The objective of this study was to analyze the relationship between antisocial behavior and academic achievement of high school students in Jimma town. Participants were 524 students 14-19 years old from government and private secondary schools. Cross sectional research designed was employed. Primary and secondary data were sources of this study. Results indicate that academic achievement was negatively associated with antisocial behavior. The result also shows that there is no significant difference between government and private schools in correlation of academic performance and antisocial behavior.The result also showed that there is a significant difference between male and female students’ academic achievement and antisocial behavior engagement, which is strong in male participants than female participants. To conclude the result showed there is a significant negative correlation between academic achievement and antisocial behavior. Therefore, the researchers recommends further studies to be conducted in the area, teachers also have to implement behavioral monitoring and modification strategies in secondary schools to minimize behavioral problem among students. Teachers, parents and other parties work together for better improvement of students’ academic and behavioral improvement.

Background Since coronavirus disease 2019 emergence, millions were infected and many were dying because of the virus. Clinical features and time to recovery of admitted clients vary across settings. Therefore showing clinical features and recovery time from COVID-19 in a different setting is necessary to design appropriate treatment and preventive measures. So, this study attempted to investigate the clinical features and time to recovery of admitted clients to Dilla University Referral Hospital treatment center, Ethiopia. Methods A retrospective study design was conducted in 220 patients confirmed by real time polymerase chain reaction and admitted to Dilla University Referral Hospital treatment center from September 2020 to July 2021. Data were collected from the patients’ record. Data entry was done by an Epi-Info version 7.2.1.0 and analyzed by Statistical Package for the Social Sciences version 25 software. Descriptive statistics were used for clinical features, and median time to recovery was computed by using Kaplan–Meier. Results Common clinical features were cough 209 (95%), shortness of breath 153 (69.5%), fever 133 (60.5%), headache 75 (34.1%), easy fatigue 68 (30.9%), joint pain 56 (25.5%), tachypnea 197 (89.5%), hypoxia 95 (43.2%), and tachycardia 83 (37.7%). The overall median recovery time for admitted cases was 5 days. There was significant difference between recovery probability of severe and moderate cases, severe and mild cases (p=0.00), who had normal body temperature and hypothermic (p=0.05), who had normal breathing rate and bradypnea patients (p= 0.014). Conclusion COVID-19 patients frequently show cough, shortness of breath, fever, headache, easy fatigue and joint pain. Median time to recovery was 5 days. Having a normal body temperature, normal breathing rate, and severe disease status had statistically significant association with median recovery time. So, close follow up is required for client admitted with severe disease.

Background: Millions were infected and many were dying because of the coronavirus disease 2019, since its emergence. The patients experience asymptomatic, mild, moderate, severe and critical disease with varying signs and symptoms. Decreased lymphocytes and abnormal liver and renal function tests are common among COVID-19 patients. Severe and critical cases show higher number of white blood cells, and neutrophils. However, studies showed different laboratory findings in different disease status. Therefore, this study investigated laboratory findings of COVID-19 admitted patients at Dilla University Referral Hospital treatment center, South Ethiopia. Methods: A retrospective study design was conducted on 220 patients confirmed by real time polymerase chain reaction, and admitted to Dilla University Referral Hospital treatment center from September 2020 to July 2021. Data were collected from the patients' record, and analyzed by GraphPad Prism version 8.0.1.244 software. Descriptive statistics were used to analyze the frequency while independent t-test was used to compare means of each parameter for each disease status. Results: Of the 220 study cases, 120 (54.5%) were severe, 89 (40.5%) were moderate and 11 (5.0%) were mild. One hundred forty (71.1%) of the 197 laboratory tested cases, 87 (77.7%) of severe, and 49 (64.5%) of the moderate cases had neutrophils above normal range. However, 134 (68.0%) of them, 82 (73.2%) of severe and 49 (64.5%) of moderate cases showed decreased lymphocyte level. Most of the cases showed an increased level of aspartate transaminase, alanine transaminase, alkaline phosphatase, total bilirubin, and total calcium. There was statistically significant mean neutrophils (p=0.04), number of white blood cells (p= 0.02), and creatinine level (p=0.00) difference between severe and mild cases. Conclusion: Most of the severe COVID-19 patients showed increased neutrophils, liver function tests; and decreased lymphocytes; suggesting higher inflammation and lymphopenia. Therefore, patients with severe and critical disease status require close follow-up.

We would like to thank you for giving us the chance to respond to the letter "COVID-19 clinical features and recovery time: Factors affecting the outcome". We also thank Abdul Moeed, and Zunera Huda for reading, and for their interest to contribute to our article entitled, Clinical Features and Time to Recovery of Admitted COVID-19 Cases at Dilla University Referral Hospital Treatment Center, South Ethiopia. In our study, clinical features like tachycardia and headache were not shown as predictors of recovery time, even though some literatures, as Abdul Moeed, and Zunera Huda stated, showed as a predictive factor of prolonged length to recovery. This may be due to the sample size or sociodemographic factors differences; we analyzed only the records of 220 admitted patients and used only the baseline data that need further analysis with full follow up data.We cannot generalize; the patients admitted in 2021 were more likely to have a shorter pre-discharge holding time compared to those hospitalized in 2020. The reason is: 1. the therapeutic management regimes use and healthcare providers' skills vary from region to region, and from health facility to health facility since the therapeutic management for covid-19 is mainly supportive care. 2. The immunization and immunity status of the patients, and a covid-19 variant involved can also matter. Likewise, severity of the disease can be affected by the variant that caused the disease which can also affects the time to recovery.As our study was retrospective study, we analyzed only the data collected from the patients' records. Therefore, we could not get full information on supportive care practices; that is why we could not include them in to the analysis. We share with them the idea that further large-scale studies with well-developed methodologies are needed.