Mathematical modelling of the emergence and spread of antibiotic resistant bacteria in healthcare settings: a stochastic approach
Lead Research Organisation:
University of Leeds
Department Name: Applied Mathematics
Abstract
See Case for Support for abbreviations and references.
Antibiotic resistance of pathogenic bacteria has historically arisen in parallel with the development of new antibiotics; this race posing a major health problem worldwide where bacteria seem to be winning [33]. A paradigmatic example is methicillin-resistant Staphylococcus aureus (MRSA), which can cause severe infections in the bloodstream and the lung and that, after developing resistance against penicillin, has become resistant also against a second antibiotic, methicillin. Development of resistance against antibiotic can occur due to antibiotic pressure, where non adequate prescription policies play a fundamental role. This is one of the reasons for DRB being a particular challenging problem in healthcare facilities, together with other reasons such as the presence of aged individuals with weaken immune systems. The problem of the presence of DRB in HCSs has taken the next step by their spread in the community (non-healthcare environments). This has led to the appearance of new strains which are able to cause severe infections in healthy individuals. Moreover, the infiltration of these new community-related strains in HCSs has become an additional challenge.
In order to avoid the emergence and spread of DRB in HCSs, different strategies are usually followed: appropriate antibiotic prescription policies, management of staffing levels, isolation of infected patients, compliance of hygiene procedures, etc. However, most of HCSs usually follow a combination of these procedures, and the individual efficacy of each of them is hard to measure. This quantification is important not only due to the scarcity of resources in these clinical environments, but also because some of these policies entail moral and ethical problems. Mathematical models have proven to be a robust tool for addressing the efficacy of these individual strategies, as well as for identifying the factors involved in the emergence and spread of DRB in HCSs.
The aim of this fellowship is to contribute to the mathematical modelling in the area, in order to answer a number of open questions. Particular questions that will be addressed within this fellowship are: which is the importance of some factors, such as the contamination of the healthcare setting environment (for example, equipment), in the spread of resistant bacteria in healthcare settings? How does this spread occur in different healthcare settings (for example, in hospitals versus nursing homes)? What is the impact caused by the existing heterogeneities among individuals within the HCS (healthy individuals, such as HCWs, versus moderate or severe ill patients; adults versus children; patients under antibiotic treatment, ...)?. Additional questions to be addressed within this fellowship are related to the use of clinical data for refining the mathematical models, and the consideration of new mathematical models that can explain the process by which DRB arises within a particular individual.
The emergence and spread of DRB is a major problem worldwide. However, due to financial reasons (for example, some antibiotics newly developed are only effective for a few years, with the subsequent development of new DRB strains) the number of pharmaceutical companies working in new antibiotics development is scarce, and governmental financial incentives are usually required [24]. Moreover, it is worth noting that, in Europe, it has been estimated that infections with MDRB cause around 25000 deaths per year [25], with an estimated cost of 16 million additional bed-days (translating into 7 billion Euros in direct medical costs) [19]. Thus, it is necessary to combine the development of new antibiotics with control intervention measures to avoid the emergence and the spread of DRB among HCSs, which is at the same time crucial to implement intervention strategies based in quantitative knowledge.
Antibiotic resistance of pathogenic bacteria has historically arisen in parallel with the development of new antibiotics; this race posing a major health problem worldwide where bacteria seem to be winning [33]. A paradigmatic example is methicillin-resistant Staphylococcus aureus (MRSA), which can cause severe infections in the bloodstream and the lung and that, after developing resistance against penicillin, has become resistant also against a second antibiotic, methicillin. Development of resistance against antibiotic can occur due to antibiotic pressure, where non adequate prescription policies play a fundamental role. This is one of the reasons for DRB being a particular challenging problem in healthcare facilities, together with other reasons such as the presence of aged individuals with weaken immune systems. The problem of the presence of DRB in HCSs has taken the next step by their spread in the community (non-healthcare environments). This has led to the appearance of new strains which are able to cause severe infections in healthy individuals. Moreover, the infiltration of these new community-related strains in HCSs has become an additional challenge.
