Victor Daka

73 papers receiving 633 citations

Peers

Victor Daka
Comparison fields: 5 of 82
  • Applied Microbiology and Biotechnology 247
  • Molecular Medicine 115
  • Geriatrics and Gerontology 41
  • Health 95
  • Modeling and Simulation 38
Replace Ruth Lindizyani Mfune with:
Ruth Lindizyani Mfune Zambia
Moses Mukosha Zambia
Md. Ariful Islam Bangladesh
Kevin Escandón-Vargas Colombia
Jacinda C. Abdul‐Mutakabbir United States
Esther van Kleef United Kingdom
Nandini Shetty United Kingdom
Joshua Havumaki United States
Christopher Finn McQuaid United Kingdom
Donna M Lecky United Kingdom
Victor Daka relative to Ruth Lindizyani Mfune Zambia Ruth Lindizyani Mfune's profile →
Citations per field
00.5×1.5×2.0×
Ruth Lindizyani Mfune · 1×
Citations per year

Countries citing papers authored by Victor Daka

Since Specialization
Citations

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

Fields of papers citing papers by Victor Daka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202356
2 202234
3 202233
4 202231
5 201928
6 202328
7 202223
8 202023
9 202320
10 202219
11 202218
12 202317
13 202417
14 202317
15 202116
16 202116
17 202215
18 202314
19 202413
20 201312

About Victor Daka

Victor Daka is a scholar working on Applied Microbiology and Biotechnology, Infectious Diseases, Health, Clinical Psychology and Epidemiology, having authored 79 papers that have together received 671 indexed citations. Recurring topics across this work include Antibiotic Use and Resistance (18 papers), Vaccine Coverage and Hesitancy (15 papers), COVID-19 and Mental Health (10 papers), Antibiotic Resistance in Bacteria (7 papers), COVID-19 epidemiological studies (6 papers), Global Maternal and Child Health (6 papers), Pharmaceutical and Antibiotic Environmental Impacts (6 papers) and SARS-CoV-2 and COVID-19 Research (6 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (247 citations), Molecular Medicine (115 citations), Geriatrics and Gerontology (41 citations), Health (95 citations) and Modeling and Simulation (38 citations). Victor Daka has collaborated with scholars based in Zambia, United Kingdom and China. Frequent co-authors include Steward Mudenda, Ruth Lindizyani Mfune, Scott Kaba Matafwali, Webrod Mufwambi, Billy Chabalenge, Maisa Kasanga, Moses Mukosha, Michelo Banda, Christabel Nang’andu Hikaambo and Brian Godman. Their work appears in journals such as PLoS ONE, African Journal of Laboratory Medicine, BMJ Open, Vaccines and Antibiotics.

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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