Effectiveness of maternal influenza vaccination during pregnancy against laboratory-confirmed seasonal influenza among infants under 6 months of age in Ontario, Canada.

BACKGROUND: Randomized trials conducted in low- and middle-income settings demonstrated efficacy of influenza vaccination during pregnancy against influenza infection among infants <6 months of age. However, vaccine effectiveness (VE) estimates from settings with different population characteristics and influenza seasonality remain limited. METHODS: We conducted a test-negative study in Ontario, Canada. All influenza virus tests among infants <6 months from 2010-2019 were identified and linked with health databases to ascertain information on maternal-infant dyads. VE was estimated from the odds ratio for influenza vaccination during pregnancy among cases versus controls, computed using logistic regression with adjustment for potential confounders. RESULTS: Among 23,806 infants tested for influenza, 1,783 (7.5%) were positive and 1,708 (7.2%) were born to mothers vaccinated against influenza during pregnancy. VE against laboratory-confirmed infant influenza infection was 64% (95% confidence interval [CI]: 50%-74%). VE was similar by trimester of vaccination (1st/2nd: 66%, 40%-80%; 3rd: 63%, 46%-74%), infant age at testing (0-<2 months: 63%, 46%-75%; 2-<6 months: 64%, 36%-79%), and gestational age at birth (≥37 weeks: 64%, 50%-75%; < 37 weeks: 61%, 4%-86%). VE against influenza hospitalization was 67% (95%CI: 50%-78%). CONCLUSIONS: Influenza vaccination during pregnancy offers effective protection to infants <6 months, for whom vaccines are not currently available.

Mathematical modeling of the dynamics of COVID-19 variants of concern: Asymptotic and finite-time perspectives.

The COVID-19 pandemic has seen multiple waves, in part due to the implementation and relaxation of social distancing measures by the public health authorities around the world, and also caused by the emergence of new variants of concern (VOCs) of the SARS-Cov-2 virus. As the COVID-19 pandemic is expected to transition into an endemic state, how to manage outbreaks caused by newly emerging VOCs has become one of the primary public health issues. Using mathematical modeling tools, we investigated the dynamics of VOCs, both in a general theoretical framework and based on observations from public health data of past COVID-19 waves, with the objective of understanding key factors that determine the dominance and coexistence of VOCs. Our results show that the transmissibility advantage of a new VOC is a main factor for it to become dominant. Additionally, our modeling study indicates that the initial number of people infected with the new VOC plays an important role in determining the size of the epidemic. Our results also support the evidence that public health measures targeting the newly emerging VOC taken in the early phase of its spread can limit the size of the epidemic caused by the new VOC (Wu et al., 2139Wu, Scarabel, Majeed, Bragazzi, & Orbinski, ; Wu et al., 2021).

Lentiviral Infections Persist in Brain despite Effective Antiretroviral Therapy and Neuroimmune Activation.

HIV infection persists in different tissue reservoirs among people with HIV (PWH) despite effective antiretroviral therapy (ART). In the brain, lentiviruses replicate principally in microglia and trafficking macrophages. The impact of ART on this viral reservoir is unknown. We investigated the activity of contemporary ART in various models of lentivirus brain infection. HIV-1 RNA and total and integrated DNA were detected in cerebral cortex from all PWH (n = 15), regardless of ART duration or concurrent plasma viral quantity and, interestingly, integrated proviral DNA levels in brain were significantly higher in the aviremic ART-treated group (P < 0.005). Most ART drugs tested (dolutegravir, ritonavir, raltegravir, and emtricitabine) displayed significantly lower 50% effective concentration (EC50) values in lymphocytes than in microglia, except tenofovir, which showed 1.5-fold greater activity in microglia (P < 0.05). In SIV-infected Chinese rhesus macaques, despite receiving suppressive (n = 7) or interrupted (n = 8) ART, brain tissues had similar SIV-encoded RNA and total and integrated DNA levels compared to brains from infected animals without ART (n = 3). SIV and HIV-1 capsid antigens were immunodetected in brain, principally in microglia/macrophages, regardless of ART duration and outcome. Antiviral immune responses were comparable in the brains of ART-treated and untreated HIV- and SIV-infected hosts. Both HIV-1 and SIV persist in brain tissues despite contemporary ART, with undetectable virus in blood. ART interruption exerted minimal effect on the SIV brain reservoir and did not alter the neuroimmune response profile. These studies underscore the importance of augmenting ART potency in different tissue compartments. IMPORTANCE Antiretroviral therapy (ART) suppresses HIV-1 in plasma and CSF to undetectable levels. However, the impact of contemporary ART on HIV-1 brain reservoirs remains uncertain. An active viral reservoir in the brain during ART could lead to rebound systemic infection after cessation of therapy, development of drug resistance mutations, and neurological disease. ART's impact, including its interruption, on brain proviral DNA remains unclear. The present studies show that in different experimental platforms, contemporary ART did not suppress viral burden in the brain, regardless of ART component regimen, the duration of therapy, and its interruption. Thus, new strategies for effective HIV-1 suppression in the brain are imperative to achieve sustained HIV suppression.

