Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities.

The two nearby Amazonian cities of Iquitos and Manaus endured explosive COVID-19 epidemics and may well have suffered the world's highest infection and death rates over 2020, the first year of the pandemic. State-of-the-art epidemiological and modeling studies estimated that the populations of both cities came close to attaining herd immunity (>70% infected) at the termination of the first wave and were thus protected. This makes it difficult to explain the more deadly second wave of COVID-19 that struck again in Manaus just months later, simultaneous with the appearance of a new P.1 variant of concern, creating a catastrophe for the unprepared population. It was suggested that the second wave was driven by reinfections, but the episode has become controversial and an enigma in the history of the pandemic. We present a data-driven model of epidemic dynamics in Iquitos, which we also use to explain and model events in Manaus. By reverse engineering the multiple epidemic waves over 2 y in these two cities, the partially observed Markov process model inferred that the first wave left Manaus with a highly susceptible and vulnerable population (≈40% infected) open to invasion by P.1, in contrast to Iquitos (≈72% infected). The model reconstructed the full epidemic outbreak dynamics from mortality data by fitting a flexible time-varying reproductive number [Formula: see text] while estimating reinfection and impulsive immune evasion. The approach is currently highly relevant given the lack of tools available to assess these factors as new SARS-CoV-2 virus variants appear with different degrees of immune evasion.

Reconstructing household transmission dynamics to estimate the infectiousness of asymptomatic influenza virus infections.

There has long been controversy over the potential for asymptomatic cases of the influenza virus to have the capacity for onward transmission, but recognition of asymptomatic transmission of COVID-19 stimulates further research into this topic. Here, we develop a Bayesian methodology to analyze detailed data from a large cohort of 727 households and 2515 individuals in the 2009 pandemic influenza A(H1N1) outbreak in Hong Kong to characterize household transmission dynamics and to estimate the relative infectiousness of asymptomatic versus symptomatic influenza cases. The posterior probability that asymptomatic cases [36% of cases; 95% credible interval (CrI): 32%, 40%] are less infectious than symptomatic cases is 0.82, with estimated relative infectiousness 0.57 (95% CrI: 0.11, 1.54). More data are required to strengthen our understanding of the contribution of asymptomatic cases to the spread of influenza.

High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains.

The high genetic diversity of influenza viruses means that traditional serological assays have too low throughput to measure serum antibody neutralization titers against all relevant strains. To overcome this challenge, we developed a sequencing-based neutralization assay that simultaneously measures titers against many viral strains using small serum volumes using a workflow similar to traditional neutralization assays. The key innovation is to incorporate unique nucleotide barcodes into the hemagglutinin (HA) genomic segment, and then pool viruses with numerous different barcoded HA variants and quantify the infectivity of all of them simultaneously using next-generation sequencing. With this approach, a single researcher performed the equivalent of 2,880 traditional neutralization assays (80 serum samples against 36 viral strains) in approximately 1 month. We applied the sequencing-based assay to quantify the impact of influenza vaccination on neutralization titers against recent human H1N1 strains for individuals who had or had not also received a vaccine in the previous year. We found that the viral strain specificities of the neutralizing antibodies elicited by vaccination vary among individuals and that vaccination induced a smaller increase in titers for individuals who had also received a vaccine the previous year-although the titers 6 months after vaccination were similar in individuals with and without the previous-year vaccination. We also identified a subset of individuals with low titers to a subclade of recent H1N1 even after vaccination. We provide an experimental protocol (dx.doi.org/10.17504/protocols.io.kqdg3xdmpg25/v1) and computational pipeline (https://github.com/jbloomlab/seqneut-pipeline) for the sequencing-based neutralization assays to facilitate the use of this method by others. IMPORTANCE: We describe a new approach that can rapidly measure how the antibodies in human serum inhibit infection by many different influenza strains. This new approach is useful for understanding how viral evolution affects antibody immunity. We apply the approach to study the effect of repeated influenza vaccination.

Forecasting of influenza activity and associated hospital admission burden and estimating the impact of COVID-19 pandemic on 2019/20 winter season in Hong Kong.

