J. Mugisha

1.2k citations
93 papers · 892 · h-index 16

Impact in

Papers in

J. Mugisha

82 papers receiving 830 citations

Peers

J. Mugisha
Comparison fields: 5 of 97
  • Modeling and Simulation 302
  • Public Health, Environmental and Occupational Health 485
  • Virology 43
  • Infectious Diseases 162
  • General Agricultural and Biological Sciences 73
Replace Fahad Al Basir with:
Fahad Al Basir India
Lorenzo Pellis United Kingdom
D.J. Rogers United Kingdom
Eve Miguel France
M.G. Garner Australia
Nathan Breit United States
Weerapong Thanapongtharm Thailand
Livingstone S. Luboobi Uganda
Marisa Peyre France
Elisabeta Vergu France
J. Mugisha relative to Fahad Al Basir India Fahad Al Basir's profile →
Citations per field
00.5×7.3×
Fahad Al Basir · 1×
Citations per year

Countries citing papers authored by J. Mugisha

Since Specialization
Citations

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

Fields of papers citing papers by J. Mugisha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside J. Mugisha, 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 J. Mugisha Line = papers co-authored together J. Mugisha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200789
2 200958
3 201041
4 202138
5 201633
6 201331
7 200730
8 201826
9 201425
10 200523
11 200721
12 202119
13 201818
14 200518
15 201216
16 200715
17 202015
18 201515
19 201514
20
Mathematical Model for Malaria and Meningitis Co-infection among Children
201114

About J. Mugisha

J. Mugisha is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation, Infectious Diseases, Genetics and Agronomy and Crop Science, having authored 93 papers that have together received 892 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (32 papers), COVID-19 epidemiological studies (19 papers), Evolution and Genetic Dynamics (16 papers), Viral Infections and Vectors (12 papers), Agricultural Innovations and Practices (9 papers), Animal Disease Management and Epidemiology (7 papers), HIV Research and Treatment (7 papers) and Agriculture and Rural Development Research (6 papers). The work is most often cited by research in Modeling and Simulation (302 citations), Public Health, Environmental and Occupational Health (485 citations), Virology (43 citations), Infectious Diseases (162 citations) and General Agricultural and Biological Sciences (73 citations). J. Mugisha has collaborated with scholars based in Uganda, South Africa and Kenya. Frequent co-authors include Livingstone S. Luboobi, Julius Tumwiine, Ibrahim M. Elmojtaba, Amos Ssematimba, Celestino Obua, Mark Kimathi, Obiora Cornelius Collins, E. Karamura, Kevin J. Duffy and M. W. Shaw. Their work appears in journals such as Applied Mathematics and Computation, Mathematical Biosciences, PLoS ONE, Heliyon and Nonlinear Analysis Real World Applications.

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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