Racial/Ethnic Differences in COVID-19-Traumatic Symptoms, Sleep, Coping Outcomes in a Group of New-Yorkers (preprint)

Background: Little research has examined within/between group predictors and mediators of race/ethnic differences or disparities in mental and sleep health outcomes arising from the experience of the COVID-19 pandemic. Objectives: This study sought to evaluate the effect of COVID-19 experiences on trauma-related symptoms and sleep quality among a multiracial/ethnic sample in New York. Method: This is a cross-sectional study conducted online among multiethnic adults (n=541) who experienced the pandemic in New York from September to November 2020. Comparisons of characteristics and mean scores by race/ethnicity status were conducted using one-way ANOVA and independent samples t-tests for continuous variables and chi-square tests for categorical variables. Multilinear regression was used for associations between social determinants of health and/or SES, trauma-related symptoms, coping, and sleep. Results: Compared to Whites [Mean (SD)= (24.1(7.6)] and other group [Mean (SD)=24.9(8.2), Blacks [Mean (SD)=(26.3(6.4)] and Hispanics [Mean(SD)=(27.2(8.2)] reported higher level of peritraumatic distress [ df= 3; F=4273; p=0.005). The prevalence of clinically significant PTSD symptoms was 21.4%(n=113): [Whites=31(16.3%); Blacks=28(25.7%); Hispanics=24(25%); and other groups=30(22.4%); x2 =4.93; p=0.177]. This rate doubled [48.3%(257)] when it comes to the overall clinically significant depression level. Compared to all subcategories, [Blacks=52(47.7%); Hispanics =62(64.6%); other group=66(49.3%)], depression symptoms were lower among Whites [77(39.9%; x2 =15.71; p=0.001]. We found a prevalence of insufficient sleep <6 hours of 41%(198): [Whites=69(39.4%); Blacks=43(41.7%); Hispanics=46(52.3%); other groups=40(34.2%); x2=12.21; p=0.057]. Several unique demographic predictors of PTSD emerged for distinct racial/ethnic groups. Among Blacks, sex [{beta} = -0.22; p < .01] and employment [{beta} = -0.159; p < .05] emerged as significant predictors for PTSD, but for no other racial/ethnic group. Interestingly, among Hispanics [{beta} = -0.144; p = .064] and Blacks [{beta} = -0.174; p = .0.076], coping strategies did not mitigate PTSD or depressive symptoms. Conclusion: As New York and the rest of the world are trying to bounce back from the COVID-19 consequences, mental health outcomes are devastating, particularly among historically marginalized communities. This study provides insight into the emergency for policymakers to invest in racial justice programs and provide free access to culturally responsive mental health care for the most vulnerable groups.

Predicting the Number of COVID-19 Infections and Deaths in USA (preprint)

Background: Uncertainties surrounding the 2019 novel coronavirus (COVID-19) remain a major global health challenge and requires attention. Researchers and medical experts have made remarkable efforts to reduce the number of cases and prevent future outbreaks through vaccines and other measures. However, there is little evidence on how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection entropy can be applied in predicting the possible number of infections and deaths. In addition, more studies on how the COVID-19 infection density contributes to the rise in infections are needed. This study demonstrates how the SARS-COV-2 daily infection entropy can be applied in predicting the number of infections within a given period. In addition, the infection density within a given population attributes to an increase in the number of COVID-19 cases and, consequently, the new variants. Result: Using the COVID-19 initial data reported by Johns Hopkins University, World Health Organization and Global Initiative on Sharing All Influenza Data, the result shows that the original SAR-COV-2 strain has R0<1 with an initial infection growth rate entropy of 9.11 bits for the United States. At close proximity the average infection time for an infected individual to infect others within a susceptible population is approximately 7 minutes. Assuming no vaccines were available, in the United States, the number of infections could range between 41,220,199 and 82,440,398 in late March 2022 with approximately, 1,211,036 deaths. However, with the available vaccines, nearly 48 Million COVID-19 cases and 706, 437 deaths have been prevented. Conclusion: The proposed technique will contribute to the ongoing investigation of the COVID-19 pandemic and a blueprint to address the uncertainties surrounding the pandemic.