Dr Richard White BSc MSc PhD
About Richard White
Mathematical and statistical modelling of the transmission and control of infectious diseases
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Richard G White (BSc, MSc, PhD) is Reader in Infectious Disease Modelling in the Centre for the Mathematical Modelling of Infectious Diseases and the TB Centre at the London School of Hygiene and Tropical Medicine. He is Director of the TB Modelling and Analysis Consortium (TB MAC) and leads the TB Modelling Group.
Richard was awarded a BSc in Physics from Durham University and an MSc in Medical Demography from LSHTM. He was awarded a PhD in infectious disease modelling in 2006, led the establishment of the LSHTM’s Centre for the Mathematical Modelling of Infectious Diseases in 2007, and was awarded a Methodology Research Fellowship from the Medical Research Council in 2009.
Richard teaches on the mathematical modelling of the spread and control of infectious diseases in the UK and internationally. He organises the LSHTM Infectious Disease Modelling summer short course and MSc Module with Emilia Vynnycky (Public Health England), Adam Kucharski and Katie Atkins (LSHTM).
He is co-author of the textbook An Introduction to Infectious Disease Modelling published by Oxford University Press.
Richard's research focus is the mathematical and statistical modelling of the transmission and control of infectious diseases, particularly TB and HIV.
He has co-authored over 90 peer-reviewed scientific publications. He is currently principal investigator of 5 research grants: the 'TB Modelling and Analysis Consortium' (BMGF), 'Methods for allocative efficiency of the Global Fund TB, HIV and Malaria Country Grants' (USAID), 'Data utilization and modelling to support TB control policy and practice in South Africa' (BMGF), 'Estimating the impact of IPT and ART on TB incidence in general populations in South Africa' (PEPFAR), and 'Calibration and analysis of complex models: methodological development and application to impact of ART in Africa' (UK MRC).
Richard currently welcomes PhD proposals in the area of TB modelling, for start from late 2016 onwards.
- Disease control
- Infectious disease policy
- Public health
- Social and structural determinants of health
- Statistical methods
- Mathematical modelling
Disease and Health Conditions
- Infectious disease
- Sexually transmitted disease
- Latin America & Caribbean (all income levels)
- Least developed countries: UN classification
- Middle East & North Africa (all income levels)
- North America
- Sub-Saharan Africa (all income levels)
- South Africa
- United Kingdom
- United States
- Model Calibration
Effect of pre-exposure prophylaxis and combination HIV prevention for men who have sex with men in the UK: a mathematical modelling study.
Punyacharoensin, N. ; Edmunds, W.J. ; De Angelis, D. ; Delpech, V. ; Hart, G. ; Elford, J. ; Brown, A. ; Gill, O.N. ; White, R.G. ;
Lancet HIV, 2016; 3(2):e94-e104
Tuberculosis control in South African gold mines: mathematical modeling of a trial of community-wide isoniazid preventive therapy.
Vynnycky, E. ; Sumner, T. ; Fielding, K.L. ; Lewis, J.J. ; Cox, A.P. ; Hayes, R.J. ; Corbett, E.L. ; Churchyard, G.J. ; Grant, A.D. ; White, R.G. ;
Am J Epidemiol, 2015; 181(8):619-32
Ability of preventive therapy to cure latent Mycobacterium tuberculosis infection in HIV-infected individuals in high-burden settings.
Houben, R.M. ; Sumner, T. ; Grant, A.D. ; White, R.G. ;
Proc Natl Acad Sci U S A, 2014;
Impact and cost-effectiveness of new tuberculosis vaccines in low- and middle-income countries.
Knight, G.M.; Griffiths, U.K.; Sumner, T.; Laurence, Y.V.; Gheorghe, A.; Vassall, A.; Glaziou, P.; White, R.G.;
Proc Natl Acad Sci U S A, 2014; 111(43):15520-5
HIV Treatment as Prevention: Optimising the Impact of Expanded HIV Treatment Programmes
Delva, W.; Eaton, J.W.; Meng, F.; Fraser, C.; White, R.G.; Vickerman, P.; Boily, M.C.; Hallett, T.B.;
Plos Medicine, 2012; 9(7):e1001258
An Introduction to Infectious Disease Modelling
Vynnycky, E.; White, R.G.
Oxford University Press 2010
Male circumcision for HIV prevention in high HIV prevalence settings: what can mathematical modelling contribute to informed decision making?
UNAIDS/WHO/SACEMA Expert Group on Modelling the Impact and Cost of Male Circumcision for HIV Prevention, (Hankins, C; Hargrove, J; Williams, B; Abu-Raddad, L; Auvert, B; Bollinger, L; Dorrington, R; Ghani, A; Gray, R; Hallett, T; Kahn, JG; Lohse, N; Nagelkerke, N; Porco, T; Schmid, G; Stover, J; Weiss, H; Welte, A; White, P; White, R.; ).;
PLoS Med, 2009; 6(9):e1000109
Quantifying HIV-1 transmission due to contaminated injections.
White, R.G.; Cooper, B.S.; Kedhar, A.; Orroth, K.K.; Biraro, S.; Baggaley, R.F.; Whitworth, J.; Korenromp, E.L.; Ghani, A.; Boily, M.C.; Hayes, R.J.;
Proc Natl Acad Sci U S A, 2007; 104(23):9794-9
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