Wastewater Based Epidemiology, Phylogenetic Analysis and Machine Learning Approach to Describe the Evolution of SARS-CoV-2 in the South-East of Spain (preprint)

The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, water samples from two wastewater treatment plants (WWTPs) located at the south east of Spain (Region of Murcia) namely Murcia, and Cartagena, were analyzed by RT-qPCR, Phylogenetic Analysis, and Machine Learning Approach. The aim was to determine whether SARS-CoV-2 detection in the WWTPs of these two cities could serve as a proxy for the virus's spread in the population. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population and variant occurrences were in line with clinical reported data. Additionally, the phylogenetic analysis showed that samples obtained in close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical Clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing the Accumulated Natural Vector (ANV) of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.

Anthropological analysis of the life experiences of patient Covid - 19 in ICU: from fear to gratitude

The pandemic caused by the SARS-CoV-2 coronavirus has put both the health system and society at large in check. Methodology: qualitative study with micro-ethnographic and descriptive approach of the life experiences and experiences of patients diagnosed with Covid19 who required admission to the ICU, through the semi-structured open interview. The participants were two patients who did not require invasive respiratory measures, a 66-year-old man and a 57-year-old woman. Results: In-depth discourse analysis emerged 5 main dimensions with 23 subdimensions. The main dimensions were: life experiences related to the Covid-19;life experiences related to the stay in ICU;media as a source of information;support networks;and, future perspectives. Conclusions: the fear of the unknown aggravated by infodemia and the "apocalyptic" images of a dystopian reality has injected in the patients a sensation of fragility never before felt. The expression of perceived fear in these patients diagnosed with Covid-19 and admission to the ICU is of real terror. Depersonalization related to IPEs and dehumanization as a result of isolation and restriction of visits have set back advances in health humanization and people-centred care.