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| http://dx.doi.org/10.1111/eci.13537 | DOI Listing |
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COVID-19 reinfection in pregnancy: assessment of Severity and pregnancy outcomes in England.
J Infect
December 2024
UK Health Security Agency, London, United Kingdom.
Background: Disease severity and pregnancy outcomes following SARS-CoV-2 reinfections in pregnancy are not well understood.
Methods: We linked women aged 18 to 50 years testing positive in the community for COVID-19 between April 2021 and March 2022 to hospital, vaccine and maternal services databases. We compared hospital and intensive care unit (ICU) admission rates following infection and reinfection in pregnant and non-pregnant women, and low birthweight, prematurity and stillbirth in women infected and reinfected during pregnancy.
Predicting higher risk factors for COVID-19 short-term reinfection in patients with rheumatic diseases: a modeling study based on XGBoost algorithm.
J Transl Med
December 2024
Department of Rheumatology and Immunology, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, China.
Background: Corona virus disease 2019 (COVID-19) reinfection, particularly short-term reinfection, poses challenges to the management of rheumatic diseases and may increase adverse clinical outcomes. This study aims to develop machine learning models to predict and identify the risk of short-term COVID-19 reinfection in patients with rheumatic diseases.
Methods: We developed four prediction models using explainable machine learning to assess the risk of short-term COVID-19 reinfection in 543 patients with rheumatic diseases.
Unraveling the fear of COVID-19 reinfection: insights from frontline doctors in China.
Psychol Health Med
December 2024
Department of Emergency, The Third People's Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China.
Considering the end of global emergency status of Coronavirus-19 (COVID-19) and the persistent risk of reinfection for healthcare workers (HCWs), it is important to evaluate the attitude of the HCWs toward reinfecting with COVID-19. To gather information about participants' concerns regarding reinfection with COVID-19, a comprehensive online questionnaire was administered to all individuals involved in the study. DASS-21 was used to assess their mental health.
View Article and Find Full Text PDFThe Mental Burden of the COVID-19 Pandemic: A Retrospective Post-pandemic View From a Romanian Sample.
Cureus
October 2024
Faculty of Medicine, 'Ovidius' University, Constanta, ROU.
Background: The enduring psychological effects of the COVID-19 pandemic continue to affect individuals long after the immediate health concerns have subsided. This research aims to identify specific groups within the Romanian population who are at a higher risk of experiencing mental health challenges that can interfere with everyday life and may lead to more serious mental health disorders.
Methods: Conducted as a cross-sectional survey, this study assessed the severity of psychological distress using the Depression, Anxiety, and Stress Scale-21 (DASS-21) questionnaire in relation to COVID-19-related information and socio-demographic data to investigate the factors associated with psychological distress during the COVID-19 pandemic in Romania.
Analysis of re-infection cases and influencing factors post first severe COVID-19 wave in Jiangsu Province, China.
J Infect Dev Ctries
September 2024
Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Introduction: This study aimed to assess COVID-19 re-infection rates among individuals previously infected between 2020 and November 2022, particularly during the first wave of high-intensity transmission, and to identify the risk factors associated with re-infection in Jiangsu Province, China.
Methodology: Epidemiological investigations were conducted through telephone interviews and face-to-face visits in February and March 2023. Statistical analyses included the Chi-square or Fisher`s exact test for categorical data, Student's t-test for numerical data, Poisson regression for influencing factors, and Kaplan-Meier for cumulative re-infection risk.
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