ABSTRACT
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.
Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Hospitalization , Humans , Retrospective Studies , SARS-CoV-2/genetics , Washington/epidemiologyABSTRACT
Since the global withdrawal of Sabin 2 oral poliovirus vaccine (OPV) from routine immunization, the Global Polio Eradication Initiative (GPEI) has reported multiple circulating vaccine-derived poliovirus type 2 (cVDPV2) outbreaks. Here, we generated an agent-based, mechanistic model designed to assess OPV-related vaccine virus transmission risk in populations with heterogeneous immunity, demography, and social mixing patterns. To showcase the utility of our model, we present a simulation of mOPV2-related Sabin 2 transmission in rural Matlab, Bangladesh based on stool samples collected from infants and their household contacts during an mOPV2 clinical trial. Sabin 2 transmission following the mOPV2 clinical trial was replicated by specifying multiple, heterogeneous contact rates based on household and community membership. Once calibrated, the model generated Matlab-specific insights regarding poliovirus transmission following an accidental point importation or mass vaccination event. We also show that assuming homogeneous contact rates (mass action), as is common of poliovirus forecast models, does not accurately represent the clinical trial and risks overestimating forecasted poliovirus outbreak probability. Our study identifies household and community structure as an important source of transmission heterogeneity when assessing OPV-related transmission risk and provides a calibratable framework for expanding these analyses to other populations. Trial Registration: ClinicalTrials.gov This trial is registered with clinicaltrials.gov, NCT02477046.
Subject(s)
Mass Vaccination/statistics & numerical data , Models, Statistical , Poliomyelitis , Poliovirus Vaccine, Oral , Poliovirus , Bangladesh , Humans , Poliomyelitis/epidemiology , Poliomyelitis/prevention & control , Poliomyelitis/virology , Randomized Controlled Trials as TopicABSTRACT
The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.
Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , Systems Analysis , Basic Reproduction Number , COVID-19/etiology , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Testing , COVID-19 Vaccines , Computational Biology , Computer Simulation , Contact Tracing , Disease Progression , Hand Disinfection , Host Microbial Interactions , Humans , Masks , Mathematical Concepts , Pandemics , Physical Distancing , Quarantine , SoftwareABSTRACT
The oral polio vaccine (OPV) contains live-attenuated polioviruses that induce immunity by causing low virulence infections in vaccine recipients and their close contacts. Widespread immunization with OPV has reduced the annual global burden of paralytic poliomyelitis by a factor of 10,000 or more and has driven wild poliovirus (WPV) to the brink of eradication. However, in instances that have so far been rare, OPV can paralyze vaccine recipients and generate vaccine-derived polio outbreaks. To complete polio eradication, OPV use should eventually cease, but doing so will leave a growing population fully susceptible to infection. If poliovirus is reintroduced after OPV cessation, under what conditions will OPV vaccination be required to interrupt transmission? Can conditions exist in which OPV and WPV reintroduction present similar risks of transmission? To answer these questions, we built a multi-scale mathematical model of infection and transmission calibrated to data from clinical trials and field epidemiology studies. At the within-host level, the model describes the effects of vaccination and waning immunity on shedding and oral susceptibility to infection. At the between-host level, the model emulates the interaction of shedding and oral susceptibility with sanitation and person-to-person contact patterns to determine the transmission rate in communities. Our results show that inactivated polio vaccine (IPV) is sufficient to prevent outbreaks in low transmission rate settings and that OPV can be reintroduced and withdrawn as needed in moderate transmission rate settings. However, in high transmission rate settings, the conditions that support vaccine-derived outbreaks have only been rare because population immunity has been high. Absent population immunity, the Sabin strains from OPV will be nearly as capable of causing outbreaks as WPV. If post-cessation outbreak responses are followed by new vaccine-derived outbreaks, strategies to restore population immunity will be required to ensure the stability of polio eradication.