Like other tropical and subtropical regions, influenza viruses can circulate year-round in Hong Kong. However, during the COVID-19 pandemic, there was a significant decrease in influenza activity. The objective of this study was to retrospectively forecast influenza activity during the year 2020 and assess the impact of COVID-19 public health social measures (PHSMs) on influenza activity and hospital admissions in Hong Kong. Using weekly surveillance data on influenza virus activity in Hong Kong from 2010 to 2019, we developed a statistical modeling framework to forecast influenza virus activity and associated hospital admissions. We conducted short-term forecasts (1-4 weeks ahead) and medium-term forecasts (1-13 weeks ahead) for the year 2020, assuming no PHSMs were implemented against COVID-19. We estimated the reduction in transmissibility, peak magnitude, attack rates, and influenza-associated hospitalization rate resulting from these PHSMs. For short-term forecasts, mean ambient ozone concentration and school holidays were found to contribute to better prediction performance, while absolute humidity and ozone concentration improved the accuracy of medium-term forecasts. We observed a maximum reduction of 44.6% (95% CI: 38.6% - 51.9%) in transmissibility, 75.5% (95% CI: 73.0% - 77.6%) in attack rate, 41.5% (95% CI: 13.9% - 55.7%) in peak magnitude, and 63.1% (95% CI: 59.3% - 66.3%) in cumulative influenza-associated hospitalizations during the winter-spring period of the 2019/2020 season in Hong Kong. The implementation of PHSMs to control COVID-19 had a substantial impact on influenza transmission and associated burden in Hong Kong. Incorporating information on factors influencing influenza transmission improved the accuracy of our predictions.

Pandemic fatigue impedes mitigation of COVID-19 in Hong Kong.

Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines and mobile telephones from May 2020 to February 2021. We analyze the epidemiological impact of pandemic fatigue by using the large and detailed cross-sectional telephone surveys to quantify risk perception and self-reported protective behaviors and mathematical models to incorporate population protective behaviors. Our retrospective prediction suggests that an increase of 100 daily new reported cases would lead to 6.60% (95% CI: 4.03, 9.17) more people worrying about being infected, increase 3.77% (95% CI: 2.46, 5.09) more people to avoid social gatherings, and reduce the weekly mean reproduction number by 0.32 (95% CI: 0.20, 0.44). Accordingly, the fourth wave would have been 14% (95% CI%: -53%, 81%) smaller if not for pandemic fatigue. This indicates the important role of mitigating pandemic fatigue in maintaining population protective behaviors for controlling COVID-19.

Hemagglutination Inhibition Antibody Titers as Mediators of Influenza Vaccine Efficacy Against Symptomatic Influenza A(H1N1), A(H3N2), and B/Victoria Virus Infections.

BACKGROUND: The hemagglutination inhibition antibody (HAI) titer contributes only a part of vaccine-induced protection against influenza virus infections. Using causal mediation analysis, we quantified the proportion of vaccine efficacy mediated by postvaccination HAI titers. METHODS: We conducted causal mediation analyses using data from a randomized, active-comparator controlled, phase III, trial of an inactivated, split-virion seasonal quadrivalent influenza vaccine in children conducted from October 2010 to December 2011 in 8 countries. Vaccine efficacy was estimated using a weighted Cox proportional hazards model. Estimates were decomposed into the direct and indirect effects mediated by postvaccination HAI titers. RESULTS: The proportions of vaccine efficacy mediated by postvaccination HAI titers were estimated to be 22% (95% confidence interval, 18%--47%) for influenza A(H1N1), 20% (16%-39%) for influenza A(H3N2), and 37% (26%-85%) for influenza B/Victoria. CONCLUSIONS: HAI titers partially mediate influenza vaccine efficacy against influenza A(H1N1), A(H3N2), and B/Victoria. Our estimates were lower than in previous studies, possibly reflecting expected heterogeneity in antigenic similarity between vaccine and circulating viruses across seasons.

Estimation of the Time-Varying Effective Reproductive Number of COVID-19 Based on Multivariate Time Series of Severe Health Outcomes.

The time-varying effective reproduction number (Rt at time t) measures the transmissibility of SARS-CoV-2 and is conventionally based on daily case counts, which may suffer from time-varying ascertainment. We analyzed Rt estimates from case counts and severe COVID-19 (intensive care unit admissions, severe or critical cases, and mortality) across 2022 in Hong Kong's fifth and sixth waves of infection. Within the fifth wave, the severe disease-based Rt (3.5) was significantly higher than the case-based Rt (2.4) but not in the sixth wave. During periods with fluctuating underreporting, data based on severe diseases may provide more reliable Rt estimates.

Interplay between viral shedding, age, and symptoms on individual infectiousness of influenza cases in households.

