Martín
López-García

Lecturer

Department of Applied Mathematics, School of Mathematics

University of Leeds

About Me

I am a Lecturer in the School of Mathematics at the University of Leeds. During 2016-2019, I was an MRC Skills Development Fellow and the PI for the MRC funded project

Mathematical modelling of the emergence and spread of antibiotic resistant bacteria in healthcare settings: a stochastic approach

In this project, the aim is to develop new stochastic models (and new mathematical tools for analysing them) regarding the spread of bacteria in hospital settings. My hope is to identify the most probable routes of bacterial spread in these settings, and to identify the most effective control strategies that can be applied, by using hospital data and Bayesian statistical techniques for parameter estimation.

I am a member of the Mathematical Biology and Medicine Group at the University of Leeds, and of the Stochastic Modelling Group at the Complutense University of Madrid. I carry out research in Mathematical Modelling in Health & Disease, and I am interested in a variety of processes involved in Infection & Immunity, including the analysis of the immune response, the within-host modelling of viral and bacterial infections, as well as the analysis of population-level epidemic processes.

I also collaborate in the HECOIRA project, an Engineering and Physical Sciences Research council and University of Leeds four year funded project in collaboration with St James’ University Teaching Hospital in Leeds, Hairmyres Hospital in Lanarkshire, Monaghans and Apex4D. In this project, led by Prof. Catherine Noakes (School of Civil Engineering, University of Leeds), the aim is to develop new approaches that optimise hospital design and operation with core infection control and patient wellbeing in mind.

Research

You can find my publications below. Press on the title of any publication and you will be redirected to the paper site.

    2020
  1. Jeffrey P-A, López-García M, Castro M, Lythe G, Molina-París C (2020) On exact and approximate approaches for stochastic receptor-ligand competition dynamics: an ecological perspective. Mathematics, 8: 1014.

  2. Wilson AM, King M-F, López-García M, Weir MH, Sexton JD, Kostov GE, Julian TR, Canales RA, Noakes CJ, Reynolds KA (2020) Evaluating a transfer gradient assumption in a fomite-mediated microbial transmission model using an experimental and Bayesian approach. Journal of the Royal Society Interface, 17: 20200121.

  3. Wilson AM, Abney SE, King M-F, Weir MH, López-García M, Sexton JD, Dancer S, Proctor J, Noakes CJ, Reynolds KA (2020) COVID-19 and non-traditional mask use: How do various materials compare in infection risk reduction for those wearing masks? Journal of Hospital Infection, published on-line.

  4. King M-F, López-García M, Atedoghu KP, Zhang N, Wilson AM, Weterings M, Hiwar W, Dancer SJ, Noakes CJ, Fletcher LA (2020) Bacterial transfer to fingertips during sequential surface contacts with and without gloves. Indoor Air, 00: 1-12.

  5. Carruthers J, Lythe G, López-García M, Gillard JJ, Laws TR, Lukaszewski R, Molina-París C (2020) Stochastic dynamics of Francisella tularensis infection and replication. PLoS Computational Biology, 16: e1007752.

  6. 2019
  7. Carruthers J, López-García M, Lythe G, Molina-París C (2019) Multi-scale modelling of bacterial infections. Mathematics Today, Sept 2019.

  8. Ward J, López-García M (2019) Exact analysis of summary statistics for continuous-time discrete-state Markov processes on networks using graph-automorphism lumping. Applied Network Science, 4: 108.

  9. López-García M, King M-F, Noakes CJ (2019) A multicompartment SIS stochastic model with zonal ventilation for the spread of nosocomial infections: detection, outbreak management and infection control. Risk Analysis, 39: 1825-1842.

  10. de la Higuera L, López-García M, Castro M, Abourashchi N, Lythe G, Molina-París C (2019) Fate of a naive T cell: a stochastic journey. Frontiers in Immunology, 10: 194.

  11. 2018
  12. Castro M, López-García M, Lythe G, Molina-París C (2018) First passage events in biological systems with non-exponential inter-event times. Scientific Reports, 8: 15054.