Subject(s)
Disease Outbreaks/prevention & control , Immunity, Herd , Poliomyelitis/prevention & control , Poliovirus Vaccine, Inactivated/administration & dosage , Poliovirus Vaccine, Oral/administration & dosage , Poliovirus/immunology , Global Health , Humans , Immunity, Active , Immunization Schedule , Mass Vaccination/statistics & numerical data , Models, Statistical , Poliomyelitis/epidemiology , Poliomyelitis/immunology , Poliomyelitis/transmissionABSTRACT
BACKGROUND: Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses. METHODS: Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits. RESULTS: Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase. CONCLUSION: High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths.
Subject(s)
Epidemics/prevention & control , Physical Distancing , Respiratory Tract Infections/transmission , Respiratory Tract Infections/virology , Weather , COVID-19 , Cities , Humans , Incidence , Models, Theoretical , Retrospective Studies , WashingtonABSTRACT
From January 21 through February 23, 2020, public health agencies detected 14 U.S. cases of coronavirus disease 2019 (COVID-19), all related to travel from China (1,2). The first nontravel-related U.S. case was confirmed on February 26 in a California resident who had become ill on February 13 (3). Two days later, on February 28, a second nontravel-related case was confirmed in the state of Washington (4,5). Examination of four lines of evidence provides insight into the timing of introduction and early transmission of SARS-CoV-2, the virus that causes COVID-19, into the United States before the detection of these two cases. First, syndromic surveillance based on emergency department records from counties affected early by the pandemic did not show an increase in visits for COVID-19-like illness before February 28. Second, retrospective SARS-CoV-2 testing of approximately 11,000 respiratory specimens from several U.S. locations beginning January 1 identified no positive results before February 20. Third, analysis of viral RNA sequences from early cases suggested that a single lineage of virus imported directly or indirectly from China began circulating in the United States between January 18 and February 9, followed by several SARS-CoV-2 importations from Europe. Finally, the occurrence of three cases, one in a California resident who died on February 6, a second in another resident of the same county who died February 17, and a third in an unidentified passenger or crew member aboard a Pacific cruise ship that left San Francisco on February 11, confirms cryptic circulation of the virus by early February. These data indicate that sustained, community transmission had begun before detection of the first two nontravel-related U.S. cases, likely resulting from the importation of a single lineage of virus from China in late January or early February, followed by several importations from Europe. The widespread emergence of COVID-19 throughout the United States after February highlights the importance of robust public health systems to respond rapidly to emerging infectious threats.
Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Sentinel Surveillance , Betacoronavirus/genetics , COVID-19 , Humans , Pandemics , Phylogeny , SARS-CoV-2 , Travel , United States/epidemiologyABSTRACT
BACKGROUND: Wild type 2 poliovirus was last observed in 1999. The Sabin-strain oral polio vaccine type 2 (OPV2) was critical to eradication, but it is known to revert to a neurovirulent phenotype, causing vaccine-associated paralytic poliomyelitis. OPV2 is also transmissible and can establish circulating lineages, called circulating vaccine-derived polioviruses (cVDPVs), which can also cause paralytic outbreaks. Thus, in April 2016, OPV2 was removed from immunization activities worldwide. Interrupting transmission of cVDPV2 lineages that survive cessation will require OPV2 in outbreak response, which risks seeding new cVDPVs. This potential cascade of outbreak responses seeding VDPVs, necessitating further outbreak responses, presents a critical risk to the OPV2 cessation effort. METHODS: The EMOD individual-based disease transmission model was used to investigate OPV2 use in outbreak response post-cessation in West African populations. A hypothetical outbreak response in northwest Nigeria is modeled, and a cVDPV2 lineage is considered established if the Sabin strain escapes the response region and continues circulating 9 months post-response. The probability of this event was investigated in a variety of possible scenarios. RESULTS: Under a broad range of scenarios, the probability that widespread OPV2 use in outbreak response (~2 million doses) establishes new cVDPV2 lineages in this model may exceed 50% as soon as 18 months or as late as 4 years post-cessation. CONCLUSIONS: The risk of a cycle in which outbreak responses seed new cVDPV2 lineages suggests that OPV2 use should be managed carefully as time from cessation increases. It is unclear whether this risk can be mitigated in the long term, as mucosal immunity against type 2 poliovirus declines globally. Therefore, current programmatic strategies should aim to minimize the possibility that continued OPV2 use will be necessary in future years: conducting rapid and aggressive outbreak responses where cVDPV2 lineages are discovered, maintaining high-quality surveillance in all high-risk settings, strengthening the use of the inactivated polio vaccine as a booster in the OPV2-exposed and in routine immunization, and gaining access to currently inaccessible areas of the world to conduct surveillance.
