockdowns, substantially reducing deaths and the number of infected hosts, at lower economic cost. If a lockdown is put in place early in the course of the epidemic, it always dominates the “laissez-faire” policy of doing nothing.
Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater
(Springer Nature, 2023) Sapoval, Nicolae; Liu, Yunxi; Lou, Esther G.; Hopkins, Loren; Ensor, Katherine B.; Schneider, Rebecca; Stadler, Lauren B.; Treangen, Todd J.
As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).
SARS-CoV-2 Exposure in Norway Rats (Rattus norvegicus) from New York City
(American Society for Microbiology, 2023) Wang, Yang; Lenoch, Julianna; Kohler, Dennis; DeLiberto, Thomas J.; Tang, Cynthia Y.; Li, Tao; Tao, Yizhi Jane; Guan, Minhui; Compton, Susan; Zeiss, Caroline; Hang, Jun; Wan, Xiu-Feng
Millions of Norway rats (Rattus norvegicus) inhabit New York City (NYC), presenting the potential for transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from humans to rats. We evaluated SARS-CoV-2 exposure among 79 rats captured from NYC during the fall of 2021. Our results showed that 13 of the 79 rats (16.5%) tested IgG- or IgM-positive, and partial SARS-CoV-2 genomes were recovered from all 4 rats that were qRT-PCR (reverse transcription-quantitative PCR)-positive. Genomic analyses suggest these viruses were associated with genetic lineage B, which was predominant in NYC in the spring of 2020 during the early pandemic period. To further investigate rat susceptibility to SARS-CoV-2 variants, we conducted a virus challenge study and showed that Alpha, Delta, and Omicron variants can cause infections in wild-type Sprague Dawley (SD) rats, including high replication levels in the upper and lower respiratory tracts and induction of both innate and adaptive immune responses. Additionally, the Delta variant resulted in the highest infectivity. In summary, our results indicate that rats are susceptible to infection with Alpha, Delta, and Omicron variants, and wild Norway rats in the NYC municipal sewer systems have been exposed to SARS-CoV-2. Our findings highlight the need for further monitoring of SARS-CoV-2 in urban rat populations and for evaluating the potential risk of secondary zoonotic transmission from these rat populations back to humans. IMPORTANCE The host tropism expansion of SARS-CoV-2 raises concern for the potential risk of reverse-zoonotic transmission of emerging variants into rodent species, including wild rat species. In this study, we present both genetic and serological evidence for SARS-CoV-2 exposure to the New York City wild rat population, and these viruses may be linked to the viruses that were circulating during the early stages of the pandemic. We also demonstrated that rats are susceptible to additional variants (i.e., Alpha, Delta, and Omicron) that have been predominant in humans and that susceptibility to infection varies by variant. Our findings highlight the reverse zoonosis of SARS-CoV-2 to urban rats and the need for further monitoring of SARS-CoV-2 in rat populations for potential secondary zoonotic transmission to humans.
Aging and Burnout for Nurses in an Acute Care Setting: The First Wave of COVID-19
(MDPI, 2023) Beier, Margaret E.; Cockerham, Mona; Branson, Sandy; Boss, Lisa
We examined the relationship between age, coping, and burnout during the peak of the COVID-19 pandemic with nurses in Texas (N = 376). Nurses were recruited through a professional association and snowball sampling methodology for the cross-sectional survey study. Framed in lifespan development theories, we expected that nurse age and experience would be positively correlated with positive coping strategies (e.g., getting emotional support from others) and negatively correlated with negative coping strategies (e.g., drinking and drug use). We also expected age to be negatively related to the emotional exhaustion and depersonalization facets of burnout and positively related to the personal accomplishment facet of burnout. Findings were largely supported in that age was positively associated with positive coping and personal accomplishment and age and experience were negatively correlated with negative coping and depersonalization. Age was not, however, associated with emotional exhaustion. Mediation models further suggest that coping explains some of the effect of age on burnout. A theoretical extension of lifespan development models into an extreme environment and practical implications for coping in these environments are discussed.
