Rice Coronavirus Research

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

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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.
Living Situation and Physical Activity in the COVID-19 Pandemic Among American Private University Students
(Western Kentucky University, 2022) Villarreal, Eduardo Gonzalez; Kabiri, Laura S.; Diep, Cassandra S.; Perkins, Hedi Y.; Perkins-Ball, Amanda M.; Rodriguez, Augusto X.
Many university students experienced changes during the COVID-19 pandemic, including potential changes in physical activity (PA) levels and living situation. As PA behaviors in young adulthood help establish life-long habits and future health outcomes, the purpose of this study was to investigate overall change in PA, as well as change in PA due to living situation, among private university students during the COVID-19 pandemic. Private university students (n = 109) between 18 and 25 years of age completed an online survey that included the International Physical Activity Questionnaire – Short Form. T-tests examined changes in overall time spent in PA from before to during the COVID-19 pandemic, and the differences in MET-minute distributions between groups. Students performed significantly less activity during the COVID-19 pandemic than before (t(108) = 3.51, p = .001, d = 0.493), with 70.6% of all students meeting exercise recommendations before the pandemic and 51.4% after. Students living with vs. without a parent/guardian attained similar PA levels (t(107) = -.114, p = .910) before the pandemic (73.1% vs. 69.9%, respectively), but students living with a parent/guardian engaged in significantly less PA (t(107) = 2.04, p = .044, d = 0.475) than those living without a parent/guardian during the pandemic (37.5% vs. 57.1%, respectively). The declines in PA suggest the need for targeted interventions and education among private university students. In order to maximize the health benefits of PA, it is crucial that activity engagement return to at least pre-COVID-19 levels.
Blocked by Gender: Disparities in COVID19 infection detection in Tamil Nadu, India
(Frontiers Media S.A., 2022) Samanta, Tannistha; Gopalan, Kaushik; Devi, Tanmay
Globally, a gender gap in COVID-19 has been noted with men reporting higher share of both morbidity and deaths compared to women. While the gender gap in fatalities has been similar across the globe, there have been interesting disparities in the detection of COVID-19 cases in men and women. While wealthier, more developed nations have generally seen similar case detection in men and women, LMICs especially in Asia have seen far greater proportion of COVID-19 cases among men than women. We utilize age and sex-disaggregated data from the southern Indian state of Tamil Nadu across two waves of the pandemic (May 2020 – Nov 2020, and March 2021, to June 2021) and find that there were only ~70% as many detected COVID-19 cases among women as there were among men. Our initial reading suggested that this might be a protective effect of lower labor force participation rates among women across much of South Asia. However, subsequent sero-prevalence results from Tamil Nadu conducted on October-November 2020, and June-July, 2021 suggest that infection incidence has been similar among men and women; as is the case in countries with better health infrastructure. This empirical puzzle suggests that reduced case detection among women cannot be immediately associated with limited public exposure, but rather evidence of a chronic neglect of women in healthcare access. Overall, we contend that an attention to the gender context holds promise to effective interventions in detection and prevention that goes beyond the traditional epidemiological logic of diseases.
Creation of a Global Vaccine Risk Index
(Public Library of Science, 2022) Nuzhath, Tasmiah; Hotez, Peter J.; Damania, Ashish; Liu, P. Shuling; Colwell, Brian; James A Baker III Institute of Public Policy
The World Health Organization has identified vaccine hesitancy as one of its top ten global health threats for 2019. Efforts are underway to define the factors responsible for reductions in vaccine confidence. However, as global measles cases accelerated beginning in 2018, it became evident that additional factors were promoting measles re-emergence, including war, political and socio-economic collapse, shifting poverty, and vulnerability to weather events and climate change. Accordingly, we propose a Global Vaccine Risk Index (VRI) to consider these variables as a more comprehensive means to identify vulnerable nations where we might expect measles and other vaccine-preventable diseases to emerge or re-emerge. In Sub-Saharan African and Middle Eastern nations, conflict and political instability predominated as the basis for high vaccine risk scores, whereas in Southeast Asian countries, the major reasons included climate variability, current levels of measles vaccination coverage, and economic and educational disparities. In Europe, low vaccine confidence and refugee movements predominated, while in the Americas, economic disparities and vaccine confidence were important. The VRI may serve as a useful indicator and predictor for international agencies committed to childhood immunizations and might find relevance for accelerating future COVID19 vaccination programs.