BACKGROUND: Understanding factors affecting the infectiousness of influenza cases is crucial for disease prevention and control. Viral shedding is expected to correlate with infectiousness of cases, but it is strongly associated with age and the presence of symptoms. METHODS: To elucidate this complex interplay, we analyze with an individual-based household transmission model a detailed household transmission study of influenza with 442 households and 1710 individuals from 2008 to 2017 in Hong Kong, to characterize the household transmission dynamics and identify factors affecting transmissions. RESULTS: We estimate that age, fever symptoms and viral load were all associated with higher infectiousness. However, by model comparison, the best model includes age and fever as factors affecting individual infectiousness, and estimates that pre-school and school-age children were 317% (95% credible interval (CrI): 103%, 1042%) and 161% (95% CrI: 33%, 601%) more infectious than adults respectively, and patients having fever had 146% (95% CrI: 37%, 420%) higher infectiousness. Adding heterogeneity on individual infectiousness of cases does not improve the model fit, suggesting these factors could explain the difference in individual infectiousness. CONCLUSIONS: Our study clarifies the contribution of age, symptoms and viral shedding to individual infectiousness of influenza cases in households.

Comparison of Bivalent and Monovalent mRNA Vaccine Boosters.

In this cohort study conducted in Hong Kong where both bivalent and monovalent formulations of BNT162b2 were available, there were no significant differences in the mortality or hospitalization between those who received bivalent and monovalent mRNA as second boosters. Bivalent and monovalent mRNA boosters appear equally protective against clinical outcomes.

Preliminary findings from the Dynamics of the Immune Responses to Repeat Influenza Vaccination Exposures (DRIVE I) Study: a Randomized Controlled Trial.

BACKGROUND: Studies have reported that repeated annual vaccination may influence influenza vaccination effectiveness in the current season. METHODS: We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. In the first two years, participants received vaccination (V) or saline placebo (P) as follows: P-P, P-V, or V-V. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera collected at 5 timepoints from 95 participants were tested for antibodies against vaccine strains. RESULTS: From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with smaller increases for repeat vaccinees who on average had higher pre-vaccination titers in year 2. There were statistically significant differences in the proportion of participants achieving >=four-fold rises in antibody titer for the repeat vaccinees for influenza A(H1N1), B/Victoria and B/Yamagata, but not for A(H3N2). Among participants who received vaccination in year 2, there were no statistically significant differences between the P-V and V-V groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. CONCLUSIONS: In the first two years, during which influenza did not circulate, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection.

Effectiveness of Vaccines and Antiviral Drugs in Preventing Severe and Fatal COVID-19, Hong Kong.

We compared the effectiveness and interactions of molnupiravir and nirmatrelvir/ritonavir and 2 vaccines, CoronaVac and Comirnaty, in a large population of inpatients with COVID-19 in Hong Kong. Both the oral antiviral drugs and vaccines were associated with lower risks for all-cause mortality and progression to serious/critical/fatal conditions (study outcomes). No significant interaction effects were observed between the antiviral drugs and vaccinations; their joint effects were additive. If antiviral drugs were prescribed within 5 days of confirmed COVID-19 diagnosis, usage was associated with lower risks for the target outcomes for patients >60, but not <60, years of age; no significant clinical benefit was found if prescribed beyond 5 days. Among patients >80 years of age, 3-4 doses of Comirnaty vaccine were associated with significantly lower risks for target outcomes. Policies should encourage COVID-19 vaccination, and oral antivirals should be made accessible to infected persons within 5 days of confirmed diagnosis.

Public Health Impact of Paxlovid as Treatment for COVID-19, United States.

We evaluated the population-level benefits of expanding treatment with the antiviral drug Paxlovid (nirmatrelvir/ritonavir) in the United States for SARS-CoV-2 Omicron variant infections. Using a multiscale mathematical model, we found that treating 20% of symptomatic case-patients with Paxlovid over a period of 300 days beginning in January 2022 resulted in life and cost savings. In a low-transmission scenario (effective reproduction number of 1.2), this approach could avert 0.28 million (95% CI 0.03-0.59 million) hospitalizations and save US $56.95 billion (95% CI US $2.62-$122.63 billion). In a higher transmission scenario (effective reproduction number of 3), the benefits increase, potentially preventing 0.85 million (95% CI 0.36-1.38 million) hospitalizations and saving US $170.17 billion (95% CI US $60.49-$286.14 billion). Our findings suggest that timely and widespread use of Paxlovid could be an effective and economical approach to mitigate the effects of COVID-19.

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic.

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

Prior infections and effectiveness of SARS-CoV-2 vaccine in test-negative studies: A systematic review and meta-analysis.

