est global pandemics in history (1), but its typical symptoms and relevant clinical predictors are still unknown. By March 2022, >79 million Americans had contracted COVID-19, and >963,000 had died (2,3). Multiple studies have found that older adults (4,5) and persons with chronic medical conditions, such as diabetes, hypertension, and renal failure, were particularly susceptible to contracting 7).Healthcare workers (HCWs) are another highly susceptible subpopulation (8-10) because of their time spent caring for COVID-19 patients (11). Of importance, 40% of HCWs identify as a racial minority; of those, 16% are Black, 13% Hispanic, and 7% Asian/ other (12)(13)(14). Kirby reported that doctors from racial and ethnic minority communities were twice as likely to deal with patients without access to personal protective equipment (PPE) than White colleagues (15). Available data suggest that Black persons are more likely to hold jobs considered essential (e.g., HCW, medical assistant, food preparation, home care aide) than their White counterparts. In addition, ethnic minorities work disproportionately in the top 9 occupations exposed to COVID-19 and, therefore, are at high risk for infection (16). However, they are less likely to publicly express their workplace safety concerns for fear of job loss (17).The initial surge in COVID-19 cases led to a profound increase in HCWs' exposure to the virus. However, the extent to which increased exposure in HCWs led to increased risk for death-and which demographic characteristics, severity indicators, and symptoms best predict this risk-remains unclear. Most previous research has used non-HCWs as controls, leading to biases due to differences in occupation, education, and treatment accessibility. In addition, a nationwide study evaluating COVID-19 symptoms and deaths among HCWs is lacking, especially one that accounts for the second and third COVID-19 surges.To fill these knowledge gaps, we used COVID-19 surveillance data from the Centers for Disease Control

Background: While most COVID-19 research has focused on older individuals with multi-comorbidities, few studies have assessed the predictors of fatality among health care workers (HCWs). This study evaluated if demographics and COVID-19 symptomatology predicted COVID-19 fatality and the temporal trends and spatial distribution among HCWs.Methods: We used a case-control design to compare HCW deaths related to COVID-19 (laboratory-confirmed) with three control groups (i.e., Non-HCW deaths, HCW non-deaths, and non-HCW non-deaths). Patient-level data with 33 variables, including COVID-19 confirmed cases, deaths, demographics, and various specific COVID symptoms reported by all states in the US, have been obtained from the Restricted Access Dataset by the US CDC since January 2020. A logistic regression model was used by regressing the outcome variable against each predictor while controlling for gender, age group, race, and ethnicity.Results: The percentages of 50-69 years old, Hispanics (8.7%), Black (32%), and Asian (23.1%) in HCW death were significantly higher than in their respective controls. The fatality and all severe indicators were higher among the deaths than non-deaths, but not different for HCWs than non-HCWs. Significantly increased risks for deaths were observed with pre-existing medical conditions (RR: 7.24, 95% CI: 5.40-9.70), shortness of breath (RR: 5.73, 95% CI:4.50-7.31), fever (RR:3.52, 95% CI: 2.71-4.56), cough (RR:2.02, 95% CI: 1.54-2.65), and diarrhea (RR: 1.57, 95% CI:1.20-2.05). Conclusion: Older and minority HCWs experienced relatively higher COVID-19 fatality. Severe symptoms are similarly prevalent among HCW deaths and non-HCW deaths. Pre-existing medical conditions, shortness of breath and fever symptoms may be critical COVID indicators for HCWs.

The outbreak of Covid-19 presents an unprecedented threat to public health with a devastating effect on the world economy and health system. In March 2020, the government of the United States responded by adopting the use of face masks as one of the measures to prevent the spread of coronavirus in public places. The increase in the spread of coronavirus necessitated the need for researchers to evaluate the effectiveness of face masks as a measure to control the spread of coronavirus. It became of more concern when alternatives to face masks were observed in public places. This article reviewed factors that affect the effectiveness of face masks and the choice of an effective face mask as reported by several studies. The use of appropriate face masks and other measures to prevent the spread of coronavirus should be encouraged at all levels. Keywords: COVID-19, SARS-CoV-2, FACE-MASKS.

Livestock farm waste contributes substantially to annual worldwide emissions of GHG (Greenhouse Gases), including CH 4 (Methane) and CO 2 (Carbon Dioxide). However, despite evidence of global climate change and its adverse health effects, studies on anthropogenic contributions to the increasing levels of GHG, particularly from livestock waste management practices, have not been adequately explored, especially in less developed countries. This study determined waste management practices and outdoor levels of CH 4 and CO 2 at three selected livestock farms (A-C) in Ibadan, Oyo State, Nigeria. Each study farm consisted of poultry, cattle and pig units. A 30-point observational checklist documented adequacy of solid waste management practices. Ambient concentrations of CH 4 and CO 2 at farm buildings and at waste disposal sites were monitored every other day, twice each day of monitoring (morning and evening hours), for eight weeks during months of September-November in 2013. Average scores for the waste management practices for Farms A-C were 29.6%, 33.3% and 18.5%, respectively. Morning and evening CH 4 concentrations in parts per million (ppm) at main buildings of Farms A-C were 2,538 ± 773 and 1,916 ± 662, 2,325 ± 773 and 1,180 ± 483, and 2,389 ± 687 and 1,854 ± 571, respectively. Morning and evening CO 2 concentrations (ppm) at Farms A-C main buildings were 350 ± 130 and 330 ± 110, 470 ± 100 and 440 ± 100, and 430 ± 80 and 400 ± 70, respectively. Morning and evening CH 4 concentrations (ppm) at Farms A-C waste disposal sites were 2,452 ± 495 and 1,614 ± 372, 1,527 ± 390 and 1,736 ± 269, and 2,345 ± 615 and 1,690 ± 387, respectively. Morning and evening CO 2 concentrations (ppm) at Farms A-C waste disposal sites were 330 ± 90, 370 ± 60 and 350 ± 30, respectively. Waste management practices were inadequate; solid waste management practices like infrequent evacuation of slurry waste and open burning of waste may have contributed to the production of CH 4 and CO 2 . This study suggested proper handling, removal and disposal of farm waste which can reduce production of GHGs like CH 4 and CO 2 .

No abstract