In order to avoid the emergence and spread of DRB in HCSs, different strategies are usually followed: appropriate antibiotic prescription policies, management of staffing levels, isolation of infected patients, compliance of hygiene procedures, etc. However, most of HCSs usually follow a combination of these procedures, and the individual efficacy of each of them is hard to measure. This quantification is important not only due to the scarcity of resources in these clinical environments, but also because some of these policies entail moral and ethical problems. Mathematical models have proven to be a robust tool for addressing the efficacy of these individual strategies, as well as for identifying the factors involved in the emergence and spread of DRB in HCSs.
The aim of this fellowship is to contribute to the mathematical modelling in the area, in order to answer a number of open questions. Particular questions that will be addressed within this fellowship are: which is the importance of some factors, such as the contamination of the healthcare setting environment (for example, equipment), in the spread of resistant bacteria in healthcare settings? How does this spread occur in different healthcare settings (for example, in hospitals versus nursing homes)? What is the impact caused by the existing heterogeneities among individuals within the HCS (healthy individuals, such as HCWs, versus moderate or severe ill patients; adults versus children; patients under antibiotic treatment, ...)?. Additional questions to be addressed within this fellowship are related to the use of clinical data for refining the mathematical models, and the consideration of new mathematical models that can explain the process by which DRB arises within a particular individual.
The emergence and spread of DRB is a major problem worldwide. However, due to financial reasons (for example, some antibiotics newly developed are only effective for a few years, with the subsequent development of new DRB strains) the number of pharmaceutical companies working in new antibiotics development is scarce, and governmental financial incentives are usually required [24]. Moreover, it is worth noting that, in Europe, it has been estimated that infections with MDRB cause around 25000 deaths per year [25], with an estimated cost of 16 million additional bed-days (translating into 7 billion Euros in direct medical costs) [19]. Thus, it is necessary to combine the development of new antibiotics with control intervention measures to avoid the emergence and the spread of DRB among HCSs, which is at the same time crucial to implement intervention strategies based in quantitative knowledge.
Technical Summary
See Case for Support document for abbreviations and references.
This fellowship focusses on the mathematical modelling of the emergence and spread of DRB in HCSs. Due to the small population sizes involved in HCSs, the stochastic approach is considered. Main aims of this research amount to: (i) to develop intra-host models for the emergence of DRB; (ii) to relate the quantitative information obtained from these models with new epidemiological models in the population level for the spread of these bacteria strains among individuals in HCSs. These new models will address at the same time a number of open questions in the area (e.g., competition between different strains, or consideration of HCSs different than hospitals); (iii) to develop new stochastic models and tools for analysing the efficacy of intervention measures for controlling the spread of DRB in HCSs; (iv) to adapt tools that I already developed [P7,P10], and develop new mathematical/statistical tools, to address the intrinsic heterogeneity among individuals in HCSs; and (v) to relate models with clinical data.
In order to attain the objectives listed above, I will make use of a wide range of techniques in which I have expertise. Among others, these techniques amount to: study of stochastic descriptors, analysis of first-passage times and absorption probabilities, use of auxiliary Markov chains, Laplace-Stieltjes transforms and probability generating functions, consideration of phase-type distributions, and algorithmic approaches within the matrix-analytic techniques [17]. On the other hand, particular skills development objectives within this fellowship are to widen my clinical knowledge in DRB, and to apply statistical techniques in order to relate the stochastic models developed within this fellowship with clinical data provided by clinical collaborators. To this end, different statistical techniques (the ABC algorithm, the Gibbs sampler or Monte Carlo Markov Chain methods) will be considered.