The contagion number: How fast can a disease spread?
(National Library of Serbia, 2023) Blessley, Misty; Davila, Randy; Hale, Trevor; Pepper, Ryan
The burning number of a graph models the rate at which a disease, information, or other externality can propagate across a network. The burning number is known to be NP-hard even for a tree. Herein, we define a relative of the burning number that we coin the contagion number (CN). We aver that the CN is a better metric to model disease spread than the burning number as it only counts first time infections (i.e., constrains a node from getting the same disease/same variant/same alarm more than once). This is important because the Centers for Disease Control and Prevention report that COVID-19 reinfections are rare. This paper delineates a method to solve for the contagion number of any tree, in polynomial time, which addresses how fast a disease could spread (i.e., a worst-cast analysis) and then employs simulation to determine the average contagion number (ACN) (i.e., a most-likely analysis) of how fast a disease would spread. The latter is analyzed on scale-free graphs, which are used to model human social networks generated through a preferential attachment mechanism. With CN differing across network structures and almost identical to ACN, our findings advance disease spread understanding and reveal the importance of network structure. In a borderless world without replete resources, understanding disease spread can do much to inform public policy and managerial decision makers’ allocation decisions. Furthermore, our direct interactions with supply chain executives at two COVID-19 vaccine developers provided practical grounding on what the results suggest for achieving social welfare objectives.
The COVID-19 Challenge Now Is Getting Into Heads, Arms Will Follow
(Taylor & Francis, 2021) O’Rourke, Thomas; Iammarino, Nicholas
With the onset and rapid spread of COVID-19 without a safe and effective vaccine, initial efforts to reduce community spread focused on basic public health measures such as mask wearing, social distancing, handwashing, avoiding large gatherings, and suspected cases isolation and quarantine. Following was the development of the COVID-19 vaccination and a shift to immunize the U.S. population to achieve herd immunity and halt the pandemic. Many diverse methods to influence vaccine uptake behaviors have been implemented including increasing the number and accessibility of vaccine sites, lowering the eligible age, relaxing eligibility requirements, public education and outreach campaigns, introducing state, local and job-based incentives and, in some instances, vaccine mandates. With two-thirds of the population now vaccinated with at least one shot, additional gains will be more difficult requiring more creative approaches rooted in behavior change theories and strategies. The behaviors associated with COVID-19 are not new and “tried and true” behaviorally oriented prevention strategies created long before COVID-19 arrived can effectively be used to educate people. Health educators and professionals can play a critical role with this remaining resistant population subset and must employ behaviorally oriented messages that are factually accurate, persuasive and relevant, and culturally and linguistically appropriate.
Modeling the positive testing rate of COVID-19 in South Africa using a semi-parametric smoother for binomial data
(Frontiers, 2023) Owokotomo, Olajumoke Evangelina; Manda, Samuel; Cleasen, Jürgen; Kasim, Adetayo; Sengupta, Rudradev; Shome, Rahul; Subhra Paria, Soumya; Reddy, Tarylee; Shkedy, Ziv
Identification and isolation of COVID-19 infected persons plays a significant role in the control of COVID-19 pandemic. A country's COVID-19 positive testing rate is useful in understanding and monitoring the disease transmission and spread for the planning of intervention policy. Using publicly available data collected between March 5th, 2020 and May 31st, 2021, we proposed to estimate both the positive testing rate and its daily rate of change in South Africa with a flexible semi-parametric smoothing model for discrete data. There was a gradual increase in the positive testing rate up to a first peak rate in July, 2020, then a decrease before another peak around mid-December 2020 to mid-January 2021. The proposed semi-parametric smoothing model provides a data driven estimates for both the positive testing rate and its change. We provide an online R dashboard that can be used to estimate the positive rate in any country of interest based on publicly available data. We believe this is a useful tool for both researchers and policymakers for planning intervention and understanding the COVID-19 spread.
