The Coronavirus Disease 2019 Rebound Study: A Prospective Cohort Study to Evaluate Viral and Symptom Rebound Differences in Participants Treated With Nirmatrelvir Plus Ritonavir Versus Untreated Controls.

BACKGROUND: The uptake of nirmatrelvir plus ritonavir (NPR) in patients with coronavirus disease 2019 (COVID-19) has been limited by concerns around the rebound phenomenon despite the scarcity of evidence around its epidemiology. The purpose of this study was to prospectively compare the epidemiology of rebound in NPR-treated and untreated participants with acute COVID-19 infection. METHODS: We designed a prospective, observational study in which participants who tested positive for COVID-19 and were clinically eligible for NPR were recruited to be evaluated for either viral or symptom clearance and rebound. Participants were assigned to the treatment or control group based on their decision to take NPR. Following initial diagnosis, both groups were provided 12 rapid antigen tests and asked to test on a regular schedule for 16 days and answer symptom surveys. Viral rebound based on test results and COVID-19 symptom rebound based on patient-reported symptoms were evaluated. RESULTS: Viral rebound incidence was 14.2% in the NPR treatment group (n = 127) and 9.3% in the control group (n = 43). Symptom rebound incidence was higher in the treatment group (18.9%) compared to controls (7.0%). There were no notable differences in viral rebound by age, gender, preexisting conditions, or major symptom groups during the acute phase or at the 1-month interval. CONCLUSIONS: This preliminary report suggests that rebound after clearance of test positivity or symptom resolution is higher than previously reported. However, notably we observed a similar rate of rebound in both the NPR treatment and control groups. Large studies with diverse participants and extended follow-up are needed to better understand the rebound phenomena.

Recalibrating SARS-CoV-2 Antigen Rapid Lateral Flow Test Relative Sensitivity from Validation Studies to Absolute Sensitivity for Indicating Individuals Shedding Transmissible Virus.

Testing for SARS-CoV-2 internationally has focused on COVID-19 diagnosis among symptomatic individuals using reverse transcriptase polymerase chain reaction (PCR) tests. Recently, however, SARS-CoV-2 antigen rapid lateral flow tests (LFT) have been rolled out in several countries for testing asymptomatic individuals in public health programmes. Validation studies for LFT have been largely cross-sectional, reporting sensitivity, specificity and predictive values of LFT relative to PCR. However, because PCR detects genetic material left behind for a long period when the individual is no longer infectious, these statistics can under-represent the sensitivity of LFT for detecting infectious individuals, especially when sampling asymptomatic populations. LFTs (intended to detect individuals shedding SARS-CoV-2 antigens) validated against PCR (intended to diagnose infection) are not reporting against a gold standard of equivalent measurements. Instead, these validation studies have reported relative performance statistics that need recalibrating to the purpose for which LFT is being used. We present an approach to this recalibration. We derive a formula for recalibrating relative performance statistics from LFT vs PCR validation studies to give likely absolute sensitivity of LFT for detecting individuals who are shedding shedding SARS-CoV-2 antigens. We contrast widely reported apparent sensitivities of LFT with recalibrated absolute sensitivity for detecting individuals shedding SARS-CoV-2 antigens. After accounting for within-individual viral kinetics and epidemic dynamics within asymptomatic populations we show that a highly performant test for SARS-CoV-2 antigen should show LFT-to-PCR relative sensitivity of less than 50% in conventional validation studies, which after re-calibration would be an absolute sensitivity of more than 80%. Further studies are needed to ascertain the absolute sensitivity of LFT as a test of infectiousness in COVID-19 responses. These studies should include longitudinal series of LFT and PCR, ideally in cohorts sampled from both contacts of cases and the general population.

Real World Performance of SARS-CoV-2 Antigen Rapid Diagnostic Tests in Various Clinical Settings.