Subject(s)
Disease Outbreaks/prevention & control , Poliomyelitis/prevention & control , Poliovirus Vaccine, Oral/therapeutic use , Poliovirus/drug effects , Humans , Poliomyelitis/epidemiology , Poliovirus Vaccine, Oral/administration & dosageABSTRACT
UNLABELLED: To assess the dynamics of genetic reversion of live poliovirus vaccine in humans, we studied molecular evolution in Sabin-like poliovirus isolates from Nigerian acute flaccid paralysis cases obtained from routine surveillance. We employed a novel modeling approach to infer substitution and recombination rates from whole-genome sequences and information about poliovirus infection dynamics and the individual vaccination history. We confirmed observations from a recent vaccine trial that VP1 substitution rates are increased for Sabin-like isolates relative to the rate for the wild type due to increased nonsynonymous substitution rates. We also inferred substitution rates for attenuating nucleotides and confirmed that reversion can occur in days to weeks after vaccination. We combine our observations for Sabin-like virus evolution with the molecular clock for VP1 of circulating wild-type strains to infer that the mean time from the initiating vaccine dose to the earliest detection of circulating vaccine-derived poliovirus (cVDPV) is 300 days for Sabin-like virus type 1, 210 days for Sabin-like virus type 2, and 390 days for Sabin-like virus type 3. Phylogenetic relationships indicated transient local transmission of Sabin-like virus type 3 and, possibly, Sabin-like virus type 1 during periods of low wild polio incidence. Comparison of Sabin-like virus recombinants with known Nigerian vaccine-derived poliovirus recombinants shows that while recombination with non-Sabin enteroviruses is associated with cVDPV, the recombination rates are similar for Sabin isolate-Sabin isolate and Sabin isolate-non-Sabin enterovirus recombination after accounting for the time from dosing to the time of detection. Our study provides a comprehensive picture of the evolutionary dynamics of the oral polio vaccine in the field. IMPORTANCE: The global polio eradication effort has completed its 26th year. Despite success in eliminating wild poliovirus from most of the world, polio persists in populations where logistical, social, and political factors have not allowed vaccination programs of sustained high quality. One issue of critical importance is eliminating circulating vaccine-derived polioviruses (cVDPVs) that have properties indistinguishable from those of wild poliovirus and can cause paralytic disease. cVDPV emerges due to the genetic instability of the Sabin viruses used in the oral polio vaccine (OPV) in populations that have low levels of immunity to poliovirus. However, the dynamics responsible are incompletely understood because it has historically been difficult to gather and interpret data about evolution of the Sabin viruses used in OPV in regions where cVDPV has occurred. This study is the first to combine whole-genome sequencing of poliovirus isolates collected during routine surveillance with knowledge about the intrahost dynamics of poliovirus to provide quantitative insight into polio vaccine evolution in the field.
Subject(s)
Capsid Proteins/genetics , Point Mutation , Poliomyelitis/prevention & control , Poliomyelitis/virology , Poliovirus Vaccine, Oral/adverse effects , Poliovirus/genetics , Poliovirus/isolation & purification , Child , Child, Preschool , Evolution, Molecular , Female , Humans , Infant , Infant, Newborn , Male , Molecular Epidemiology , Mutation Rate , Nigeria/epidemiology , Phylogeny , Poliomyelitis/epidemiology , Poliovirus Vaccine, Oral/administration & dosage , RNA, Viral/genetics , Sequence Homology , Time Factors , VirulenceABSTRACT
Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input-output properties such that an input's ability to trigger a response depends on the size of that input relative to its local statistical context. This "gain-scaling" strategy has been shown to be an efficient coding strategy. We report here that this property emerges during early development as an intrinsic property of single neurons in mouse sensorimotor cortex, coinciding with the disappearance of spontaneous waves of network activity, and can be modulated by changing the balance of spike-generating currents. Simultaneously, developing neurons move toward a common intrinsic operating point and a stable ratio of spike-generating currents. This developmental trajectory occurs in the absence of sensory input or spontaneous network activity. Through a combination of electrophysiology and modeling, we demonstrate that developing cortical neurons develop the ability to perform nearly perfect gain scaling by virtue of the maturing spike-generating currents alone. We use reduced single neuron models to identify the conditions for this property to hold.