Prior infection with SARS-CoV-2 can provide protection against infection and severe COVID-19. We aimed to determine the impact of pre-existing immunity on the vaccine effectiveness (VE) estimates. We systematically reviewed and meta-analysed 66 test-negative design (TND) studies that examined VE against infection or severe disease (hospitalization, ICU admission, or death) for primary vaccination series. Pooled VE among studies that included people with prior COVID-19 infection was lower against infection (pooled VE: 77%; 95% confidence interval (CI): 72%, 81%) and severe disease (pooled VE: 86%; 95% CI: 83%, 89%), compared with studies that excluded people with prior COVID-19 infection (pooled VE against infection: 87%; 95% CI: 85%, 89%; pooled VE against severe disease: 93%; 95% CI: 91%, 95%). There was a negative correlation between VE estimates against infection and severe disease, and the cumulative incidence of cases before the start of the study or incidence rates during the study period. We found clear empirical evidence that higher levels of pre-existing immunity were associated with lower VE estimates. Prior infections should be treated as both a confounder and effect modificatory when the policies target the whole population or stratified by infection history, respectively.

Addressing current limitations of household transmission studies by collecting contact data.

Modeling studies of household transmission data have helped characterize the role of children in influenza and COVID-19 epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of SARS-CoV-2-like and influenza-like infections in a synthetic population of 1,000 households assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong.

The serial interval distribution is used to approximate the generation time distribution, an essential parameter to infer the transmissibility (${R}_t$) of an epidemic. However, serial interval distributions may change as an epidemic progresses. We examined detailed contact tracing data on laboratory-confirmed cases of COVID-19 in Hong Kong during the five waves from January 2020 to July 2022. We reconstructed the transmission pairs and estimated time-varying effective serial interval distributions and factors associated with longer or shorter intervals. Finally, we assessed the biases in estimating transmissibility using constant serial interval distributions. We found clear temporal changes in mean serial interval estimates within each epidemic wave studied and across waves, with mean serial intervals ranged from 5.5 days (95% CrI: 4.4, 6.6) to 2.7 (95% CrI: 2.2, 3.2) days. The mean serial intervals shortened or lengthened over time, which were found to be closely associated with the temporal variation in COVID-19 case profiles and public health and social measures and could lead to the biases in predicting ${R}_t$. Accounting for the impact of these factors, the time-varying quantification of serial interval distributions could lead to improved estimation of ${R}_t$, and provide additional insights into the impact of public health measures on transmission.

Mitigation of respiratory syncytial virus epidemics by RSVpreF vaccines after the COVID-19 pandemic in the UK: a modelling study.

BACKGROUND: The RSVpreF vaccines have breakthrough progress. The respiratory syncytial virus (RSV) vaccine for older adults from GlaxoSmithKline was the first RSV vaccine approved by the US Food and Drug Administration (FDA) in early May 2023, followed by the subsequent FDA approval of Pfizer's RSV vaccines for older adults and pregnant women. We aimed to estimate the public health impact of the potential population-level administrations of the RSVpreF vaccine in the UK. METHODS: In this modelling study, we used national census and contact survey data to construct an individual-based mathematical model, with interpersonal connections characterising household structure, social settings, and age-specific contact patterns. We considered both within-host viral-load dynamics and between-host RSV transmission. We modelled the coverages of RSV vaccines for older people (age ≥60 years) and pregnant women, using influenza vaccination data from the 2018-19 season. We explored a range of possible transmissibility and estimated the health burden averted by RSVpreF vaccine over a 300-day period as compared with the control scenario without vaccines. FINDINGS: In a low-transmission scenario (Re=1·2), RSVpreF would avert a total population of 2·35 (95% credible interval [CrI] 1·24-3·77) million infections, 12.80 (95% CrI 8·60-17·06) thousand hospital admissions, and 0·93 (95% CrI 0·69-1·25) thousand deaths, with 1·82 (1·41-2·33) million infections, 12·44 (8·50-16·38) thousand hospital admissions, and 0·93 (0·67-1·23) thousand deaths averted for people aged 60 years and older. In a high-transmission scenario (Re=2·0), RSVpreF would avert 2·01 (1·37-2·68) million infections, 14·67 (10·05-18·33) thousand hospital admissions, and 1·12 (0·80-1·35) thousand deaths. The majority averted would still be among older adults. INTERPRETATION: Our mathematical models will help improve the vaccine schedules of RSVpreF. Future work will address several limitations when data become available, including the incorporation of population immunity, potential vaccine hesitancy, and other factors affecting vaccine uptake and effectiveness. FUNDING: Government of the Hong Kong Special Administrative Region, the European Research Council, and Ministry of Science and Technology of the People's Republic of China.

Evaluating the impact of extended dosing intervals on mRNA COVID-19 vaccine effectiveness in adolescents.