OBJECTIVE: To assess the validity of Antigen rapid diagnostic tests (Ag-RDT) for SARS-CoV-2 as decision support tool in various hospital-based clinical settings. DESIGN: Retrospective cohort study among symptomatic and asymptomatic patients and Healthcare workers (HCW). SETTING: A large tertiary teaching medical center serving as a major COVID-19 hospitalizing facility. PARTICIPANTS AND METHODS: Ag-RDTs' performance was assessed in three clinical settings: 1. Symptomatic patients and HCW presenting at the Emergency Departments 2. Asymptomatic patients screened upon hospitalization 3. HCW of all sectors tested at the HCW clinic following exposure. RESULTS: We obtained 5172 samples from 4595 individuals, who had both Ag-RDT and quantitative real-time PCR (qRT-PCR) results available. Of these, 485 samples were positive by qRT-PCR. The positive percent agreement (PPA) of Ag-RDT was greater for lower cycle threshold (Ct) values, reaching 93% in cases where Ct-value was <25 and 85% where Ct-value was <30. PPA was similar between symptomatic and asymptomatic individuals. We observed a significant correlation between Ct-value and time from infection onset (p<0.001). CONCLUSIONS: Ag-RDT are highly sensitive to the infectious stage of COVID-19 manifested by either high viral load (lower Ct) or proximity to infection, whether patient is symptomatic or asymptomatic. Thus, this simple-to-use and inexpensive detection method can be used as a decision support tool in various in-hospital clinical settings, assisting patient flow and maintaining sufficient hospital staffing.

Mathematical Modeling to Inform Vaccination Strategies and Testing Approaches for Coronavirus Disease 2019 (COVID-19) in Nursing Homes.

BACKGROUND: Nursing home residents and staff were included in the first phase of coronavirus disease 2019 vaccination in the United States. Because the primary trial endpoint was vaccine efficacy (VE) against symptomatic disease, there are limited data on the extent to which vaccines protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the ability to infect others (infectiousness). Assumptions about VE against infection and infectiousness have implications for changes to infection prevention guidance for vaccinated populations, including testing strategies. METHODS: We use a stochastic agent-based Susceptible-Exposed-Infectious (Asymptomatic/Symptomatic)-Recovered model of a nursing home to simulate SARS-CoV-2 transmission. We model 3 scenarios, varying VE against infection, infectiousness, and symptoms, to understand the expected impact of vaccination in nursing homes, increasing staff vaccination coverage, and different screening testing strategies under each scenario. RESULTS: Increasing vaccination coverage in staff decreases total symptomatic cases in the nursing home (among staff and residents combined) in each VE scenario. In scenarios with 50% and 90% VE against infection and infectiousness, increasing staff coverage reduces symptomatic cases among residents. If vaccination only protects against symptoms, and asymptomatic cases remain infectious, increased staff coverage increases symptomatic cases among residents. However, this is outweighed by the reduction in symptomatic cases among staff. Higher frequency testing-more than once weekly-is needed to reduce total symptomatic cases if the vaccine has lower efficacy against infection and infectiousness, or only protects against symptoms. CONCLUSIONS: Encouraging staff vaccination is not only important for protecting staff, but might also reduce symptomatic cases in residents if a vaccine confers at least some protection against infection or infectiousness.

TIPICO XI: report of the first series and podcast on infectious diseases and vaccines (aTIPICO).

TIPiCO is an annual expert meeting and workshop on infectious diseases and vaccination. The edition of 2020 changed its name and format to aTIPiCO, the first series and podcasts on infectious diseases and vaccines. A total of 13 prestigious experts from different countries participated in this edition launched on the 26 November 2020. The state of the art of coronavirus disease-2019 (COVID-19) and the responsible pathogen, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and the options to tackle the pandemic situation were discussed in light of the knowledge in November 2020. Despite COVID-19, the status of other infectious diseases, including influenza infections, respiratory syncytial virus disease, human papillomavirus infection, measles, pertussis, tuberculosis, meningococcal disease, and pneumococcal disease, were also addressed. The essential lessons that can be learned from these diseases and their vaccines to use in the COVID-19 pandemic were also commented with the experts.

Reopening Scenarios

We use a five-age epidemiological model, combined with 66-sector economic accounting, to address a variety of questions concerning the economic reopening. We calibrate/estimate the model using contact survey data and data on weekly historical individual actions and non-pharmaceutical interventions in the weeks ending March 8 – May 16, 2020. Going forward, we model a decision-maker (governor) as following reopening guidelines like those proposed by the White House and the CDC. The sectoral accounting, combined with information on personal proximity and ability to work from home by sector, make it possible to construct a GDP-to-Risk index of which sectors provide the greatest increment in GDP per marginal increase in R0. Through simulations, we find that: a strong economic reopening is possible;a “smart” reopening, preferencing some sectors over others, makes only modest improvements over a broad reopening;and all this hinges on retaining strong restrictions on non-work social contacts. If non-work contacts – going to bars, shopping without social distancing and masks, large group gatherings, etc. – return only half-way to the pre-COVID-19 baseline, the current decline in deaths reverses leading to a second wave of business closures.

Development of at-home sample collection logistics for large-scale seroprevalence studies.

