2 research outputs found
Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update
Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread
outside of China, Europe has experienced large epidemics. In response, many
European countries have implemented unprecedented non-pharmaceutical
interventions including case isolation, the closure of schools and
universities, banning of mass gatherings and/or public events, and most
recently, wide-scale social distancing including local and national lockdowns.
In this technical update, we extend a semi-mechanistic Bayesian hierarchical
model that infers the impact of these interventions and estimates the number of
infections over time. Our methods assume that changes in the reproductive
number - a measure of transmission - are an immediate response to these
interventions being implemented rather than broader gradual changes in
behaviour. Our model estimates these changes by calculating backwards from
temporal data on observed to estimate the number of infections and rate of
transmission that occurred several weeks prior, allowing for a probabilistic
time lag between infection and death.
In this update we extend our original model [Flaxman, Mishra, Gandy et al
2020, Report #13, Imperial College London] to include (a) population saturation
effects, (b) prior uncertainty on the infection fatality ratio, (c) a more
balanced prior on intervention effects and (d) partial pooling of the lockdown
intervention covariate. We also (e) included another 3 countries (Greece, the
Netherlands and Portugal).
The model code is available at
https://github.com/ImperialCollegeLondon/covid19model/
We are now reporting the results of our updated model online at
https://mrc-ide.github.io/covid19estimates/
We estimated parameters jointly for all M=14 countries in a single
hierarchical model. Inference is performed in the probabilistic programming
language Stan using an adaptive Hamiltonian Monte Carlo (HMC) sampler
Carcinomatous encephalitis as clinical presentation of occult lung adenocarcinoma: case report Encefalite carcinomatosa como apresentação inicial de adenocarcinoma de pulmão oculto: relato de caso
Carcinomatous encephalitis is a rare entity, originally described by Madow and Alpers in 1951, which is characterized by tumoral spreading perivascular, without mass effect. Clinical manifestations such as hemiparesis, seizures, ataxia, speech difficulties, cerebrospinal fluid findings as well as computed tomography are nonspecific. This leads the physician to pursue more frequent diseases that could explain those manifestations - toxic, metabolic, and/or infectious encephalopathy. A magnetic resonance imaging (MRI) with gadolinium, the method of choice, presumes the diagnosis. Previous reports of this unusual form of metastatic disease have described patients with prior diagnosis of pulmonary adenocarcinoma. We present the case of carcinomatous encephalitis in a 76-years-old woman as the primary manifestation of occult pulmonary adenocarcinoma with its clinical, imaging, and anatomopathological findings.<br>A "encefalite" carcinomatosa é entidade rara, descrita originalmente por Madow e Alpers em 1951 e caracterizada pela disseminação tumoral perivascular, sem causar efeito de massa. As manifestações clínicas como hemiparesia, convulsões, ataxia, alterações de fala, os achados do líquido cefalorraquidiano e da tomografia computadorizada de crânio são inespecíficos, o que faz buscar outras causas mais freqüentes que justifiquem o quadro -encefalopatia tóxica, metabólica e/ou infecciosa. A ressonância magnética com gadolínio é o exame de eleição, frente à suspeita clínica. Todos os casos de "encefalite" carcinomatosa foram relatados em pacientes com diagnóstico prévio de adenocarcinoma de pulmão. Nesse sentido. Apresentamos caso de encefalite carcinomatosa, em mulher de 76 anos como manifestação primária de adenocarcinoma de pulmão oculto, com seus aspectos clínicos, de imagem e anatomopatológicos