Imperial College London

Dr. Nimalan Arinaminpathy (Nim Pathy)

Faculty of MedicineSchool of Public Health

Reader in Mathematical Epidemiology
 
 
 
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Contact

 

nim.pathy Website

 
 
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Location

 

Praed StreetSt Mary's Campus

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Summary

 

Summary

I apply mathematical and statistical tools to study the transmission dynamics of infectious diseases, with equal interest in basic science and policy-focused analysis. 

Research interests

A major focus of my research is in the interface between health/economic systems and infectious diseases, particularly in the context of human tuberculosis. This includes understanding how health systems shape the control of infectious diseases (with the Public Health Foundation of India), and studying financing mechanisms for the supply of drugs to countries in need (with the Stop TB Partnership).

I am periodically seconded to the US Centers for Disease Control and Prevention, where I apply mathematical modelling to the surveillance and control of seasonal and pandemic influenza, amongst other topics.

More broadly, events in global financial markets since 2007 have heightened interest in applying insights from other systems, including infectious disease epidemiology, to understanding the spread and control of 'contagion' in modern financial systems. With colleagues from the Bank of England and the University of Oxford, I maintain a continuing involvement in this area.   

Biographical sketch

I trained in Applied Mathematics (BA Cambridge 2000, D.Phil Oxford 2005); between these programmes I spent a year as a scientist in a government research lab (Dstl, 2001). 

Following my DPhil I trained in mathematical epidemiology as a postdoctoral researcher, first at the University of Oxford and then at Princeton University (USA) before returning to the UK.

Publications

Journals

Mandal S, Das H, Deo S, et al., 2021, Combining serology with case-detection, to allow the easing of restrictions against SARS-CoV-2: a modelling-based study in India, Scientific Reports, Vol:11, ISSN:2045-2322, Pages:1-9

Fu H, Lewnard JA, Frost I, et al., 2021, Modelling the global burden of drug-resistant tuberculosis avertable by a post-exposure vaccine, Nature Communications, Vol:12, ISSN:2041-1723, Pages:1-9

Ricks S, Denkinger CM, Schumacher SG, et al., 2020, The potential impact of urine-LAM diagnostics on tuberculosis incidence and mortality: a modelling analysis, Plos Medicine, Vol:17, ISSN:1549-1277

Cilloni L, Arinaminpathy N, Stagg H, et al., 2020, Trade-offs between cost and accuracy in active case-finding for tuberculosis: a dynamic modelling analysis, Plos Medicine, Vol:17, ISSN:1549-1277, Pages:1-20

Cilloni L, Fu H, Vesga JF, et al., 2020, The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis, Eclinicalmedicine, Vol:28, ISSN:2589-5370

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