Subject(s)
Action Potentials/physiology , Models, Neurological , Neurons/physiology , Somatosensory Cortex/cytology , Animals , Female , Male , Mice , Mice, Inbred BALB C , Nerve Net/cytology , Nerve Net/embryology , Nerve Net/physiology , Organ Culture Techniques , Patch-Clamp Techniques , Somatosensory Cortex/embryology , Somatosensory Cortex/physiology , Synapses/physiologyABSTRACT
Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/transmission , COVID-19/epidemiology , SARS-CoV-2/isolation & purification , Washington/epidemiology , Pandemics , Cities/epidemiology , Seasons , Travel/statistics & numerical dataABSTRACT
The oral poliovirus vaccines (OPVs) are one of the most effective disease eradication tools in public health. However, the OPV strains are genetically unstable and can cause outbreaks of circulating, vaccine-derived Type 2 poliovirus (cVDPV2) that are clinically indistinguishable from wild poliovirus (WPV) outbreaks. Here, we developed a Sabin 2 reversion model that simulates the reversion of Sabin 2 to reacquire a WPV-like phenotype based on the clinical differences in shedding duration and infectiousness between individuals vaccinated with Sabin 2 and those infected with WPV. Genetic reversion is informed by a canonical reversion pathway defined by three gatekeeper mutations (A481G, U2909C, and U398C) and the accumulation of deleterious nonsynonymous mutations. Our model captures essential aspects of both phenotypic and molecular evolution and simulates transmission using a multiscale transmission model that consolidates the relationships among immunity, susceptibility, and transmission risk. Despite rapid Sabin 2 attenuation reversal, we show that the emergence of a revertant virus does not guarantee a cVDPV2 outbreak. When simulating outbreaks in Matlab, Bangladesh, we found that cVDPV2 outbreaks are most likely in areas with low population-level immunity and poor sanitation. In Matlab, our model predicted that declining immunity against Type 2 poliovirus following the cessation of routine OPV vaccination was not enough to promote cVDPV2 emergence. However, cVDPV2 emergencedepended on the average viral exposure dose per contact, which was modeled as a combination of the viral concentration per fecal gram and the average fecal-oral dose per contact. These results suggest that cVDPV2 emergence risk can be mitigated by reducing the amount of infectious fecal material individuals are exposed to. Thus, a combined strategy of assessing and improving sanitation levels in conjunction with high-coverage vaccination campaigns could limit the future cVDPV2 emergence.
ABSTRACT
Much of the world's population had already been infected with COVID-19 by the time the Omicron variant emerged at the end of 2021, but the scale of the Omicron wave was larger than any that had come before or has happened since, and it left a global imprinting of immunity that changed the COVID-19 landscape. In this study, we simulate a South African population and demonstrate how population-level vaccine effectiveness and efficiency changed over the course of the first 2 years of the pandemic. We then introduce three hypothetical variants and evaluate the impact of vaccines with different properties. We find that variant-chasing vaccines have a narrow window of dominating pre-existing vaccines but that a variant-chasing vaccine strategy may have global utility, depending on the rate of spread from setting to setting. Next-generation vaccines might be able to overcome uncertainty in pace and degree of viral evolution.
