Although the COVID-19 pandemic has left no country untouched there has been limited research to understand clinical and immunological responses in African populations. Here we comprehensively characterise patients hospitalised with suspected or confirmed COVID-19, and healthy community controls. PCR-confirmed COVID-19 participants were more likely to receive dexamethasone and a beta-lactam antibiotic, and survive to hospital discharge than PCR-/IgG+ and PCR-/IgG-participants. PCR-/IgG+ participants exhibited a nasal and systemic cytokine signature analogous to PCR-confirmed COVID-19 participants, but increased propensity for Staphylococcus aureus and Streptococcus pneumoniae colonisation. We did not find evidence that HIV co-infection in COVID-19 participants was associated with mortality or altered cytokine responses. The nasal immune signature in PCR-/IgG+ and PCR-confirmed COVID-19 participants was distinct and predominated by chemokines and neutrophils. In addition, PCR-/IgG+ individuals with high COVID-19 clinical suspicion had inflammatory profiles analogous to PCR-confirmed disease and potentially represent a target population for COVID-19 treatment strategies.SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5×10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.Universal mask wearing is recommended by the Centers for Disease Control and Prevention to help control the spread of COVID-19. Masks reduce the expulsion of respiratory aerosols (called source control) and offer some protection to the wearer. However, masks vary greatly in their designs and construction materials, and it is not clear which are most effective. Our study tested 15 reusable cloth masks (which included face masks, neck gaiters, and bandanas), two medical masks, and two N95 filtering facepiece respirators as source control devices for aerosols ≤ 7 µm produced during simulated coughing and exhalation. These measurements were compared with the mask filtration efficiencies, airflow resistances, and fit factors. The source control collection efficiencies for the cloth masks ranged from 17% to 71% for coughing and 35% to 66% for exhalation. The filtration efficiencies of the cloth masks ranged from 1.4% to 98%, while the fit factors were 1.3 to 7.4 on an elastomeric manikin headform and 1.0 to 4.0 on human test subjects. The correlation coefficients between the source control efficacies and the other performance metrics ranged from 0.31 to 0.66 and were significant in all but one case. However, none of the alternative metrics were strong predictors of the source control performance of cloth masks. Our results suggest that a better understanding of the relationships between source control performance and metrics like filtration efficiency, airflow resistance, and fit factor are needed to develop simple methods to estimate the effectiveness of masks as source control devices for respiratory aerosols.The COVID-19 pandemic has exposed the need to understand the unique risk drivers that contribute to uneven morbidity and mortality in US communities. Addressing the community-specific social determinants of health that correlate with spread of SARS-CoV-2 provides an opportunity for targeted public health intervention to promote greater resilience to viral respiratory infections in the future. Our work combined publicly available COVID-19 statistics with county-level social determinants of health information. see more Machine learning models were trained to predict COVID-19 case growth and understand the unique social, physical and environmental risk factors associated with higher rates of SARS-CoV-2 infection in Tennessee and Georgia counties. Model accuracy was assessed comparing predicted case counts to actual positive case counts in each county. The predictive models achieved a mean r-squared (R 2 ) of 0.998 in both states with accuracy above 90% for all time points examined. Using these models, we tracked the social determinants of health, with a specific focus on demographics, that were strongly associated with COVID-19 case growth in Tennessee and Georgia counties. The demographic results point to dynamic racial trends in both states over time and varying, localized patterns of risk among counties within the same state. Identifying the specific risk factors tied to COVID-19 case growth can assist public health officials and policymakers target regional interventions to mitigate the burden of future outbreaks and minimize long-term consequences including emergence or exacerbation of chronic diseases that are a direct consequence of infection.The effect of SARS-CoV-2 infection on response to mRNA-based SARS-CoV-2 vaccines is not well-described. We assessed longitudinal SARS-CoV-2-specific antibody responses pre- and post-vaccination among individuals with and without prior infection. The antibody response to the first vaccine dose was almost two-fold higher in individuals who were seropositive before vaccination compared to those who were seronegative, suggesting that prior infection primes the immune response to the first dose of mRNA-based vaccine.

Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic.

In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term.

Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI 3.