Infectious Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Exhaled Aerosols and Efficacy of Masks During Early Mild Infection
(Oxford University Press, 2022) Adenaiye, Oluwasanmi O.; Lai, Jianyu; Bueno de Mesquita, P. Jacob; Hong, Filbert; Youssefi, Somayeh; German, Jennifer; Tai, S.H. Sheldon; Albert, Barbara; Schanz, Maria; Weston, Stuart; Hang, Jun; Fung, Christian; Chung, Hye Kyung; Coleman, Kristen K.; Sapoval, Nicolae; Treangen, Todd; Berry, Irina Maljkovic; Mullins, Kristin; Frieman, Matthew; Ma, Tianzhou; Milton, Donald K.; University of Maryland StopCOVID Research Group
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemiology implicates airborne transmission; aerosol infectiousness and impacts of masks and variants on aerosol shedding are not well understood.We recruited coronavirus disease 2019 (COVID-19) cases to give blood, saliva, mid-turbinate and fomite (phone) swabs, and 30-minute breath samples while vocalizing into a Gesundheit-II, with and without masks at up to 2 visits 2 days apart. We quantified and sequenced viral RNA, cultured virus, and assayed serum samples for anti-spike and anti-receptor binding domain antibodies.We enrolled 49 seronegative cases (mean days post onset 3.8 ± 2.1), May 2020 through April 2021. We detected SARS-CoV-2 RNA in 36% of fine (≤5 µm), 26% of coarse (>5 µm) aerosols, and 52% of fomite samples overall and in all samples from 4 alpha variant cases. Masks reduced viral RNA by 48% (95% confidence interval [CI], 3 to 72%) in fine and by 77% (95% CI, 51 to 89%) in coarse aerosols; cloth and surgical masks were not significantly different. The alpha variant was associated with a 43-fold (95% CI, 6.6- to 280-fold) increase in fine aerosol viral RNA, compared with earlier viruses, that remained a significant 18-fold (95% CI, 3.4- to 92-fold) increase adjusting for viral RNA in saliva, swabs, and other potential confounders. Two fine aerosol samples, collected while participants wore masks, were culture-positive.SARS-CoV-2 is evolving toward more efficient aerosol generation and loose-fitting masks provide significant but only modest source control. Therefore, until vaccination rates are very high, continued layered controls and tight-fitting masks and respirators will be necessary.
Advancing methods for wastewater disease surveillance of antibiotic resistance and SARS-CoV-2
(2022-09-19) Lou, Esther; Stadler, Lauren B.