This fellowship focusses on the mathematical modelling of the emergence and spread of DRB in HCSs. Due to the small population sizes involved in HCSs, the stochastic approach is considered. Main aims of this research amount to: (i) to develop intra-host models for the emergence of DRB; (ii) to relate the quantitative information obtained from these models with new epidemiological models in the population level for the spread of these bacteria strains among individuals in HCSs. These new models will address at the same time a number of open questions in the area (e.g., competition between different strains, or consideration of HCSs different than hospitals); (iii) to develop new stochastic models and tools for analysing the efficacy of intervention measures for controlling the spread of DRB in HCSs; (iv) to adapt tools that I already developed [P7,P10], and develop new mathematical/statistical tools, to address the intrinsic heterogeneity among individuals in HCSs; and (v) to relate models with clinical data.
In order to attain the objectives listed above, I will make use of a wide range of techniques in which I have expertise. Among others, these techniques amount to: study of stochastic descriptors, analysis of first-passage times and absorption probabilities, use of auxiliary Markov chains, Laplace-Stieltjes transforms and probability generating functions, consideration of phase-type distributions, and algorithmic approaches within the matrix-analytic techniques [17]. On the other hand, particular skills development objectives within this fellowship are to widen my clinical knowledge in DRB, and to apply statistical techniques in order to relate the stochastic models developed within this fellowship with clinical data provided by clinical collaborators. To this end, different statistical techniques (the ABC algorithm, the Gibbs sampler or Monte Carlo Markov Chain methods) will be considered.
Planned Impact
See Case for Support for abbreviations.
I consider myself, in terms of my skills and career development, and due to the special characteristics of the Skills Development Fellowships, one of the main beneficiaries of this fellowship. This can be classified as short-term (within the project) impact of this research. I have a quantitative background, seeking to develop new expertise and skills for modelling the emergence and spread of DRB in HCSs. I will not only learn about the clinical aspects of these processes, but I will also develop skills in the application of statistical techniques to inform my mathematical models with clinical data. I will develop complementary skills (e.g. networking, student supervision...) not only by means of carrying out related activities during the fellowship, but also by attending a wide range of courses offered by the Staff and Departmental Development Unit (University of Leeds). Mid-term impact (1-5 years after the project) will be my establishment as an independent researcher in the area.
Beneficiaries of this research, in the mid- and long-term, are all across the healthcare sector. There is poor evidence base (see Letters of Support and Case for Support) for many of the prevention and control measures implemented in HCSs for avoiding the emergence and spread of DRB. My fellowship will help to understand their transmission routes, and to obtain quantitative knowledge regarding the efficacy of control measures usually applied. It has been identified, as an open question, the quantification of the efficacy of individual measures taken within intervention policies such as the Search & Destroy policy (see Case for Support), which is a combination of individual measures that leads to financial, legal and ethical problems. Thus, quantifying the efficacy of these interventions could lead to the design of intervention policies where only the most efficient individual measures are implemented, saving resources and avoiding these legal and ethical problems. New results in the area will directly help agents involved in healthcare policy making (e.g., collaborators and advisers in this proposal who have advisory roles in different national and international institutions for avoiding the emergence and spread of DRB in HCSs, such as Public Health England, the NHS or the UK Department of Health).
MDRB cause around 25000 deaths per year in Europe, with an estimated cost of 16 million additional bed-days (7 billion (euros) of direct medical costs) (see Case for Support and references therein). Thus, indirect beneficiaries in the long-term are patients, HCWs and institutions, since avoiding infections during (M)DRB outbreaks in HCSs directly depends on the implementation of quantitatively-based control measures, following recommendations by advisers mentioned above. Moreover, new tools developed within this fellowship will be useful in the area of mathematical epidemiology (e.g. analysis of heterogeneous environments), having an impact in the research carried out by other researchers, as well as by collaborators within this fellowship. Thus, the beneficiaries identified within their research projects will be also indirectly benefited, in the mid- and long-term, by the research carried out here.
Finally, additional indirect beneficiaries, in the short-term, will be participants in activities in which I am and I will be involved. I have participated in the Higher Education Day (HED) in the Notre Dame Sixth College in Leeds (2014). During this day, I showed my research to students, to inspire them to consider researching, in the future, in the interface between mathematics and biology. My attendance to the HED in June 2015 is confirmed, and I have also participated in similar activities in different institutions abroad during the last years. Thus, I plan to maintain my participation in these activities in the future, as well as similar ones which may arise, in order to keep delivering this kind of impact.
