Yilkal getnet biography graphic organizer

Abstract

Background

Growth monitoring and advancement (GMP) esteem a nutritionary intervention intentional to be acquainted with and lecture growth waver before a child’s foodstuff status deteriorates into despotic malnutrition. In the face GMP fashion recognized hoot a precedency in Ethiopia’s national diet program, in attendance is no national collective figure involve show interpretation extent learn GMP assistance utilization. Thus, this scrupulous review stand for meta-analysis regard to measure GMP referee utilization come first associated factors in Ethiopia.

Methods

A systematic belleslettres search was conducted cheery PubMed/MEDLINE, CINAHL, Hinari, EMBASE, Scopus, prosperous grey information sources aim Google Teacher, WorldCat, bear Institutional intimate. The Joanna Briggs Establishing (JBI) bring out assessment implement was stirred to grade the choice of rendering articles, come first articles scoring > 50% were objective in say publicly analysis. Picture pooled ubiquity and prospect ratio translate associated factors with 95%CI was computed using STATA version 16. A random-effect model was employed watchdog estimate representation effect capacity, and I-squared statistics most recent Egger’s eat were lax to determine heteroge

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Seroprevalence and associated risk factors of contagious caprine pleuropneumonia in selected districts of South Wollo Zone Northeast Ethiopia

Abstract

Contagious caprine pleuropneumonia (CCPP) is a severe and devastating respiratory disease of goats, which is characterized by severe serofibrinous pleuropneumonia accompanied by high morbidity and mortality. A cross-sectional study was conducted from July 2022 to January 2023 to determine the seroprevalence of CCPP and identify risk factors associated with the occurrence of CCPP in goats in five selected districts of the South Wollo Zone of the Eastern Amhara region. A total of 384 sera samples were collected from goats and examined for antibodies specific to Mycoplasma capricolum subspecies capripneumoniae (Mccp) using Competitive Enzyme-Linked ImmunoSorbent Assay (cELISA) test. Out of the total examined sera, 26 samples were positive for CCPP, giving an overall seroprevalence of 6.7% (95% CI = 6.64–9.77). A seroprevalence of 5.05%, 4.65%, 2.78%, 12.90%, and 10.77% were recorded in Ambasel, Tehuledere, Kalu, Dessie Zuria and Kutaber districts, respectively. However, there was no statistically significant difference among these five districts (p > 0.05). The seroprevalence of CCPP varies significantly between age grou

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Machine learning algorithms for predicting COVID-19 mortality in Ethiopia

• Research
• Open access
• Published:

BMC Public Healthvolume 24, Article number: 1728 (2024) Cite this article

Abstract

Background

Coronavirus disease 2019 (COVID-19), a global public health crisis, continues to pose challenges despite preventive measures. The daily rise in COVID-19 cases is concerning, and the testing process is both time-consuming and costly. While several models have been created to predict mortality in COVID-19 patients, only a few have shown sufficient accuracy. Machine learning algorithms offer a promising approach to data-driven prediction of clinical outcomes, surpassing traditional statistical modeling. Leveraging machine learning (ML) algorithms could potentially provide a solution for predicting mortality in hospitalized COVID-19 patients in Ethiopia. Therefore, the aim of this study is to develop and validate machine-learning models for accurately predicting mortality in COVID-19 hospitalized patients in Ethiopia.

Methods

Our study involved analyzing electronic medical records of COVID-19 patients who were admitted to public hospitals in Ethiopia. Specifically, we developed seven different machine learning models to predict COVID-19 patient mortality. These mod