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Most COVID-19 vaccines require two doses, however with limited vaccine supply, policymakers are considering single-dose vaccination as an alternative strategy. Using a mathematical model combined with optimization algorithms, we determined optimal allocation strategies with one and two doses of vaccine under various degrees of viral transmission. Under low transmission, we show that the optimal allocation of vaccine vitally depends on the single-dose efficacy. With high single-dose efficacy, single-dose vaccination is optimal, preventing up to 22% more deaths than a strategy prioritizing two-dose vaccination for older adults. With low or moderate single-dose efficacy, mixed vaccination campaigns with complete coverage of older adults are optimal. However, with modest or high transmission, vaccinating older adults first with two doses is best, preventing up to 41% more deaths than a single-dose vaccination given across all adult populations. Our work suggests that it is imperative to determine the efficacy and durability of single-dose vaccines, as mixed or single-dose vaccination campaigns may have the potential to contain the pandemic much more quickly. Most COVID-19 vaccines require two doses but a single dose provides partial protection, so it is unclear how best to prioritize vaccine distribution in the context of limited supply. Here, the authors show that campaigns in which some age groups receive one dose while others receive both doses may be optimal.

SARS-CoV-2 is difficult to contain because many transmissions occur during pre-symptomatic infection. Unlike influenza, most SARS-CoV-2-infected people do not transmit while a small percentage infect large numbers of people. We designed mathematical models which link observed viral loads with epidemiologic features of each virus, including distribution of transmissions attributed to each infected person and duration between symptom onset in the transmitter and secondarily infected person. We identify that people infected with SARS-CoV-2 or influenza can be highly contagious for less than 1 day, congruent with peak viral load. SARS-CoV-2 super-spreader events occur when an infected person is shedding at a very high viral load and has a high number of exposed contacts. The higher predisposition of SARS-CoV-2 toward super-spreading events cannot be attributed to additional weeks of shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks, likely due to aerosolization.

HIV and herpes simplex virus type 2 (HSV-2) infections cause a substantial global disease burden and are epidemiologically correlated. Two previous systematic reviews of the association between HSV-2 and HIV found evidence that HSV-2 infection increases the risk of HIV acquisition, but these reviews are now more than a decade old. For this systematic review and meta-analysis, we searched PubMed, MEDLINE, and Embase (from Jan 1, 2003, to May 25, 2017) to identify studies investigating the risk of HIV acquisition after exposure to HSV-2 infection, either at baseline (prevalent HSV-2 infection) or during follow-up (incident HSV-2 infection). Studies were included if they were a cohort study, controlled trial, or case-control study (including case-control studies nested within a cohort study or clinical trial); if they assessed the effect of pre-existing HSV-2 infection on HIV acquisition; and if they determined the HSV-2 infection status of study participants with a type-specific assay. We calculated pooled random-effect estimates of the association between prevalent or incident HSV-2 infection and HIV seroconversion. We also extended previous investigations through detailed meta-regression and subgroup analyses. In particular, we investigated the effect of sex and risk group (general population vs higher-risk populations) on the relative risk (RR) of HIV acquisition after prevalent or incident HSV-2 infection. Higher-risk populations included female sex workers and their clients, men who have sex with men, serodiscordant couples, and attendees of sexually transmitted infection clinics. We identified 57 longitudinal studies exploring the association between HSV-2 and HIV. HIV acquisition was almost tripled in the presence of prevalent HSV-2 infection among general populations (adjusted RR 2·7, 95% CI 2·2–3·4; number of estimates [Ne]=22) and was roughly doubled among higher-risk populations (1·7, 1·4–2·1; Ne=25). Incident HSV-2 infection in general populations was associated with the highest risk of acquisition of HIV (4·7, 2·2–10·1; Ne=6). Adjustment for confounders at the study level was often incomplete but did not significantly affect the results. We found moderate heterogeneity across study estimates, which was explained by risk group, world region, and HSV-2 exposure type (prevalent vs incident). We found evidence that HSV-2 infection increases the risk of HIV acquisition. This finding has important implications for management of individuals diagnosed with HSV-2 infection, particularly for those who are newly infected. Interventions targeting HSV-2, such as new HSV vaccines, have the potential for additional benefit against HIV, which could be particularly powerful in regions with a high incidence of co-infection. World Health Organization.

