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1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309420

ABSTRACT

We develop a novel temporal complex network approach to quantify the US county level spread dynamics of COVID-19. The objective is to study the effects of the local spread dynamics, COVID-19 cases and death, and Google search activities on the US stock market. We use both conventional econometric and Machine Learning (ML) models. The results suggest that COVID-19 cases and deaths, its local spread, and Google searches have impacts on abnormal stock prices between January 2020 to May 2020. In addition, incorporating information about local spread significantly improves the performance of forecasting models of the abnormal stock prices at longer forecasting horizons. On the other hand, although a few COVID-19 related variables, e.g., US total deaths and US new cases exhibit causal relationships on price volatility, COVID-19 cases and deaths, local spread of COVID-19, and Google search activities do not have impacts on price volatility.

2.
Allergy Asthma Proc ; 43(1): e1-e10, 2022 Jan 01.
Article in English | MEDLINE | ID: covidwho-1605122

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) pandemic has greatly affected health-care provision across the globe. Management of chronic ailments has become challenging because of the strained health-care resources and social distancing measures that prevent on-site clinical visits and treatments. Hereditary angioedema (HAE) is a debilitating, chronic disease characterized by unpredictable swelling attacks in various parts of the body. Controlling HAE symptoms often requires long-term prophylactic medication use and regular medical care; however, limited scientific information has been published about HAE medical care during the COVID-19 pandemic. Objective: To gather patient and health-care professional (HCP) perspectives on the global impact that COVID-19 has had, and the future impact it will have on HAE medical care and to identify differences in perceptions across economic and geographic boundaries. Methods: We conducted two independent but similar online global surveys to capture patient and HCP perspectives on the impact that COVID-19 has had, and the future impact it will have on HAE medical care. Results: Both patients and HCPs globally reported that the pandemic has limited the availability of HAE medical care, and they expect the restrictions to continue far beyond the pandemic. In addition, the results of our study suggested that telehealth use has increased across the globe but has been more successfully implemented in high-income countries. Conclusion: Patients and HCPs expect that HAE-related care will be negatively impacted by the pandemic for many years. Disparities in medical care and technologic infrastructure may exacerbate these challenges in non-high-income countries. Supportive tools and global infrastructure should be established to provide aid to non-high-income countries throughout the pandemic and several years after.


Subject(s)
Angioedemas, Hereditary , COVID-19 , Pandemics , Angioedemas, Hereditary/diagnosis , Angioedemas, Hereditary/epidemiology , Angioedemas, Hereditary/therapy , Humans , Surveys and Questionnaires
3.
Physica A ; 589: 126423, 2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1447056

ABSTRACT

We develop a novel temporal complex network approach to quantify the US county level spread dynamics of COVID-19. We use both conventional econometric and Machine Learning (ML) models that incorporate the local spread dynamics, COVID-19 cases and death, and Google search activities to assess if incorporating information about local spreads improves the predictive accuracy of models for the US stock market. The results suggest that COVID-19 cases and deaths, its local spread, and Google searches have impacts on abnormal stock prices between January 2020 to May 2020. Furthermore, incorporating information about local spread significantly improves the performance of forecasting models of the abnormal stock prices at longer forecasting horizons.

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