The role of malignant tissue on the thermal distribution of cancerous breast.

The present work focuses on the integration of analytical and numerical strategies to investigate the thermal distribution of cancerous breasts. Coupled stationary bioheat transfer equations are considered for the glandular and heterogeneous tumor regions, which are characterized by different thermophysical properties. The cross-section of the cancerous breast is identified by a homogeneous glandular tissue that surrounds the heterogeneous tumor tissue, which is assumed to be a two-phase periodic composite with non-overlapping circular inclusions and a square lattice distribution, wherein the constituents exhibit isotropic thermal conductivity behavior. Asymptotic periodic homogenization method is used to find the effective properties in the heterogeneous region. The tissue effective thermal conductivities are computed analytically and then used in the homogenized model, which is solved numerically. Results are compared with appropriate experimental data reported in the literature. In particular, the tissue scale temperature profile agrees with experimental observations. Moreover, as a novelty result we find that the tumor volume fraction in the heterogeneous zone influences the breast surface temperature.

Correction to "Cuban Abdala vaccine: Effectiveness in preventing severe disease and death from COVID-19 in Havana, Cuba; A cohort study" [The Lancet Regional Health - Americas 2022; 16: 100366] https://doi.org/10.1016/j.lana.2022.100366.

[This corrects the article DOI: 10.1016/j.lana.2022.100366.].

Cuban Abdala vaccine: Effectiveness in preventing severe disease and death from COVID-19 in Havana, Cuba; A cohort study.

Background: COVID-19 vaccines have proven safe and efficacious in reducing severe illness and death. Cuban protein subunit vaccine Abdala has shown safety, tolerability and efficacy (92·3% [95% CI: 85·7‒95·8]) against SARS-CoV-2 in clinical trials. This study aimed to estimate Abdala's real-world vaccine effectiveness (VE). Methods: This retrospective cohort study in Havana analyzed Cuban Ministry of Public Health databases (May 12-August 31, 2021) to assess VE in preventing severe illness and death from COVID-19 (primary outcomes). Cox models accounting for time-varying vaccination status and adjusting by demographics were used to estimate hazard ratios. A subgroup analysis by age group and a sensitivity analysis including a subgroup of tested persons (qRT-PCR) were conducted. Daily cases and deaths were modelled accounting for different VE. Findings: The study included 1 355 638 persons (Mean age: 49·5 years [SD: 18·2]; 704 932 female [52·0%]; ethnicity data unavailable): 1 324 vaccinated (partially/fully) and 31 433 unvaccinated. Estimated VE against severe illness was 93·3% (95% CI: 92·1-94·3) in partially- vaccinated and 98·2% (95% CI: 97·9-98·5) in fully-vaccinated and against death was 94·1% (95% CI: 92·5-95·4) in partially-vaccinated and 98·7% (95% CI: 98·3-99·0) in fully-vaccinated. VE exceeded 92·0% in all age groups. Daily cases and deaths during the study period corresponded to a VE above 90%, as predicted by models. Interpretation: The Cuban Abdala protein subunit vaccine was highly effective in preventing severe illness and death from COVID-19 under real-life conditions. Funding: Cuban Ministry of Public Health. Genetic Engineering and Biotechnology Centre.

Asymptotic Homogenization Applied to Flexoelectric Rods.

In this manuscript, the equilibrium problem for a flexoelectric one-dimensional composite material is studied. The two-scales asymptotic homogenization method is used to derive the homogenized formulation of this problem. The manuscript offers a step-by-step methodology to derive effective coefficients and to solve local problems. As an illustrative example, results reported in the literature for piezoelectric composites are obtained as a particular case of the formulation derived here. Finally, three flexoelectric/piezoelectric composites are studied to illustrate the influence of the flexoelectric property on the effective coefficients and the global behavior of the structure.

El modelo SIR básico y políticas antiepidémicas de salud pública para la COVID-19 en Cuba / The Basic SIR Model and Antiepidemic Policies in Public Health against COVID-19 in Cuba

El modelo básico SIR (Susceptibles-Infectados-Recuperados) de Kermack y McKendrick, es un modelo de compartimentos donde la población bajo estudio se divide en clases epidemiológicas y se describe un flujo entre ellas. Un sistema sanitario robusto que proporcione al modelo datos confiables y aunados a políticas públicas de salud coherentes, contribuye a controlar los impactos de contingencias epidémicas. De ahí que el objetivo del presente estudio sea aplicar el modelo SIR, sin profundizar en el aparato matemático que lo acompaña, para conocer el impacto de la COVID-19 en Cuba, con énfasis en La Habana, como centro de la epidemia en el país en el período del 11 de marzo al 16 de julio de 2020. Para ello se muestra el modelo con coeficientes variables en el tiempo y su utilidad como modelo dinámico para hacer proyecciones en situaciones epidémicas; se aplica a regiones locales específicas y se manifiestan sus potencialidades para analizar rebrotes por la aparición de eventos locales que se alejan de las predicciones previstas. Este trabajo es parte de los esfuerzos que, en todos los órdenes, ha desarrollado el Ministerio de Salud Pública de Cuba para enfrentar la pandemia de la COVID-19(AU)

The basic SIR (Susceptible-Infected-Recovered) model of Kermack-McKendrick is a compartmental model in which the population under study is divided into epidemiological classes, in between which a flow is described. A robust health system that provides reliable data to the model and combined with coherent public health policies contributes to controlling the impacts of epidemic contingencies. Hence, the objective of this study is to apply the SIR model, without delving into the mathematical apparatus that accompanies it, to know the impact of COVID-19 in Cuba, with an emphasis on Havana, as the center of the epidemic in the country in the period from March 11 to July 16, 2020. To do this, the model is shown with variable coefficients over time, together with its usefulness as a dynamic model to make projections in epidemic situations. It is applied to specific local regions and its potentialities to analyze outbreaks are manifested by the onset of local events that are far from the foreseen predictions. This work is part of the efforts that, in all orders, the Cuban Ministry of Public Health has developed to confront the COVID-19 pandemic(AU)

La ocurrencia de rebrotes de la COVID-19 y su relación con el número reproductivo

RESUMEN El peligro de la ocurrencia de endemia por la COVID-19 es una preocupación del gobierno y epidemiólogos cubanos, pero conocer alguna métrica que influya en su surgimiento es de gran utilidad para evitarla. El objetivo de este trabajo es demostrar mediante modelos dinámicos y teoría cualitaiva de ecuaciones diferenciales, cómo el número reproductivo básico Ro constituye una métrica que incide en la ocurrencia de estos eventos. Se empleó un modelo de tipo SIR con demografía adaptado a las condiciones de Cuba. Los resultados demostraron que se consigue dar respuesta, desde el punto de vista matemático, a las condiciones que pueden causar un rebrote de la enfermedad. Recomendamos mantener activadas las medidas epidemiológicas que se relacionan en este trabajo y que ayudan a mantener controlados los casos confirmados que aparezcan y evitar de esta manera posibles rebrotes.

ABSTRACT The danger of the occurrence of endemic COVID-19 worries the Cuban government as well as epidemiologists. Knowledge about a metric that influences its emergence is a very useful tool to prevent it. The purpose of the study was to prove through dynamic models and the qualitative theory of differential equations that the basic reproduction number R0 is a metric influencing the occurrence of these events. A SIR model was used, which was adjusted to Cuban conditions. Results showed that a mathematical response may be provided to conditions potentially causing a fresh outbreak of the disease. We recommend to maintain activated the epidemiological measures referred to in the paper, which help keep under control the confirmed cases occurring, thus preventing possible fresh outbreaks.