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“Everything…Fell Apart Once Covid-19 Hit”—Leveraging The Covid-19 Response To Strengthen Public Health Activities Toward Ending The Hiv Epidemic: A Qualitative Study, Samantha A. Devlin, Moctezuma Garcia, Kayo Fujimoto, Camden Hallmark, Marlene Mcneese, John Schneider, Moira C. Mcnulty
“Everything…Fell Apart Once Covid-19 Hit”—Leveraging The Covid-19 Response To Strengthen Public Health Activities Toward Ending The Hiv Epidemic: A Qualitative Study, Samantha A. Devlin, Moctezuma Garcia, Kayo Fujimoto, Camden Hallmark, Marlene Mcneese, John Schneider, Moira C. Mcnulty
Faculty Research, Scholarly, and Creative Activity
COVID-19 caused widespread disruption of activities for Ending the HIV Epidemic (EHE). In this study we assessed public health perspectives on leveraging the COVID-19 response to advance the goals of EHE. We conducted a qualitative study with 33 public health partners in the Midwestern and Southern United States from October 2020 to February 2022. Participants were asked how the strategies developed for COVID-19 could be applied to the HIV epidemic. Interviews were recorded, transcribed, and examined using rapid qualitative analysis. Four themes emerged: (1) Rebuilding teams and adapting culture for success in EHE activities; (2) Recognizing and modernizing the role …
Racial Bias Beliefs Related To Covid-19 Among Asian Americans, Native Hawaiians, And Pacific Islanders: Findings From The Covid-19 Effects On The Mental And Physical Health Of Asian Americans And Pacific Islanders Survey Study (Compass), Van Ta Park, Janice Y. Tsoh, Marcelle Dougan, Bora Nam, Marian Tzuang, Quyen N. Vuong, Joon Bang, Oanh L. Meyer
Racial Bias Beliefs Related To Covid-19 Among Asian Americans, Native Hawaiians, And Pacific Islanders: Findings From The Covid-19 Effects On The Mental And Physical Health Of Asian Americans And Pacific Islanders Survey Study (Compass), Van Ta Park, Janice Y. Tsoh, Marcelle Dougan, Bora Nam, Marian Tzuang, Quyen N. Vuong, Joon Bang, Oanh L. Meyer
Faculty Research, Scholarly, and Creative Activity
Background: During the COVID-19 pandemic, there have been increased reports of racial biases against Asian American and Native Hawaiian and Pacific Islander individuals. However, the extent to which different Asian American and Native Hawaiian and Pacific Islander groups perceive and experience (firsthand or as a witness to such experiences) how COVID-19 has negatively affected people of their race has not received much attention. Objective: This study used data from the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS), a nationwide, multilingual survey, to empirically examine COVID-19-related racial bias beliefs among Asian …
Differences In Covid-19 Vaccine Concerns Among Asian Americans And Pacific Islanders: The Compass Survey, Van Ta Park, Marcelle Dougan, Oanh Meyer, Bora Nam, Marian Tzuang, Linda Park, Quyen Vuong, Janice Tsoh
Differences In Covid-19 Vaccine Concerns Among Asian Americans And Pacific Islanders: The Compass Survey, Van Ta Park, Marcelle Dougan, Oanh Meyer, Bora Nam, Marian Tzuang, Linda Park, Quyen Vuong, Janice Tsoh
Faculty Research, Scholarly, and Creative Activity
Background: Understanding concerns for receiving COVID-19 vaccines is key to ensuring appropriately tailored health communications to increase vaccine uptake. However, limited data exists about vaccine concerns among Asian Americans and Pacific Islanders (AAPI). Methods: Data from the COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS), a cross-sectional, national survey for AAPI adults in the U.S. were used (N=1,646). Descriptive statistics were used to assess sample characteristics including proportions of AAPI with various COVID-19 vaccine concerns, categorized as none, side-effects only, unsafe only, and multiple reasons, and differences in vaccine concerns by socio-demographics. Ordinary multivariable logistic …
A Comparison Of Univariate And Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals During The Covid-19 Pandemic, Egbe Etu Etu, Leslie Monplaisir, Sara Masoud, Suzan Arslanturk, Joshua Emakhu, Imokhai Tenebe, Joseph B. Miller, Tom Hagerman, Daniel Jourdan, Seth Krupp
A Comparison Of Univariate And Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals During The Covid-19 Pandemic, Egbe Etu Etu, Leslie Monplaisir, Sara Masoud, Suzan Arslanturk, Joshua Emakhu, Imokhai Tenebe, Joseph B. Miller, Tom Hagerman, Daniel Jourdan, Seth Krupp
Faculty Research, Scholarly, and Creative Activity
The COVID-19 pandemic has heightened the existing concern about the uncertainty surrounding patient arrival and the overutilization of resources in emergency departments (EDs). The prediction of variations in patient arrivals is vital for managing limited healthcare resources and facilitating data-driven resource planning. The objective of this study was to forecast ED patient arrivals during a pandemic over different time horizons. A secondary objective was to compare the performance of different forecasting models in predicting ED patient arrivals. We included all ED patient encounters at an urban teaching hospital between January 2019 and December 2020. We divided the data into training …
Lockdowns As A War On The Poor: Looking At Outcomes In Silicon Valley, John B. Estill
Lockdowns As A War On The Poor: Looking At Outcomes In Silicon Valley, John B. Estill
Faculty Research, Scholarly, and Creative Activity
COVID-19 has led to unprecedented state-sponsored assaults on individual liberty including mask requirements, lockdowns, and mandatory testing and vaccinations. Unfortunately, these broad restrictions have multiple unintended consequences beyond the simple stripping away of individual rights. Silicon Valley, centered in Santa Clara County, represents a particularly compelling case. There has been much dialogue about the digital divide separating poor service workers from wealthy techies, and mandatory lockdowns have had a particularly damaging effect on the divide. They will continue to have negative ramifications long into the future.