Wastewater surveillance of SARS-CoV-2 and influenza in preK-12 schools shows school, community, and citywide infections
(Elsevier, 2023) Wolken, Madeline; Sun, Thomas; McCall, Camille; Schneider, Rebecca; Caton, Kelsey; Hundley, Courtney; Hopkins, Loren; Ensor, Katherine; Domakonda, Kaavya; Prashant, Kalvapalle; Persse, David; Williams, Stephen; Stadler, Lauren B.
Wastewater surveillance is a passive and efficient way to monitor the spread of infectious diseases in large populations and high transmission areas such as preK-12 schools. Infections caused by respiratory viruses in school-aged children are likely underreported, particularly because many children may be asymptomatic or mildly symptomatic. Wastewater monitoring of SARS-CoV-2 has been studied extensively and primarily by sampling at centralized wastewater treatment plants, and there are limited studies on SARS-CoV-2 in preK-12 school wastewater. Similarly, wastewater detections of influenza have only been reported in wastewater treatment plant and university manhole samples. Here, we present the results of a 17-month wastewater monitoring program for SARS-CoV-2 (n = 2176 samples) and influenza A and B (n = 1217 samples) in 51 preK-12 schools. We show that school wastewater concentrations of SARS-CoV-2 RNA were strongly associated with COVID-19 cases in schools and community positivity rates, and that influenza detections in school wastewater were significantly associated with citywide influenza diagnosis rates. Results were communicated back to schools and local communities to enable mitigation strategies to stop the spread, and direct resources such as testing and vaccination clinics. This study demonstrates that school wastewater surveillance is reflective of local infections at several population levels and plays a crucial role in the detection and mitigation of outbreaks.
Analysis of bronchoalveolar lavage fluid metatranscriptomes among patients with COVID-19 disease
(Springer Nature, 2022) Jochum, Michael; Lee, Michael D.; Curry, Kristen; Zaksas, Victoria; Vitalis, Elizabeth; Treangen, Todd; Aagaard, Kjersti; Ternus, Krista L.
To better understand the potential relationship between COVID-19 disease and hologenome microbial community dynamics and functional profiles, we conducted a multivariate taxonomic and functional microbiome comparison of publicly available human bronchoalveolar lavage fluid (BALF) metatranscriptome samples amongst COVID-19 (n = 32), community acquired pneumonia (CAP) (n = 25), and uninfected samples (n = 29). We then performed a stratified analysis based on mortality amongst the COVID-19 cohort with known outcomes of deceased (n = 10) versus survived (n = 15). Our overarching hypothesis was that there are detectable and functionally significant relationships between BALF microbial metatranscriptomes and the severity of COVID-19 disease onset and progression. We observed 34 functionally discriminant gene ontology (GO) terms in COVID-19 disease compared to the CAP and uninfected cohorts, and 21 GO terms functionally discriminant to COVID-19 mortality (q < 0.05). GO terms enriched in the COVID-19 disease cohort included hydrolase activity, and significant GO terms under the parental terms of biological regulation, viral process, and interspecies interaction between organisms. Notable GO terms associated with COVID-19 mortality included nucleobase-containing compound biosynthetic process, organonitrogen compound catabolic process, pyrimidine-containing compound biosynthetic process, and DNA recombination, RNA binding, magnesium and zinc ion binding, oxidoreductase activity, and endopeptidase activity. A Dirichlet multinomial mixtures clustering analysis resulted in a best model fit using three distinct clusters that were significantly associated with COVID-19 disease and mortality. We additionally observed discriminant taxonomic differences associated with COVID-19 disease and mortality in the genus Sphingomonas, belonging to the Sphingomonadacae family, Variovorax, belonging to the Comamonadaceae family, and in the class Bacteroidia, belonging to the order Bacteroidales. To our knowledge, this is the first study to evaluate significant differences in taxonomic and functional signatures between BALF metatranscriptomes from COVID-19, CAP, and uninfected cohorts, as well as associating these taxa and microbial gene functions with COVID-19 mortality. Collectively, while this data does not speak to causality nor directionality of the association, it does demonstrate a significant relationship between the human microbiome and COVID-19. The results from this study have rendered testable hypotheses that warrant further investigation to better understand the causality and directionality of host–microbiome–pathogen interactions.
