Peter J. Dodd

7.2k total citations · 1 hit paper
108 papers, 4.3k citations indexed

About

Peter J. Dodd is a scholar working on Infectious Diseases, Epidemiology and Economics and Econometrics. According to data from OpenAlex, Peter J. Dodd has authored 108 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Infectious Diseases, 58 papers in Epidemiology and 18 papers in Economics and Econometrics. Recurrent topics in Peter J. Dodd's work include Tuberculosis Research and Epidemiology (74 papers), Pneumonia and Respiratory Infections (28 papers) and Pneumocystis jirovecii pneumonia detection and treatment (25 papers). Peter J. Dodd is often cited by papers focused on Tuberculosis Research and Epidemiology (74 papers), Pneumonia and Respiratory Infections (28 papers) and Pneumocystis jirovecii pneumonia detection and treatment (25 papers). Peter J. Dodd collaborates with scholars based in United Kingdom, United States and South Africa. Peter J. Dodd's co-authors include Rein M G J Houben, James A. Seddon, J. J. Halliwell, Charalambos Sismanidis, Courtney M. Yuen, Geoff P. Garnett, Timothy B. Hallett, Renia Coghlan, Elizabeth Gardiner and Helen E. Jenkins and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Peter J. Dodd

95 papers receiving 4.2k citations

Hit Papers

The Global Burden of Latent Tuberculosis Infection: A Re-... 2016 2026 2019 2022 2016 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter J. Dodd United Kingdom 28 3.1k 2.2k 1.1k 331 271 108 4.3k
Fengcai Zhu China 38 3.6k 1.2× 2.0k 0.9× 171 0.1× 647 2.0× 207 0.8× 240 6.2k
Maia Lesosky South Africa 28 1.5k 0.5× 1.1k 0.5× 434 0.4× 99 0.3× 35 0.1× 105 2.6k
Hongzhou Lu China 27 3.5k 1.1× 1.3k 0.6× 199 0.2× 350 1.1× 23 0.1× 187 6.5k
Charles A. Boucher Netherlands 68 9.7k 3.1× 4.2k 1.9× 1.3k 1.1× 1.3k 4.0× 44 0.2× 345 17.4k
Adithya Cattamanchi United States 37 3.8k 1.2× 3.1k 1.4× 1.6k 1.3× 242 0.7× 11 0.0× 213 5.3k
John White United States 26 914 0.3× 1.0k 0.5× 1.6k 1.4× 24 0.1× 523 1.9× 117 5.5k
Klaus Reither Switzerland 35 2.3k 0.7× 1.6k 0.7× 856 0.7× 266 0.8× 8 0.0× 125 3.3k
J. Lucian Davis United States 34 2.5k 0.8× 2.3k 1.0× 765 0.7× 188 0.6× 10 0.0× 164 3.8k
Payam Nahid United States 32 3.3k 1.1× 2.5k 1.1× 1.2k 1.0× 348 1.1× 24 0.1× 102 4.6k
Mark D. Perkins Switzerland 43 6.4k 2.0× 5.4k 2.4× 2.6k 2.3× 769 2.3× 47 0.2× 104 10.5k

Countries citing papers authored by Peter J. Dodd

Since Specialization
Citations

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

Fields of papers citing papers by Peter J. Dodd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter J. Dodd. 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 Peter J. Dodd. The network helps show where Peter J. Dodd may publish in the future.