BACKGROUND: Extending the dosing interval of a primary series of mRNA COVID-19 vaccination has been employed to reduce myocarditis risk in adolescents, but previous evaluation of impact on vaccine effectiveness (VE) is limited to risk after second dose. METHODS: We quantified the impact of the dosing interval based on case notifications and vaccination uptake in Hong Kong from January to April 2022, based on calendar-time proportional hazards models and matching approaches. RESULTS: We estimated that the hazard ratio (HR) and odds ratio (OR) of infections after the second dose for extended (28 days or more) versus regular (21-27 days) dosing intervals ranged from 0.86 to 0.99 from calendar-time proportional hazards models, and from 0.85 to 0.87 from matching approaches, respectively. Adolescents in the extended dosing groups (including those who did not receive a second dose in the study period) had a higher hazard of infection than those with a regular dosing interval during the intra-dose period (HR 1.66; 95% CI 1.07, 2.59; p = 0.02) after the first dose. CONCLUSIONS: Implementing an extended dosing interval should consider multiple factors including the degree of myocarditis risk, the degree of protection afforded by each dose, and the extra protection achievable using an extended dosing interval.

Effectiveness of nirmatrelvir/ritonavir and molnupiravir in non-hospitalized adults with COVID-19: systematic review and meta-analysis of observational studies.

OBJECTIVE: To determine the effectiveness of nirmatrelvir/ritonavir and molnupiravir among vaccinated and unvaccinated non-hospitalized adults with COVID-19. METHODS: Observational studies of nirmatrelvir/ritonavir or molnupiravir compared to no antiviral drug treatment for COVID-19 in non-hospitalized adults with data on vaccination status were included. We searched MEDLINE, EMBASE, Scopus, Web of Science, WHO COVID-19 Research Database and medRxiv for reports published between 1 January 2022 and 8 November 2023. The primary outcome was a composite of hospitalization or mortality up to 35 days after COVID-19 diagnosis. Risk of bias was assessed with ROBINS-I. Risk ratios (RR), hazard ratios (HR) and risk differences (RD) were separately estimated using random-effects models. RESULTS: We included 30 cohort studies on adults treated with nirmatrelvir/ritonavir (n = 462 279) and molnupiravir (n = 48 008). Nirmatrelvir/ritonavir probably reduced the composite outcome (RR 0.62, 95%CI 0.55-0.70; I2 = 0%; moderate certainty) with no evidence of effect modification by vaccination status (RR Psubgroup = 0.47). In five studies, RD estimates against the composite outcome for nirmatrelvir/ritonavir were 1.21% (95%CI 0.57% to 1.84%) in vaccinated and 1.72% (95%CI 0.59% to 2.85%) in unvaccinated subgroups.Molnupiravir may slightly reduce the composite outcome (RR 0.75, 95%CI 0.67-0.85; I2 = 32%; low certainty). Evidence of effect modification by vaccination status was inconsistent among studies reporting different effect measures (RR Psubgroup = 0.78; HR Psubgroup = 0.08). In two studies, RD against the composite outcome for molnupiravir were -0.01% (95%CI -1.13% to 1.10%) in vaccinated and 1.73% (95%CI -2.08% to 5.53%) in unvaccinated subgroups. CONCLUSIONS: Among cohort studies of non-hospitalized adults with COVID-19, nirmatrelvir/ritonavir is effective against the composite outcome of severe COVID-19 independent of vaccination status. Further research and a reassessment of molnupiravir use among vaccinated adults are warranted. REGISTRATION: PROSPERO CRD42023429232.

Interpretations of Studies on SARS-CoV-2 Vaccination and Post-acute COVID-19 Sequelae.

This article discusses causal interpretations of epidemiologic studies of the effects of vaccination on sequelae after acute severe acute respiratory syndrome coronavirus 2 infection. To date, researchers have tried to answer several different research questions on this topic. While some studies assessed the impact of postinfection vaccination on the presence of or recovery from post-acute coronavirus disease 2019 syndrome, others quantified the association between preinfection vaccination and postacute sequelae conditional on becoming infected. However, the latter analysis does not have a causal interpretation, except under the principal stratification framework-that is, this comparison can only be interpreted as causal for a nondiscernible stratum of the population. As the epidemiology of coronavirus disease 2019 is now nearly entirely dominated by reinfections, including in vaccinated individuals, and possibly caused by different Omicron subvariants, it has become even more important to design studies on the effects of vaccination on postacute sequelae that address precise causal questions and quantify effects corresponding to implementable interventions.