Samuel Manda

137 papers receiving 2.3k citations

Peers

Samuel Manda
Comparison fields: 5 of 149
  • Infectious Diseases 429
  • Health 162
  • Modeling and Simulation 87
  • Pediatrics, Perinatology and Child Health 309
  • Statistics and Probability 116
Replace Samuel J. Clark with:
Samuel J. Clark United States
Miguel Ángel Luque-Fernández United Kingdom
Bethany Hedt‐Gauthier United States
Chodziwadziwa Whiteson Kabudula South Africa
Temesgen T. Zewotir South Africa
Eric Tchetgen Tchetgen United States
Laina D. Mercer United States
Jessie K. Edwards United States
Yalemzewod Assefa Gelaw Ethiopia
Júlia Moreira Pescarini Brazil
Samuel Manda relative to Samuel J. Clark United States Samuel J. Clark's profile →
Citations per field
00.5×1.6×
Samuel J. Clark · 1×
Citations per year

Countries citing papers authored by Samuel Manda

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Manda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 142 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200896
2 199994
3 201583
4 202281
5 201572
6 202167
7 200465
8 201661
9 200560
10 201854
11 200852
12 200150
13 201648
14 201944
15 202244
16 201543
17 201343
18 201439
19 200739
20 200533

About Samuel Manda

Samuel Manda is a scholar working on Infectious Diseases, Statistics and Probability, Pediatrics, Perinatology and Child Health, Modeling and Simulation and Health, having authored 142 papers that have together received 2.4k indexed citations. Recurring topics across this work include HIV/AIDS Research and Interventions (18 papers), Statistical Methods and Bayesian Inference (17 papers), Global Maternal and Child Health (15 papers), Statistical Methods and Inference (12 papers), COVID-19 epidemiological studies (9 papers), Child Nutrition and Water Access (9 papers), Bayesian Methods and Mixture Models (8 papers) and Insurance, Mortality, Demography, Risk Management (8 papers). The work is most often cited by research in Infectious Diseases (429 citations), Health (162 citations), Modeling and Simulation (87 citations), Pediatrics, Perinatology and Child Health (309 citations) and Statistics and Probability (116 citations). Samuel Manda has collaborated with scholars based in South Africa, United Kingdom and United States. Frequent co-authors include Renate Meyer, Mark S. Gilthorpe, Paxie Wanangwa Chirwa, Henry Godwell Mwambi, Carl J. Lombard, Jonathan Mutau Kamwi, Tarylee Reddy, William M. Bolstad, Richard G. Feltbower and Chris P Gale. Their work appears in journals such as PLoS ONE, International Journal of Environmental Research and Public Health, Geospatial health, BMC Medical Research Methodology and Scientific Reports.

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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