I consider myself, in terms of my skills and career development, and due to the special characteristics of the Skills Development Fellowships, one of the main beneficiaries of this fellowship. This can be classified as short-term (within the project) impact of this research. I have a quantitative background, seeking to develop new expertise and skills for modelling the emergence and spread of DRB in HCSs. I will not only learn about the clinical aspects of these processes, but I will also develop skills in the application of statistical techniques to inform my mathematical models with clinical data. I will develop complementary skills (e.g. networking, student supervision...) not only by means of carrying out related activities during the fellowship, but also by attending a wide range of courses offered by the Staff and Departmental Development Unit (University of Leeds). Mid-term impact (1-5 years after the project) will be my establishment as an independent researcher in the area.
Beneficiaries of this research, in the mid- and long-term, are all across the healthcare sector. There is poor evidence base (see Letters of Support and Case for Support) for many of the prevention and control measures implemented in HCSs for avoiding the emergence and spread of DRB. My fellowship will help to understand their transmission routes, and to obtain quantitative knowledge regarding the efficacy of control measures usually applied. It has been identified, as an open question, the quantification of the efficacy of individual measures taken within intervention policies such as the Search & Destroy policy (see Case for Support), which is a combination of individual measures that leads to financial, legal and ethical problems. Thus, quantifying the efficacy of these interventions could lead to the design of intervention policies where only the most efficient individual measures are implemented, saving resources and avoiding these legal and ethical problems. New results in the area will directly help agents involved in healthcare policy making (e.g., collaborators and advisers in this proposal who have advisory roles in different national and international institutions for avoiding the emergence and spread of DRB in HCSs, such as Public Health England, the NHS or the UK Department of Health).
MDRB cause around 25000 deaths per year in Europe, with an estimated cost of 16 million additional bed-days (7 billion (euros) of direct medical costs) (see Case for Support and references therein). Thus, indirect beneficiaries in the long-term are patients, HCWs and institutions, since avoiding infections during (M)DRB outbreaks in HCSs directly depends on the implementation of quantitatively-based control measures, following recommendations by advisers mentioned above. Moreover, new tools developed within this fellowship will be useful in the area of mathematical epidemiology (e.g. analysis of heterogeneous environments), having an impact in the research carried out by other researchers, as well as by collaborators within this fellowship. Thus, the beneficiaries identified within their research projects will be also indirectly benefited, in the mid- and long-term, by the research carried out here.
Finally, additional indirect beneficiaries, in the short-term, will be participants in activities in which I am and I will be involved. I have participated in the Higher Education Day (HED) in the Notre Dame Sixth College in Leeds (2014). During this day, I showed my research to students, to inspire them to consider researching, in the future, in the interface between mathematics and biology. My attendance to the HED in June 2015 is confirmed, and I have also participated in similar activities in different institutions abroad during the last years. Thus, I plan to maintain my participation in these activities in the future, as well as similar ones which may arise, in order to keep delivering this kind of impact.
Organisations
- University of Leeds (Fellow, Lead Research Organisation)
- Comillas Pontifical University (Collaboration)
- University of Arizona (Collaboration)
- Complutense University of Madrid (Collaboration)
- UNIVERSITY OF NOTTINGHAM (Collaboration)
- Médecins Sans Frontières (MSF) (Collaboration)
- Defence Science & Technology Laboratory (DSTL) (Collaboration)
- University of Pittsburgh (Collaboration)
- London School of Hygiene and Tropical Medicine (LSHTM) (Collaboration)
- Indian Institute of Science Bangalore (Collaboration)
- UNIVERSITY OF LEEDS (Collaboration)
- University of Adelaide (Collaboration)
- Jimenez Diaz Hospital Foundation (Project Partner)
- The Leeds Teaching Hospitals Charitable (Project Partner)
People |
ORCID iD |
| Martin Lopez-Garcia (Principal Investigator / Fellow) |
Publications
Carruthers J
(2020)
Stochastic dynamics of Francisella tularensis infection and replication.
