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1.
J Acquir Immune Defic Syndr ; 90(4): 408-417, 2022 08 01.
Article in English | MEDLINE | ID: covidwho-1909062

ABSTRACT

BACKGROUND: The effect of the COVID-19 epidemic on HIV self-testing (HIVST) remains unclear. We aimed to quantify the impact of COVID restrictions on HIVST kit purchasing behaviors in mainland China. METHODS: Deidentified transaction data were retrieved from a large online shopping platform. An interrupted time series model was constructed to examine the impact of COVID restrictions on the weekly number of anonymous customers purchasing HIVST kits, online orders, and purchased kits. RESULTS: A total of 2.32 million individuals submitted 4.46 million orders for 4.84 million HIVST kits between January 7, 2016, and April 22, 2020. Compared with expected levels, assuming COVID-19 epidemic and related restrictions had not happened, the number of purchasers, orders, and kits decreased by an estimated 10,500 (51.7%), 18,000 (55.3%), and 18,500 (54.9%) in the first week (January 23, 2020, to January 29, 2020) after COVID restrictions were implemented, respectively. As restrictions eased, the number of purchasers, orders, and kits increased by an average of 7.4%, 4.8%, and 4.9% per week, respectively. In the first week after COVID restrictions were lifted (April 9, 2020, to April 15, 2020), the number of purchasers returned to expected levels, whereas the number of orders and kits were still lower than expected levels. The impact of COVID restrictions on outcomes at the beginning of COVID restrictions and the increasing trends of outcomes were larger among those living in regions with higher COVID-19 incidence (eg, Wuhan city and Hubei province). CONCLUSIONS: Online sales of HIVST kits were significantly impacted by COVID restrictions, and HIVST kit purchasing patterns returned to expected levels after restrictions were lifted.


Subject(s)
COVID-19 , HIV Infections , COVID-19/epidemiology , Commerce , HIV Infections/diagnosis , HIV Infections/epidemiology , HIV Infections/prevention & control , HIV Testing , Humans , Mass Screening , Self-Testing
2.
Hum Vaccin Immunother ; 17(12): 4964-4970, 2021 12 02.
Article in English | MEDLINE | ID: covidwho-1565873

ABSTRACT

OBJECTIVES: The coronavirus disease-2019 (COVID-19) pandemic continues to ravage the world. People living with HIV (PLHIV) are one of the most vulnerable groups. This study aims to identify the factors associated with the uptake and adverse reactions of COVID-19 vaccination. METHODS: We recruited PLHIV in China by convenience sampling between 7 and 23 February 2021. Participants were asked to complete an online questionnaire. Chi-squared test and multivariable logistic regression were used to assess factors associated with vaccine uptake. RESULTS: A total of 527 vaccinated and 1091 unvaccinated PLHIV were recruited. Individuals who had a higher education, engaged in occupations with a higher risk of COVID-19 infection, received influenza or pneumonia vaccine in the past 3 years (5.40, 3.36-8.77), believed in the effectiveness of vaccines (3.01, 2.20-4.12), and received media information regarding COVID-19 vaccine (2.23, 1.61-3.11), were more likely to be vaccinated. Concerning about adverse reactions (0.31, 0.22-0.44), negative impact on the progression of HIV/AIDS (0.36, 0.26-0.50) or antiretroviral therapy (ART) (0.61, 0.44-0.85), disclosure of HIV infection status (0.69, 0.49-0.96), comorbidities (0.33, 0.22-0.47), being unmarried (0.43, 0.28-0.66) and older age were negatively associated with vaccination. Of the 527 vaccinated PLHIV, 155 (29.4%) PLHIV reported adverse reactions, with pain at the injection site being the most common (18.2%). CONCLUSIONS: PLHIV, who are concerned about adverse reactions, negative impact on ART outcome and disclosure of HIV infection status, were less likely to adopt COVID-19 vaccination. To increase vaccination coverage among PLHIV, health-care professionals should emphasize the benefits and necessity of vaccination and provide consultancy regarding adverse reactions.


Subject(s)
COVID-19 , HIV Infections , Influenza Vaccines , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/adverse effects , Case-Control Studies , China/epidemiology , HIV Infections/complications , Humans , Influenza Vaccines/adverse effects , SARS-CoV-2 , Vaccination/adverse effects
3.
Infect Dis Poverty ; 10(1): 94, 2021 Jul 05.
Article in English | MEDLINE | ID: covidwho-1352672

