ABSTRACT
Climate change is disrupting the fundamental conditions of human life and exacerbating existing inequity by placing further burdens on communities that are already vulnerable. Risk exposure varies by where people live and work. In this article, we examine the spatial overlap of the compound risks of COVID-19 and extreme heat in New York City. We assess the relationship between socio-demographic and natural, built and social environmental characteristics, and the spatial correspondence of COVID-19 daily case rates across three pandemic waves. We use these data to create a compound risk index combining heat, COVID-19, density and social vulnerability. Our findings demonstrate that the compound risk of COVID-19 and heat are public health and equity challenges. Heat and COVID-19 exposure are influenced by natural, built, and social environmental factors, including access to mitigation infrastructure. Socio-demographic characteristics are significant indicators of COVID-19 and heat exposure and of where compound vulnerability exists. Using GIS mapping, we illustrate how COVID-19 risk geographies change across the three waves of the pandemic and the particular impact of vaccinations before the onset of the third wave. We, then, use our compound risk index to assess heat interventions undertaken by the City, identify neighborhoods of both adequate and inadequate coverage and provide recommendations for future interventions. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
Background: The recent outbreak caused by SARS-CoV-2, known as COVID-19, has been cataloged as a global catastrophe due to the growing number of infected cases and deaths since November 2019;this infectious, contagious disease, to date, does not have a vaccine or specific treatment available, which is why the number of cases continues to increase. SARS-CoV-2 infects humans as a result of the interaction between the receptor-binding domain of the viral spike protein and the receptor of the angiotensin-converting enzyme-2 (rACE2), located predominantly in the alveolar cells. Objective: This study aims to identify inhibitory peptides of the protein-protein interaction between the receptor-binding-domain of the spike protein of SARS-CoV-2 and the angiotensin-converting enzyme-2 receptor through computational tools. Methods: Through the Research Collaboratory for Structural Bioinformatics protein database, crystals were selected and interaction models were carried out between the viral protein and the ACE2;thereafter, the study designed inhibitory peptides of the interaction through the Rosetta web server, validated their interaction through ClusPro and, finally, determined the theoretical physicochemical and cytotoxic properties. Results: A protein complex was generated and modeled through ClusPro;the balanced model was selected with the lowest binding energy. From the protein interactions of each of the crystals and from the model, eight peptides of 20 residues were obtained. The theoretical evaluation showed non-toxic peptides, six soluble in water, and two insoluble. Conclusion: We found eight peptides that interacted with the receptor-binding-domain of the spike protein of SARS-CoV-2, which could avoid contact with the cell receptor and generate interference in the infection process.