S. Garba

944 citations
37 papers · 719 · h-index 13

Impact in

Papers in

S. Garba

33 papers receiving 691 citations

Peers

S. Garba
Comparison fields: 5 of 75
  • Modeling and Simulation 410
  • Public Health, Environmental and Occupational Health 525
  • Infectious Diseases 184
  • Genetics 211
  • Animal Science and Zoology 36
Replace Festus Abiodun Oguntolu with:
Festus Abiodun Oguntolu Nigeria
J. Mugisha Uganda
Baba Seidu Ghana
Livingstone S. Luboobi Uganda
Mayowa M. Ojo South Africa
Abid Ali Lashari Pakistan
Mini Ghosh India
Eric Okyere Ghana
Tailei Zhang China
Getachew Teshome Tilahun Ethiopia
S. Garba relative to Festus Abiodun Oguntolu Nigeria Festus Abiodun Oguntolu's profile →
Citations per field
00.5×20×40×53×
Festus Abiodun Oguntolu · 1×
Citations per year

Countries citing papers authored by S. Garba

Since Specialization
Citations

This map shows the geographic impact of S. Garba'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 S. Garba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Garba more than expected).

Fields of papers citing papers by S. Garba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Garba. 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 S. Garba. The network helps show where S. Garba may publish in the future.

Co-authors

The 20 scholars most cited alongside S. Garba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S. Garba Line = papers co-authored together S. Garba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008273
2 202082
3 201247
4 201036
5 201735
6 201034
7 201224
8 201321
9 201120
10 201418
11 201916
12 201414
13 201512
14 20139
15 20188
16 20208
17 20127
18 20187
19 20207
20
Relative Importance of External Quality Attributes of Shell Eggs: A Consumer Preference Approach
20125

About S. Garba

S. Garba is a scholar working on Public Health, Environmental and Occupational Health, Genetics, Modeling and Simulation, Infectious Diseases and Animal Science and Zoology, having authored 37 papers that have together received 719 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (21 papers), COVID-19 epidemiological studies (14 papers), Evolution and Genetic Dynamics (14 papers), Genetic and phenotypic traits in livestock (5 papers), Rangeland Management and Livestock Ecology (3 papers), Viral Infections and Vectors (3 papers), Animal Diversity and Health Studies (3 papers) and Garlic and Onion Studies (2 papers). The work is most often cited by research in Modeling and Simulation (410 citations), Public Health, Environmental and Occupational Health (525 citations), Infectious Diseases (184 citations), Genetics (211 citations) and Animal Science and Zoology (36 citations). S. Garba has collaborated with scholars based in South Africa, Nigeria and Canada. Frequent co-authors include Abba B. Gumel, Mohd Rizam Abu Bakar, Jean Lubuma, Mohammad A. Safi, Berge Tsanou, U. A. Birnin-Yauri, Roumen Anguelov, Akeem Adebayo Jimoh, E. B. Ibitoye and Alun L. Lloyd. Their work appears in journals such as Mathematical Methods in the Applied Sciences, Mathematical Biosciences, Veterinary Record, Mathematical and Computer Modelling and Applied Mathematics and Computation.

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.

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