Pamela Nabeta

7.2k total citations · 1 hit paper
28 papers, 2.6k citations indexed

About

Pamela Nabeta is a scholar working on Epidemiology, Infectious Diseases and Surgery. According to data from OpenAlex, Pamela Nabeta has authored 28 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Epidemiology, 20 papers in Infectious Diseases and 7 papers in Surgery. Recurrent topics in Pamela Nabeta's work include Tuberculosis Research and Epidemiology (18 papers), Mycobacterium research and diagnosis (12 papers) and Pneumonia and Respiratory Infections (11 papers). Pamela Nabeta is often cited by papers focused on Tuberculosis Research and Epidemiology (18 papers), Mycobacterium research and diagnosis (12 papers) and Pneumonia and Respiratory Infections (11 papers). Pamela Nabeta collaborates with scholars based in Switzerland, United States and Peru. Pamela Nabeta's co-authors include Catharina Boehme, David Alland, Camilla Rodrigues, Mark D. Perkins, Doris Hillemann, Mark P. Nicol, Robert Blakemore, Martin Jones, Sabine Ruesch-Gerdes and David H. Persing and has published in prestigious journals such as New England Journal of Medicine, The Lancet and PLoS ONE.

In The Last Decade

Pamela Nabeta

27 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Rapid Molecular Detection of Tuberculosis and Rifampin Resistance

2010 1.6k citations Catharina Boehme, Pamela Nabeta et al. New England Journal of Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pamela Nabeta Switzerland	14	2.2k	1.8k	1.2k	310	266	28	2.6k
Shubhada Shenai India	15	2.0k 0.9×	1.7k 0.9×	1.0k 0.8×	124 0.4×	287 1.1×	23	2.3k
Paul R. Klatser Netherlands	35	2.8k 1.3×	2.2k 1.2×	1.1k 0.9×	306 1.0×	479 1.8×	116	3.8k
Claudio Piersimoni Italy	26	1.8k 0.8×	1.8k 1.0×	902 0.7×	66 0.2×	205 0.8×	65	2.3k
Ana Milovic United States	5	1.5k 0.7×	1.2k 0.7×	807 0.7×	107 0.3×	152 0.6×	7	1.7k
Laura Flores United States	18	1.5k 0.7×	1.3k 0.7×	1.2k 1.0×	82 0.3×	171 0.6×	20	2.0k
Vladyslav Nikolayevskyy United Kingdom	27	2.1k 1.0×	1.7k 1.0×	903 0.7×	97 0.3×	372 1.4×	70	2.4k
Hee Jae Huh South Korea	32	2.1k 1.0×	2.0k 1.1×	303 0.2×	249 0.8×	400 1.5×	190	3.3k
Fernando Alcaide Spain	29	1.5k 0.7×	1.8k 1.0×	618 0.5×	65 0.2×	349 1.3×	73	2.5k
Elvira Richter Germany	42	3.8k 1.7×	3.9k 2.2×	1.8k 1.4×	148 0.5×	575 2.2×	129	5.0k
Neil W. Anderson United States	18	700 0.3×	545 0.3×	677 0.6×	153 0.5×	205 0.8×	55	1.9k

Countries citing papers authored by Pamela Nabeta

Since Specialization

Citations

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

Fields of papers citing papers by Pamela Nabeta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pamela Nabeta

This figure shows the co-authorship network connecting the top 25 collaborators of Pamela Nabeta. A scholar is included among the top collaborators of Pamela Nabeta 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 Pamela Nabeta. Pamela Nabeta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lounnas, Manon, Pamela Nabeta, Morten Rühwald, et al.. (2025). Centrifuge-free stool processing methods for Xpert MTB/RIF Ultra tuberculosis diagnosis in children in Uganda and Zambia: an observational, prospective, diagnostic accuracy study. The Lancet Microbe. 6(8). 101055–101055. 1 indexed citations

Carratalá-Castro, Lucía, Belén Saavedra, Petra de Haas, et al.. (2024). Performance of stool-based molecular tests and processing methods for paediatric tuberculosis diagnosis: a systematic review and meta-analysis. The Lancet Microbe. 6(6). 100963–100963. 3 indexed citations

Singh, Urvashi B., Anuj Bhatnagar, Sangeeta Sharma, et al.. (2023). GeneXpert Ultra in Urine Samples for Diagnosis of Extra-Pulmonary Tuberculosis. Current Microbiology. 80(11). 361–361. 3 indexed citations

Wobudeya, Eric, Maryline Bonnet, Elisabetta Walters, et al.. (2022). Diagnostic Advances in Childhood Tuberculosis—Improving Specimen Collection and Yield of Microbiological Diagnosis for Intrathoracic Tuberculosis. Pathogens. 11(4). 389–389. 14 indexed citations

