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Background The coronavirus (COVID-19) pandemic was reported from Wuhan, China, on December 31, 2019, and the pandemic was spread to more than 212 countries in the globe. This meta-analysis aimed to assess the pooled incidence of COVID-19 complications and to identify the association between the incidence of complications and age. Methods Comprehensive databases, PubMed, Hinari, and Google Scholar, were used to locate potential articles for this review. Data were extracted using Microsoft Excel and imported to the STATA/MP version 16.0 software for analysis. Heterogeneity between studies was assessed using the Cochrane Q test statistics and I2 test, and small study effect was checked using Egger’s statistical test at 5% significant level. Sensitivity analysis was checked. A random-effects model was conducted to estimate the pooled incidence of COVID-19 complications. Univariate meta-regression was conducted to identify the association between the mean ages with each complication. Results From the total of 1237 studies, 12 studies were included with a total of 3064 COVID-19 patients. The most complications were acute respiratory distress syndrome (30.93%, 95%CI 21.3–40.6%) followed by acute liver injury (22.8%, 95%CI 14–31.5%), shock (10.9%, 95%CI 7.4–14.4%), acute kidney injury (7%, 95%CI 3.8–10.4%), and acute cardiac injury (6.4%, 95%CI 2.8–15.6%). Univariate meta-regression revealed that as the mean age increased by 1 year, the incidence of acute respiratory distress syndrome, acute kidney injury, acute cardiac injury, and shock increased by a factor of 2.9 (β = 2.9, 95%CI 2.4–3.4, adjusted R2 = 88), 0.4 (β = 0.4, 95%CI 0.04–0.72, adjusted R2 = 54), 1.6 (β = 1.6, 95%CI 1.1–2.1, adjusted R2 = 85), and 1.1 (β = 1.1, 95%CI 0.8–1.5, adjusted R2 = 26) times respectively. Conclusion Significant complications of COVID-19 viral infections were reported. Older populations were a high-risk group of developing adverse complications as compared to their counterparts. Health care professionals should give primary attention to those risk group individuals.

Background Person-centered maternity care is providing care that is respectful and responsive to individual women’s preferences, needs, and values and ensuring that their values guide all clinical decisions during childbirth. Although person-centered health care is one of the factors that increase client satisfaction and increased health service utilization in Ethiopia, little is known about predictors of person-centered maternity care. Therefore, the aim of this study was to identify the determinant factors of person-centered maternity care among mothers who gave birth in selected health facilities in Dessie town, Northeastern, Ethiopia. Methods A community-based cross-sectional study was conducted with a total of 317 study participants at Dessie town selected by a simple random sampling technique. The data was coded and entered Epi-data version 4.4 and analyzed using SPSS version 23. Descriptive statistics was presented using tables and figures. Multivariable linear regression analysis was used to identify factors associated with Person-Centered Maternity Care. Two sides P-value < 0.05 was taken to declare statistically significant. Results Overall, 310 study participants participated with a response rate of 97.8%. In multivariable linear regression, rural residence (β = -4.12; 95% CI: -7.60, -0.67), family average monthly income ≤ 3000 birr (β = -6.20, 95% CI: -9.40, -3.04), night time delivery(β = -2.98, 95%CI: -5.90, -0.06), dead fetus outcome during delivery (β = -12.7; 95% CI: -21.80, -3.50), and 2–7 days health facility length of stay (β = -5.07, 95% CI: -9.20, -0.92) were significantly decreased Person Center Maternity Care score, whereas private health institution delivery (β = 14.13, 95% CI: 7.70, 20.60) is significantly increased Person centered maternity care score. Conclusions This study revealed that most of the factors that affect person-centered maternity care are modifiable factors. Therefore, Primary attention should be given to improve the quality of care through effective communication between clients and providers at each level of the health care delivery system to increase the uptake of high-quality facility-based births.

IntroductionInternet addiction is characterized by excessive and uncontrolled use of the internet affecting everyday life. Adolescents are the primary risk group for internet addiction. Data on internet addiction is lacking in Africa. Thus, this review aimed to determine the pooled prevalence of internet addiction and its associated factors among high school and university students in Africa.MethodsA comprehensive literature search was conducted using electronic databases (PubMed/MEDLINE, Web of science, Hinari, and Google scholar) to locate potential studies. Heterogeneity between studies was checked using Cochrane Q test statistics and I2 test statistics and small-study effects were checked using Egger's statistical test at a 5% significance level. A sensitivity analysis was performed. A random-effects model was employed to estimate the pooled prevalence and associated factors of internet addiction among students. The primary outcome of measure of this review was the prevalence of internet addiction and the secondary outcome of measures are the factors associated with internet addiction.ResultsA total of 5,562 studies were identified among the five databases. Of these, 28 studies from 10 countries with 14,946 high school and university students were included in this review. The overall pooled prevalence of internet addiction among the students was 34.53% [95% Confidence Interval (CI): 26.83, 42.23, I2 = 99.20%]. Male sex [Pooled Odds Ratio (POR) = 1.92, 95% CI:1.43, 2.57 I2 = 0.00], urban residence (POR = 2.32, 95% CI:1.19, 4.53, I2 = 59.39%), and duration of daily internet use for more than 4 h (POR = 2.25, 95% CI:1.20, 4.21, I2 = 0.00%, were significantly associated with internet addiction among adolescents.ConclusionAlmost one-third of university and high school students in Africa are addicted to the internet. Male students, those from urban areas, and those who use the internet for more than 4 h per day have higher odds of internet addiction. Thus, we recommend that health planners and policymakers pay attention to the use of the internet and internet addiction in Africa.