John Mwaba

930 citations
24 papers · 319 · h-index 11

Impact in

Papers in

    • Vibrio bacteria research studies 15
    • Escherichia coli research studies 3
    • Influenza Virus Research Studies 5

John Mwaba

21 papers receiving 302 citations

Peers

John Mwaba
Comparison fields: 5 of 68
  • Endocrinology 208
  • Molecular Medicine 69
  • Modeling and Simulation 43
  • Applied Microbiology and Biotechnology 15
  • Food Science 107
Replace David Opare with:
David Opare Ghana
Georges Dahourou United States
Vu Thuy Duong Vietnam
Sulochana Manandhar Nepal
José Paulo Langa Mozambique
S. J. Utsalo Nigeria
Octavie Lunguya Belgium
James Meiring United Kingdom
Wenjia Xiao China
Jacquelyn McCormick United Kingdom
John Mwaba relative to David Opare Ghana David Opare's profile →
Citations per field
00.5×3.3×
David Opare · 1×
Citations per year

Countries citing papers authored by John Mwaba

Since Specialization
Citations

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

Fields of papers citing papers by John Mwaba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201467
2 200652
3 202028
4 202122
5 201820
6 201719
7 201717
8 201812
9 202012
10 202111
11 202210
12 20238
13 20207
14 20197
15 20226
16 20235
17 20245
18 20164
19 20213
20 20173

About John Mwaba

John Mwaba is a scholar working on Endocrinology, Epidemiology, Infectious Diseases, Food Science and Molecular Medicine, having authored 24 papers that have together received 319 indexed citations. Recurring topics across this work include Vibrio bacteria research studies (15 papers), Salmonella and Campylobacter epidemiology (7 papers), Antibiotic Resistance in Bacteria (6 papers), Influenza Virus Research Studies (5 papers), Vaccine Coverage and Hesitancy (4 papers), Viral gastroenteritis research and epidemiology (4 papers), Escherichia coli research studies (3 papers) and COVID-19 epidemiological studies (2 papers). The work is most often cited by research in Endocrinology (208 citations), Molecular Medicine (69 citations), Modeling and Simulation (43 citations), Applied Microbiology and Biotechnology (15 citations) and Food Science (107 citations). John Mwaba has collaborated with scholars based in Zambia, United States and Ghana. Frequent co-authors include James Mwansa, Geoffrey Kwenda, Roma Chilengi, Michelo Simuyandi, Caroline Cleopatra Chisenga, Thandavarayan Ramamurthy, Munirul Alam, M. Ansaruzzaman, N. A. Bhuiyan and G. Balakrish Nair. Their work appears in journals such as PLoS ONE, PLoS Medicine, Epidemiology and Infection, International Health and Journal of Clinical Microbiology.

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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