Dr Prabin Dahal
Research groups
Prabin Dahal
DPhil PGCertTLHE FHEA
Head of Statistics & Sciences, Infectious Diseases Data Observatory
- Head of Statistics and Sciences, Infectious Diseases Data Observatory
- Module lead in Medical Statistics, MSc in Modelling for Global Health
- Teaching Fellow in Epidemiology & Statistics, MSc in International Health and Tropical Medicine
Research summary
I am a statistician based at Infectious Diseases Data Observatory (IDDO). I have a broad interest in epidemiology of infectious diseases (Malaria and Visceral Leishmaniasis in particular). My research has primarily focused on delineation of dose-response relationships for commonly used antimalarial drugs through individual participant data meta-analysis and assessment of safety of antileishmanial drugs.
Prior to my current role, I completed first and second degrees in Statistics from the University of Reading, spent a year at Safety Assessment and Pharmaceutical Development unit at GlaxoSmithKline supporting pre-clinical studies, and completed DPhil in Clinical Medicine on investigation of statistical issues in antimalarial clinical studies.
I was a Susan and George Brownlee Junior Research Fellow in Biomedical Sciences at Linacre College (2019-2021).
Recent publications
Evaluation of scientific outcomes of TDR-supported clinical research and development fellows in low- and middle-income countries: a bibliometric analysis.
Journal article
Vahedi M. et al, (2026), Infectious diseases of poverty, 15
A snapshot of selected neglected tropical disease research using the World Health Organization International Clinical Trials Registry Platform database, 1999–2023
Journal article
Peploe R. et al, (2026), PLOS Neglected Tropical Diseases, 20, e0014338 - e0014338
Corrigendum to SPICE-GRADE: simultaneous processing of indirect causal evidence in complex pathways using GRADE - an exploratory case study. [Journal of Clinical Epidemiology, 194C (2026) 112219].
Journal article
Eachempati P. et al, (2026), Journal of clinical epidemiology, 197
SPICE-GRADE: simultaneous processing of indirect causal evidence in complex pathways using GRADE - an exploratory case study.
Journal article
Eachempati P. et al, (2026), Journal of clinical epidemiology, 194
Informing optimal testing and isolation strategies across different stages of the diagnostic development pipeline using mathematical models: SARS-CoV-2 in the UK as a case study
Journal article
Aguas R. et al, (2026), BMJ Public Health, 4, e002993 - e002993
Estimating the changing prevalence of molecular markers of artemisinin partial resistance in Plasmodium falciparum malaria in Sub-Saharan Africa
Preprint
Harrison LE. et al, (2026)