Subject(s)
COVID-19 , Vaccines , Humans , COVID-19/prevention & control , Pandemics/prevention & control , SARS-CoV-2ABSTRACT
Environmental pathogen surveillance is a sensitive tool that can detect early-stage outbreaks, and it is being used to track poliovirus and other pathogens. However, interpretation of longitudinal environmental surveillance signals is difficult because the relationship between infection incidence and viral load in wastewater depends on time-varying shedding intensity. We developed a mathematical model of time-varying poliovirus shedding intensity consistent with expert opinion across a range of immunization states. Incorporating this shedding model into an infectious disease transmission model, we analysed quantitative, polymerase chain reaction data from seven sites during the 2013 Israeli poliovirus outbreak. Compared to a constant shedding model, our time-varying shedding model estimated a slower peak (four weeks later), with more of the population reached by a vaccination campaign before infection and a lower cumulative incidence. We also estimated the population shed virus for an average of 29 days (95% CI 28-31), longer than expert opinion had suggested for a population that was purported to have received three or more inactivated polio vaccine (IPV) doses. One explanation is that IPV may not substantially affect shedding duration. Using realistic models of time-varying shedding coupled with longitudinal environmental surveillance may improve our understanding of outbreak dynamics of poliovirus, SARS-CoV-2, or other pathogens.
Subject(s)
COVID-19 , Poliomyelitis , Poliovirus , Disease Outbreaks/prevention & control , Environmental Monitoring , Humans , Infant , Israel/epidemiology , Poliomyelitis/epidemiology , Poliomyelitis/prevention & control , Poliovirus Vaccine, Inactivated , Poliovirus Vaccine, Oral , Public Health , SARS-CoV-2 , Virus SheddingABSTRACT
Importance: Few US studies have reexamined risk factors for SARS-CoV-2 positivity in the context of widespread vaccination and new variants or considered risk factors for cocirculating endemic viruses, such as rhinovirus. Objectives: To evaluate how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these with the risk factors associated with rhinovirus test positivity. Design, Setting, and Participants: This case-control study used a test-negative design with multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 25-month period. The study was conducted among symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study in King County, Washington, from June 2020 to July 2022. Exposures: Self-reported data for 15 demographic and health behavior variables and 16 symptoms. Main Outcomes and Measures: Reverse transcription-polymerase chain reaction-confirmed SARS-CoV-2 or rhinovirus infection. Results: Analyses included data from 23â¯498 individuals. The median (IQR) age of participants was 34.33 (22.42-45.08) years, 13â¯878 (59.06%) were female, 4018 (17.10%) identified as Asian, 654 (2.78%) identified as Black, and 2193 (9.33%) identified as Hispanic. Close contact with an individual with SARS-CoV-2 (adjusted odds ratio [aOR], 3.89; 95% CI, 3.34-4.57) and loss of smell or taste (aOR, 3.49; 95% CI, 2.77-4.41) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated individual with SARS-CoV-2 (aOR, 2.03; 95% CI, 1.56-2.79) was associated with lower odds of testing positive than contact with an unvaccinated individual with SARS-CoV-2 (aOR, 4.04; 95% CI, 2.39-7.23). Sore throat was associated with Omicron infection (aOR, 2.27; 95% CI, 1.68-3.20) but not Delta infection. Vaccine effectiveness for participants fully vaccinated with a booster dose was 93% (95% CI, 73%-100%) for Delta, but not significant for Omicron. Variables associated with rhinovirus test positivity included being younger than 12 years (aOR, 3.92; 95% CI, 3.42-4.51) and experiencing a runny or stuffy nose (aOR, 4.58; 95% CI, 4.07-5.21). Black race, residing in south King County, and households with 5 or more people were significantly associated with both SARS-CoV-2 and rhinovirus test positivity. Conclusions and Relevance: In this case-control study of 23â¯498 symptomatic individuals, estimated risk factors and symptoms associated with SARS-CoV-2 infection changed over time. There was a shift in reported symptoms between the Delta and Omicron variants as well as reductions in the protection provided by vaccines. Racial and sociodemographic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection. Trends in testing behavior and availability may influence these results.
Subject(s)
COVID-19 , SARS-CoV-2 , Female , Humans , Adult , Middle Aged , Male , Rhinovirus , Case-Control Studies , COVID-19/diagnosis , COVID-19/epidemiology , Cross-Sectional Studies , Risk FactorsABSTRACT
Background: Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods: We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results: 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions: Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.