BACKGROUND: Serological studies rely on the recruitment of representative cohorts; however, such efforts are specially complicated by the conditions surrounding the COVID19 pandemic. METHODS: We aimed to design and implement a fully remote methodology for conducting safe serological surveys that also allow for the engagement of representative study populations. RESULTS: This design was well-received and effective. 2,066 participants ≥18 years old were enrolled, reflecting the ethnic and racial composition of Massachusetts. >70% of them reported being satisfied/extremely satisfied with the online enrollment and at-home self-collection of blood samples. While 18.6% reported some discomfort experienced with the collection process, 72.2% stated that they would be willing to test weekly if enrolled in a long-term study. CONCLUSIONS: High engagement and positive feedback from participants, as well as the quality of self-collected specimens, point to the usefulness of this fully remote, self-collection-based study design for future safer and efficient population-level serological surveys.

A Global lmmunological Observatory to meet a time of pandemics.

SARS-CoV-2 presents an unprecedented international challenge, but it will not be the last such threat. Here, we argue that the world needs to be much better prepared to rapidly detect, define and defeat future pandemics. We propose that a Global Immunological Observatory and associated developments in systems immunology, therapeutics and vaccine design should be at the heart of this enterprise.

Vaccine nationalism and the dynamics and control of SARS-CoV-2.

Vaccines provide powerful tools to mitigate the enormous public health and economic costs that the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to exert globally, yet vaccine distribution remains unequal among countries. To examine the potential epidemiological and evolutionary impacts of "vaccine nationalism," we extend previous models to include simple scenarios of stockpiling between two regions. In general, when vaccines are widely available and the immunity they confer is robust, sharing doses minimizes total cases across regions. A number of subtleties arise when the populations and transmission rates in each region differ, depending on evolutionary assumptions and vaccine availability. When the waning of natural immunity contributes most to evolutionary potential, sustained transmission in low-access regions results in an increased potential for antigenic evolution, which may result in the emergence of novel variants that affect epidemiological characteristics globally. Overall, our results stress the importance of rapid, equitable vaccine distribution for global control of the pandemic.

Cross-Sectional Assessment of SARS-CoV-2 Viral Load by Symptom Status in Massachusetts Congregate Living Facilities.

Transmission of coronavirus disease 2019 (COVID-19) from people without symptoms confounds societal mitigation strategies. From April to June 2020, we tested nasopharyngeal swabs by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) from 15 514 staff and 16 966 residents of nursing homes and assisted living facilities in Massachusetts. Cycle threshold (Ct) distributions were very similar between populations with (n = 739) and without (n = 2179) symptoms at the time of sampling (mean Ct, 25.7 vs 26.4; ranges 12-38). However, as local cases waned, those without symptoms shifted towards higher Ct. With such similar viral load distributions, existing testing modalities should perform comparably regardless of symptoms, contingent upon time since infection.

Estimating epidemiologic dynamics from cross-sectional viral load distributions.

Estimating an epidemic's trajectory is crucial for developing public health responses to infectious diseases, but case data used for such estimation are confounded by variable testing practices. We show that the population distribution of viral loads observed under random or symptom-based surveillance-in the form of cycle threshold (Ct) values obtained from reverse transcription quantitative polymerase chain reaction testing-changes during an epidemic. Thus, Ct values from even limited numbers of random samples can provide improved estimates of an epidemic's trajectory. Combining data from multiple such samples improves the precision and robustness of this estimation. We apply our methods to Ct values from surveillance conducted during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in a variety of settings and offer alternative approaches for real-time estimates of epidemic trajectories for outbreak management and response.

Estimation of Transmission of COVID-19 in Simulated Nursing Homes With Frequent Testing and Immunity-Based Staffing.