in PLoS computational biology
Carruthers J
(2019)
Multi-Scale Modelling of Bacterial Infections
in Mathematics Today
Carruthers J
(2018)
A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory.
in Frontiers in microbiology
Castro M
(2018)
First passage events in biological systems with non-exponential inter-event times.
in Scientific reports
Gómez-Corral A
(2018)
Perturbation analysis in finite LD-QBD processes and applications to epidemic models.
in Numerical linear algebra with applications
King MF
(2021)
Why is mock care not a good proxy for predicting hand contamination during patient care?
in The Journal of hospital infection
King MF
(2020)
Bacterial transfer to fingertips during sequential surface contacts with and without gloves.
in Indoor air
López-García M
(2018)
A unified stochastic modelling framework for the spread of nosocomial infections.
in Journal of the Royal Society, Interface
| Description | Contribution to evidence support within the Scientific Advisory Group for Emergencies (SAGE) during the COVID-19 pandemic |
| Geographic Reach | National |
| Policy Influence Type | Participation in a guidance/advisory committee |
| Impact | I do not belong to SAGE personally, but have contributed as a co-author to a few SAGE evidence reports focused on the environmental transmission of SARS-CoV-2. This contribution surrounds the contribution of the fomite route (i.e. contact with contaminated surfaces) to COVID-19 transmission. This contribution has been based on research developed within this award. In particular, techniques from the papers below [1,2] where implemented to provide some preliminary estimates of infection risk via the fomite route, which informed some key recommendations within these SAGE reports. [1] 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. [2] 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, 30: 993-1004. Directly related to this research and impact, I am currently involved in two national projects for SARS-CoV-2 transmission modelling: TRACK and a National Core Study project led by HSE. The aim in TRACK is to try to estimate infection risk in public transport settings, in collaboration with DfT, PHE, Dstl and other academic partners. The National Core Study project, which involves many institutions and partners within the UK, aims to better understand transmission risk for SARS-CoV-2, and potential mitigation strategies for different environments related to workplace settings. |
| URL | https://press.hse.gov.uk/2020/11/04/hses-chief-scientific-adviser-welcomes-introduction-of-new-covid... |
| Description | International Centre for Theoretical Sciences (Bangalore, India) - Funding for organising the DMPH 2019 conference at ICTS |
| Amount | ₹1,500,000 (INR) |
| Organisation | International Centre for Theoretical Sciences |
| Sector | Academic/University |
| Country | India |
| Start | 07/2019 |
| End | 07/2019 |
| Description | London Mathematical Society Scheme 3 Grant |
| Amount | £350 (GBP) |
| Organisation | London Mathematical Society |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 04/2017 |
| Description | London Mathematical Society Scheme 3 Grant |
| Amount | £1,600 (GBP) |
| Organisation | London Mathematical Society |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 09/2017 |
| End | 08/2018 |
| Description | Medical Research Council: MRC Festival Open Award |
| Amount | £1,205 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2018 |
| End | 07/2018 |
| Description | PhD Studentship - EPSRC CASE Competition - University of Leeds |
| Amount | £75,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2019 |
| End | 03/2023 |
| Description | School of Mathematics Research Funds |
| Amount | £500 (GBP) |
| Organisation | University of Leeds |
| Department | School of Mathematics Leeds |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 04/2017 |
| Description | School of Mathematics Research Funds |
| Amount | £540 (GBP) |
| Organisation | University of Leeds |
| Department | School of Mathematics Leeds |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 03/2017 |
| End | 03/2017 |
| Description | School of Mathematics Research Funds, University of Leeds - Funding for organising the SMHD 2019 conference in Leeds |
| Amount | £3,000 (GBP) |
| Organisation | University of Leeds |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 09/2019 |
| End | 09/2019 |
| Description | School of Mathematics: Research Funds |
| Amount | £400 (GBP) |
| Organisation | University of Exeter |
| Department | School of Mathematics |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 02/2018 |
| End | 02/2018 |
| Description | TRACK: Transport Risk Assessment for COVID Knowledge |
| Amount | £1,374,632 (GBP) |
| Funding ID | EP/V032658/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2020 |
| End | 03/2022 |
| Title | A unified stochastic modelling framework for antibiotic resistant bacteria in hospital settings |
