Mareli Claassens

7.8k total citations
46 papers, 804 citations indexed

About

Mareli Claassens is a scholar working on Infectious Diseases, Epidemiology and Surgery. According to data from OpenAlex, Mareli Claassens has authored 46 papers receiving a total of 804 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Infectious Diseases, 34 papers in Epidemiology and 11 papers in Surgery. Recurrent topics in Mareli Claassens's work include Tuberculosis Research and Epidemiology (41 papers), Pneumonia and Respiratory Infections (20 papers) and Pneumocystis jirovecii pneumonia detection and treatment (11 papers). Mareli Claassens is often cited by papers focused on Tuberculosis Research and Epidemiology (41 papers), Pneumonia and Respiratory Infections (20 papers) and Pneumocystis jirovecii pneumonia detection and treatment (11 papers). Mareli Claassens collaborates with scholars based in South Africa, United Kingdom and Namibia. Mareli Claassens's co-authors include Nulda Beyers, Rory Dunbar, Helen Ayles, Donald G. Skinner, Cari van Schalkwyk, Donald A. Enarson, E. Du Toit, Martien W. Borgdorff, Carl Lombard and Peter Godfrey‐Faussett and has published in prestigious journals such as The Lancet, PLoS ONE and PEDIATRICS.

In The Last Decade

Mareli Claassens

44 papers receiving 792 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mareli Claassens South Africa 15 649 469 149 92 85 46 804
Dag Gundersen Storla Norway 7 662 1.0× 495 1.1× 226 1.5× 57 0.6× 58 0.7× 9 794
Nathaniel Smith United States 15 673 1.0× 299 0.6× 113 0.8× 36 0.4× 57 0.7× 41 1.3k
Ashwin Dharmadhikari United States 13 452 0.7× 374 0.8× 102 0.7× 18 0.2× 29 0.3× 16 821
Suvanand Sahu United Kingdom 16 817 1.3× 518 1.1× 140 0.9× 58 0.6× 71 0.8× 30 971
Sanne van Kampen Netherlands 12 598 0.9× 470 1.0× 214 1.4× 50 0.5× 49 0.6× 22 788
Anna H. van’t Hoog Netherlands 18 705 1.1× 496 1.1× 188 1.3× 132 1.4× 94 1.1× 36 968
Monde Muyoyeta Zambia 18 863 1.3× 660 1.4× 219 1.5× 92 1.0× 98 1.2× 65 1.2k
Nonhlanhla Yende‐Zuma South Africa 18 667 1.0× 444 0.9× 157 1.1× 188 2.0× 53 0.6× 72 1.0k
Christy Hanson United States 18 583 0.9× 429 0.9× 98 0.7× 79 0.9× 74 0.9× 24 932
Kathryn Schnippel South Africa 21 1.0k 1.6× 794 1.7× 252 1.7× 112 1.2× 129 1.5× 54 1.3k

Countries citing papers authored by Mareli Claassens

Since Specialization
Citations

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

Fields of papers citing papers by Mareli Claassens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mareli Claassens

This figure shows the co-authorship network connecting the top 25 collaborators of Mareli Claassens. A scholar is included among the top collaborators of Mareli Claassens based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mareli Claassens. Mareli Claassens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ayles, Helen, et al.. (2024). Cost-effectiveness analysis of a prediction model for community-based screening of active tuberculosis. Journal of Global Health. 14. 4226–4226. 1 indexed citations
2.
Günther, Gunar, Graeme Hoddinott, Hsien-Ho Lin, et al.. (2024). Enhanced active case finding of drug-resistant tuberculosis in Namibia: a protocol for the hotspots, hospitals, and households (H3TB) study. BMJ Open. 14(2). e082665–e082665.
3.
Wyk, Susanna S van, Marriott Nliwasa, F. Lu, et al.. (2024). Drug-Resistant Tuberculosis Case-Finding Strategies: Scoping Review. JMIR Public Health and Surveillance. 10. e46137–e46137. 1 indexed citations
4.
Wyk, Susanna S van, Marriott Nliwasa, James A. Seddon, et al.. (2022). Case-Finding Strategies for Drug-Resistant Tuberculosis: Protocol for a Scoping Review. JMIR Research Protocols. 11(12). e40009–e40009. 2 indexed citations
5.
Burger, Ronelle, Judy Caldwell, Mareli Claassens, et al.. (2021). Who is more likely to return for TB test results? A survey at three high-burden primary healthcare facilities in Cape Town, South Africa. International Journal of Infectious Diseases. 113. 259–267. 2 indexed citations
6.
Osman, Muhammad, Cari van Schalkwyk, Pren Naidoo, et al.. (2021). Mortality during tuberculosis treatment in South Africa using an 8-year analysis of the national tuberculosis treatment register. Scientific Reports. 11(1). 15894–15894. 11 indexed citations
7.
Günther, Gunar, Jan Heyckendorf, J.-P. Zellweger, et al.. (2021). Defining Outcomes of Tuberculosis (Treatment): From the Past to the Future. Respiration. 100(9). 843–852. 10 indexed citations
8.
9.
Schalkwyk, Cari van, et al.. (2018). Estimating the magnitude of pulmonary tuberculosis patients missed by primary health care clinics in South Africa. The International Journal of Tuberculosis and Lung Disease. 22(3). 264–272. 37 indexed citations
10.
11.
Claassens, Mareli, Cari van Schalkwyk, Sian Floyd, Helen Ayles, & Nulda Beyers. (2017). Symptom screening rules to identify active pulmonary tuberculosis: Findings from the Zambian South African Tuberculosis and HIV/AIDS Reduction (ZAMSTAR) trial prevalence surveys. PLoS ONE. 12(3). e0172881–e0172881. 21 indexed citations
12.
Skinner, Donald G. & Mareli Claassens. (2016). Why test for tuberculosis? A qualitative study from South Africa. Public Health Action. 6(4). 212–216. 1 indexed citations
13.
Rose, Alexandra L., et al.. (2015). Antiretroviral treatment among co-infected tuberculosis patients in integrated and non-integrated facilities. Public Health Action. 5(2). 112–115. 4 indexed citations
14.
Elliott, Elizabeth, et al.. (2014). Factors affecting treatment outcomes in drug-resistant tuberculosis cases in the Northern Cape, South Africa. Public Health Action. 4(3). 201–203. 15 indexed citations
15.
Naidoo, Pren, et al.. (2014). Characteristics of clients who access mobile compared to clinic HIV counselling and testing services: a matched study from Cape Town, South Africa. BMC Health Services Research. 14(1). 658–658. 22 indexed citations
16.
Ayles, Helen, Monde Muyoyeta, E. Du Toit, et al.. (2013). Effect of household and community interventions on the burden of tuberculosis in southern Africa: the ZAMSTAR community-randomised trial. The Lancet. 382(9899). 1183–1194. 162 indexed citations
17.
Kumar, Rakesh, A. M. V. Kumar, Mareli Claassens, et al.. (2013). Number of sputum specimens during treatment follow-up of tuberculosis patients: two or one?. Public Health Action. 3(4). 304–307. 3 indexed citations
18.
Chinnakali, Palanivel, A. M. V. Kumar, A. Thirumal Raj, et al.. (2013). Uptake of HIV testing and HIV positivity among presumptive tuberculosis patients at Puducherry, South India. Public Health Action. 3(3). 220–223. 9 indexed citations
19.
20.
Claassens, Mareli. (2012). Overdiagnosis of and treatment initiation delay in smear-negative pulmonary tuberculosis patients [Editorial]. Public Health Action. 2(4). 100–100. 1 indexed citations

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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