Medicine and Health Sciences Commons^™

The Public Health Impact Of Paxlovid Covid-19 Treatment In The United States, Yuan Bai, Zhanwei Du, Lin Wang, Eric H. Y. Lau, Isaac Fung, Petter Holme, Ben Cowling, Alison Galvani, Robert Krug, Lauren Ancel Meyers

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

The antiviral drug Paxlovid has been shown to rapidly reduce viral load. Coupled with vaccination, timely administration of safe and effective antivirals could provide a path towards managing COVID-19 without restrictive non-pharmaceutical measures. Here, we estimate the population-level impacts of expanding treatment with Paxlovid in the US using a multi-scale mathematical model of SARS-CoV-2 transmission that incorporates the within-host viral load dynamics of the Omicron variant. We find that, under a low transmission scenario (Re∼1.2) treating 20% of symptomatic cases would be life and cost saving, leading to an estimated 0.26 (95% CrI: 0.03, 0.59) million hospitalizations averted, 30.61 (95% …

A Pharmacoepidemiological Study Of Myocarditis And Pericarditis Following The First Dose Of Mrna Covid-19 Vaccine In Europe, Joana Tome, Logan Cowan, Isaac Fung

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

This study assessed the myocarditis and pericarditis reporting rate of the first dose of mRNA COVID-19 vaccines in Europe. Myocarditis and pericarditis data pertinent to mRNA COVID19 vaccines (1 January 2021–11 February 2022) from EudraVigilance database were combined with European Centre for Disease Prevention and Control (ECDC)’s vaccination tracker data. The reporting rate was expressed as events (occurring within 28 days of the first dose) per 1 million individuals vaccinated. An observed-to-expected (OE) analysis quantified excess risk for myocarditis or pericarditis following the first mRNA COVID-19 vaccination. The reporting rate of myocarditis per 1 million individuals vaccinated was 17.27 (95% …

Association Between The Health Belief Model, Exercise, And Nutrition Behaviors During The Covid-19 Pandemic, Keagan Kiely, Bill Mase, Andrew R. Hansen, Jessica S. Schwind

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

Introduction: The COVID-19 pandemic has affected our nation’s health further than the infection it causes. Physical activity levels and dietary intake have suffered while individuals grapple with the changes in behavior to reduce viral transmission. With unique nuances regarding the access to physical activity and nutrition during the pandemic, the constructs of Health Belief Model (HBM) may present themselves differently in nutrition and exercise behaviors compared to precautions implemented to reduce viral transmission studied in previous research. The purpose of this study was to investigate the extent of exercise and nutritional behavior change during the COVID-19 pandemic and explain the …

Spatially Refined Time-Varying Reproduction Numbers Of Covid-19 By Health District In Georgia, Usa, March–December 2020, Chigozie A. Ogwara, Arshpreet Kaur Mallhi, Xinyi Hua, Kamalich Muniz-Rodriguez, Jessica S. Schwind, Xiaolu Zhou, Jeffery A. Jones, Joanne Chopak-Foss, Gerardo Chowell, Isaac Chun-Hai Fung

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

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, Rt of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package ‘EpiEstim’ to the time series of historical daily incidence of confirmed cases, 2 March–15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log10-transformed per capita cumulative case count and log10-transformed population size. We observe …

Sars-Cov-2 Transmission In Alberta, British Columbia, And Ontario, Canada, December 25, 2019, To December 1, 2020, Isaac Chun-Hai Fung, Yuen Wai Hung, Sylvia Ofori, Kamalich Muniz-Rodriguez, Po-Ying Lai, Gerardo Chowell

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

Objective:

This study aimed to investigate coronavirus disease (COVID-19) epidemiology in Alberta, British Columbia, and Ontario, Canada.

Methods:

Using data through December 1, 2020, we estimated time-varying reproduction number, R t , using EpiEstim package in R, and calculated incidence rate ratios (IRR) across the 3 provinces.

Results:

In Ontario, 76% (92 745/121 745) of cases were in Toronto, Peel, York, Ottawa, and Durham; in Alberta, 82% (49 878/61 169) in Calgary and Edmonton; in British Columbia, 90% (31 142/34 699) in Fraser and Vancouver Coastal. Across 3 provinces, R t dropped to ≤ 1 after April. …

Lag Effects Of Ozone, Pm2.5, And Meteorological Factors On Covid-19 New Cases At The Disease Epicenter In Queens, New York, Atin Adhikari, Jingjing Yin

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

The influences of environmental factors on COVID-19 may not be immediate and could be lagged for days to weeks. This study investigated the choice of lag days for calculating cumulative lag effects of ozone, PM2.5, and five meteorological factors (wind speed, temperature, relative humidity, absolute humidity, and cloud percentages) on COVID-19 new cases at the epicenter of Queens County, New York, before the governor’s executive order on wearing of masks in public places (1 March to 11 April 2020). Daily data for selected air pollutants and meteorological factors were collected from the US EPA Air Quality System, weather observation station …

Covid-19 Pandemic In Brazil: Clinical Manifestation And Effect Of Comorbidities On Outcomes Of Hospitalized Sari Cases, Mario Keko, Karl E. Peace

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

Hospitalized SARI cases of 2020 reported to the Ministry of Health of Brazil through the SIVEP Gripe system are subject to our analysis. They are classified as COVID-19 and non-COVID-19 and clinical manifestations and comorbidities are reported for each group. The time trend in the number of cases reported in 2020 is compared to the previous year and the performance of the PCR test is explored in each group. The proportion of death is reported among different subgroups of the patients by epidemiological week. Logistic and Poisson regression models are used to check the effect of comorbidities on clinical outcomes.

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 …

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 …