World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
42
Citations
7075
World Ranking
1795
National Ranking
126

Dankmar Böhning publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Dankmar Böhning sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 200 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Dankmar Böhning D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Dankmar Böhning sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 42 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Dankmar Böhning is affiliated with the University of Southampton in the United Kingdom. Their research primarily intersects the fields of Medicine and Mathematics, with a strong focus on Statistics and Probability, Epidemiology, and Modeling and Simulation. Additional expertise includes Endocrinology, Diabetes and Metabolism, and Infectious Diseases.

The scientist's work covers several key topics, including Census and Population Estimation, Data-Driven Disease Surveillance, Statistical Methods and Bayesian Inference, Statistical Methods in Clinical Trials, COVID-19 epidemiological studies, Meta-analysis and systematic reviews, and studies related to HIV, Drug Use, and Sexual Risk.

Dankmar Böhning has published extensively in various academic venues, contributing fifteen works to Biometrical Journal and three each to bioRxiv (Cold Spring Harbor Laboratory), Journal of Statistical Computation and Simulation, and SSRN Electronic Journal. There are also publications in Biometrics.

Frequent collaborators of Dankmar Böhning include Patarawan Sangnawakij, Antonello Maruotti, Marco Alfò, Heinz Holling, and Arne C. Bathke.

Recent publications by Dankmar Böhning include:

  1. Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods (2020, International Journal of Infectious Diseases)
  2. Delayed antibiotic prescribing for respiratory tract infections: individual patient data meta-analysis (2021, BMJ)
  3. Bayesian spatio-temporal joint disease mapping of Covid-19 cases and deaths in local authorities of England (2021, Spatial Statistics)
  4. Fewer COVID-19 Neurological Complications with Dexamethasone and Remdesivir (2022, Annals of Neurology)
  5. Estimating the size of undetected cases of the COVID-19 outbreak in Europe: an upper bound estimator (2020, Epidemiologic Methods)

Best Publications

  • Multinomial logistic regression algorithm

    Dankmar Böhning

  • The zero-inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology

    D. Böhning;E. Dietz;P. Schlattmann;L. Mendonça

  • Computer-Assisted Analysis of Mixtures and Applications: Meta-Analysis, Disease Mapping, and Others

    Dankmar Böhning

  • The distribution of the likelihood ratio for mixtures of densities from the one-parameter exponential family

    Dankmar Böhning;Ekkehart Dietz;Rainer Schaub;Peter Schlattmann

  • Monotonicity of quadratic-approximation algorithms

    Dankmar Böhning;Bruce G. Lindsay

  • Computer-assisted analysis of mixtures (C.A.MAM): statistical algorithms.

    Dankmar Bohning;Peter Schlattmann;Bruce Lindsay

  • On estimation of the Poisson parameter in zero-modified Poisson models

    Ekkehart Dietz;Dankmar Böhning

  • Zero‐Inflated Poisson Models and C.A.MAN: A Tutorial Collection of Evidence

    Dankmar Böhning

  • Some general points in estimating heterogeneity variance with the DerSimonian–Laird estimator

    Dankmar Böhning;Uwe Malzahn;Ekkehart Dietz;Peter Schlattmann

  • Mixture models and disease mapping.

    Peter Schlattmann;Dankmar Böhning

  • The lower bound method in probit regression

    Dankmar Böhning

  • Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods.

    Dankmar Böhning;Irene Rocchetti;Antonello Maruotti;Heinz Holling

  • Revisiting youden's index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

    Dankmar Böhning;Walailuck Böhning;Heinz Holling

  • A review of reliable maximum likelihood algorithms for semiparametric mixture models

    Dankmar Böhning

  • Meta‐analysis of clinical trials with rare events

    Dankmar Böhning;Kalliopi Mylona;Alan Kimber

  • A vertex-exchange-method in D-optimal design theory

    D. Böhning

  • Nonparametric estimation of heterogeneity variance for the standardised difference used in meta-analysis

    Uwe Malzahn;Dankmar Bohning;Heinz Holling

  • Estimating the number of drug users in Bangkok 2001: a capture-recapture approach using repeated entries in one list.

    Dankmar Böhning;Busaba Suppawattanabodee;Wilai Kusolvisitkul;Chukiat Viwatwongkasem

  • Estimators in capture–recapture studies with two sources

    Sarah Brittain;Dankmar Böhning

  • Numerical estimation of a probability measure

    Dankmar Böhning

  • Meta-analysis: a unifying meta-likelihood approach framing unobserved heterogeneity, study covariates, publication bias, and study quality.

    D. Böhning

  • Convergence of a fixed point algorithm

    Dankmar Bohning

  • The zero-inflated Poisson model and the decayed, missing and filled teeth index

    Dankmar Bohning;Ekkehart Dietz;Peter Schlattmann;Lisette Mendonga

Frequent Co-Authors

Heinz Holling
Heinz Holling University of Münster
Peter G. M. van der Heijden
Peter G. M. van der Heijden University of Southampton
Matthias Greiner
Matthias Greiner Federal Institute for Risk Assessment
Paul Meredith
Paul Meredith Swansea University
Bruce G. Lindsay
Bruce G. Lindsay Pennsylvania State University
Paul Little
Paul Little University of Southampton
Claire Foster
Claire Foster University of Southampton
Lucy Yardley
Lucy Yardley University of Bristol
Diana Eccles
Diana Eccles University of Southampton
Geoffrey J. McLachlan
Geoffrey J. McLachlan University of Queensland

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