  13. López-García M, Nowicka M, Bendtsen C, Lythe G, Ponnambalam S, Molina-París C (2018) Quantifying phosphorylation timescales of receptor-ligand complexes: a Markovian matrix-analytic approach. Royal Society Open Biology, 8: 180126.

  14. Carruthers J, López-García M, Gillard JJ, Laws TR, Lythe G, Molina-París C (2018) A novel stochastic multi-scale model of Francisella tularensis infection to predict risk of infection in a laboratory. Frontiers in Microbiology, 9: 1165.

  15. López-García M, Kypraios T (2018) A unified stochastic modelling framework for the spread of nosocomial infections. Journal of the Royal Society Interface, 15: 20180060.

  16. Sambaturu N, Mukherjee S, López-García M, Molina-París C, Menon GI, Chandra N (2018) Role of genetic heterogeneity in determining the epidemiological severity of H1N1 influenza. PLoS Computational Biology, 14: e1006069.

  17. Gómez-Corral A, López-García M (2018) Perturbation analysis in finite LD-QBD processes and applications to epidemic models. Numerical Linear Algebra with Applications, 25: e2160.

  18. López-García M, Nowicka M, Fearnley GW, Ponnambalam S, Lythe G, Molina-París C (2018) Performance measures in stochastic processes and the matrix-analytic approach. In: Munsky B, Hlavacek W, Tsimring L (eds.) Quantitative Biology: Theory, Computational Methods and Examples of Models, MIT Press, 2018

  19. Gómez-Corral A, López-García M (2018) A within-host stochastic model for nematode infection. Mathematics, 6: 143.

  20. López-García M, Aruru M, Pyne S (2018) Health analytics and disease modeling for better understanding of healthcare associated infections. BLDE University Journal of Health Sciences, 3: 69-74.

  21. 2017
  22. Artalejo JR, Gómez-Corral A, López-García M, Molina-París C (2017) Stochastic descriptors to study the fate and potential of naive T cell clonotypes in the periphery. Journal of Mathematical Biology, 74: 673-708.

  23. Gómez-Corral A, López-García M (2017) On SIR epidemic models with generally distributed infectious periods: number of secondary cases and probability of infection. International Journal of Biomathematics, 10: 1750024 (13 pages).

  24. de la Higuera L, López-García M, Lythe G, Molina-París C (2017) IL-2 stimulation of regulatory T cells: a stochastic and algorithmic approach. In: Pahle J, Matthäus F, Graw F (eds.) Modeling Cellular Systems, 81-105.

  25. 2016
  26. López-García M (2016) Stochastic descriptors in an SIR epidemic model for heterogeneous individuals in small networks. Mathematical Biosciences, 271: 42-61.

  27. 2015
  28. Economou A, Gómez-Corral A, López-García M (2015) A stochastic SIS epidemic model with heterogeneous contacts. Physica A: Statistical Mechanics and its Applications, 421: 78-97.

  29. Gómez-Corral A, López-García M (2015) Lifetime and reproduction of a marked individual in a two-species competition process. Applied Mathematics and Computation, 264: 223-245.

  30. 2014
  31. Gómez-Corral A, López-García M (2014) Maximum queue lengths during a fixed time interval in the M/M/c retrial queue. Applied Mathematics and Computation, 235: 124-136.

  32. Gómez-Corral A, López-García M (2014) Control strategies for a stochastic model of host-parasite interaction in a seasonal environment. Journal of Theoretical Biology, 354: 1-11.

  33. 2013
  34. Gómez-Corral A, López-García M (2013) Maximum population sizes in host-parasitoid models. International Journal of Biomathematics, 6: 1350002 (28 pages).

  35. Gómez-Corral A, López-García M (2013) Modeling host-parasitoid interactions with correlated events. Applied Mathematical Modelling, 37: 5452-5463.

  36. 2012
  37. Gómez-Corral A, López-García M (2012) Extinction times and size of the surviving species in a two-species competition process. Journal of Mathematical Biology, 64: 255-289.