An unprecedented breadth of longitudinal viral and multi-scale immunological data has been gathered during SARS-CoV-2 infection. However, due to the high complexity, non-linearity, multi-dimensionality, mixed anatomic sampling, and possible autocorrelation of available immune data, it is challenging to identify the components of the innate and adaptive immune response that drive viral elimination. Novel mathematical models and analytical approaches are required to synthesize contemporaneously gathered cytokine, transcriptomic, flow cytometry, antibody response, and viral load data into a coherent story of viral control, and ultimately to discriminate drivers of mild versus severe infection. We investigated a dataset describing innate, SARS-CoV-2 specific T cell, and antibody responses in the lung during early and late stages of infection in immunologically naïve rhesus macaques. We used multi-model inference and ensemble modeling approaches from ecology and weather forecasting to compare and combine various competing models. Model outputs suggest that the innate immune response plays a crucial role in controlling early infection, while SARS-CoV-2 specific CD4+ T cells correspond to later viral elimination, and anti-spike IgG antibodies do not impact viral dynamics. Among the numerous genes potentially contributing to the innate response, we identified IFI27 as most closely linked to viral load decline. A 90% knockdown of the innate response from our validated model resulted in a ~10-fold increase in peak viral load during infection. Our approach provides a novel methodological framework for future analyses of similar complex, non-linear multi-component immunologic data sets.

Antiretroviral therapy (ART) suppresses viral replication in people living with HIV. Yet, infected cells persist for decades on ART and viremia returns if ART is stopped. Persistence has been attributed to viral replication in an ART sanctuary and long-lived and/or proliferating latently infected cells. Using ecological methods and existing data, we infer that >99% of infected cells are members of clonal populations after one year of ART. We reconcile our results with observations from the first months of ART, demonstrating mathematically how a fossil record of historic HIV replication permits observed viral evolution even while most new infected cells arise from proliferation. Together, our results imply cellular proliferation generates a majority of infected cells during ART. Therefore, reducing proliferation could decrease the size of the HIV reservoir and help achieve a functional cure. HIV infected cells persist for decades in patients under ART, but the mechanisms responsible remain unclear. Here, Reeves et al. use modeling approaches adapted from ecology to show that cellular proliferation, rather than viral replication, generates a majority of infected cells during ART.

Broadly neutralizing antibodies (bNAbs) are promising agents to prevent HIV infection and achieve HIV remission without antiretroviral therapy (ART). As with ART, bNAb combinations are likely needed to cover HIV’s extensive diversity. Not all bNAbs are identical in terms of their breadth, potency, and in vivo longevity (half-life). Given these differences, it is important to optimally select the composition, or dose ratio, of combination bNAb therapies for future clinical studies. We developed a model that synthesizes 1) pharmacokinetics, 2) potency against a wide HIV diversity, 3) interaction models for how drugs work together, and 4) correlates that translate in vitro potency to clinical protection. We found optimization requires drug-specific balances between potency, longevity, and interaction type. As an example, tradeoffs between longevity and potency are shown by comparing a combination therapy to a bi-specific antibody (a single protein merging both bNAbs) that takes the better potency but the worse longevity of the two components. Then, we illustrate a realistic dose ratio optimization of a triple combination of VRC07, 3BNC117, and 10–1074 bNAbs. We apply protection estimates derived from both a non-human primate (NHP) challenge study meta-analysis and the human antibody mediated prevention (AMP) trials. In both cases, we find a 2:1:1 dose emphasizing VRC07 is nearly optimal. Our approach can be immediately applied to optimize the next generation of combination antibody prevention and cure studies.

Trial results for two COVID-19 vaccines suggest at least 90% efficacy against symptomatic disease (VE DIS ). It remains unknown whether this efficacy is mediated by lowering SARS-CoV-2 infection susceptibility ( VE SUSC ) or development of symptoms after infection (VE SYMP ). We aim to assess and compare the population impact of vaccines with different efficacy profiles (VE SYMP and VE SUSC ) satisfying licensure criteria. We developed a mathematical model of SARS-CoV-2 transmission, calibrated to data from King County, Washington. Rollout scenarios starting December 2020 were simulated with combinations of VE SUSC and VE SYMP resulting in up to 100% VE DIS . We assumed no reduction of infectivity upon infection conditional on presence of symptoms. Proportions of cumulative infections, hospitalizations and deaths prevented over 1 year from vaccination start are reported. Rollouts of 1 M vaccinations (5000 daily) using vaccines with 50% VE DIS are projected to prevent 23–46% of infections and 31–46% of deaths over 1 year. In comparison, vaccines with 90% VE DIS are projected to prevent 37–64% of infections and 46–64% of deaths over 1 year. In both cases, there is a greater reduction if VE DIS is mediated mostly by VE SUSC . The use of a “symptom reducing” vaccine will require twice as many people vaccinated than a “susceptibility reducing” vaccine with the same 90% VE DIS to prevent 50% of the infections and death over 1 year. Delaying the start of the vaccination by 3 months decreases the expected population impact by more than 50%. Vaccines which prevent COVID-19 disease but not SARS-CoV-2 infection, and thereby shift symptomatic infections to asymptomatic infections, will prevent fewer infections and require larger and faster vaccination rollouts to have population impact, compared to vaccines that reduce susceptibility to infection. If uncontrolled transmission across the U.S. continues, then expected vaccination in Spring 2021 will provide only limited benefit.