Importance: Nursing homes and other long-term care facilities have been disproportionately impacted by the COVID-19 pandemic. Strategies are urgently needed to reduce transmission in these high-risk populations. Objective: To evaluate COVID-19 transmission in nursing homes associated with contact-targeted interventions and testing. Design, Setting, and Participants: This decision analytical modeling study developed an agent-based susceptible-exposed-infectious (asymptomatic/symptomatic)-recovered model between July and September 2020 to examine SARS-CoV-2 transmission in nursing homes. Residents and staff of a simulated nursing home with 100 residents and 100 staff split among 3 shifts were modeled individually; residents were split into 2 cohorts based on COVID-19 diagnosis. Data were analyzed from September to October 2020. Exposures: In the resident cohorting intervention, residents who had recovered from COVID-19 were moved back from the COVID-19 (ie, infected with SARS-CoV-2) cohort to the non-COVID-19 (ie, susceptible and uninfected with SARS-CoV-2) cohort. In the immunity-based staffing intervention, staff who had recovered from COVID-19 were assumed to have protective immunity and were assigned to work in the non-COVID-19 cohort, while susceptible staff worked in the COVID-19 cohort and were assumed to have high levels of protection from personal protective equipment. These interventions aimed to reduce the fraction of people's contacts that were presumed susceptible (and therefore potentially infected) and replaced them with recovered (immune) contacts. A secondary aim of was to evaluate cumulative incidence of SARS-CoV-2 infections associated with 2 types of screening tests (ie, rapid antigen testing and polymerase chain reaction [PCR] testing) conducted with varying frequency. Main Outcomes and Measures: Estimated cumulative incidence proportion of SARS-CoV-2 infection after 3 months. Results: Among the simulated cohort of 100 residents and 100 staff members, frequency and type of testing were associated with smaller outbreaks than the cohorting and staffing interventions. The testing strategy associated with the greatest estimated reduction in infections was daily antigen testing, which reduced the mean cumulative incidence proportion by 49% in absence of contact-targeted interventions. Under all screening testing strategies, the resident cohorting intervention and the immunity-based staffing intervention were associated with reducing the final estimated size of the outbreak among residents, with the immunity-based staffing intervention reducing it more (eg, by 19% in the absence of testing) than the resident cohorting intervention (eg, by 8% in the absence of testing). The estimated reduction in transmission associated with these interventions among staff varied by testing strategy and community prevalence. Conclusions and Relevance: These findings suggest that increasing the frequency of screening testing of all residents and staff, or even staff alone, in nursing homes may reduce outbreaks in this high-risk setting. Immunity-based staffing may further reduce spread at little or no additional cost and becomes particularly important when daily testing is not feasible.

Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes.

Given vaccine dose shortages and logistical challenges, various deployment strategies are being proposed to increase population immunity levels to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Two critical issues arise: How timing of delivery of the second dose will affect infection dynamics and how it will affect prospects for the evolution of viral immune escape via a buildup of partially immune individuals. Both hinge on the robustness of the immune response elicited by a single dose as compared with natural and two-dose immunity. Building on an existing immuno-epidemiological model, we find that in the short term, focusing on one dose generally decreases infections, but that longer-term outcomes depend on this relative immune robustness. We then explore three scenarios of selection and find that a one-dose policy may increase the potential for antigenic evolution under certain conditions of partial population immunity. We highlight the critical need to test viral loads and quantify immune responses after one vaccine dose and to ramp up vaccination efforts globally.

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings.

Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.

Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening.

The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with presymptomatic, symptomatic, and asymptomatic infections, the reopening of societies and the control of virus spread will be facilitated by robust population screening, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are too low to detect, followed by exponential viral growth, leading to peak viral load and infectiousness and ending with declining titers and clearance. Given the pattern of viral load kinetics, we model the effectiveness of repeated population screening considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective screening depends largely on frequency of testing and speed of reporting and is only marginally improved by high test sensitivity. We therefore conclude that screening should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.

Estimating internationally imported cases during the early COVID-19 pandemic.

Early in the COVID-19 pandemic, predictions of international outbreaks were largely based on imported cases from Wuhan, China, potentially missing imports from other cities. We provide a method, combining daily COVID-19 prevalence and flight passenger volume, to estimate importations from 18 Chinese cities to 43 international destinations, including 26 in Africa. Global case importations from China in early January came primarily from Wuhan, but the inferred source shifted to other cities in mid-February, especially for importations to African destinations. We estimate that 10.4 (6.2 - 27.1) COVID-19 cases were imported to these African destinations, which exhibited marked variation in their magnitude and main sources of importation. We estimate that 90% of imported cases arrived between 17 January and 7 February, prior to the first case detections. Our results highlight the dynamic role of source locations, which can help focus surveillance and response efforts.

Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance.

The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with pre-symptomatic, symptomatic, and asymptomatic infections, the re-opening of societies and the control of virus spread will be facilitated by robust surveillance, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are usually too low to detect, followed by an exponential viral growth, leading to a peak viral load and infectiousness, and ending with declining viral levels and clearance. Given the pattern of viral load kinetics, we model surveillance effectiveness considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective surveillance depends largely on frequency of testing and the speed of reporting, and is only marginally improved by high test sensitivity. We therefore conclude that surveillance should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.