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Full-Text Articles in Physical Sciences and Mathematics

A Spectral Adjustment For Spatial Confounding, Yawen Guan, Garritt L. Page, Brian J. Reich, Massimo Ventrucci, Shu Yang Dec 2020

A Spectral Adjustment For Spatial Confounding, Yawen Guan, Garritt L. Page, Brian J. Reich, Massimo Ventrucci, Shu Yang

Department of Statistics: Faculty Publications

Adjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. In this paper, we derive necessary conditions on the coherence between the treatment variable of interest and the unmeasured confounder that ensure the causal effect of the treatment is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. The key assumption that ensures identifiability is that confounding present at global scales dissipates at local scales. We show that this assumption in the spectral domain is …


Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake Dec 2020

Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake

Theses & Dissertations

Small area estimation (SAE) has been widely used in a variety of applications to draw estimates in geographic domains represented as a metropolitan area, district, county, or state. The direct estimation methods provide accurate estimates when the sample size of study participants within each area unit is sufficiently large, but it might not always be realistic to have large sample sizes of study participants when considering small geographical regions. Meanwhile, high dimensional socio-ecological data exist at the community level, providing an opportunity for model-based estimation by incorporating rich auxiliary information at the individual and area levels. Thus, it is critical …


The Use Of Penalized Regression Analysis To Identify County-Level Demographic And Socioeconomic Variables Predictive Of Increased Covid-19 Cumulative Case Rates In The State Of Georgia, Holly L. Richmond, Joana Tome, Haresh Rochani, Isaac Chun-Hai Fung, Gulzar H. Shah, Jessica S. Schwind Oct 2020

The Use Of Penalized Regression Analysis To Identify County-Level Demographic And Socioeconomic Variables Predictive Of Increased Covid-19 Cumulative Case Rates In The State Of Georgia, Holly L. Richmond, Joana Tome, Haresh Rochani, Isaac Chun-Hai Fung, Gulzar H. Shah, Jessica S. Schwind

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables …


Call To Action: Sars-Cov-2 And Cerebrovascular Disorders (Cascade), Shahram Abootalebi, Benjamin M. Aertker, Mohammad Sobhan Andalibi, Negar Asdaghi, Ozlem Aykac, M. Reza Azarpazhooh, M. Cecilia Bahit, Kristian Barlinn, Hamidon Basri, Reza Bavarsad Shahripour, Anna Bersano, Jose Biller, Afshin Borhani-Haghighi, Robert D. Brown, Bruce Cv Campbell, Salvador Cruz-Flores, Deidre Anne De Silva, Mario Di Napoli, Afshin A. Divani, Randall C. Edgell, Johanna T. Fifi, Abdoreza Ghoreishi, Teruyuki Hirano, Keun Sik Hong, Chung Y. Hsu, Josephine F. Huang, Manabu Inoue, Amanda L. Jagolino, Moira Kapral, Hoo Fan Kee, Zafer Keser, Rakesh Khatri Sep 2020

Call To Action: Sars-Cov-2 And Cerebrovascular Disorders (Cascade), Shahram Abootalebi, Benjamin M. Aertker, Mohammad Sobhan Andalibi, Negar Asdaghi, Ozlem Aykac, M. Reza Azarpazhooh, M. Cecilia Bahit, Kristian Barlinn, Hamidon Basri, Reza Bavarsad Shahripour, Anna Bersano, Jose Biller, Afshin Borhani-Haghighi, Robert D. Brown, Bruce Cv Campbell, Salvador Cruz-Flores, Deidre Anne De Silva, Mario Di Napoli, Afshin A. Divani, Randall C. Edgell, Johanna T. Fifi, Abdoreza Ghoreishi, Teruyuki Hirano, Keun Sik Hong, Chung Y. Hsu, Josephine F. Huang, Manabu Inoue, Amanda L. Jagolino, Moira Kapral, Hoo Fan Kee, Zafer Keser, Rakesh Khatri

Epidemiology and Biostatistics Publications

Background and purpose: The novel severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), now named coronavirus disease 2019 (COVID-19), may change the risk of stroke through an enhanced systemic inflammatory response, hypercoagulable state, and endothelial damage in the cerebrovascular system. Moreover, due to the current pandemic, some countries have prioritized health resources towards COVID-19 management, making it more challenging to appropriately care for other potentially disabling and fatal diseases such as stroke. The aim of this study is to identify and describe changes in stroke epidemiological trends before, during, and after the COVID-19 pandemic. Methods: This is an international, multicenter, hospital-based …


Excess Mortality From Covid-19: A Commentary On The Italian Experience, Paolo Pasquariello, Saverio Stranges Jun 2020

Excess Mortality From Covid-19: A Commentary On The Italian Experience, Paolo Pasquariello, Saverio Stranges

Epidemiology and Biostatistics Publications

No abstract provided.


A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages, Lu Dong, Zhe Li, Isaac Fung May 2020

A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages, Lu Dong, Zhe Li, Isaac Fung

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

We investigated the adoption of World Health Organization (WHO) naming of COVID-19 into the respective languages among the Group of Twenty (G20) countries, and the variation of COVID-19 naming in the Chinese language across different health authorities. On May 7, 2020, we identified the websites of the national health authorities of the G20 countries to identify naming of COVID-19 in their respective languages, and the websites of the health authorities in mainland China, Hong Kong, Macau, Taiwan and Singapore and identify their Chinese name for COVID-19. Among the G20 nations, Argentina, China, Italy, Japan, Mexico, Saudi Arabia and Turkey do …


The Incubation Period Of Coronavirus Disease 2019 (Covid-19) From Publicly Reported Confirmed Cases: Estimation And Application, Stephen A. Lauer, Kyra H. Grantz, Qifang Bi, Forest K. Jones, Qulu Zheng, Hannah R. Meredith, Andrew S. Azman, Nicholas G. Reich, Justin Lessler Jan 2020

The Incubation Period Of Coronavirus Disease 2019 (Covid-19) From Publicly Reported Confirmed Cases: Estimation And Application, Stephen A. Lauer, Kyra H. Grantz, Qifang Bi, Forest K. Jones, Qulu Zheng, Hannah R. Meredith, Andrew S. Azman, Nicholas G. Reich, Justin Lessler

Biostatistics and Epidemiology Faculty Publications Series

Background:

A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities.

Objective:

To estimate the length of the incubation period of COVID-19 and describe its public health implications.

Design:

Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020.

Setting:

News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. …


An Examination Of Covid-19 Statistical Modeling, Shane Vaughan Jan 2020

An Examination Of Covid-19 Statistical Modeling, Shane Vaughan

Williams Honors College, Honors Research Projects

The 2019 novel coronavirus, also known as COVID-19, is an infectious disease which was first reported in late 2019 and soon spread to become a global pandemic, prompting major action from world governments. Soon after, many institutions began attempts to analyze and predict the spread and severity of the disease via statistical modeling. Some information is not available for public consumption; however, a number of institutions have published the results of their analyses and some have made public repositories of the code used to build the models. This research paper attempts use these and other resources to examine the modeling …