Toward the design of a tailored training course for birth assistance: an Ethiopian experience.

Simulation in healthcare has already demonstrated extraordinary potential in high-income countries. However, to date, few authors have explored the possibility of applying simulation-based training in African settings, highlighting the necessity of need-based training protocols capable of addressing economic, social, and cultural aspects. In this framework, this research investigates the main features a simulation training course on umbilical cord care and placenta management should have to be considered effective and sustainable in an African healthcare environment. Local facilitators were identified as the best resources for defining course contents and providing technical lectures to mitigate cultural, linguistic, and social issues. For the training program, the design of a new low-cost medium-fidelity simulator was explored and a preliminary evaluation was performed. Finally, the propensity of 25 students to attend a simulation training course was investigated using a questionnaire. The attitude of the enrolled students was positive, endorsing the future introduction of simulation training into the educational offers of Ethiopian colleges

Track E Implementation Science, Health Systems and Economics

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138412/1/jia218443.pd

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Lightweight Model for Botnet Attack Detection in Software Defined Network-Orchestrated IoT

The Internet of things (IoT) is being used in a variety of industries, including agriculture, the military, smart cities and smart grids, and personalized health care. It is also being used to control critical infrastructure. Nevertheless, because the IoT lacks security procedures and lack the processing power to execute computationally costly antimalware apps, they are susceptible to malware attacks. In addition, the conventional method by which malware-detection mechanisms identify a threat is through known malware fingerprints stored in their database. However, with the ever-evolving and drastic increase in malware threats in the IoT, it is not enough to have traditional antimalware software in place, which solely defends against known threats. Consequently, in this paper, a lightweight deep learning model for an SDN-enabled IoT framework that leverages the underlying IoT resource-constrained devices by provisioning computing resources to deploy instant protection against botnet malware attacks is proposed. The proposed model can achieve 99% precision, recall, and F1 score and 99.4% accuracy. The execution time of the model is 0.108 milliseconds with 118 KB size and 19,414 parameters. The proposed model can achieve performance with high accuracy while utilizing fewer computational resources and addressing resource-limitation issues

The effects of ANC follow up on essential newborn care practices in east Africa: a systematic review and meta-analysis

Abstract In the situation of high maternal morbidity and mortality in Sub-Saharan Africa, less than 80% of pregnant women receive antenatal care services. To date, the overall effect of antenatal care (ANC) follow up on essential newborn practice have not been estimated in East Africa. Therefore, this study aims to identify the effect of ANC follow up on essential newborn care practice in East Africa. We reported this review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). We searched articles using PubMed, Cochrane library, African journal online (AJOL), and HINARI electronic databases as well as Google/Google scholar search engines. Heterogeneity and publication bias between studies were assessed using I2 test statistics and Egger’s significance test. Forest plots were used to present the findings. In this review, 27 studies containing 34,440 study participants were included. The pooled estimate of essential newborn care practice was 38% (95% CI 30.10–45.89) in the study area. Women who had one or more antenatal care follow up were about 3.71 times more likely practiced essential newborn care compared to women who had no ANC follow up [OR 3.71, 95% CI 2.35, 5.88]. Similarly, women who had four or more ANC follow up were 2.11 times more likely practiced essential newborn care compared to women who had less than four ANC follow up (OR 2.11, 95% CI 1.33, 3.35). Our study showed that the practice of ENBC was low in East Africa. Accordingly, those women who had more antenatal follow up were more likely practiced Essential newborn care. Thus, to improve the practice of essential newborn care more emphasis should be given on increasing antenatal care follow up of pregnant women in East Africa