  38. Gómez-Corral A, López-García M (2012) On the number of births and deaths during an extinction cycle, and the survival of a certain individual in a competition process. Computers & Mathematics with Applications, 64: 236-259.

Media

My research has attracted some attention from different media. This is a recent article published by The Hindu Indian national newspaper, about our recent work published in PLoS Computational Biology:

Genetic diversity can prevent rapid spread of infectious diseases (The Hindu, 31-03-2018, in English)

A related piece of news is

Diversity in our genes may hold the key to the spread of infections (Research Matters, 10-09-2018, in English)

I was also interviewed by the Spanish newspaper "Infolibre", within its "Talento a la fuga" (Fleeing talent!) section, as an example of Spanish scientists having to leave Spain due to budget cuts in science carried out by the Spanish government

Spanish mathematician as an example of the British commitment to research (InfoLibre, 08-05-2016, in Spanish)

You can also find many news online due to the Vicent Caselles prize that I was recently awarded by the Spanish Mathematical Society and the BBVA Foundation, for the research carried out during my PhD and early postdoctoral stage

Awarded for "solving challenges of our time" (El Pais, 04-10-2016, in Spanish)
Once again the Vicent Caselles awards recognize originality, relevance and creativity of six Spanish mathematicians (BBVA, 18-07-2016, in English)
Reward for the scientific contributions of six young mathematical researchers (Europa Press, 15-07-2016, in Spanish)

You can find some videos and a personal interview by the Spanish newspaper ABC here

Six young Spaniards receive the Vicent Caselles Mathematical Research Awards (ABC, 04-10-2016, in Spanish)

You can also find here a piece of news at the Madrid regional TV (TeleMadrid) devoted to my research:

Spread of bacteria in hospitals analysed with mathematical models (TeleMadrid, 06-10-2016, in Spanish)

Teaching

I have participated in the following teaching activities:
  1. Module: MATH5315M Applied Statistics and Probability, MSc in Financial Mathematics, Leeds University Business School.
    Hours: 40 (Module leader)
    Date: Semester 1, 2019/2020
    Place: University of Leeds, United Kingdom.

  2. Module: MATH5315M Applied Statistics and Probability, MSc in Financial Mathematics, Leeds University Business School.
    Hours: 40 (Module leader)
    Date: Semester 1, 2018/2019
    Place: University of Leeds, United Kingdom.

  3. Module: MATH5315M Applied Statistics and Probability, MSc in Financial Mathematics, Leeds University Business School.
    Hours: 40 (Module leader)
    Date: Semester 1, 2017/2018
    Place: University of Leeds, United Kingdom.

  4. Module: MATH5315M Applied Statistics and Probability, MSc in Financial Mathematics, Leeds University Business School.
    Hours: 40 (Module leader)
    Date: Semester 1, 2016/2017
    Place: University of Leeds, United Kingdom.

  5. Module: MATH1050 Calculus and Mathematical Analysis, BSc Mathematics, School of Mathematics.
    Hours: 10 (Tutor)
    Date: Semester 1, 2016/2017
    Place: University of Leeds, United Kingdom.

  6. Module: Probability Theory, Degree in Mathematics.
    Hours: 45 (Tutor)
    Date: Semester 1, 2012/2013
    Place: Complutense University of Madrid, Spain.

  7. Module: Probability Theory, Degree in Mathematics.
    Hours: 60 (Tutor)
    Date: Semester 1, 2011/2012
    Place: Complutense University of Madrid, Spain.
I have also participated in several development assistance projects, organized by the Complutense University of Madrid (Spain) and the Spanish Agency for the International Development Assistance (AECID). The aim of these projects, led by Dr. Begoña Vitoriano, is to improve the formation of the students in MSc Statistics in different developing countries, providing them fundamental tools to participate in incipient research activity in their country, contributing to its development. This participation has meant teaching as lecturer the modules:
  1. Module: Stochastic Processes, MSc in Statistics.
    Hours: 45 (Module leader)
    Date: September 2016
    Place: Maputo (Mozambique).

