Incidence and predictors of initial antiretroviral therapy regimen change among children in public health facilities of Bahir Dar City, Northwest Ethiopia, 2021: multicenter retrospective follow-up study.

BACKGROUND: The inconsistent use of antiretroviral therapy can lead to the risk of cross-resistance between drugs. This reduces subsequent antiretroviral drug options. The burden of initial antiretroviral therapy ranges from 11.3% in South Africa to 71.8% in Malaysia. There is evidence that it is important to maintain children's initial antiretroviral therapy regimens. However, the incidence and predictive factors of initial antiretroviral therapy regimen changes in the research context are still unknown in the study setting. So, the study was aimed to assess incidence and predictors of initial antiretroviral therapy regimen changes among children in public health facilities of Bahir Dar city. METHODS: A retrospective follow-up study was conducted in 485 children who received antiretroviral therapy between January 1, 2011 and December 30, 2020. These children were selected using simple random sampling techniques. The data were entered by Epi data 3.1 and the analysis was completed by STATA 14.0. The missing data was treated with multiple imputation method. The data were also summarized by median or mean, interquartile range or standard deviation, proportion and frequency. The survival time was determined using the Kaplan Meier curve. The Cox Proportional Hazard model was fitted to identify predictors of initial antiretroviral therapy regimen change. The global and Shoenfeld graphical proportional hazard tests were checked. Any statistical test was considered significant at P-value < 0.05. Finally, the data were presented in the form of tables, graphics and text. RESULT: Among the 459 study participants, 315 of them underwent initial regimen changes during the study accumulation period. The shortest and longest follow up time of the study were 1 month and 118 months, respectively. The overall incidence rate of initial regimen change was 1.85, 95% CI (1.66-2.07) per 100 person-month observation and the median follow up time of 49 (IQR 45, 53) months. The independent predictors of initial regimen changes were poor adherence (AHR = 1.49, 95%CI [1.16, 1.92]), NVP based regimen (AHR = 1.45, 95%CI [1.15, 1.84]) comparing to EFV based regimen, LPVr based regimen (AHR = 0.22, 95%CI: (0.07, 0.70)) comparing to EFV based regimen, history of tuberculosis (AHR = 1.59, 95%CI [1.14, 2.23]) and being male (AHR = 1.28, 95%CI [1.02, 1.60]). CONCLUSIONS AND RECOMMENDATIONS: In this study, the incidence of initial regimen change was high. The risk of initial regimen change would be increased by being male, poor adherence, having history of tuberculosis and NVP based initial regimen. Therefore, strengthening the health care providers' adherence counseling capability, strengthening tuberculosis screening and prevention strategies and care of initial regimen type choice needs attention in the HIV/AIDS care and treatment programs.

Incubation Period of Severe Acute Respiratory Syndrome Novel Coronavirus 2 that Causes Coronavirus Disease 2019: A Systematic Review and Meta-Analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has currently become a major global public health problem. The prevalence of COVID-19 has increased rapidly worldwide. Because there is no effective COVID-19 vaccine available yet, it is increasingly important to understand the average incubation period of severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, to design appropriate preventive and control strategies. OBJECTIVE: This systematic review and meta-analysis was designed to estimate the pooled average incubation period of SARS-CoV-2, the virus that causes COVID-19. METHODS: We conducted a systematic electronic web-based search of online databases, including PubMed, Google Scholar, Embase, and the World Health Organization Hinari portal. We included peer-reviewed research studies written in the English language on the incubation period of SARS-CoV-2 using pre-defined quality and inclusion criteria. STATA version 15 statistical software was used to analyze the data. Joanna Briggs Institute critical appraisal quality assessment tool for observational studies was utilized to evaluate the included studies. We extracted relevant data and presented in a tabular form. The I 2 test was used to assess heterogeneity across studies. Funnel plot asymmetry and Egger tests were used to check for publication bias. The final effect size was determined by applying a random-effects model. RESULTS: Our search identified 206 studies, amongst which 18 studies, representing 22,595 participants were included in the final analysis. The pooled average incubation period of SARS-CoV-2 was 5.7 days (95% CI, 5.1-6.4). Subgroup analyses by geographic location showed that the pooled average incubation period of SARS-CoV-2 was 6.1 days (95% CI, 5.34-6.94) in China and 4.54 (95% CI, 3.9-5.2) in other countries (Singapore, South Korea, and globally). CONCLUSIONS: The pooled average incubation period of SARS-CoV-2 was about 6 days. The longest incubation period was observed in China. Global health initiatives as well as local health planners should consider this average incubation period when designing optimal prevention and control strategies for SARS-CoV-2. (Curr Ther Res Clin Exp. 2020; 81:XXX-XXX).