ABSTRACT
Mental health is an integral part of human existence and is most likely underestimated when it comes to human health. The thoughts that occupy the mind affects how a person feel and it corresponds to action which may have beneficial or harmful results. Thoughts are commonly expressed in words through written or verbal communication. In this study, the sentiments of young people are determined through the responses that they provide as they share their social media engagement experiences. With Natural Language Processing (NLP) and the implementation of Valence Aware Dictionary and s Entiment Reasoner (VADER), word clouds were produced containing significant words that indicate positive and negative sentiments. Results show common words in the positive sentiment as well as in the negative sentiment that support and represent the reality of the experience of young people as they engage in different social media activities.
ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread to most countries around the world. Disproportionate spread of COVID-19 among the Indian community in Kuwait prompted heightened surveillance in this community. Aims: To study the epidemiological characteristics of COVID-19 patients and their contacts among the Indian community in Kuwait. Methods: Data collection was done as a part of contact tracing efforts undertaken by the Kuwaiti Ministry of Health. Results: We analysed contact-tracing data for the initial 1348 laboratory-confirmed Indian patients and 6357 contacts (5681 close and 676 casual). The mean (standard deviation) age of the patients was 39.43 (10.5) years and 76.5% of the cases were asymptomatic or had only mild symptoms. Asymptomatic patients were significantly older [40.05 (10.42) years] than patients with severe symptoms [37.54 (10.54) years] (P = 0.024). About 70% of the patients were living in shared accommodation. Most of the close contacts were living in the same household, as compared with casual contacts, who were primarily workplace contacts (P < 0.001). Among the different occupations, healthcare workers had the highest proportion of cases (18.4%). Among the 216 pairs of cases with a clear relationship between the index and secondary cases, the mean serial interval was estimated to be 3.89 (3.69) days, with a median of 3 and interquartile range of 1–5 days. Conclusion: An early increase in the number of COVID-19 cases among the Indian community could be primarily attributed to crowded living conditions and the high proportion of healthcare workers in this community.
ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread to most countries around the world. Disproportionate spread of COVID-19 among the Indian community in Kuwait prompted heightened surveillance in this community. Aims: To study the epidemiological characteristics of COVID-19 patients and their contacts among the Indian community in Kuwait. Methods: Data collection was done as a part of contact tracing efforts undertaken by the Kuwaiti Ministry of Health. Results: We analysed contact-tracing data for the initial 1348 laboratory-confirmed Indian patients and 6357 contacts (5681 close and 676 casual). The mean (standard deviation) age of the patients was 39.43 (10.5) years and 76.5% of the cases were asymptomatic or had only mild symptoms. Asymptomatic patients were significantly older [40.05 (10.42) years] than patients with severe symptoms [37.54 (10.54) years] (P = 0.024). About 70% of the patients were living in shared accommodation. Most of the close contacts were living in the same household, as compared with casual contacts, who were primarily workplace contacts (P < 0.001). Among the different occupations, healthcare workers had the highest proportion of cases (18.4%). Among the 216 pairs of cases with a clear relationship between the index and secondary cases, the mean serial interval was estimated to be 3.89 (3.69) days, with a median of 3 and interquartile range of 1–5 days. Conclusion: An early increase in the number of COVID-19 cases among the Indian community could be primarily attributed to crowded living conditions and the high proportion of healthcare workers in this community.