Additional file 1 of The origin, dissemination, and molecular networks of HIV-1 CRF65_cpx strain in Hainan Island, China

Additional file 1: Table S1. List of 83 sequences of CRF65_cpx downloaded from the HIV Sequence Database. Figure S1. Maximum-likelihood (ML) phylogenetic tree of HIV-1 pol sequences. The ML tree, containing 711 sequences, was constructed with all available subtype C and CRF65_cpx sequences from China, and references of other subtypes (A1, A2, B, B', D, K, F1, F2, H, N, CRF01_AE, CRF07_BC, CRF08_BC and other CRFs) from the HIV Sequence Database by FastTree v2.2.10. Group N was set as outgroup. Background colours represent subtypes: the green denotes reference sequences (except subtype C and CRF65_cpx), the blue represents subtype C and the yellow indicates CRF65_cpx. Under the yellow background, the blue clade represents CRF65_cpx from Hainan Island, the yellow clade represents CRF65_cpx from other provinces, the red clade represents the sequences used for CRF65_cpx identification [1], and the dark brown clade denotes the CRF65_cpx misclassified as subtype C. The numbers near the red dots represent the Shimodaira-Hasegawa (SH)-like node support values. The tip label consists of subtype, sampling year, and GenBank accession. Figure S2. Bayesian maximum clade credibility (MCC) tree of Hainan monophyletic clade. The MCC tree was constructed using Dataset-2, including 55 sequences from Hainan Island. The values next to the green dots indicate the times of the most recent common ancestors. Line colors indicate different cities within Hainan Island. Scale years are shown at the bottom of the figure

Table_1_Prevalence of depressive symptoms and correlates among individuals who self-reported SARS-CoV-2 infection after optimizing the COVID-19 response in China.DOCX

BackgroundThe burden of depression symptoms has increased among individuals infected with SARS-CoV-2 during COVID-19 pandemic. However, the prevalence and associated factors of depressive symptoms among individuals infected with SARS-CoV-2 remain uncertain after optimizing the COVID-19 response in China.MethodsAn online cross-sectional survey was conducted among the public from January 6 to 30, 2023, using a convenience sampling method. Sociodemographic and COVID-19 pandemic-related factors were collected. The depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Logistic regression analysis was performed to explore the associated factors with depressive symptoms.ResultsA total of 2,726 participants completed the survey. The prevalence of depression symptoms was 35.3%. About 58% of the participants reported experiencing insufficient drug supply. More than 40% of participants reported that they had missed healthcare appointments or delayed treatment. One-third of participants responded experiencing a shortage of healthcare staff and a long waiting time during medical treatment. Logistic regression analysis revealed several factors that were associated with depression symptoms, including sleep difficulties (OR, 2.84; 95% CI, 2.34–3.44), chronic diseases (OR, 2.15; 95% CI, 1.64–2.82), inpatient treatment for COVID-19 (OR, 3.24; 95% CI, 2.19–4.77), with COVID-19 symptoms more than 13 days (OR, 1.30, 95% CI 1.04–1.63), re-infection with SARS-CoV-2 (OR, 1.52; 95% CI, 1.07–2.15), and the increased in demand for healthcare services (OR, 1.32; 95% CI, 1.08–1.61).ConclusionThis study reveals a moderate prevalence of depression symptoms among individuals infected with SARS-CoV-2. The findings underscore the importance of continued focus on depressive symptoms among vulnerable individuals, including those with sleeping difficulties, chronic diseases, and inpatient treatment for COVID-19. It is necessary to provide mental health services and psychological interventions for these vulnerable groups during the COVID-19 epidemic.</p