In a pivotal trial (EPIC-HR), a 5-day course of oral ritonavir-boosted nirmatrelvir, given early during symptomatic SARS-CoV-2 infection (within three days of symptoms onset), decreased hospitalization and death by 89.1% and nasal viral load by 0.87 log relative to placebo in high-risk individuals. Yet, nirmatrelvir/ritonavir failed as post-exposure prophylaxis in a trial, and frequent viral rebound has been observed in subsequent cohorts. We develop a mathematical model capturing viral-immune dynamics and nirmatrelvir pharmacokinetics that recapitulates viral loads from this and another clinical trial (PLATCOV). Our results suggest that nirmatrelvir’s in vivo potency is significantly lower than in vitro assays predict. According to our model, a maximally potent agent would reduce the viral load by approximately 3.5 logs relative to placebo at 5 days. The model identifies that earlier initiation and shorter treatment duration are key predictors of post-treatment rebound. Extension of treatment to 10 days for Omicron variant infection in vaccinated individuals, rather than increasing dose or dosing frequency, is predicted to lower the incidence of viral rebound significantly. Viral rebound has been observed following treatment with Paxlovid. Here the authors develop a mathematical model for viral-immune dynamics and nirmatrelvir pharmacokinetics and suggest that early treatment preserves susceptible cells and blunts the innate immune response without fully eliminating infection. They project that treatment extension for 10 days may overcome this effect.

Most proviruses persisting in people living with HIV (PWH) on antiretroviral therapy (ART) are defective. However, rarer intact proviruses almost always reinitiate viral rebound if ART stops. Therefore, assessing therapies to prevent viral rebound hinges on specifically quantifying intact proviruses. We evaluated the same samples from 10 male PWH on ART using the two-probe intact proviral DNA assay (IPDA) and near full length (nfl) Q4PCR. Both assays admitted similar ratios of intact to total HIV DNA, but IPDA found ~40-fold more intact proviruses. Neither assay suggested defective proviruses decay over 10 years. However, the mean intact half-lives were different: 108 months for IPDA and 65 months for Q4PCR. To reconcile this difference, we modeled additional longitudinal IPDA data and showed that decelerating intact decay could arise from very long-lived intact proviruses and/or misclassified defective proviruses: slowly decaying defective proviruses that are intact in IPDA probe locations (estimated up to 5%, in agreement with sequence library based predictions). The model also demonstrates how misclassification can lead to underestimated efficacy of therapies that exclusively reduce intact proviruses. We conclude that sensitive multi-probe assays combined with specific nfl-verified assays would be optimal to document absolute and changing levels of intact HIV proviruses. Quantifying intact proviruses is key to understanding decreases in HIV reservoirs but results can differ depending on the method. To balance sensitivity and specificity of two assays, the authors use mathematical models and measurements of intact and defective proviruses to assess how misclassification can impact estimates of natural and therapeutic reservoir reduction.

A reservoir of HIV-infected cells that persists despite suppressive antiretroviral therapy (ART) is the source of viral rebound upon ART cessation and the major barrier to a cure. Understanding reservoir seeding dynamics will help identify the best timing for HIV cure strategies. Here we characterize reservoir seeding using longitudinal samples from before and after ART initiation in individuals who sequentially became infected with genetically distinct HIV variants (superinfected). We previously identified cases of superinfection in a cohort of Kenyan women, and the dates of both initial infection and superinfection were determined. Six women, superinfected 0.2-5.2 years after initial infection, were subsequently treated with ART 5.4-18.0 years after initial infection. We performed next-generation sequencing of HIV gag and env RNA from plasma collected during acute infection as well as every ~2 years thereafter until ART initiation, and of HIV DNA from PBMCs collected 0.9-4.8 years after viral suppression on ART. We assessed phylogenetic relationships between HIV DNA reservoir sequences and longitudinal plasma RNA sequences prior to ART, to determine proportions of initial and superinfecting variants in the reservoir. The proportions of initial and superinfection lineage variants present in the HIV DNA reservoir were most similar to the proportions present in HIV RNA immediately prior to ART initiation. Phylogenetic analysis confirmed that the majority of HIV DNA reservoir sequences had the smallest pairwise distance to RNA sequences from timepoints closest to ART initiation. Our data suggest that while reservoir cells are created throughout pre-ART infection, the majority of HIV-infected cells that persist during ART entered the reservoir near the time of ART initiation. We estimate the half-life of pre-ART DNA reservoir sequences to be ~25 months, which is shorter than estimated reservoir decay rates during suppressive ART, implying continual decay and reseeding of the reservoir up to the point of ART initiation.