Modelling COVID-19 mutant dynamics: understanding the interplay between viral evolution and disease transmission dynamics.

Understanding virus mutations is critical for shaping public health interventions. These mutations lead to complex multi-strain dynamics often under-represented in models. Aiming to understand the factors influencing variants' fitness and evolution, we explore several scenarios of virus spreading to gain qualitative insight into the factors dictating which variants ultimately predominate at the population level.

Modeling spillover dynamics: understanding emerging pathogens of public health concern.

The emergence of infectious diseases with pandemic potential is a major public health threat worldwide. The World Health Organization reports that about 60% of emerging infectious diseases are zoonoses, originating from spillover events. Although the mechanisms behind spillover events remain unclear, mathematical modeling offers a way to understand the intricate interactions among pathogens, wildlife, humans, and their shared environment.

Beyond Conventional Carbon Activation: Creating Porosity without Etching Using Cesium Effect.

Facile synthesis of porous carbon with high yield and high specific surface area (SSA) from low-cost molecular precursors offers promising opportunities for their industrial applications. However, conventional activation methods using potassium and sodium hydroxides or carbonates suffer from low yields (<20%) and poor control over porosity and composition especially when high SSAs are targeted (>2000 m g) because nanopores are typically created by etching. Herein, a non-etching activation strategy is demonstrated using cesium salts of low-cost carboxylic acids as the sole precursor in producing porous carbons with yields of up to 25% and SSAs reaching 3008 m g.

Optimal vaccination strategies for a heterogeneous population using multiple objectives: The case of L- and L-formulations.

The choice of the objective functional in optimization problems coming from biomedical and epidemiological applications plays a key role in optimal control outcomes. In this study, we investigate the role of the objective functional on the structure of the optimal control solution for an epidemic model for sexually transmitted infections that includes a core group with higher sexual activity levels than the rest of the population. An optimal control problem is formulated to find a targeted vaccination program able to control the spread of the infection with minimum vaccine deployment.

Data-driven estimation of the instantaneous reproduction number and growth rates for the 2022 monkeypox outbreak in Europe.

Objective: To estimate the instantaneous reproduction number Rt and the epidemic growth rates for the 2022 monkeypox outbreaks in the European region.

Methods: We gathered daily laboratory-confirmed monkeypox cases in the most affected European countries from the beginning of the outbreak to September 23, 2022. A data-driven estimation of the instantaneous reproduction number is obtained using a novel filtering type Bayesian inference.

Optimal vaccine allocation for the control of sexually transmitted infections.

The burden of sexually transmitted infections (STIs) poses a challenge due to its large negative impact on sexual and reproductive health worldwide. Besides simple prevention measures and available treatment efforts, prophylactic vaccination is a powerful tool for controlling some viral STIs and their associated diseases. Here, we investigate how prophylactic vaccines are best distributed to prevent and control STIs.

The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modelling approach.

November 2020 received a string of encouraging results from leading vaccine developers raising hopes for the imminent availability of an effective and safe vaccine against the SARS-CoV-2. In the present work, we discuss the theoretical impact of introducing a vaccine across a range of scenarios. In particular, we investigate how vaccination coverage, efficacy and delivery time affect the control of the transmission dynamics in comparison to mobility restrictions.

Modeling the transmission dynamics and the impact of the control interventions for the COVID-19 epidemic outbreak.

In this paper we develop a compartmental epidemic model to study the transmission dynamics of the COVID-19 epidemic outbreak, with Mexico as a practical example. In particular, we evaluate the theoretical impact of plausible control interventions such as home quarantine, social distancing, cautious behavior and other self-imposed measures. We also investigate the impact of environmental cleaning and disinfection, and government-imposed isolation of infected individuals.

Modeling Public Health Campaigns for Sexually Transmitted Infections via Optimal and Feedback Control.

Control of sexually transmitted infections (STIs) poses important challenges to public health authorities. Obstacles for STIs' control include low priority in public health programs and disease transmission mechanisms. This work uses a compartmental pair model to explore different public health strategies on the evolution of STIs.

The role of behavioral changes and prompt treatment in the control of STIs.

In this paper, we study general recovery functions and treatment in the dynamics of an model for sexually transmitted infections with nonzero partnership length. It is shown how partnership dynamics influences the predicted prevalence at the steady state and the basic reproduction number. Sobol's indices are used to evaluate the contribution of model parameters to the overall variance of .

Control Strategies in Multigroup Models: The Case of the Star Network Topology.

In this paper, we propose control strategies for multigroup epidemic models. We use compartmental [Formula: see text] models to study the dynamics of n host groups sharing the same source of infection in addition to the transmission among members of the same group. In particular, we consider a model for infectious diseases with free-living pathogens in the environment and a metapopulation model with a central patch.