  2. Module: Stochastic Processes, MSc in Statistics.
    Hours: 45 (Module leader)
    Date: September 2014
    Place: Maputo (Mozambique).

  3. Module: Stochastic Processes, MSc in Statistics.
    Hours: 45 (Module leader)
    Date: August 2013
    Place: San Salvador (El Salvador).
Other teaching activities amount to:
  1. Activity: ESTALMAT lecturer (Special program for the encouragement of the mathematical talent among highschool students, Spanish Government).
    Place and Date: Valencia, Spain, 2009.

  2. Activity: Instructor in the VI Modelling Week UCM (Event for mathematics degree students modeling problems brought by different companies, organized by the Complutense University of Madrid, Spain).
    Place and Date: Complutense University of Madrid, Spain, 2012.

Videogames

I usually use these videogames when delivering interactive and hands-on talks in Schools and Colleges. If you want, you can have a look at the slides that I use in these talks: Slides. Contact me if you want me to give a talk in your School!


You need Flash installed in order to play these videogames

Moving particle!

This videogame shows how a discrete-time Markov chain works. This particle moves, at each step, one unit to the left with probability p, and to the right with probability 1-p. Position 9 is a reflecting barrier, so that if the particle is at position 9, it moves left in the next step with probability 1. Position 0 is an absorbing barrier, so that the particle stops once it reaches position 0. Can you guess how many movements are needed for reaching position 0? Choose a value for p, a starting position, simulate the process 100 times and observe how long it takes for the particle to reach position 0 in each simulation.



Hospital Infections! - Scenario 1

This videogame shows how we can use stochastic processes to simulate the spread of a hospital-acquired (nosocomial) infection in an intensive care unit. You need to allocate 8 patients in 8 different beds. Press a bed to allocate a patient, and press again to remove the patient from that bed. Once the 8 patients have been allocated, press "Simulate Bacterial Outbreak". The computer will simulate a bacterial outbreak in this intensive care unit, and predict how many patients (histogram and average) will get infected during the outbreak. Try different configurations until you find the best allocation of patients leading to the smallest outbreak. Note that patients sharing the same room are more likely to infect each other.

Scenario 2

In this scenario, there are some patients (pink color) suffering from a chronic disease. It has been estimated that patients suffering from this disease take four times as long to recover from a bacterial infection than non-chronic patients (black color). You need to allocate 4 non-chronic and 4 chronic patients in 8 different beds. Press a bed once to allocate a non-chronic patient, press again to allocate a chronic patient, and press again to remove the patient from that bed. Once the 8 patients have been allocated, press "Simulate Bacterial Outbreak". The computer will simulate a bacterial outbreak in this intensive care unit, and predict how many patients (histogram and average) will get infected during the outbreak. Try different configurations until you find the best allocation of patients leading to the smallest outbreak. Note that patients sharing the same room are more likely to infect each other. Is it better to allocate chronic and non-chronic patients in different rooms? Or is it better to mix them up?

Scenario 3

In this scenario, we deal with a bacteria that spreads through the air, and we are given the opportunity to design the indoor ventilation of the hospital. This ventilation will have an impact on how the bacteria spreads, so you need to be wise choosing the best possible ventilation setting to avoid the spread of the bacteria. You can choose among three ventilation settings, and you can also choose where the patient starting the bacterial outbreak is located (by pressing on a bed). Once you are ready, press "Simulate Bacterial Outbreak". The computer will simulate a bacterial outbreak in this intensive care unit, and predict how many patients (histogram and average) will get infected during the outbreak. Try different configurations until you find the best ventilation setting for each possible location of the patient starting the outbreak.

Contact Me

If you are interested in my research, or would like to enquiry about the possibility of carrying out a PhD in this research area -Mathematical Biology, Immunology and Epidemiology-, please drop me an email.

Location

Office 10.18d, School of Mathematics, University of Leeds

Phone

+44 (0)113-343-8951
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