The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control: the value and limitations of early models.

Mathematical models of epidemics are important tools for predicting epidemic dynamics and evaluating interventions. Yet, because early models are built on limited information, it is unclear how long they will accurately capture epidemic dynamics. Using a stochastic SEIR model of COVID-19 fitted to reported deaths, we estimated transmission parameters at different time points during the first wave of the epidemic (March-June, 2020) in Santa Clara County, California. Although our estimated basic reproduction number ([Formula: see text]) remained stable from early April to late June (with an overall median of 3.76), our estimated effective reproduction number ([Formula: see text]) varied from 0.18 to 1.02 in April before stabilizing at 0.64 on 27 May. Between 22 April and 27 May, our model accurately predicted dynamics through June; however, the model did not predict rising summer cases after shelter-in-place orders were relaxed in June, which, in early July, was reflected in cases but not yet in deaths. While models are critical for informing intervention policy early in an epidemic, their performance will be limited as epidemic dynamics evolve. This paper is one of the first to evaluate the accuracy of an early epidemiological compartment model over time to understand the value and limitations of models during unfolding epidemics.

HVEM signaling promotes protective antibody-dependent cellular cytotoxicity (ADCC) vaccine responses to herpes simplex viruses.

Herpes simplex virus (HSV) glycoprotein D (gD) not only is required for virus entry and cell-to-cell spread but also binds the host immunomodulatory molecule, HVEM, blocking interactions with its ligands. Natural infection primarily elicits neutralizing antibodies targeting gD, but subunit protein vaccines designed to induce this response have failed clinically. In contrast, preclinical studies demonstrate that an HSV-2 single-cycle strain deleted in gD, ΔgD-2, induces primarily non-neutralizing antibodies that activate Fcγ receptors (FcγRs) to mediate antibody-dependent cellular cytotoxicity (ADCC). These studies were designed to test the hypothesis that gD interferes with ADCC through engagement of HVEM. Immunization of Hvem-/- mice with ΔgD-2 resulted in significant reduction in HSV-specific IgG2 antibodies, the subclass associated with FcγR activation and ADCC, compared with wild-type controls. This translated into a parallel reduction in active and passive vaccine protection. A similar decrease in ADCC titers was observed in Hvem-/- mice vaccinated with an alternative HSV vaccine candidate (dl5-29) or an unrelated vesicular stomatitis virus-vectored vaccine. Unexpectedly, not only did passive transfer of immune serum from ΔgD-2-vaccinated Hvem-/- mice fail to protect wild-type mice but transfer of immune serum from ΔgD-2-vaccinated wild-type mice failed to protect Hvem-/- mice. Immune cells isolated from Hvem-/- mice were impaired in FcγR activation, and, conversely, addition of gD protein or anti-HVEM antibodies to in vitro murine or human FcγR activation assays inhibited the response. These findings uncover a previously unrecognized role for HVEM signaling in generating and mediating ADCC and an additional HSV immune evasion strategy.

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control.

Non-pharmaceutical interventions to combat COVID-19 transmission have worked to slow the spread of the epidemic but can have high socio-economic costs. It is critical we understand the efficacy of non-pharmaceutical interventions to choose a safe exit strategy. Many current models are not suitable for assessing exit strategies because they do not account for epidemic resurgence when social distancing ends prematurely (e.g., statistical curve fits) nor permit scenario exploration in specific locations. We developed an SEIR-type mechanistic epidemiological model of COVID-19 dynamics to explore temporally variable non-pharmaceutical interventions. We provide an interactive tool and code to estimate the transmission parameter, ß, and the effective reproduction number, R eff . We fit the model to Santa Clara County, California, where an early epidemic start date and early shelter-in-place orders could provide a model for other regions. As of April 22, 2020, we estimate an R eff of 0.982 (95% CI: 0.849 - 1.107) in Santa Clara County. After June 1 (the end-date for Santa Clara County shelter-in-place as of April 27), we estimate a shift to partial social distancing, combined with rigorous testing and isolation of symptomatic individuals, is a viable alternative to indefinitely maintaining shelter-in-place. We also estimate that if Santa Clara County had waited one week longer before issuing shelter-in-place orders, 95 additional people would have died by April 22 (95% CI: 7 - 283). Given early life-saving shelter-in-place orders in Santa Clara County, longer-term moderate social distancing and testing and isolation of symptomatic individuals have the potential to contain the size and toll of the COVID-19 pandemic in Santa Clara County, and may be effective in other locations.