Covid-19 Models For Hospital Surge Capacity Planning: A Systematic Review, Michael G. Klein, Carolynn J. Cheng, Evonne Lii, Keying Mao, Hamza Mesbahi, Tianjie Zhu, John A. Muckstadt, Nathaniel Hupert
Covid-19 Models For Hospital Surge Capacity Planning: A Systematic Review, Michael G. Klein, Carolynn J. Cheng, Evonne Lii, Keying Mao, Hamza Mesbahi, Tianjie Zhu, John A. Muckstadt, Nathaniel Hupert
Faculty Research, Scholarly, and Creative Activity
Objective: Health system preparedness for coronavirus disease (COVID-19) includes projecting the number and timing of cases requiring various types of treatment. Several tools were developed to assist in this planning process. This review highlights models that project both caseload and hospital capacity requirements over time. Methods: We systematically reviewed the medical and engineering literature according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We completed searches using PubMed, EMBASE, ISI Web of Science, Google Scholar, and the Google search engine. Results: The search strategy identified 690 articles. For a detailed review, we selected 6 models that met …
Spartan Face Mask Detection And Facial Recognition System, Ziwei Song, Kristie Nguyen, Tien Nguyen, Catherine Cho, Jerry Gao
Spartan Face Mask Detection And Facial Recognition System, Ziwei Song, Kristie Nguyen, Tien Nguyen, Catherine Cho, Jerry Gao
Faculty Research, Scholarly, and Creative Activity
According to the World Health Organization (WHO), wearing a face mask is one of the most effective protections from airborne infectious diseases such as COVID-19. Since the spread of COVID-19, infected countries have been enforcing strict mask regulation for indoor businesses and public spaces. While wearing a mask is a requirement, the position and type of the mask should also be considered in order to increase the effectiveness of face masks, especially at specific public locations. However, this makes it difficult for conventional facial recognition technology to identify individuals for security checks. To solve this problem, the Spartan Face Detection …
Prediction Of Length Of Stay In The Emergency Department For Covid-19 Patients: A Machine Learning Approach, Egbe Etu Etu, Leslie Monplaisir, Suzan Arslanturk, Sara Masoud, Celestine Aguwa, Ihor Markevych, Joseph Miller
Prediction Of Length Of Stay In The Emergency Department For Covid-19 Patients: A Machine Learning Approach, Egbe Etu Etu, Leslie Monplaisir, Suzan Arslanturk, Sara Masoud, Celestine Aguwa, Ihor Markevych, Joseph Miller
Faculty Research, Scholarly, and Creative Activity
The coronavirus disease (COVID-19) outbreak has become a global public health threat. The influx of COVID-19 patients has prolonged the length of stay (LOS) in the emergency department (ED) in the United States. Our objective is to develop a reliable prediction model for COVID-19 patient ED LOS and identify clinical factors, such as age and comorbidities, associated with LOS within a '4-hour target.' Data were collected from an urban, demographically diverse hospital in Detroit for all COVID-19 patients' ED presentations from March 16 to December 29, 2020. We trained four machine learning models, namely logistic regression (LR), gradient boosting (GB), …
Discrimination Experiences During Covid-19 Among A National, Multi-Lingual, Community-Based Sample Of Asian Americans And Pacific Islanders: Compass Findings, Van M. Ta Park, Marcelle M. Dougan, Oanh L. Meyer, Bora Nam, Marian Tzuang, Linda G. Park, Quyen Vuong, Joon Bang, Janice Y. Tsoh
Discrimination Experiences During Covid-19 Among A National, Multi-Lingual, Community-Based Sample Of Asian Americans And Pacific Islanders: Compass Findings, Van M. Ta Park, Marcelle M. Dougan, Oanh L. Meyer, Bora Nam, Marian Tzuang, Linda G. Park, Quyen Vuong, Joon Bang, Janice Y. Tsoh
Faculty Research, Scholarly, and Creative Activity
Reports of escalated discrimination among Asian Americans and Pacific Islanders (AAPIs) due to COVID-19 are alarming, making this a public health priority. However, there are limited empirical studies on the scope and impact of COVID-19-related discrimination among AAPIs. Using the COVID-19 Effects on the Mental and Physical Health of AAPI Survey Study (COMPASS) data (N = 4971; survey period: October 2020–February 2021), which is a U.S.-wide multi-lingual survey, we examined the prevalence of, and factors associated with discrimination experiences attributable to being an AAPI during the COVID-19 pandemic. Overall, 60.7% reported experiencing discrimination; the group prevalence ranged from 80.0% (Hmong) …