ABSTRACT
BACKGROUND: The COVID-19 pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. METHODS: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. FINDINGS: 58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSION: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. SUMMARY: Hospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.
ABSTRACT
The emergence of circulating vaccine-derived polioviruses through evolution of the oral polio vaccine (OPV) poses a significant obstacle to polio eradication. Understanding the early genetic changes that occur as OPV evolves and transmits is important for preventing future outbreaks. Here, we use deep sequencing to define the evolutionary trajectories of type 2 OPV in a vaccine trial. By sequencing 497 longitudinal stool samples from 271 OPV2 recipients and household contacts, we were able to examine the extent of convergent evolution in vaccinated individuals and the amount of viral diversity that is transmitted. In addition to rapid reversion of key attenuating mutations, we identify strong selection at 19 sites across the genome. We find that a tight transmission bottleneck limits the onward transmission of these early adaptive mutations. Our results highlight the distinct evolutionary dynamics of live attenuated virus vaccines and have important implications for the success of next-generation OPV.
Subject(s)
Evolution, Molecular , Poliovirus Vaccine, Oral/genetics , Poliovirus/genetics , Selection, Genetic , Feces/virology , Genetic Variation , Genome, Viral , High-Throughput Nucleotide Sequencing , Humans , Mutation , Poliomyelitis/prevention & control , Poliomyelitis/transmission , Poliomyelitis/virology , Poliovirus/immunology , Poliovirus/pathogenicity , Poliovirus Vaccine, Oral/immunology , Randomized Controlled Trials as Topic , Vaccines, Attenuated/genetics , Vaccines, Attenuated/immunology , Whole Genome SequencingABSTRACT
Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here, we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We perform this analysis using Covasim, an open-source agent-based model, which has been calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we find that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.
Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Contact Tracing/methods , Quarantine/methods , Humans , SARS-CoV-2/isolation & purification , United StatesABSTRACT
Importance: The association between COVID-19 symptoms and SARS-CoV-2 viral levels in children living in the community is not well understood. Objective: To characterize symptoms of pediatric COVID-19 in the community and analyze the association between symptoms and SARS-CoV-2 RNA levels, as approximated by cycle threshold (Ct) values, in children and adults. Design, Setting, and Participants: This cross-sectional study used a respiratory virus surveillance platform in persons of all ages to detect community COVID-19 cases from March 23 to November 9, 2020. A population-based convenience sample of children younger than 18 years and adults in King County, Washington, who enrolled online for home self-collection of upper respiratory samples for SARS-CoV-2 testing were included. Exposures: Detection of SARS-CoV-2 RNA by reverse transcription-polymerase chain reaction (RT-PCR) from participant-collected samples. Main Outcomes and Measures: RT-PCR-confirmed SARS-CoV-2 infection, with Ct values stratified by age and symptoms. Results: Among 555 SARS-CoV-2-positive participants (mean [SD] age, 33.7 [20.1] years; 320 were female [57.7%]), 47 of 123 children (38.2%) were asymptomatic compared with 31 of 432 adults (7.2%). When symptomatic, fewer symptoms were reported in children compared with adults (mean [SD], 1.6 [2.0] vs 4.5 [3.1]). Symptomatic individuals had lower Ct values (which corresponded to higher viral RNA levels) than asymptomatic individuals (adjusted estimate for children, -3.0; 95% CI, -5.5 to -0.6; P = .02; adjusted estimate for adults, -2.9; 95% CI, -5.2 to -0.6; P = .01). The difference in mean Ct values was neither statistically significant between symptomatic children and symptomatic adults (adjusted estimate, -0.7; 95% CI, -2.2 to 0.9; P = .41) nor between asymptomatic children and asymptomatic adults (adjusted estimate, -0.6; 95% CI, -4.0 to 2.8; P = .74). Conclusions and Relevance: In this community-based cross-sectional study, SARS-CoV-2 RNA levels, as determined by Ct values, were significantly higher in symptomatic individuals than in asymptomatic individuals and no significant age-related differences were found. Further research is needed to understand the role of SARS-CoV-2 RNA levels and viral transmission.