Vaccination as an Alternative to Non-Drug Interventions to Prevent Local Resurgence of COVID-19

Background While a COVID-19 vaccine protects people from serious illness and death, it remains concern when and how to relax from the high cost strict non-pharmaceutical interventions (NPIs). Methods We developed a stochastic calculus model to identify the level of vaccine coverage that would allow safe relaxation of NPIs, and the vaccination strategies that can best achieve this level of coverage. We applied Monto Carlo simulations more than 10,000 times to remove random fluctuation effects and obtain fitted/predicted epidemic curve based on various parameters with 95% confidence interval (95% CI) at each time point. Results We found that a vaccination coverage of 50.42% was needed for the safe relaxation of NPIs, if the vaccine effectiveness was 79.34%. However, with the increasing of variants transmissibility and the decline of vaccine effectiveness for variants, the threshold for lifting NPIs would be higher. We estimated that more than 8 months were needed to achieve the vaccine coverage threshold in the combination of accelerated vaccination strategy and key groups firstly strategy. Conclusion If there are sufficient doses of vaccine then an accelerated vaccination strategy should be used, and if vaccine supply is insufficient then high-risk groups should be targeted for vaccination first. Sensitivity analyses results shown that the higher the transmission rate of the virus and the lower annual vaccine supply, the more difficult the epidemic could be under control. In conclusion, as vaccine coverage improves, the NPIs can be gradually relaxed. Until that threshold is reached, however, strict NPIs are still needed to contain the epidemic. The more transmissible SARS-CoV-2 variant lead to higher resurgence probability, which indicates the importance of accelerated vaccination and achieving the vaccine coverage earlier. Trial registration We did not involve clinical trial.

Polymer-Assisted Condensation: A Mechanism for Hetero-Chromatin Formation and Epigenetic Memory

We consider the formation of droplets from a 2-component liquid mixture induced by a large polymer chain that has preferential solubility with one of the components. We assume that the liquid mixture is in a fully miscible state, but far above the critical interaction limit of the two species. We show that the polymer coil acts as a chemical potential trap, which can shift the mixture inside the polymer volume into the partially miscible state and thus triggers the formation of a polymer-bound droplet of the preferred solvent phase which we denote as polymer-assisted condensation (PAC). We propose a simple mean-field model which can predict the essential feature of PAC and perform molecular-dynamics simulations to show that the predicted phase behavior is robust against fluctuation effects. Our model aims to understand the formation of macromolecular condensates inside the cell nucleus, such as those formed by heterochromatin 1 (HP1). We propose that such droplets organize the spatial structure of chromatin into hetero- and euchromatin and ensure the propagation of epigenetic information through the cell generations.

Field-Theoretic Simulations for Block Copolymer Melts Using the Partial Saddle-Point Approximation

Field-theoretic simulations (FTS) provide an efficient technique for investigating fluctuation effects in block copolymer melts with numerous advantages over traditional particle-based simulations. For systems involving two components (i.e., A and B), the field-based Hamiltonian, Hf[W−,W+], depends on a composition field, W−(r), that controls the segregation of the unlike components and a pressure field, W+(r), that enforces incompressibility. This review introduces researchers to a promising variant of FTS, in which W−(r) fluctuates while W+(r) tracks its mean-field value. The method is described in detail for melts of AB diblock copolymer, covering its theoretical foundation through to its numerical implementation. We then illustrate its application for neat AB diblock copolymer melts, as well as ternary blends of AB diblock copolymer with its A- and B-type parent homopolymers. The review concludes by discussing the future outlook. To help researchers adopt the method, open-source code is provided that can be run on either central processing units (CPUs) or graphics processing units (GPUs).

Deterministic Sudden Changes and Stochastic Fluctuation Effects on Stability and Persistence Dynamics of Two-Predator One-Prey Model

In this paper, we present new results on deterministic sudden changes and stochastic fluctuations’ effects on the dynamics of a two-predator one-prey model. We purpose to study the dynamics of the model with some impacting factors as the problem statement. The methodology depends on investigating the seasonality and stochastic terms which make the predator-prey interactions more realistic. A theoretical analysis is introduced for studying the effects of sudden deterministic changes, using three different cases of sudden changes. We show that the system in a good situation presents persistence dynamics only as a stable dynamical behavior. However, the system in a bad situation leads to three main outcomes as follows: first, constancy at the initial conditions of the prey and predators; second, extinction of the whole system; third, extinction of both predators, resulting in the growth of the prey population until it reaches a peak carrying capacity. We perform numerical simulations to study effects of stochastic fluctuations, which show that noise strength leads to an increase in the oscillations in the dynamical behavior and became more complex and finally leads to extinction when the strength of the noise is high. The random noises transfer the dynamical behavior from the equilibrium case to the oscillation case, which describes some unstable environments.