Modeling the Effects of Latency Reversing Drugs During HIV-1 and SIV Brain Infection with Implications for the "Shock and Kill" Strategy.

Combination antiretroviral therapy (cART) has greatly increased life expectancy for human immunodeficiency virus-1 (HIV-1)-infected patients. Even given the remarkable success of cART, the virus persists in many different cells and tissues. The presence of viral reservoirs represents a major obstacle to HIV-1 eradication. These viral reservoirs contain latently infected long-lived cells. The "Shock and Kill" therapeutic strategy aims to reactivate latently infected cells by latency reversing agents (LRAs) and kill these reactivated cells by strategies involving the host immune system. The brain is a natural anatomical reservoir for HIV-1 infection. Brain macrophages, including microglia and perivascular macrophages, display productive HIV-1 infection. A mathematical model was used to analyze the dynamics of latently and productively infected brain macrophages during viral infection and this mathematical model enabled prediction of the effects of LRAs applied to the "Shock and Kill" strategy in the brain. The model was calibrated using reported data from simian immunodeficiency virus (SIV) studies. Our model produces the overarching observation that effective cART can suppress productively infected brain macrophages but leaves a residual latent viral reservoir in brain macrophages. In addition, our model demonstrates that there exists a parameter regime wherein the "Shock and Kill" strategy can be safe and effective for SIV infection in the brain. The results indicate that the "Shock and Kill" strategy can restrict brain viral RNA burden associated with severe neuroinflammation and can lead to the eradication of the latent reservoir of brain macrophages.

Why is it difficult to accurately predict the COVID-19 epidemic?

Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have shown a wide range of variations. In our study, we demonstrate that nonidentifiability in model calibrations using the confirmed-case data is the main reason for such wide variations. Using the Akaike Information Criterion (AIC) for model selection, we show that an SIR model performs much better than an SEIR model in representing the information contained in the confirmed-case data. This indicates that predictions using more complex models may not be more reliable compared to using a simpler model. We present our model predictions for the COVID-19 epidemic in Wuhan after the lockdown and quarantine of the city on January 23, 2020. We also report our results of modeling the impacts of the strict quarantine measures undertaken in the city after February 7 on the time course of the epidemic, and modeling the potential of a second outbreak after the return-to-work in the city.

Bayesian inference for dynamical systems.

Bayesian inference is a common method for conducting parameter estimation for dynamical systems. Despite the prevalent use of Bayesian inference for performing parameter estimation for dynamical systems, there is a need for a formalized and detailed methodology. This paper presents a comprehensive methodology for dynamical system parameter estimation using Bayesian inference and it covers utilizing different distributions, Markov Chain Monte Carlo (MCMC) sampling, obtaining credible intervals for parameters, and prediction intervals for solutions. A logistic growth example is given to illustrate the methodology.

Modeling brain lentiviral infections during antiretroviral therapy in AIDS.

Understanding HIV-1 replication and latency in different reservoirs is an ongoing challenge in the care of patients with HIV/AIDS. A mathematical model was created to describe and predict the viral dynamics of HIV-1 and SIV infection within the brain during effective combination antiretroviral therapy (cART). The mathematical model was formulated based on the biology of lentiviral infection of brain macrophages and used to describe the dynamics of transmission and progression of lentiviral infection in brain. Based on previous reports quantifying total viral DNA levels in brain from HIV-1 and SIV infections, estimates of integrated proviral DNA burden were made, which were used to calibrate the mathematical model predicting viral accrual in brain macrophages from primary infection. The annual rate at which susceptible brain macrophages become HIV-1 infected was estimated to be 2.90×10-7-4.87×10-6 per year for cART-treated HIV/AIDS patients without comorbid neurological disorders. The transmission rate for SIV infection among untreated macaques was estimated to be 5.30×10-6-1.37×10-5 per year. An improvement in cART effectiveness (1.6-48%) would suppress HIV-1 infection in patients without neurological disorders. Among patients with advanced disease, a substantial improvement in cART effectiveness (70%) would eradicate HIV-1 provirus from the brain within 3-32 (interquartile range 3-9) years in patients without neurological disorders, whereas 4-51 (interquartile range 4-16) years of efficacious cART would be required for HIV/AIDS patients with comorbid neurological disorders. HIV-1 and SIV provirus burdens in the brain increase over time. A moderately efficacious antiretroviral therapy regimen could eradicate HIV-1 infection in the brain that was dependent on brain macrophage lifespan and the presence of neurological comorbidity.