| Description | In this collaboration with Dr. Theodore Kypraios, we have developed a new unified stochastic modelling framework for the emergence and spread of antibiotic resistant bacteria in healthcare settings. This framework allows one to consider: - spontaneous patient colonization, - patient-staff contamination/colonization, - environmental contamination, - patient cohorting, - health-care workers (HCWs) hand-washing compliance levels, among other factors affecting bacterial spread in hospital settings. I believe this will represent a significant step forward in the area, since it is a single unified framework which contains many existing models in the literature as particular case studies. Thus, by computing the reproduction number of the different agents in the hospital ward, one is able to identify the most probable routes of bacterial spread for different outbreaks in different hospital settings. In particular, bacterial outbreaks involving Vancomycin-resistant Enterococci, or Methicillin-resistant Staphylococcus aureus, are analysed in this work for outbreaks occurring at different hospital wards, such as the Respiratory Intensive Care Unit at Beijing Tongren Hospital, or the onco-haematological unit at the University Medical Center Freiburg in Germany. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | I believe this work, once published, will represent a significant step forward in the area, since it is a single unified framework which contains many existing models in the literature as particular case studies. This is supported by reviewers' comments received regarding the submission of this work at the Journal of the Royal Society Interface (currently under review), comments such as "This very-well written manuscript [...] is nice work [...]. I think it is relevant for more applied researchers and might have impact on policy in hospitals.", or "This is a very well-written paper that uses interesting mathematics to address an important problem in public health in a novel and useful way. The model and analysis are clearly described, and the case-studies are excellent. [...] the paper would be a great contribution to JRSI." |
| Title | A new method for perturbation analysis in epidemic models - an application to hospital-acquired infections |
| Description | This new computational & analytical method is explained within the manuscript "Perturbation analysis in finite LD-QBD processes and applications to epidemic models" which is a collaboration with Dr. Antonio Gomez-Corral (Complutense University of Madrid, Spain). When analysing a mathematical model for the spread dynamics of a pathogen among a population, such as patients and healthcare workers among a hospital ward, a typical difficulty that arises is to estimate the parameter values of this model (the infection rates between patients and healthcare workers, the average infectious period of each individual,...), and also to estimate how much each of these parameters affect the outputs of the model (e.g., how much the recovery period length of each individual affects the total number of infected individuals at the end of the outbreak? When a bacterial outbreak arises in a hospital ward, how much the average length of stay of patients in this ward affects the disease spread dynamics?,...). This impact can be estimated by carrying out a perturbation analysis of the computational model. However, a typical difficulty that arises is that the number of parameters in these computational/mathematical models combinatorially increases with the number of individuals (i.e., patients and healthcare workers) in the hospital ward. In this manuscript, we develop a new analytical and computational methodology that allows for an efficient and comprehensive perturbation analysis of the epidemic model under study. We illustrate this methodology by applying it to a computational model for the spread of two bacterial strains (an antibiotic-susceptible, AS, and an antibiotic-resistant AR, strain) within a hospital ward. The perturbation analysis allows to obtain the following clinical insights: (i) Implementing control strategies against the AS strain can be counter-productive, since the AS strain competes with the AR strain for infecting patients, (ii) The rate at which patients are discharged as well as the infectiousness of the AS and AR bacterial strains are the most important factors affecting the dynamics of these infections. (iii) The usage of antibiotics which are effective against both strains of bacteria is specially effective for reducing the length of the outbreak. This control strategy also seems to play a significant role in reducing the peak of the outbreak. (iv) The usage of antibiotics which are only effective against the strain of AS bacteria can have a negative impact for controlling the AR bacterial strain outbreak. This is related to the fact that these antibiotics have no direct impact on the recovery of patients infected by AR bacterial strain, but at the same time it helps to remove from the system its direct competitor (i.e., the AS bacterial strain). |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2016 |
