PubMed COVID-19 Clinical Care

No abstract

To achieve a sustainable future, it is imperative to transform human actions collectively and underlying social structures. Decades of research in social sciences have offered complementary insights into how such transformations might occur. However

Puerto Rico has experienced the full impact of the COVID-19 pandemic. Since SARS-CoV-2, the virus that causes COVID-19, was first detected on the island in March of 2020, it spread rapidly though the island’s population and became a critical threat

Since the beginning of the COVID-19 pandemic in early 2020, global efforts to respond to and control COVID-19 have varied widely with some countries, including Australia, successfully containing local transmission, and minimising negative impacts to

The wide use of IT resources to assess and manage the recent COVID-19 pandemic allows to increase the effectiveness of the countermeasures and the pervasiveness of monitoring and prevention. Unfortunately, the literature reports that IoT devices, a

The COVID-19 pandemic amplified and intensified dramatic changes already emerging within the nursing workforce. This article examines and extrapolates from current trends to enable nurse leaders to prepare for the future nursing workforce and

In the current scenario, most countries are affected by COVID-19, a pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has a massive impact on human health. Previous studies showed that some traditionally used

COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares observed with expected deaths based on the assumption that the

As a result of the SARS-CoV-2 pandemic numerous scientific groups have generated antibodies against a single target: the CoV-2 spike antigen. This has provided an unprecedented opportunity to compare the efficacy of different methods and the

On the occasion of the Spatial Statistics' 10th Anniversary, I reflect on the past and present of Bayesian disease mapping and look into its future. I focus on some key developments of models, and on recent evolution of multivariate and adaptive