SARS-CoV-2 Viral Load in the Nasopharynx at Time of First Infection Among Unvaccinated Individuals: A Secondary Cross-Protocol Analysis of 4 Randomized Trials.

Importance: SARS-CoV-2 viral load (VL) in the nasopharynx is difficult to quantify and standardize across settings, but it may inform transmission potential and disease severity. Objective: To characterize VL at COVID-19 diagnosis among previously uninfected and unvaccinated individuals by evaluating the association of demographic and clinical characteristics, viral variant, and trial with VL, as well as the ability of VL to predict severe disease. Design, Setting, and Participants: This secondary cross-protocol analysis used individual-level data from placebo recipients from 4 harmonized, phase 3 COVID-19 vaccine efficacy trials sponsored by Moderna, AstraZeneca, Janssen, and Novavax. Participants were SARS-CoV-2 negative at baseline and acquired COVID-19 during the blinded phase of the trials. The setting included the US, Brazil, South Africa, Colombia, Argentina, Peru, Chile, and Mexico; start dates were July 27, 2020, to December 27, 2020; data cutoff dates were March 26, 2021, to July 30, 2021. Statistical analysis was performed from November 2022 to June 2023. Main Outcomes and Measures: Linear regression was used to assess the association of demographic and clinical characteristics, viral variant, and trial with polymerase chain reaction-measured log10 VL in nasal and/or nasopharyngeal swabs taken at the time of COVID-19 diagnosis. Results: Among 1667 participants studied (886 [53.1%] male; 995 [59.7%] enrolled in the US; mean [SD] age, 46.7 [14.7] years; 204 [12.2%] aged 65 years or older; 196 [11.8%] American Indian or Alaska Native, 150 [9%] Black or African American, 1112 [66.7%] White; 762 [45.7%] Hispanic or Latino), median (IQR) log10 VL at diagnosis was 6.18 (4.66-7.12) log10 copies/mL. Participant characteristics and viral variant explained only 5.9% of the variability in VL. The independent factor with the highest observed differences was trial: Janssen participants had 0.54 log10 copies/mL lower mean VL vs Moderna participants (95% CI, 0.20 to 0.87 log10 copies/mL lower). In the Janssen study, which captured the largest number of COVID-19 events and variants and used the most intensive post-COVID surveillance, neither VL at diagnosis nor averaged over days 1 to 28 post diagnosis was associated with COVID-19 severity. Conclusions and Relevance: In this study of placebo recipients from 4 randomized phase 3 trials, high variability was observed in SARS-CoV-2 VL at the time of COVID-19 diagnosis, and only a fraction was explained by individual participant characteristics or viral variant. These results suggest challenges for future studies of interventions seeking to influence VL and elevates the importance of standardized methods for specimen collection and viral load quantitation.

High Asymptomatic Carriage With the Omicron Variant in South Africa.

We report a 23% asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) Omicron carriage rate in participants being enrolled into a clinical trial in South Africa, 15-fold higher than in trials before Omicron. We also found lower CD4 + T-cell counts in persons with human immunodeficiency virus (HIV) strongly correlated with increased odds of being SARS-CoV-2 polymerase chain reaction (PCR) positive.

High Rate of Asymptomatic Carriage Associated with Variant Strain Omicron.

The early widespread dissemination of Omicron indicates the urgent need to better understand the transmission dynamics of this variant, including asymptomatic spread among immunocompetent and immunosuppressed populations. In early December 2021, the Ubuntu clinical trial, designed to evaluate efficacy of the mRNA-1273 vaccine (Moderna) among persons living with HIV (PLWH), began enrolling participants. Nasal swabs are routinely obtained at the initial vaccination visit, which requires participants to be clinically well to receive their initial jab. Of the initial 230 participants enrolled between December 2 and December 17, 2021, 71 (31%) were PCR positive for SARS-CoV-2: all of whom were subsequently confirmed by S gene dropout to be Omicron; 48% of the tested samples had cycle threshold (CT) values <25 and 18% less than 20, indicative of high titers of asymptomatic shedding. Asymptomatic carriage rates were similar in SARS-CoV-2 seropositive and seronegative persons (27% respectively). These data are in stark contrast to COVID-19 vaccine studies conducted pre-Omicron, where the SARS-CoV-2 PCR positivity rate at the first vaccination visit ranged from <1%-2.4%, including a cohort of over 1,200 PLWH largely enrolled in South Africa during the Beta outbreak. We also evaluated asymptomatic carriage in a sub study of the Sisonke vaccine trial conducted in South African health care workers, which indicated 2.6% asymptomatic carriage during the Beta and Delta outbreaks and subsequently rose to 16% in both PLWH and PHLWH during the Omicron period.