ABSTRACT

BACKGROUND: Various modalities of vaccines against coronavirus disease 2019 (COVID-19), based on different platforms and immunization procedures, have been successively approved for marketing worldwide. A comprehensive review for clinical trials assessing the safety of COVID-19 vaccines is urgently needed to make an accurate judgment for mass vaccination. MAIN TEXT: A systematic review and meta-analysis was conducted to determine the safety of COVID-19 vaccine candidates in randomized controlled trials (RCTs). Data search was performed in PubMed, Embase, Cochrane library, Scopus, Web of Science, and MedRxiv. Included articles were limited to RCTs on COVID-19 vaccines. A total of 73,633 subjects from 14 articles were included to compare the risks of adverse events following immunization (AEFI) after vaccinating different COVID-19 vaccines. Pooled risk ratios (RR) of total AEFI for inactivated vaccine, viral-vectored vaccine, and mRNA vaccine were 1.34 [95% confidence interval (CI) 1.11-1.61, P < 0.001], 1.65 (95% CI 1.31-2.07, P < 0.001), and 2.01 (95% CI 1.78-2.26, P < 0.001), respectively. No significant differences on local and systemic AEFI were found between the first dose and second dose. In addition, people aged ≤ 55 years were at significantly higher risk of AEFI than people aged ≥ 56 years, with a pooled RR of 1.25 (95% CI 1.15-1.35, P < 0.001). CONCLUSIONS: The safety and tolerance of current COVID-19 vaccine candidates are acceptable for mass vaccination, with inactivated COVID-19 vaccines candidates having the lowest reported AEFI. Long-term surveillance of vaccine safety is required, especially among elderly people with underlying medical conditions.


Subject(s)
COVID-19 Vaccines/adverse effects , COVID-19/prevention & control , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 Vaccines/administration & dosage , Female , Humans , Male , Middle Aged , Randomized Controlled Trials as Topic , Young Adult
4.
Front Med (Lausanne) ; 7: 321, 2020.
Article in English | MEDLINE | ID: covidwho-633920

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019 and quickly spread throughout China and the rest of the world. Many mathematical models have been developed to understand and predict the infectiousness of COVID-19. We aim to summarize these models to inform efforts to manage the current outbreak. Methods: We searched PubMed, Web of science, EMBASE, bioRxiv, medRxiv, arXiv, Preprints, and National Knowledge Infrastructure (Chinese database) for relevant studies published between 1 December 2019 and 21 February 2020. References were screened for additional publications. Crucial indicators were extracted and analysed. We also built a mathematical model for the evolution of the epidemic in Wuhan that synthesised extracted indicators. Results: Fifty-two articles involving 75 mathematical or statistical models were included in our systematic review. The overall median basic reproduction number (R0) was 3.77 [interquartile range (IQR) 2.78-5.13], which dropped to a controlled reproduction number (Rc) of 1.88 (IQR 1.41-2.24) after city lockdown. The median incubation and infectious periods were 5.90 (IQR 4.78-6.25) and 9.94 (IQR 3.93-13.50) days, respectively. The median case-fatality rate (CFR) was 2.9% (IQR 2.3-5.4%). Our mathematical model showed that, in Wuhan, the peak time of infection is likely to be March 2020 with a median size of 98,333 infected cases (range 55,225-188,284). The earliest elimination of ongoing transmission is likely to be achieved around 7 May 2020. Conclusions: Our analysis found a sustained Rc and prolonged incubation/ infectious periods, suggesting COVID-19 is highly infectious. Although interventions in China have been effective in controlling secondary transmission, sustained global efforts are needed to contain an emerging pandemic. Alternative interventions can be explored using modelling studies to better inform policymaking as the outbreak continues.

5.
J Infect ; 80(6): 656-665, 2020 06.
Article in English | MEDLINE | ID: covidwho-47365

ABSTRACT

OBJECTIVE: To better inform efforts to treat and control the current outbreak with a comprehensive characterization of COVID-19. METHODS: We searched PubMed, EMBASE, Web of Science, and CNKI (Chinese Database) for studies published as of March 2, 2020, and we searched references of identified articles. Studies were reviewed for methodological quality. A random-effects model was used to pool results. Heterogeneity was assessed using I2. Publication bias was assessed using Egger's test. RESULTS: 43 studies involving 3600 patients were included. Among COVID-19 patients, fever (83.3% [95% CI 78.4-87.7]), cough (60.3% [54.2-66.3]), and fatigue (38.0% [29.8-46.5]) were the most common clinical symptoms. The most common laboratory abnormalities were elevated C-reactive protein (68.6% [58.2-78.2]), decreased lymphocyte count (57.4% [44.8-69.5]) and increased lactate dehydrogenase (51.6% [31.4-71.6]). Ground-glass opacities (80.0% [67.3-90.4]) and bilateral pneumonia (73.2% [63.4-82.1]) were the most frequently reported findings on computed tomography. The overall estimated proportion of severe cases and case-fatality rate (CFR) was 25.6% (17.4-34.9) and 3.6% (1.1-7.2), respectively. CFR and laboratory abnormalities were higher in severe cases, patients from Wuhan, and older patients, but CFR did not differ by gender. CONCLUSIONS: The majority of COVID-19 cases are symptomatic with a moderate CFR. Patients living in Wuhan, older patients, and those with medical comorbidities tend to have more severe clinical symptoms and higher CFR.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , COVID-19 , China/epidemiology , Coronavirus Infections/blood , Coronavirus Infections/diagnostic imaging , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/mortality , Risk Factors
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