Frank Ball

6.7k total citations
170 papers, 4.1k citations indexed

About

Frank Ball is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, Frank Ball has authored 170 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Modeling and Simulation, 61 papers in Public Health, Environmental and Occupational Health and 35 papers in Molecular Biology. Recurrent topics in Frank Ball's work include COVID-19 epidemiological studies (76 papers), Mathematical and Theoretical Epidemiology and Ecology Models (61 papers) and Complex Network Analysis Techniques (32 papers). Frank Ball is often cited by papers focused on COVID-19 epidemiological studies (76 papers), Mathematical and Theoretical Epidemiology and Ecology Models (61 papers) and Complex Network Analysis Techniques (32 papers). Frank Ball collaborates with scholars based in United Kingdom, Australia and Sweden. Frank Ball's co-authors include Pieter Trapman, Tom Britton, Mark S.P. Sansom, Denis Mollison, Gianpaolo Scalia‐Tomba, David Sirl, Peter Donnelly, Damian Clancy, Philip D. O’Neill and Peter Neal and has published in prestigious journals such as Science, Biometrics and Biophysical Journal.

In The Last Decade

Frank Ball

158 papers receiving 3.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frank Ball United Kingdom 33 2.0k 1.3k 885 581 512 170 4.1k
Tom Britton Sweden 28 2.0k 1.0× 1.3k 1.0× 761 0.9× 1.4k 2.4× 1.3k 2.4× 112 7.5k
Denis Mollison United Kingdom 23 1.1k 0.6× 1.2k 0.9× 412 0.5× 131 0.2× 843 1.6× 42 3.2k
Eric Renshaw United Kingdom 27 740 0.4× 1.3k 0.9× 309 0.3× 359 0.6× 894 1.7× 111 4.2k
Dirk Brockmann Germany 25 2.0k 1.0× 670 0.5× 1.7k 2.0× 687 1.2× 319 0.6× 71 6.1k
Linda J. S. Allen United States 37 2.3k 1.2× 3.1k 2.3× 436 0.5× 286 0.5× 1.9k 3.8× 128 5.2k
Manuel De la Sen Spain 39 1.8k 0.9× 1.2k 0.9× 558 0.6× 92 0.2× 372 0.7× 786 6.9k
Juan J. Nieto Spain 71 10.8k 5.4× 2.6k 1.9× 982 1.1× 403 0.7× 676 1.3× 588 19.7k
Lin Wang China 40 865 0.4× 1.5k 1.1× 699 0.8× 828 1.4× 995 1.9× 278 5.6k
Glenn F. Webb United States 46 3.2k 1.6× 3.1k 2.3× 311 0.4× 1.2k 2.1× 1.4k 2.7× 184 8.4k
Fred Brauer Canada 37 4.3k 2.2× 4.5k 3.3× 796 0.9× 193 0.3× 2.2k 4.3× 142 8.1k

Countries citing papers authored by Frank Ball

Since Specialization
Citations

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

Fields of papers citing papers by Frank Ball

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Ball

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Ball. A scholar is included among the top collaborators of Frank Ball 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 Frank Ball. Frank Ball 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.
Ball, Frank & Peter Neal. (2025). The number of individuals alive in a branching process given only times of deaths. Advances in Applied Probability. 57(3). 871–906.
2.
Ball, Frank, et al.. (2023). The impact of household structure on disease-induced herd immunity. Journal of Mathematical Biology. 87(6). 83–83. 2 indexed citations
3.
Britton, Tom, Pieter Trapman, & Frank Ball. (2021). The risk for a new COVID-19 wave and how it depends on R 0 , the current immunity level and current restrictions. Royal Society Open Science. 8(7). 210386–210386. 2 indexed citations
4.
Ball, Frank. (2021). Central limit theorems for SIR epidemics and percolation on configuration model random graphs. Repository@Nottingham (University of Nottingham).
5.
Vegvari, Carolin, Sam Abbott, Frank Ball, et al.. (2021). Commentary on the use of the reproduction number R during the COVID-19 pandemic. Statistical Methods in Medical Research. 31(9). 1675–1685. 25 indexed citations
6.
Ball, Frank, et al.. (2019). A stochastic SIR network epidemic model with preventive dropping of edges. Journal of Mathematical Biology. 78(6). 1875–1951. 20 indexed citations
7.
Ball, Frank & David Sirl. (2012). An Sir Epidemic Model on a Population with Random Network and Household Structure, and Several Types of Individuals. Advances in Applied Probability. 44(1). 63–86. 9 indexed citations
8.
Stefanov, Valeri T. & Frank Ball. (2009). Reward distributions associated with some block tridiagonal transition matrices with applications to identity by descent. Advances in Applied Probability. 41(2). 523–545.
9.
Ball, Frank & Peter Neal. (2008). Network epidemic models with two levels of mixing. Mathematical Biosciences. 212(1). 69–87. 96 indexed citations
10.
Ball, Frank, Philip D. O’Neill, & James Russell Pike. (2007). Stochastic Epidemic Models in Structured Populations Featuring Dynamic Vaccination and Isolation. Journal of Applied Probability. 44(3). 571–585. 5 indexed citations
11.
Ball, Frank, Philip D. O’Neill, & James Russell Pike. (2007). Stochastic Epidemic Models in Structured Populations Featuring Dynamic Vaccination and Isolation. Journal of Applied Probability. 44(3). 571–585. 22 indexed citations
12.
Ball, Frank & Tom Britton. (2007). An epidemic model with infector-dependent severity. Advances in Applied Probability. 39(4). 949–972. 1 indexed citations
13.
Ball, Frank & Robin K. Milne. (2005). Simple derivations of properties of counting processes associated with Markov renewal processes. Journal of Applied Probability. 42(4). 1031–1043. 8 indexed citations
14.
Ball, Frank & Robin K. Milne. (2005). Simple derivations of properties of counting processes associated with Markov renewal processes. Journal of Applied Probability. 42(4). 1031–1043. 2 indexed citations
15.
Ball, Frank, et al.. (1999). Supporting Guaranteed Services in Packet Switched Networks: A Study of Two Alternative Methods.. Parallel and Distributed Processing Techniques and Applications. 2450–2456. 1 indexed citations
16.
Ball, Frank, et al.. (1997). On the Mean and Variance of Cover Times for Random Walks on Graphs. Journal of Mathematical Analysis and Applications. 207(2). 506–514.
17.
Ball, Frank & Peter Donnelly. (1995). Strong approximations for epidemic models. Stochastic Processes and their Applications. 55(1). 1–21. 137 indexed citations
18.
Bates, Susan E., Mark S.P. Sansom, Frank Ball, R. L. Ramsey, & P.N.R. Usherwood. (1990). Glutamate receptor-channel gating. Maximum likelihood analysis of gigaohm seal recordings from locust muscle. Biophysical Journal. 58(1). 219–229. 22 indexed citations
19.
Ball, Frank, Richard McGee, & Mark S.P. Sansom. (1989). Analysis of post-perturbation gating kinetics of single ion channels. Proceedings of the Royal Society of London. Series B, Biological sciences. 236(1282). 29–52. 8 indexed citations
20.
Ball, Frank. (1986). A unified approach to the distribution of total size and total area under the trajectory of infectives in epidemic models. Advances in Applied Probability. 18(2). 289–310. 136 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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