This map shows the geographic impact of Wondimu Ayele's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wondimu Ayele with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wondimu Ayele more than expected).
This network shows the impact of papers produced by Wondimu Ayele. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wondimu Ayele. The network helps show where Wondimu Ayele may publish in the future.
Co-authorship network of co-authors of Wondimu Ayele
This figure shows the co-authorship network connecting the top 25 collaborators of Wondimu Ayele.
A scholar is included among the top collaborators of Wondimu Ayele based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Wondimu Ayele. Wondimu Ayele is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Taye, Girma, et al.. (2021). Quality of Primary Health Care during COVID-19 Pandemic in Addis Ababa Ethiopia: Patients-side and facility level assessment. Ethiopian Journal of Health Development. 35(1). 98–107.1 indexed citations
7.
Taye, Girma, et al.. (2021). The Plight of COVID-19 in Ethiopia: Describing Pattern, Predicting Infections, Recoveries and Deaths Using Initial Values from Different Sources. Ethiopian Journal of Health Development. 35(1). 82–89.1 indexed citations
8.
Ayele, Wondimu, et al.. (2021). COVID 19 Epidemic Trajectory Modeling Results for Ethiopia. Ethiopian Journal of Health Development. 35(1). 25–32.2 indexed citations
9.
Taye, Girma, et al.. (2021). Hospitalization, Recovery, Death, incubation period and Severity of COVID-19: A Systematic Review. Ethiopian Journal of Health Development. 35(1). 76–81.1 indexed citations
10.
Taye, Girma, et al.. (2021). Improving the Quality of Clinical Coding through Mapping of National Classification of Diseases (NCoD) and International Classification of Disease (ICD-10).. Ethiopian Journal of Health Development. 35(1).2 indexed citations
11.
Taye, Girma, et al.. (2021). The Ethiopian Health Information System: Where are we? And where are we going?. Ethiopian Journal of Health Development. 35(1).3 indexed citations
12.
Ayele, Wondimu, et al.. (2021). Data quality and it’s correlation with Routine health information system structure and input at public health centers in Addis Ababa, Ethiopia.. Ethiopian Journal of Health Development. 35(1).4 indexed citations
13.
Taye, Girma, et al.. (2021). A mixed-methods assessment of Routine Health Information System (RHIS) Data Quality and Factors Affecting it, Addis Ababa City Administration, Ethiopia, 2020. Ethiopian Journal of Health Development. 35(1).11 indexed citations
14.
Ayele, Wondimu, et al.. (2021). Patterns of essential health services utilization and routine health information management during Covid-19 pandemic at primary health service delivery point Addis Ababa, Ethiopia. Ethiopian Journal of Health Development. 35(1). 90–97.7 indexed citations
15.
Ayele, Wondimu, et al.. (2021). Implementation of Human Development Model Impact on Data Quality and Information Use in Addis Ababa, Ethiopia. Ethiopian Journal of Health Development. 35(1).
Taye, Girma, et al.. (2021). Assessment of Routine Health information utilization and its associated factors among Health Professionals in Public Health Centers of Addis Ababa, Ethiopia. Ethiopian Journal of Health Development. 35(1).5 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.