Nim Arinaminpathy

Professor Nim Arinaminpathy is a Professor in Mathematical Epidemiology at the School of Public Health, Faculty of Medicine, Imperial College London. His affiliations include the MRC Centre for Global Infectious Disease Analysis and the NIHR Health Protection Research Unit in Respiratory Infections.

Education:

• Bachelor of Arts in Applied Mathematics (University of Cambridge, 2000)
• Doctor of Philosophy (D.Phil.) in Applied Mathematics (University of Oxford, 2005)

Research Interests: His work focuses on applying mathematical and statistical tools to study infectious disease transmission dynamics, with dual emphasis on basic science and policy-focused analysis. Key areas include:

• Control of tuberculosis (TB) in high-burden countries, particularly India, collaborating with national programs and global organizations like WHO and the Stop TB Partnership.
• Viral respiratory infections, including influenza surveillance and pandemic preparedness, with partnerships at the US CDC and Princeton University.
• Health systems strengthening, including resource allocation and cost-effectiveness analyses (e.g., the Thanzi La Onse model in Malawi).

Article Trends: Recent work highlights TB elimination strategies (e.g., radiographic screening in India), modeling impacts of interventions like rapid diagnostics for SARS-CoV-2, and influenza vaccine optimization. He emphasizes policy translation, especially for WHO-endorsed goals like the End TB Strategy.

Grants and Collaborations: Collaborations span global institutions (WHO, Stop TB Partnership, ICMR), national programs (India’s National Tuberculosis Elimination Programme), and academic institutions (Princeton University, US CDC). His models inform policy decisions on TB control, pandemic response, and health system investments.

Labs and Teams: Leads research groups at the MRC Centre for Global Infectious Disease Analysis and the NIHR Health Protection Research Unit in Respiratory Infections, fostering interdisciplinary teams in epidemiology and mathematical modeling.