Dr Sompob Saralamba
Contact information
Research groups
Sompob Saralamba
Associate Research Fellow
MAEMOD
Dr Sompob Saralamba is an infectious disease modeller at the Mahidol–Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Bangkok, and an Associate Research Fellow of the University of Oxford. His research focuses on the development and application of mathematical and computational models to understand infectious disease dynamics and to inform public health policy.
His work spans both within-host and population-level modelling, with a primary focus on malaria. He has contributed to studies on parasite dynamics, antimalarial drug response, and the emergence and spread of drug resistance. In addition, his research interests extend to dengue, antimicrobial resistance, and helminth infections.
Dr Saralamba also leads research software engineering activities within his group, with an emphasis on translating complex models into accessible and practical tools. He has developed a number of applications and platforms, including interactive dashboards and AI-based analytical tools, to support clinicians, researchers, and policymakers in data-driven decision-making.
He is actively engaged in interdisciplinary collaborations and the supervision of students and has a particular interest in the integration of artificial intelligence and software design into infectious disease modelling.
Recent publications
Antibacterial and proteomic profiling of Morus alba extract against methicillin-resistant Staphylococcus aureus.
Journal article
Reamtong O. et al, (2026), PeerJ, 14
Influence of context on engagement with COVID-19 testing: a scoping review of barriers and facilitators to testing for healthcare workers, care homes and schools in the UK
Journal article
Andersen-Waine B. et al, (2025), BMJ Open, 15, e089062 - e089062
Validating a web application's use of genetic distance to determine helminth species boundaries and aid in identification.
Journal article
Chan AHE. et al, (2025), BMC bioinformatics, 26
Exploring the antimicrobial potential of crude peptide extracts from Allium sativum and Allium oschaninii against antibiotic-resistant bacterial strains.
Journal article
Swangsri T. et al, (2024), Pharmaceutical biology, 62, 666 - 675
COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys
Journal article
Bajaj S. et al, (2024), The Lancet Digital Health, 6, e778 - e790