Physical Activity Independently Predicts Perceived Stress During the COVID-19 Pandemic in Private University Students
(Western Kentucky University, 2022) Brownell, Curtis; Kabiri, Laura; Diep, Cassandra; Perkins, Heidi; Perkins-Ball, Amanda; Rodriguez, Augusto
Physical activity has significantly declined during the COVID-19 pandemic. Declines in physical activity have correlated with increased levels of perceived stress, though studies examining physical activity and stress have failed to account for critical confounds. The present study aims to determine whether physical activity independently predicts perceived stress in students attending private four-year universities. Physical activity, socioeconomic status, resilience, gender, and perceived stress data were collected from 85 students and used in a multiple linear regression analysis. The regression model accounted for 43.5% of the variance in perceived stress (R2 = .462, p < .001). Total physical activity significantly and inversely predicted perceived stress (β = –.229, p = .007) in students irrespective of other covariates. Socioeconomic status, resilience, and gender also independently and significantly predicted perceived stress. Findings should be leveraged by university staff to promote psychological well-being and wholistic health initiatives incorporating physical activity as a primary and modifiable component.
Insights From the Virtual Team Science: Rapid Deployment During COVID-19
(Sage, 2022) Kilcullen, Molly; Feitosa, Jennifer; Salas, Eduardo
Objective: To provide insights for organizations that must rapidly deploy teams to remote work. Background: Modern situations, such as the COVID-19 pandemic, are rapidly accelerating the need for organizations to move employee teams to virtual environments, sometimes with little to no opportunities to prepare for the transition. It is likely that organizations will continually have to adapt to evolving conditions in the future. Method: This review synthesizes the literature from several sources on best practices, lessons learned, and strategies for virtual teams. Information from each article deemed relevant was then extracted and de-identified. Over 64 best practices were independently and blindly coded for relevancy for the swift deployment of virtual teams. Results: As a result of this review, tips for virtual teams undergoing rapid transition to remote work were developed. These tips are organized at the organization, team, and individual levels. They are further categorized under six overarching themes: norm setting, performance monitoring, leadership, supportive mechanisms, communication, and flexibility. Conclusion: There is a significant deficit in the literature for best practices for virtual teams for the purposes of rapid deployment, leaving it to organizations to subjectively determine what advice to adhere to. This manuscript synthesizes relevant practices and provides insights into effective virtual team rapid deployment.
Genomic Analysis of SARS-CoV-2 Alpha, Beta and Delta Variants of Concern Uncovers Signatures of Neutral and Non-Neutral Evolution
(MDPI, 2022) Kurpas, Monika Klara; Jaksik, Roman; Kuś, Pawel; Kimmel, Marek
Due to the emergence of new variants of the SARS-CoV-2 coronavirus, the question of how the viral genomes evolved, leading to the formation of highly infectious strains, becomes particularly important. Three major emergent strains, Alpha, Beta and Delta, characterized by a significant number of missense mutations, provide a natural test field. We accumulated and aligned 4.7 million SARS-CoV-2 genomes from the GISAID database and carried out a comprehensive set of analyses. This collection covers the period until the end of October 2021, i.e., the beginnings of the Omicron variant. First, we explored combinatorial complexity of the genomic variants emerging and their timing, indicating very strong, albeit hidden, selection forces. Our analyses show that the mutations that define variants of concern did not arise gradually but rather co-evolved rapidly, leading to the emergence of the full variant strain. To explore in more detail the evolutionary forces at work, we developed time trajectories of mutations at all 29,903 sites of the SARS-CoV-2 genome, week by week, and stratified them into trends related to (i) point substitutions, (ii) deletions and (iii) non-sequenceable regions. We focused on classifying the genetic forces active at different ranges of the mutational spectrum. We observed the agreement of the lowest-frequency mutation spectrum with the Griffiths–Tavaré theory, under the Infinite Sites Model and neutrality. If we widen the frequency range, we observe the site frequency spectra much more consistently with the Tung–Durrett model assuming clone competition and selection. The coefficients of the fitting model indicate the possibility of selection acting to promote gradual growth slowdown, as observed in the history of the variants of concern. These results add up to a model of genomic evolution, which partly fits into the classical drift barrier ideas. Certain observations, such as mutation “bands” persistent over the epidemic history, suggest contribution of genetic forces different from mutation, drift and selection, including recombination or other genome transformations. In addition, we show that a “toy” mathematical model can qualitatively reproduce how new variants (clones) stem from rare advantageous driver mutations, and then acquire neutral or disadvantageous passenger mutations which gradually reduce their fitness so they can be then outcompeted by new variants due to other driver mutations.