Co-authorship network of co-authors of Peter J. Dodd

This figure shows the co-authorship network connecting the top 25 collaborators of Peter J. Dodd. A scholar is included among the top collaborators of Peter J. Dodd 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 Peter J. Dodd. Peter J. Dodd 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.
Mafirakureva, Nyashadzaishe, Adrie Bekker, Nicole Salazar‐Austin, et al.. (2026). Global estimates of tuberculosis incidence during pregnancy and postpartum: a rapid review and modelling analysis. The Lancet Global Health. 14(3). e337–e346.
2.
Mafirakureva, Nyashadzaishe, Rachael Hunter, Stig Willner, et al.. (2025). Cost-effectiveness of tuberculosis infection screening at first reception into English prisons: a model-based analysis. EClinicalMedicine. 83. 103245–103245.
4.
Mafirakureva, Nyashadzaishe, Adrie Bekker, Nicole Salazar‐Austin, et al.. (2025). Global estimates of tuberculosis incidence during pregnancy and postpartum: a rapid review and modelling analysis. medRxiv. 1 indexed citations
5.
Yapa, H. Manisha, Emily MacLean, Nicolas A. Menzies, et al.. (2025). Drug-resistant tuberculosis: a priority pathogen for enhanced public health research and practice. Clinical Microbiology Reviews. 38(4). e0006425–e0006425.
6.
Mafirakureva, Nyashadzaishe, Lise Denoeud‐Ndam, Boris Tchounga, et al.. (2024). Cost-effectiveness of integrating paediatric tuberculosis services into child healthcare services in Africa: a modelling analysis of a cluster-randomised trial. BMJ Global Health. 9(12). e016416–e016416. 2 indexed citations
7.
MacPherson, Peter, Helen R. Stagg, Alvaro Schwalb, et al.. (2024). Impact of active case finding for tuberculosis with mass chest X-ray screening in Glasgow, Scotland, 1950–1963: An epidemiological analysis of historical data. PLoS Medicine. 21(11). e1004448–e1004448. 2 indexed citations
8.
Dodd, Peter J., Christopher Finn McQuaid, Ibrahim Abubakar, et al.. (2023). Improving the quality of the Global Burden of Disease tuberculosis estimates from the Institute for Health Metrics and Evaluation. International Journal of Epidemiology. 52(6). 1681–1686. 4 indexed citations
10.
Menzies, Nicolas A., Brian Allwood, Anna Dean, et al.. (2023). Global burden of disease due to rifampicin-resistant tuberculosis: a mathematical modeling analysis. Nature Communications. 14(1). 6182–6182. 19 indexed citations
12.
Houben, Rein M G J, Peter J. Dodd, Katie Dale, et al.. (2023). The prevalence of tuberculosis infection among foreign-born Canadians: a modelling study. Canadian Medical Association Journal. 195(48). E1651–E1659. 6 indexed citations
13.
Alba, Sandra, Ente Rood, Jennifer M. Ross, et al.. (2022). TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan. Tropical Medicine and Infectious Disease. 7(1). 13–13. 8 indexed citations
14.
MacPherson, Peter, McEwen Khundi, Helena R. A. Feasey, et al.. (2021). Durations of asymptomatic, symptomatic, and care-seeking phases of tuberculosis disease with a Bayesian analysis of prevalence survey and notification data. BMC Medicine. 19(1). 298–298. 27 indexed citations
15.
Dodd, Peter J., Muhammad Osman, Fiona V Cresswell, et al.. (2021). The global burden of tuberculous meningitis in adults: A modelling study. SHILAP Revista de lepidopterología. 1(12). e0000069–e0000069. 55 indexed citations
16.
Chen, Chien‐Chou, et al.. (2020). Patient pathways of tuberculosis care-seeking and treatment: an individual-level analysis of National Health Insurance data in Taiwan. BMJ Global Health. 5(6). e002187–e002187. 16 indexed citations
17.
Dodd, Peter J., et al.. (2019). Forecasting the impact of population ageing on tuberculosis incidence. PLoS ONE. 14(9). e0222937–e0222937. 17 indexed citations
18.
Strong, Mark, et al.. (2019). PNS337 IMPROVING ON CYCLE CORRECTIONS FOR TIME-HOMOGENEOUS MARKOV MODELS. Value in Health. 22. S821–S821.
19.
Opmeer, Brent C., et al.. (2017). Clinical News. British Journal of Hospital Medicine. 78(9). 488–491. 1 indexed citations
20.
McCreesh, Nicky, Clare Looker, Peter J. Dodd, et al.. (2016). Coverage of clinic-based TB screening in South Africa may be low in key risk groups. Public Health Action. 6(1). 19–21. 4 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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