Selection of HIV Envelope Strains for Standardized Assessments of Vaccine-Elicited Antibody-Dependent Cellular Cytotoxicity-Mediating Antibodies.

Antibody-dependent cellular cytotoxicity (ADCC) has been correlated with reduced risk of human immunodeficiency virus type 1 (HIV-1) infection in several preclinical vaccine trials and in the RV144 clinical trial, indicating that this is a relevant antibody function to study. Given the diversity of HIV-1, the breadth of vaccine-induced antibody responses is a critical parameter to understand if a universal vaccine is to be realized. Moreover, the breadth of ADCC responses can be influenced by different vaccine strategies and regimens, including adjuvants. Therefore, to accurately evaluate ADCC and to compare vaccine regimens, it is important to understand the range of HIV Envelope (Env) susceptibility to these responses. These evaluations have been limited because of the complexity of the assay and the lack of a comprehensive panel of viruses for the assessment of these humoral responses. Here, we used 29 HIV-1 infectious molecular clones (IMCs) representing different Envelope subtypes and circulating recombinant forms to characterize susceptibility to ADCC from antibodies in plasma from infected individuals, including 13 viremic individuals, 10 controllers, and six with broadly neutralizing antibody responses. We found in our panel that ADCC susceptibility of the IMCs in our panel did not cluster by subtype, infectivity, level of CD4 downregulation, level of shedding, or neutralization sensitivity. Using partitioning around medoids (PAM) clustering to distinguish smaller groups of IMCs with similar ADCC susceptibility, we identified nested panels of four to eight IMCs that broadly represent the ADCC susceptibility of the entire 29-IMC panel. These panels, together with reagents developed to specifically accommodate circulating viruses at the geographical sites of vaccine trials, will provide a powerful tool to harmonize ADCC data generated across different studies and to detect common themes of ADCC responses elicited by various vaccines. IMPORTANCE Antibody-dependent cellular cytotoxicity (ADCC) responses were found to correlate with reduced risk of infection in the RV144 trial of the only human HIV-1 vaccine to show any efficacy to date. However, reagents to understand the breadth and magnitude of these responses across preclinical and clinical vaccine trials remain underdeveloped. In this study, we characterize HIV-1 infectious molecular clones encoding 29 distinct Envelope strains (Env-IMCs) to understand factors that impact virus susceptibility to ADCC and use statistical methods to identify smaller nested panels of four to eight Env-IMCs that accurately represent the full set. These reagents can be used as standardized reagents across studies to fully understand how ADCC may affect efficacy of future vaccine studies and how studies differ in the breadth of responses developed.

Ecological inference for infectious disease data, with application to vaccination strategies.

Disease surveillance systems provide a rich source of data regarding infectious diseases, aggregated across geographical regions. The analysis of such ecological data is fraught with difficulties, and, unless care and suitable data summaries are available, will lead to biased estimates of individual-level parameters. We consider using surveillance data to study the impacts of vaccination. To catalog the problems of ecological inference, we start with an individual-level model, which contains familiar parameters, and derive an ecologically consistent model for infectious diseases in partially vaccinated populations. We compare with other popular model classes and highlight deficiencies. We explore the properties of the new model through simulation and demonstrate that, under standard assumptions, the ecological model provides less biased estimates. We then fit the new model to data collected on measles outbreaks in Germany from 2005-2007.