Shilton, Sonjelle, Nino Tsereteli, Antons Mozalevskis, et al.. (2022). Home-based hepatitis C self-testing in people who inject drugs and men who have sex with men in Georgia: a protocol for a randomised controlled trial. BMJ Open. 12(9). e056243–e056243. 2 indexed citations

Nabeta, Pamela, et al.. (2022). Pediatric Tuberculosis Diagnostics: Present and Future. Journal of the Pediatric Infectious Diseases Society. 11(Supplement_3). S85–S93. 9 indexed citations

Shilton, Sonjelle, Jessica Markby, Muhammad S. Jamil, et al.. (2022). Protocol for a cluster randomised controlled trial of secondary distribution of hepatitis C self-testing within the context of a house-to-house hepatitis C micro-elimination programme in Karachi, Pakistan. BMC Public Health. 22(1). 696–696. 2 indexed citations

Howlett, Patrick, et al.. (2021). Retrospective Diagnostic Accuracy Study of Abbott RealTi m e MTB against Xpert MTB/RIF Ultra and Xpert MTB/RIF for the Diagnosis of Pulmonary Tuberculosis and Susceptibility to Rifampin and Isoniazid Treatment. Microbiology Spectrum. 9(1). e0013221–e0013221. 2 indexed citations

Nabeta, Pamela, et al.. (2020). First clinical assessment of a prototype assay to detect the enzymatic activity of β-lactamase as a marker for pulmonary tuberculosis. Diagnostic Microbiology and Infectious Disease. 97(2). 115026–115026.

10.

Schumacher, Samuel G., William A. Wells, Mark P. Nicol, et al.. (2019). Guidance for Studies Evaluating the Accuracy of Sputum-Based Tests to Diagnose Tuberculosis. The Journal of Infectious Diseases. 220(Supplement_3). S99–S107. 20 indexed citations

11.

Peter, Jonny, Fernanda Carvalho de Queiroz Mello, Nguyễn Thị Ngọc Lan, et al.. (2018). Performance of the TB-LAMP diagnostic assay in reference laboratories: Results from a multicentre study. International Journal of Infectious Diseases. 68. 44–49. 20 indexed citations

12.

Dharan, Nila J., Robert Blakemore, Alex Sloutsky, et al.. (2016). Performance of the G4 Xpert® MTB/RIF assay for the detection of Mycobacterium tuberculosis and rifampin resistance: a retrospective case-control study of analytical and clinical samples from high- and low-tuberculosis prevalence settings. BMC Infectious Diseases. 16(1). 764–764. 11 indexed citations

13.

Nathavitharana, Ruvandhi R., Doris Hillemann, Joshua Havumaki, et al.. (2015). Multi-center Study to Assess the Non-inferiority of Nipro NTM + MDRTB and Hain Genotype Mtbdrplus V2 Line Probe Assays Compared to Hain Genotype Mtbdrplus V1. Open Forum Infectious Diseases. 2(suppl_1). 1 indexed citations

14.

Yoon, Christina, Adithya Cattamanchi, J. Lucian Davis, et al.. (2012). Impact of Xpert MTB/RIF Testing on Tuberculosis Management and Outcomes in Hospitalized Patients in Uganda. PLoS ONE. 7(11). e48599–e48599. 63 indexed citations

15.

Carriquiry, Gabriela, Larissa Otero, Carlos Zamudio, et al.. (2012). A Diagnostic Accuracy Study of Xpert®MTB/RIF in HIV-Positive Patients with High Clinical Suspicion of Pulmonary Tuberculosis in Lima, Peru. PLoS ONE. 7(9). e44626–e44626. 33 indexed citations

16.

Blakemore, Robert, Pamela Nabeta, Amy L. Davidow, et al.. (2011). A Multisite Assessment of the Quantitative Capabilities of the Xpert MTB/RIF Assay. American Journal of Respiratory and Critical Care Medicine. 184(9). 1076–1084. 91 indexed citations

17.

Boehme, Catharina, Pamela Nabeta, Doris Hillemann, et al.. (2010). Rapid Molecular Detection of Tuberculosis and Rifampin Resistance. New England Journal of Medicine. 363(11). 1005–1015. 1639 indexed citations breakdown →

18.

Shao, Theresa, et al.. (2009). Knowledge and attitudes of tuberculosis management in San Juan de Lurigancho district of Lima, Peru. The Journal of Infection in Developing Countries. 3(10). 783–788. 36 indexed citations

19.

Verdonck, Kristien, Germán Henostroza, Pamela Nabeta, et al.. (2007). HTLV-1 infection is frequent among out-patients with pulmonary tuberculosis in northern Lima, Peru.. PubMed. 11(10). 1066–72. 32 indexed citations

20.

Boehme, Catharina, Pamela Nabeta, Germán Henostroza, et al.. (2007). Operational Feasibility of Using Loop-Mediated Isothermal Amplification for Diagnosis of Pulmonary Tuberculosis in Microscopy Centers of Developing Countries. Journal of Clinical Microbiology. 45(6). 1936–1940. 273 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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