Ian Hall

4.0k total citations
156 papers, 2.4k citations indexed

About

Ian Hall is a scholar working on Modeling and Simulation, Infectious Diseases and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Ian Hall has authored 156 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Modeling and Simulation, 28 papers in Infectious Diseases and 25 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Ian Hall's work include COVID-19 epidemiological studies (36 papers), Nuclear physics research studies (23 papers) and Atomic and Molecular Physics (14 papers). Ian Hall is often cited by papers focused on COVID-19 epidemiological studies (36 papers), Nuclear physics research studies (23 papers) and Atomic and Molecular Physics (14 papers). Ian Hall collaborates with scholars based in United Kingdom, United States and Canada. Ian Hall's co-authors include Stephen Leach, R.G. Stokstad, G. James Rubin, Jackie Leach Scully, A. Christy, Rebecca Webster, Margaux M. I. Meslé, I.M. Naqib, Raymond Gani and Caroline E. Walters and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Physical review. B, Condensed matter.

In The Last Decade

Ian Hall

147 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ian Hall United Kingdom 27 605 473 432 319 304 156 2.4k
Kai Kadau United States 24 358 0.6× 973 2.1× 307 0.7× 314 1.0× 737 2.4× 72 3.8k
Timothy C. Germann United States 51 567 0.9× 996 2.1× 1.2k 2.8× 322 1.0× 747 2.5× 231 9.9k
Joel C. Miller United States 35 334 0.6× 1.7k 3.6× 335 0.8× 489 1.5× 530 1.7× 115 4.4k
Yong Kyun Kim South Korea 23 215 0.4× 104 0.2× 489 1.1× 40 0.1× 59 0.2× 212 2.5k
R. G. Downing United States 42 131 0.2× 126 0.3× 161 0.4× 3.2k 9.9× 1.5k 4.9× 195 6.2k
Nicolas Hengartner United States 31 118 0.2× 1.2k 2.5× 30 0.1× 1.2k 3.9× 448 1.5× 133 4.3k
Takayuki Yamaguchi Japan 28 1.2k 2.0× 37 0.1× 558 1.3× 751 2.4× 194 0.6× 212 3.8k
S. Yamada Japan 36 535 0.9× 172 0.4× 528 1.2× 1.7k 5.3× 4.2k 13.8× 283 7.4k
E. D. Adams United States 29 118 0.2× 69 0.1× 2.0k 4.6× 46 0.1× 131 0.4× 140 2.9k
Jianrong Shi China 30 196 0.3× 65 0.1× 200 0.5× 25 0.1× 88 0.3× 208 3.1k

Countries citing papers authored by Ian Hall

Since Specialization
Citations

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

Fields of papers citing papers by Ian Hall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian Hall

This figure shows the co-authorship network connecting the top 25 collaborators of Ian Hall. A scholar is included among the top collaborators of Ian Hall 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 Ian Hall. Ian Hall 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.
Schultz, David M., et al.. (2025). A within-host birth–death and time–dose–response model for Legionnaires’ disease. Royal Society Open Science. 12(7). 250226–250226.
2.
Borrow, Ray, Dominique A. Caugant, S. A. Clark, et al.. (2025). Current global trends in meningococcal disease control, risk groups and vaccination: Consensus of the Global Meningococcal Initiative. Journal of Infection. 91(5). 106635–106635.
3.
Fowler, Tom, Andrew Dodgson, Jeanette Hall, et al.. (2025). Key SARS-CoV-2 testing strategies implemented in the UK: rationale and impact. Journal of the Royal Society of Medicine. 118(4). 112–120.
4.
Miller, Daniel, Marco‐Felipe King, Ian Hall, et al.. (2024). A quantitative microbial risk assessment approach to estimate exposure to SARS-CoV-2 on a bus. Journal of Transport & Health. 38. 101829–101829. 2 indexed citations
5.
Futschik, Matthias E., Michael Kidd, Éamonn O’Moore, et al.. (2024). Faster detection of asymptomatic COVID-19 cases among care home staff in England through the combination of SARS-CoV-2 testing technologies. Scientific Reports. 14(1). 7475–7475.
6.
Bridgen, Jessica R. E., Wei Hua, Yang Han, et al.. (2023). Contact patterns of UK home delivery drivers and their use of protective measures during the COVID-19 pandemic: a cross-sectional study. Occupational and Environmental Medicine. 80(6). 333–338. 1 indexed citations
7.
Finnie, Thomas, et al.. (2023). Simplified within-host and Dose–response Models of SARS-CoV-2. Journal of Theoretical Biology. 565. 111447–111447. 5 indexed citations
8.
Tongeren, Martie van, Yang Han, Wei Hua, et al.. (2023). Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector. PLoS ONE. 18(5). e0284805–e0284805. 4 indexed citations
9.
Miller, Daniel, Marco‐Felipe King, Ursula Dalrymple, et al.. (2022). Modeling the factors that influence exposure to SARS‐CoV‐2 on a subway train carriage. Indoor Air. 32(2). e12976–e12976. 33 indexed citations
10.
Hall, Ian, et al.. (2022). Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential. Journal of Theoretical Biology. 557. 111335–111335. 5 indexed citations
11.
Fearon, Elizabeth, Christopher E. Overton, Tom Wingfield, et al.. (2021). Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic. Philosophical Transactions of the Royal Society B Biological Sciences. 376(1829). 20200267–20200267. 25 indexed citations
12.
Hua, Wei, Yang Han, David W. Denning, et al.. (2021). Risk factors associated with respiratory infectious disease-related presenteeism: a rapid review. medRxiv. 3 indexed citations
13.
14.
Wood, Richard M. & Ian Hall. (2021). Efficacy of antibiotic medication strategy following a bioterrorist attack involving Francisella tularensis. Journal of the Operational Research Society. 73(9). 2028–2042. 1 indexed citations
15.
Huang, Yibo, et al.. (2021). Impact of covid-19 on prep prescriptions in the united states: A time series analysis. 29(1). 285–285. 2 indexed citations
16.
Didelot, Xavier, Lilith K. Whittles, & Ian Hall. (2017). Model-based analysis of an outbreak of bubonic plague in Cairo in 1801. Journal of The Royal Society Interface. 14(131). 20170160–20170160. 10 indexed citations
17.
Hall, Ian, et al.. (2016). Helping nurses reconnect with their compassion.. PubMed. 111(41). 21–3. 1 indexed citations
18.
Bonsor, H.C., David Entwisle, Steven James Watson, et al.. (2013). Maximising past investment in subsurface data in urban areas for sustainable resource management: a pilot in Glasgow, UK. Technical note.. The American Journal of the Medical Sciences. 293(1). 6–12. 4 indexed citations
19.
Hall, Ian, et al.. (2012). Transmission dynamics of methicillin-resistant Staphylococcus aureus in a medical intensive care unit. Journal of The Royal Society Interface. 9(75). 2639–2652. 15 indexed citations
20.
Hall, Ian, et al.. (2011). Modeling Inhalational Tularemia: Deliberate Release and Public Health Response. Biosecurity and Bioterrorism Biodefense Strategy Practice and Science. 9(4). 331–343. 12 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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