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1.
Front Public Health ; 10: 1050673, 2022.
Article in English | MEDLINE | ID: mdl-36711379

ABSTRACT

Background: After the initial outbreak in China (December 2019), the World Health Organization declared COVID-19 a pandemic on March 11th, 2020. This paper aims to describe the first 2 years of the pandemic in Mexico. Design and methods: This is a population-based longitudinal study. We analyzed data from the national COVID-19 registry to describe the evolution of the pandemic in terms of the number of confirmed cases, hospitalizations, deaths and reported symptoms in relation to health policies and circulating variants. We also carried out logistic regression to investigate the major risk factors for disease severity. Results: From March 2020 to March 2022, the coronavirus disease 2019 (COVID-19) pandemic in Mexico underwent four epidemic waves. Out of 5,702,143 confirmed cases, 680,063 were hospitalized (11.9%), and 324,436 (5.7%) died. Even if there was no difference in susceptibility by gender, males had a higher risk of death (CFP: 7.3 vs. 4.2%) and hospital admission risk (HP: 14.4 vs. 9.5%). Severity increased with age. With respect to younger ages (0-17 years), the 60+ years or older group reached adjusted odds ratios of 9.63 in the case of admission and 53.05 (95% CI: 27.94-118.62) in the case of death. The presence of any comorbidity more than doubled the odds ratio, with hypertension-diabetes as the riskiest combination. While the wave peaks increased over time, the odds ratios for developing severe disease (waves 2, 3, and 4 to wave 1) decreased to 0.15 (95% CI: 0.12-0.18) in the fourth wave. Conclusion: The health policy promoted by the Mexican government decreased hospitalizations and deaths, particularly among older adults with the highest risk of admission and death. Comorbidities augment the risk of developing severe illness, which is shown to rise by double in the Mexican population, particularly for those reported with hypertension-diabetes. Factors such as the decrease in the severity of the SARS-CoV2 variants, changes in symptomatology, and advances in the management of patients, vaccination, and treatments influenced the decrease in mortality and hospitalizations.


Subject(s)
COVID-19 , Diabetes Mellitus , Hypertension , Male , Humans , Aged , Infant, Newborn , Infant , Child, Preschool , Child , Adolescent , COVID-19/epidemiology , SARS-CoV-2 , Pandemics , Longitudinal Studies , Mexico/epidemiology , Follow-Up Studies , RNA, Viral , Diabetes Mellitus/epidemiology , Hypertension/epidemiology
2.
Biosystems ; 98(1): 19-30, 2009 Oct.
Article in English | MEDLINE | ID: mdl-19596047

ABSTRACT

The universe of cellular forms has received scarce attention by mainstream neo-Darwinian views. The possibility that a fundamental trait of biological order may consist upon, or be guided by, developmental processes not completely amenable to natural selection was more akin to previous epochs of biological thought, i.e. the "bauplan" discussion. Thirty years ago, however, Lynn and Tucker studied the biological mechanisms responsible for defining organelles position inside cells. The fact that differentiated structures performing a specific function within the eukaryotic cell (i.e. mitochondrion, vacuole, or chloroplast) were occupying specific positions in the protoplasm was the observational and experimental support of the 'morphogenetic field' notion at the cellular level. In the present paper we study the morphogenetic field evolution yielding from an initial population of undifferentiated cells to diversified unicellular organisms as well as specialized eukaryotic cell types. The cells are represented as Julia sets and Pickover biomorphs, simulating the effect of Darwinian natural selection with a simple genetic algorithm. The morphogenetic field "defines" the locations where cells are differentiated or sub-cellular components (or organelles) become organized. It may be realized by different possibilities, one of them by diffusing chemicals along the Turing model. We found that Pickover cells show a higher diversity of size and form than those populations evolved as Julia sets. Another novelty is the way that cellular organelles and cell nucleus fill in the cell, always in dependence on the previous cell definition as Julia set or Pickover biomorph. Our findings support the existence of specific attractors representing the functional and stable form of a differentiated cell-genuine cellular bauplans. The configuration of the morphogenetic field is "attracted" towards one or another attractor depending on the environmental influences as modeled by a particular fitness function. The model promotes the classical discussions of D'Arcy Thompson and the more recent views of Waddington, Goodwin and others that consider organisms as dynamical systems that evolve through a 'master plan' of transformations, amenable to natural selection. Intriguingly, the model also connects with current developments on mechanobiology, highlighting the informational-developmental role that cytoskeletons may play.


Subject(s)
Biological Evolution , Cell Physiological Phenomena , Mechanotransduction, Cellular/physiology , Models, Biological , Morphogenesis/physiology , Subcellular Fractions/physiology , Computer Simulation
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