Dataset Information

COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

ABSTRACT:

Background

COVID-19 has caused a global public health crisis affecting most countries, including Ethiopia, in various ways. This study maps the vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia.

Methods

Thirty-eight potential indicators of vulnerability to COVID-19 infection, case severity and likelihood of death, identified based on a literature review and the availability of nationally representative data at a low geographic scale, were assembled from multiple sources for geospatial analysis. Geospatial analysis techniques were applied to produce maps showing the vulnerability to infection, case severity and likelihood of death in Ethiopia at a spatial resolution of 1 km×1 km.

Results

This study showed that vulnerability to COVID-19 infection is likely to be high across most parts of Ethiopia, particularly in the Somali, Afar, Amhara, Oromia and Tigray regions. The number of severe cases of COVID-19 infection requiring hospitalisation and intensive care unit admission is likely to be high across Amhara, most parts of Oromia and some parts of the Southern Nations, Nationalities and Peoples' Region. The risk of COVID-19-related death is high in the country's border regions, where public health preparedness for responding to COVID-19 is limited.

Conclusion

This study revealed geographical differences in vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia. The study offers maps that can guide the targeted interventions necessary to contain the spread of COVID-19 in Ethiopia.

SUBMITTER: Alene KA

PROVIDER: S-EPMC7896372 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

Alene Kefyalew Addis KA Gelaw Yalemzewod Assefa YA Fetene Dagnachew Muluye DM Koye Digsu N DN Melaku Yohannes Adama YA Gesesew Hailay H Birhanu Mulugeta Molla MM Adane Akilew Awoke AA Muluneh Muluken Dessalegn MD Dachew Berihun Assefa BA Abrha Solomon S Aregay Atsede A Ayele Asnakew Achaw AA Bezabhe Woldesellassie M WM Gebremariam Kidane Tadesse KT Gebremedhin Tesfaye T Gebremedhin Amanuel Tesfay AT Gebremichael Lemlem L Geleto Ayele Bali AB Kassahun Habtamu Tilahun HT Kibret Getiye Dejenu GD Leshargie Cheru Tesema CT Mekonnen Alemayehu A Mirkuzie Alemnesh H AH Mohammed Hassen H Tegegn Henok Getachew HG Tesema Azeb Gebresilassie AG Tesfay Fisaha Haile FH Wubishet Befikadu Legesse BL Kinfu Yohannes Y

BMJ open 20210218 2

<h4>Background</h4>COVID-19 has caused a global public health crisis affecting most countries, including Ethiopia, in various ways. This study maps the vulnerability to infection, case severity and likelihood of death from COVID-19 in Ethiopia.<h4>Methods</h4>Thirty-eight potential indicators of vulnerability to COVID-19 infection, case severity and likelihood of death, identified based on a literature review and the availability of nationally representative data at a low geographic scale, were ...[more]

PMID: 33602713

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Project description:ObjectiveIt was necessary to understand the determinants of severe COVID-19 in order to deliver targeted healthcare services to prevent further complications and mortality. Identifying the factors associated with severe COVID-19 in Addis Ababa, Ethiopia, is the aim of this study.DesignA case-control study was conducted from October 2021 to March 2022.SettingThe study was conducted at three public COVID-19 treatment centres including Ekka Kotebe General, St. Peter Hospital and St. Paul's Hospital.ParticipantsThe study participants were COVID-19 patients admitted to three COVID-19 treatment centres. Cases were patients admitted with severe COVID-19, and controls were patients with mild or moderate COVID-19. A total of 306 patients (153 cases and 153 controls) selected by simple random sampling technique participated in this study.Outcome measures and analysisData were collected by a face-to-face or telephone interviewer using a structured questionnaire. COVID-19 admission category, clinical and biomedical characteristics and comorbidity-related data were extracted from the participant's medical record. Multivariable binary logistic regression analysis was used to identify predictors of COVID-19 severity.ResultsThe odds of being old were 4.54 times higher among severe COVID-19 cases (adjusted odds ratio (AOR)=4.54, 95% CI=2.499 to 8.24), the odds of being male were 2.72 times higher among severe COVID-19 cases (AOR=2.72, 95% CI=1.46 to 5.057), being vaccinated for COVID-19 decreases the severity by 55.1% (AOR=0.449, 95% CI=0.251 to 0.801), having good knowledge about COVID-19 decreases by 65% (AOR=0.35%, 95% CI=0.195 to 0.63) among patients with severe COVID-19, the odds of being diabetic were 10.2 times higher among severe COVID-19 cases (AOR=10.2, 95% CI=4.596 to 22.61) and the odds of being hypertensive were 2.3 times higher among severe COVID-19 cases (AOR=2.26, 95% CI=1.092 to 4.685).ConclusionMale, older age, diabetes or hypertension comorbidity, COVID-19 vaccination and having inadequate knowledge about COVID-19 were determinant factors of severe COVID-19.

Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

Dataset Information

COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

Background

Methods

Results

Conclusion

Publications

COVID-19 in Ethiopia: a geospatial analysis of vulnerability to infection, case severity and death.

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