Wastewater-based epidemiology (WBE), which involves using biological indicators in sewage to provide information on the overall health of a community, is a powerful tool to monitor public health. WBE offers several advantages that make it complementary to conventional clinical surveillance: it is rapid and resource-efficient, enables broad monitoring of large populations, is able to detect symptomatic and asymptomatic infections, and is not biased by health seeking behavior or access to healthcare resources. Recent studies have shown that WBE is a powerful tool for estimating community-level prevalence of COVID-19 by measuring levels of SARS-CoV-2 RNA in wastewater, and for predicting the prevalence of clinical antibiotic resistance by screening wastewater for antibiotic resistance genes. Furthermore, WBE has enabled global collaboration through national (e.g., National Wastewater Surveillance System (NWSS) on COVID-19) and international (e.g., the Enhanced Gonococcal Antimicrobial Surveillance Program) programs to advance the integration of WBE into public health response. Despite the surge of interest in applying WBE, there are currently no standardized methods for wastewater disease monitoring, including how and when to collect samples, what methods to use for analysis, and how to interpret the data to inform action. Without a more complete understanding of the methodological challenges involved in characterizing target indicators in wastewater samples, our ability to leverage WBE for routine monitoring and international collaboration is limited. This dissertation aims to evaluate the strengths and weaknesses of several current methods used for wastewater monitoring of antimicrobial resistance (AMR) and SARS-CoV-2 and discuss implications of method selection for future WBE work. The research focuses on four objectives, corresponding to the four chapters presented in this dissertation: (1) characterize the impact of wastewater sampling designs (i.e., grab and composite sampling) on the ARG removal rates achieved by a wastewater treatment plant (WWTP), (2) elucidate the fate of different forms of cell-associated and cell-free ARGs in an emerging wastewater treatment process, (3) compare two targeted methods (i.e., RT-ddPCR and targeted amplicon sequencing) for monitoring SARS-CoV-2 mutations in wastewater, and (4) evaluate short- and long-read metagenomics and a targeted method (epicPCR) for tracking ARG host range across a WWTP. Sampling design is critical to the collection of representative samples for WBE and for estimating removal rates of genes across wastewater treatment processes. We compared grab and composite sampling in terms of their effects on removal rates for a suite of genes, including several clinically-relevant ARGs (blaNDM-1, blaOXA-1, MCR-1, MCR-5, MCR-10, and qnrA). We find that the diurnal variation of ARG loading in the WWTP influent and effluent created significantly different instantaneous ARG removal rates among all grab samples collected throughout a day, indicating grab sampling can introduce bias to ARG removal calculations. Overall, using composite samples are more representative for WBE and for assessing removal of ARGs across wastewater treatment processes as compared to grab sampling which may overestimate ARG removal rates. The form of the ARG, specifically whether it is cell-free or cell-associated, is critical to understanding ARG removal across wastewater treatment processes. We found that the fraction of cell-associated ARGs decreased whereas the fraction of cell-free ARGs increased in the treated effluent as the influent organic loading rate was gradually increased. The results indicate that the ARGs in treated effluent can transit between cell-associated and cell-free DNA in response to changing operational conditions, which should be considered to better evaluate the total ARGs in the wastewater treatment system. WBE has been widely applied to track SARS-CoV-2 infections in communities and in some cases to identify circulating variants of concern. There are several different methods that have been applied to screen for variants of concern in wastewater. We compared targeted methods for screening for SARS-CoV-2 variants of concern in wastewater samples. The results demonstrated that RT-ddPCR is more sensitive and should be applied for mutation quantification or variant confirmation in wastewater, whereas detection via targeted amplicon sequencing was influenced by the depth of sequencing, viral load, and mutation concentration. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on targeted amplicon sequencing. We compared targeted and untargeted methods for ARG detection in wastewater. The results demonstrate that despite its significantly lower sequencing depth, long-read sequencing outperforms short-read sequencing with higher sensitivity for detecting ARGs, especially for ARGs associated with mobile genetic elements (MGEs). In addition, long-read sequencing consistently revealed a wider range of ARG hosts compared to short-read sequencing. Nonetheless, the host range detected by long-read sequencing represented only a subset of the host range detected by a targeted method, epicPCR (Emulsion, Paired Isolation, and Concatenation PCR). Taken together, the results have implications for future WBE, particularly in terms of method selection: 1) collect composite samples rather than grab samples to acquire a representative view of the monitoring targets in a population; 2) include different forms of DNA (cell-associated and cell-free) to analyze ARGs because effluent ARGs are present in both forms and can transition between these forms in response to environmental conditions; 3) apply RT-ddPCR for quantitative analysis and early variant detection if targets are known; and 4) use long-read sequencing for routine wastewater AMR surveillance and use epicPCR to obtain a high-resolution host range of clinically relevant ARGs. The findings provided by this research contribute to establishing a scientific consensus on method selection for WBE, thus advancing it as a routine tool for public health surveillance.

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