Background: Globally, suicide accounts for 75% in low and middle-income countries (LMICs). Though the magnitude of suicidal behavior in High-income Countries (HIC) is higher relative to the general population, limited studies had explored suicidal behavior among medical outpatients in LMICs including this locality. Suicidal behaviors among people with the chronic medical illness are one of the commonest psychiatric emergencies that demand a major health concern by researchers and mental health task forces. People with chronic medical illnesses show suicidal ideation and attempt which are fatal problems to end life. Therefore, this study will address the gaps by determining the magnitude of suicidal behavior among Diabetes Mellitus (DM) patients in an outpatient setting of Alamata General Hospital (AGH). Methods: Institutional based cross-sectional study was conducted among medical patients attending a chronic care clinic in Alamata general Hospital from May to June 2019. A sample of 146 DM patients who were attending an outpatient chronic care clinic was included in the study. Suicidal behavior was assessed by the World Health Organization (WHO) suicidal behavior assessment through software called Statistical Package for Social Science (SPSS) Version 25. Results: The magnitude of suicidal behavior among Diabetes Mellitus patients at AGH was 30.8%, 15.8% had suicidal ideation, 14.4% had a suicidal attempt and 15.1% of them had the plan to commit suicide. Conclusion: The prevalence of suicidal behavior was found to be significantly high in Diabetes Mellitus patients. Hence, it is important to conduct more interventions to assess the suicidal behavior symptoms among Diabetes Mellitus patients.

Up-to-date and reliable land use/land cover (LULC) information forms an essential component of local and regional planning. So, the aim of the present study is to analyze and quantitatively evaluate LULC changes in Abaya-Gelana area between 1986 and 2015 using remotely sensed data and techniques. To realize the aforementioned objective, cloud free orthorectified multispectral land sat 5 thematic mapper (TM) acquired in 1986 and land sat 8 operational land imager (OLI) acquired in 2015 were used for LULC change detection. In addition to the land sat images, collateral information was obtained from topographic maps, field data, and Google earth images. After digital image processing and visual interpretation of the land sat images, supervised classification with maximum likelihood algorithm was applied and LULC maps for 1986 and 2015 were produced. Finally, post-classification comparison was made to analyze LULC changes over the past three decades. The results of the change detection analysis show that there is obvious deforestation problem in the study area which is manifested by the reduction of bushland by 46.89% and an increase in bareland by 253.34% within 29 years. Besides, a reduction in grass land, a remarkable increase in cultivated land, urban expansion, an increase in water surface are among the major LULC changes over the past three decades.

Background: Coronavirus (COVID-19) is an illness caused by a virus that can spread from person to person. The virus that causes COVID-19 is a new coronavirus that has spread throughout the world. COVID-19 symptoms can range from mild (or no symptoms) to severe illness. In late December 2019, investigation of a cluster of pneumonia cases of unknown origin in Wuhan, China resulted in identification of a novel coronavirus. The virus is distinct from both Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV), although closely related. Objective: To assess respiratory disease screening as an adverse effect and associated factors of COVID-19 recovered patients from a treatment center in Mekelle, Tigray, Ethiopia. Methods: A community based quantitative study design was conducted among 600 samples in Mekelle town, Tigray, Ethiopia. Data were collected using a structured and semi-structured questionnaire. Associations between dependent and independent variables were tested using logistic regression with the assumptions of p-values < 0.05 and confidence interval 95% and considered to be statistically significant. Results: The prevalence of respiratory disease after screening using CRQ was 24.3%. Variable like who read and wrote [AOR=2.859, 95% CI: 1.349-6.063, P=0.006]. COVID-19 symptoms such as those who had shortness of breathing [AOR=3.485, 95% CI: 1.776-6.838, P=0.001], sore throat [AOR=4.645, 95% CI: 2.107-10.242, P=0.001], and chest pain pressure was AOR=3.453, 95%CI: 1.484-8.037, P=0.04] were significant factor for respiratory disease. Conclusion: The study found that the prevalence of respiratory disease after screening using CRQ was 24.3%. Variables such as read and write, shortness of breathing, sore throat, and pneumonia were significant factors for respiratory disease.