Direct impact of COVID-19 vaccination in Chile: averted cases, hospitalizations, ICU admissions, and deaths.

BACKGROUND: Chile rapidly implemented an extensive COVID-19 vaccination campaign, deploying a diversity of vaccines with a strategy that prioritized the elderly and individuals with comorbidities. This study aims to assess the direct impact of vaccination on the number of COVID-19 related cases, hospital admissions, ICU admissions and deaths averted during the first year and a half of the campaign. METHODS: Via Chile's transparency law, we obtained access to weekly event counts categorized by vaccination status and age. Integrating this data with publicly available census and vaccination coverage information, we conducted a comparative analysis of weekly incidence rates between vaccinated and unvaccinated groups from December 20, 2020 to July 2, 2022 to estimate the direct impact of vaccination in terms of the number of cases, hospitalizations, ICU admissions and deaths averted, using an approach that avoids the need to explicitly specify the effectiveness of each vaccine deployed. RESULTS: We estimated that, from December 20, 2020 to July 2, 2022 the vaccination campaign directly prevented 1,030,648 (95% Confidence Interval: 1,016,975-1,044,321) cases, 268,784 (95% CI: 264,524-273,045) hospitalizations, 85,830 (95% CI: 83,466-88,194) ICU admissions and 75,968 (95% CI: 73,909-78,028) deaths related to COVID-19 among individuals aged 16 years and older. This corresponds to a reduction of 26% of cases, 66% of hospital admissions, 70% of ICU admissions and 67% of deaths compared to a scenario without vaccination. Individuals 55 years old or older represented 67% of hospitalizations, 73% of ICU admissions and 89% of deaths related to COVID-19 prevented. CONCLUSIONS: This study highlights the role of Chile's vaccination campaign in reducing COVID-19 disease burden, with the most substantial reductions observed in severe outcomes.

COVID-19: A Comparative Study of Contagions Peaks in Cities from Europe and the Americas.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by a group of viruses that provoke illnesses ranging from the common cold to more serious illnesses such as pneumonia. COVID-19 started in China and spread rapidly from a single city to an entire country in just 30 days and to the rest of the world in no more than 3 months. Several studies have tried to model the behavior of COVID-19 in diverse regions, based on differential equations of the SIR and stochastic SIR type, and their extensions. In this article, a statistical analysis of daily confirmed COVID-19 cases reported in eleven different cities in Europe and America is conducted. Log-linear models are proposed to model the rise or drop in the number of positive cases reported daily. A classification analysis of the estimated slopes is performed, allowing a comparison of the eleven cities at different epidemic peaks. By rescaling the curves, similar behaviors among rises and drops in different cities are found, independent of socioeconomic conditions, type of quarantine measures taken, whether more or less restrictive. The log-linear model appears to be suitable for modeling the incidence of COVID-19 both in rises and drops.

Modelling of auxin transport affected by gravity and differential radial growth.

When a tree stem deviates from verticality, as a result of different environmental factors, patterns of differential radial growth appear. Higher rates of wood production have been observed on the lower side of the tree and lower rates in the opposite side. Biological studies on plant hormones have shown that the concentration of auxin induces radial growth. They also have demonstrated the redistribution of auxin transport in response to gravity. Auxin is then designated as a mediator for differential growth. This paper presents a model for three-dimensional (3-D) auxin transport in conifer trees, which includes gravity dependence. We obtain realistic heterogeneous patterns of auxin distribution over the tree. Then, we propose a law of growth based on auxin concentration to simulate successive differential radial growths. The predicted growths are compared with experimental results of reconstruction of 3-D annual growth of Radiata pine.

Morphogenetic processes: application to cambial growth dynamics.

Both the physiological and the pathological morphogenetic processes that we can meet in embryogenesis, neogenesis and degenerative dysgenesis present common features: they are ruled by three different kinds of mechanisms, one related to cell migration, the second to cell differentiation and the third to cell proliferation. We deal here with an application to the cambial growth which essentially involves the third type of mechanism. Woody plants produce secondary tissue (secondary xylem and phloem) from a meristematic tissue called vascular cambium, responsible for the radial growth of a tree. This paper focuses on the formation of secondary xylem, considered in two dimensions in a cross-section framework. A new discrete modelling approach is used, based on the cellular scale, in order to attain a more accurate understanding of how the elementary microscopic behaviour of each cell takes part in the macroscopic morphogenesis. The mathematical model essentially uses an occurrence method simulating the main features of radial growth with simple geometric rules, such as Thom's division rule (Thom,1972)to account for the cell proliferation. The study applies to concrete instances in which the changes made in the geometrical cellular patterns of the vascular cambium clearly affect the shape of the tree, as in Pinus radiata (D. Don.).