ABSTRACT
In this work we demonstrate how to automate parts of the infectious disease-control policy-making process via performing inference in existing epidemiological models. The kind of inference tasks undertaken include computing the posterior distribution over controllable, via direct policy-making choices, simulation model parameters that give rise to acceptable disease progression outcomes. Among other things, we illustrate the use of a probabilistic programming language that automates inference in existing simulators. Neither the full capabilities of this tool for automating inference nor its utility for planning is widely disseminated at the current time. Timely gains in understanding about how such simulation-based models and inference automation tools applied in support of policy-making could lead to less economically damaging policy prescriptions, particularly during the current COVID-19 pandemic.
ABSTRACT
Introduction Coronavirus disease 2019 (COVID-19) is a devastating pandemic that may also affect the nervous system. One of its neurological manifestations is intracerebral hemorrhage (ICH). Data about pure spontaneous intraparenchymal hemorrhage related to COVID-19 is scarce. In this study, we present some patients with COVID-19 disease who also had spontaneous intraparenchymal hemorrhage along with a review of the literature. Methods This single-center prospective study was done among 2,862 patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) between March 1 and November 1, 2020. Out of 2,862 patients with SARS-CoV-2, 14 patients with neurological manifestations were assessed with a noncontrast brain computed tomography scan. Seven patients with spontaneous intraparenchymal hemorrhage were enrolled. Results All seven patients were male, with a mean age of 60.8 years old. Six patients (85.7%) only had minimal symptoms of COVID-19 without significant respiratory distress. The level of consciousness in two patients (28.5%) was less than eight, according to the Glasgow Coma Scale (GCS). Hypertension (71.4%) was the most common risk factor in their past medical history. The mean volume of hematoma was 41cc. Four patients died during hospitalization, and the others were discharged with a mean hospital stay of 42.6 days. All patients with GCS less than 11 died. Conclusion It concluded that ICH patients with COVID-19 are related to higher blood volume, cortical and subcortical location of hemorrhage, higher fatality rate, and younger age that is different to spontaneous ICH in general population. We recommend more specific neuroimaging in patients with COVID 19 such as brain magnetic resonance imaging concomitant with vascular studies in future. The impact of COVID-19 on mortality rate is not clear because of limited epidemiologic studies, but identifying the causal relationship between COVID-19 and ICH requires further clinical and laboratory studies.