Articles: pandemics.
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Int J Environ Res Public Health · May 2020
Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve.
The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility of healthcare and public health preparedness and planning against epidemics/pandemics. In addition to the medical practice for treatment and immunization, it is vital to have a thorough understanding of community spread phenomena as related research reports 17.9-30.8% confirmed cases to remain asymptomatic. ⋯ To this end, a self-organizing feature map (SOFM) is trained by using data acquired from past mobile crowdsensing (MCS) campaigns to model mobility patterns of individuals in multiple districts of a city so to maximize the assessed population with minimum agents in the shortest possible time. Through simulation results for a real street map on a mobile crowdsensing simulator and considering the worst case analysis, it is shown that on the 15th day following the first confirmed case in the city under the risk of community spread, AI-enabled mobilization of assessment centers can reduce the unassessed population size down to one fourth of the unassessed population under the case when assessment agents are randomly deployed over the entire city.
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Sam Foster, Chief Nurse, Oxford University Hospitals, considers the range of issues that needs to be considered to enable retired nurses and those redeployed from other areas to care for patients with COVID-19.
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This is an opinion piece on the role of POCUS in COVID-19, with a focus on lung ultrasound. It is not an instructional essay. Crisis management in medicine has often been likened to crisis management in the aviation industry. ⋯ The COVID-19 pandemic has changed this, clinicians are now faced with the need to make urgent decisions whilst exposed to some personal risk. Whether to embrace POCUS and lung ultrasound during this pandemic is an important decision. Whilst there are clear advantages, poorly considered overzealous uptake it is not without hazard, opportunity cost and potential risk to patient and clinician.
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The expression "flatten the curve" has gained significant attention in the midst of the COVID-19 pandemic. The idea is to decrease and/or delay the peak of an epidemic wave so as not to strain or exceed the capacity of healthcare systems. ⋯ This paper provides perspectives on the impact of containment, suppression, and mitigation measures on interdependent workforce sectors. Reflections on the trade-offs between flattening the curve versus personal liberty and socioeconomic disparities are also presented in this paper.
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JMIR Public Health Surveill · May 2020
Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model.
The coronavirus disease (COVID-19) pandemic has affected more than 200 countries and has infected more than 2,800,000 people as of April 24, 2020. It was first identified in Wuhan City in China in December 2019. ⋯ The observed predicted values showed that the confirmed cases, deaths, and recoveries will double in all the observed countries except China, Switzerland, and Germany. It was also observed that the death and recovery rates were rose faster when compared to confirmed cases over the next 2 months. The associated mortality rate will be much higher in the United States, Spain, and Italy followed by France, Germany, and the United Kingdom. The forecast analysis of the COVID-19 dynamics showed a different angle for the whole world, and it looks scarier than imagined, but recovery numbers start looking promising by July 7, 2020.