Vaccination for COVID-19 among historically underserved Latino communities in the United States: Perspectives of community health workers
(Frontiers Media S.A., 2022) Garcini, Luz M.; Ambriz, Arlynn M.; Vázquez, Alejandro L.; Abraham, Cristina; Sarabu, Vyas; Abraham, Ciciya; Lucas-Marinelli, Autumn K.; Lill, Sarah; Tsevat, Joel; Baker Institute Center for the United States and Mexico
A critical step to reduce the spread of COVID-19 is vaccination. We conducted a mixed methods project that used online surveys and focus groups with 64 Community Health Workers and Promotor/as (CHW/Ps) located near the U.S.-Mexico border to identify barriers and facilitators to COVID-19 vaccination among Latino communities that have been historically underrepresented and medically underserved. Overall, personal barriers to vaccination included mistrust of manufacturers and administrators as well as fear of: becoming infected from the vaccine, discrimination/stigmatization from healthcare professionals administering the vaccine, exploitation/manipulation by the government or health authorities, and having personal information mishandled. Environmental and community barriers included being undocumented and fear-inducing myths and beliefs. Additional barriers included limited information and logistics pertaining to vaccination access. Targeted efforts are needed to overcome barriers in a culturally and contextually sensitive manner to prevent harm and reduce risk of infection among communities that have been historically underrepresented.
Stay-at-home and face mask policy intentions inconsistent with incidence and fatality during the US COVID-19 pandemic
(Frontiers, 2022) Wu, Samuel X.; Wu, Xin
During the COVID-19 pandemic, many states imposed stay-at-home (SAH) and mandatory face mask (MFM) orders to supplement the United States CDC recommendations. The purpose of this study was to characterize the relationship between SAH and MFM approaches with the incidence and fatality of COVID-19 during the pandemic period until 23 August 2020 (about 171 days), the period with no vaccines or specific drugs that had passed the phase III clinical trials yet. States with SAH orders showed a potential 50–60% decrease in infection and fatality during the SAH period (about 45 days). After normalization to population density, there was a 44% significant increase in the fatality rate in no-SAH + no-MFM states when compared to SAH + MFM. However, many results in this study were inconsistent with the intent of public health strategies of SAH and MFM. There were similar incidence rates (1.41, 1.81, and 1.36%) and significant differences in fatality rates (3.40, 2.12, and 1.25%; p < 0.05) and mortality rates (51.43, 34.50, and 17.42 per 100,000 residents; p < 0.05) among SAH + MFM, SAH + no-MFM, and no-SAH + no-MFM states, respectively. There were no significant differences in total positive cases, average daily new cases, and average daily fatality when normalized with population density among the three groups. This study suggested potential decreases in infection and fatality with short-term SAH order. However, SAH and MFM orders from some states' policies probably had limited effects in lowering transmission and fatality among the general population. At the policy-making level, if contagious patients would not likely be placed in strict isolation and massive contact tracing would not be effective to implement, we presume that following the CDC's recommendations with close monitoring of healthcare capacity could be appropriate in helping mitigate the COVID-19 disaster while limiting collateral socioeconomic damages.

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