RESUMEN
Neurodegenerative diseases (ND) pose significant challenges for biomedicine in the twenty-first century, particularly considering the global demographic ageing and the subsequent increase in their prevalence. Characterized as progressive, chronic and debilitating, they often result in higher mortality rates compared with the general population. Research agendas and biomedical technologies are shaped by power relations, ultimately affecting patient wellbeing and care. Drawing on the concepts of bio- and necropolitics, introduced by philosophers Foucault and Mbembe, respectively, this perspective examines the interplay between the territoriality and governmentality around demographic ageing, ND and death, focussing on knowledge production as a dispositif of power by highlighting the marginal role that the phenomenon of mortality plays in the ND research landscape. We propose a shift into acknowledging the coloniality of knowledge and embracing its situatedness to attain knowledge 'from death', understood as an epistemic position from which novel approaches and practices could emerge.
Asunto(s)
Enfermedades Neurodegenerativas , Humanos , Enfermedades Neurodegenerativas/mortalidadRESUMEN
TITLE: La evolución del síndrome de Guillain-Barré asociado al SARS-CoV-2 depende del tratamiento temprano y de la vacunación.
Asunto(s)
COVID-19 , Síndrome de Guillain-Barré , Síndrome de Guillain-Barré/etiología , Humanos , SARS-CoV-2 , VacunaciónRESUMEN
We introduce a compartmental model SEIAHRV (Susceptible, Exposed, Infected, Asymptomatic, Hospitalized, Recovered, Vaccinated) with age structure for the spread of the SARAS-CoV virus. In order to model current different vaccines we use compartments for individuals vaccinated with one and two doses without vaccine failure and a compartment for vaccinated individual with vaccine failure. The model allows to consider any number of different vaccines with different efficacies and delays between doses. Contacts among age groups are modeled by a contact matrix and the contagion matrix is obtained from a probability of contagion p c per contact. The model uses known epidemiological parameters and the time dependent probability p c is obtained by fitting the model output to the series of deaths in each locality, and reflects non-pharmaceutical interventions. As a benchmark the output of the model is compared to two good quality serological surveys, and applied to study the evolution of the COVID-19 pandemic in the main Brazilian cities with a total population of more than one million. We also discuss with some detail the case of the city of Manaus which raised special attention due to a previous report of We also estimate the attack rate, the total proportion of cases (symptomatic and asymptomatic) with respect to the total population, for all Brazilian states since the beginning of the COVID-19 pandemic. We argue that the model present here is relevant to assessing present policies not only in Brazil but also in any place where good serological surveys are not available.
