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Purpose To compare the effectiveness of COVID-19 mitigation strategies in two homeless shelters in Massachusetts during the pandemic. Methods We conducted a prospective cohort study that followed guests in two Massachusetts homeless shelters between March 30 and May 13, 2020, which adopted different depopulation strategies. One set up temporary tents in its parking lot, while the other decompressed its guests to a gym and a hotel. The outcome was assessed by comparing the odds ratios of positive SARS-CoV-2 RT-PCR assays. Results Guests residing at the shelter that used temporary tents had 6.21 times (95% CI = 1.86, 20.77) higher odds of testing positive for SARS-CoV-2 at follow-up after adjusting for loss to follow up, age, gender, and race. The daily COVID-19 symptoms checklist performed poorly in detecting positive infection. Conclusions The study highlights the importance of depopulating shelter guests with stable and adequate indoor space to prevent SARS-CoV-2 transmission. Daily temperature and symptom checks should be combined with routine testing. With the rising homelessness due to mass unemployment and eviction crisis, our study supports further governmental assistance in decompressing homeless shelters during this pandemic.

Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital for the megacities implementing targeted infection prevention and control measures. In this study, the communities with confirmed cases during January 21–February 27 were collected and considered as the specific epidemic data for Beijing, Guangzhou, and Shenzhen. We evaluated the spatiotemporal variations of the epidemics before utilizing the ecological niche models (ENM) to assemble the epidemic data and nine socioeconomic variables for identifying the potential risk zones of this infection in these megacities. Three megacities were differentiated by the spatial patterns and quantities of infected communities, average cases per community, the percentages of imported cases, as well as the potential risks, although their COVID-19 infection situations have been preliminarily contained to date. With higher risks that were predominated by various influencing factors in each megacity, the potential risk zones coverd about 75% to 100% of currently infected communities. Our results demonstrate that the ENM method was capable of being employed as an early forecasting tool for identifying the potential COVID-19 infection risk zones on a fine scale. We suggest that local hygienic authorities should keep their eyes on the epidemic in each megacity for sufficiently implementing and adjusting their interventions in the zones with more residents or probably crowded places. This study would provide useful clues for relevant hygienic departments making quick responses to increasingly severe epidemics in similar megacities in the world., Graphical abstract Unlabelled Image, Highlights • COVID-19 infection still poses increasing threat to public health in the world. • We explored the feasibility of Maxent models in identifying the potential risks. • Socioeconomic factors affected the spatial distribution of potential risk zones. • Dominant influencing factors on potential risk zones varied in the megacities. • Maxent models were suitable for early identifying potential COVID-19 risk zones.

Introduction With the accumulating evidence of ocular manifestations of the 2019 novel coronavirus disease (COVID-19), the study aimed to systematically summarize the ocular manifestations in COVID-19 patients. Methods The PubMed, EMBASE, Web of Science databases were searched through June 2021. Studies that provided clinical characteristics and outcomes and reported on the ocular manifestations or conjunctival swab RT-PCR tests among COVID-19 patients were included. Results A total of 30 studies involving 5,717 patients were identified. Ocular manifestations including conjunctival hyperemia (7.6%, 95% confidence interval [CI] 1.8–8.9%), conjunctival discharge (4.8%, 95% CI 1.8–8.9%), epiphora (6.9%, 95% CI 2.8–12.8%), and foreign body sensation (6.9%, 95% CI 2.4–13.0%) were observed. The positive rate of conjunctival swab tests was 3.9% (95% CI 0.2–6.4%). Severe cases of COVID-19 were associated with an increased risk of developing ocular complications (odds ratio [OR] = 2.77, 95% CI 1.75–4.40). Conclusions Despite their relatively low incidence rate in COVID-19 patients, ocular manifestations may be non-specific and present as the initial symptoms of infection. The presence of SARS-CoV-2 in the conjunctival swabs implicates the eye as a potential source of infection. Early diagnosis and proper eye protection would help prevent viral transmission.

In 2019 coronavirus disease (COVID-19), whose main complication is respiratory involvement, different organs may also be affected in severe cases. However, COVID-19 associated cardiovascular manifestations are limited at present. The main purpose of this study was to identify potential candidate genes involved in COVID-19-associated heart damage by bioinformatics analysis. Differently expressed genes (DEGs) were identified using transcriptome profiles (GSE150392 and GSE4172) downloaded from the GEO database. After gene and pathway enrichment analyses, PPI network visualization, module analyses, and hub gene extraction were performed using Cytoscape software. A total of 228 (136 up and 92 downregulated) overlapping DEGs were identified at these two microarray datasets. Finally, the top hub genes (FGF2, JUN, TLR4, and VEGFA) were screened out as the critical genes among the DEGs from the PPI network. Identification of critical genes and mechanisms in any disease can lead us to better diagnosis and targeted therapy. Our findings identified core genes shared by inflammatory cardiomyopathy and SARS-CoV-2. The findings of the current study support the idea that these key genes can be used in understanding and managing the long-term cardiovascular effects of COVID-19.