| Provided To Others? | Yes |
| Impact | We hope that this new methodology will be broadly used in the area of computational/mathematical epidemiology in the mid-future, not only for analysing the spread dynamics of bacterial outbreaks within hospital wards, but more generally when analysing compartmental epidemic models related to many different diseases and populations. We will be able to address if this impact is achieved by tracking the amounts of citations of this manuscript once published, in the mid-future. We recently sent this manuscript to Prof. Peter Taylor (University of Melbourne, Australia) and Prof. Hal Caswell (University of Amsterdam), who are experts in the area of Mathematical Epidemiology and perturbation analysis of mathematical/computational models. Replies received from them were very encouraging and we will keep in touch with these and others researchers in the area related to this new methodology. The main output is the publication 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. |
| Title | A new methodology for analysing infection processes with non-Markovian dynamics - an application to hospital-acquired infections |
| Description | In collaboration with Dr. Mario Castro (Pontificia Comillas University, Madrid), we have developed a new methodology that allows one to analyse summary statistics or stochastic descriptors (i.e., quantities of interest) in a stochastic process with non-Markovian events. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | We looked in particular into processes related to Biology, and focused on a particular case study where the interest is in analysing the spread of an antibiotic resistant bacteria (MRSA) in a hospital ward. Our methodology allows one to incorporate realistic hospital ward screening policies into the mathematical model, which leads to non-Markovian events, and computing the probability of a single member of staff suffering the infection during the nosocomial outbreak. The main output is the publication 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. |
| Title | A new stochastic approach for analysing bacterial infection across scales: cellular, within-host and population levels |
| Description | In collaboration with researchers at the Defence Science and Technology Laboratory (DSTL), we have developed a new multi-scale model for the analysis of bacterial infections across different scales (from the intra-cellular, to the within-host and population levels). We look at the bacteria Francisella Tularensis (agent causing tularemia) as a particular case study, and construct a stochastic model that accounts for the (intra-cellular) infection dynamics of phagocytes in the lung, within-host infection dynamics (interaction between extra-cellular bacteria and phagocytes), and population level dynamics (airborne spread of bacteria in a microbiology laboratory after an accidental bacterial release). |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | Our model allows one to compute dose-response probabilities and times until patients showing symptoms. We are able then to predict the number of individual showing symptoms after an accidental bacterial release in a microbiology laboratory. Although we have focused in this work on the bacteria Francisella Tularensis, we hope this methodology can be seen as proof of concept, so that it can be applied to many different bacterial infections. The main output is the publication 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. |
| Title | A new stochastic model for analysing the airborne spread of hospital-acquired infections |
| Description | In this collaborative work with Prof. Catherine Noakes and Dr. Marco-Felipe King, within the HECOIRA project, we have been looking at how to link airflow dynamics occurring in hospital settings, with the spread of hospital-acquired infections in these settings. We propose a multi-compartment SIS stochastic model that is able to link these dynamics. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | Our stochastic model allows one to analyse the spread of hospital-acquired infections while taking into account the airflow dynamics occurring in the corresponding hospital ward. Moreover, it allows one to explore the impact of outbreak management and screening policies in the spread dynamics. The main output is the manuscript López-García M, King M-F, Noakes CJ (2019) A multi-compartment SIS stochastic model with zonal ventilation for the spread of nosocomial infections: detection, outbreak management and infection control. Risk Analysis, in press, which has been recently accepted for publication. |
| Title | A new technique for linking HLA class-I genetic heterogeneities at the individual level with infection spread dynamics occurring at the population level |
| Description | This work, which is an interdisciplinary and collaborative work with researchers at the Department of Biochemistry (Indian Institute of Science, Bangalore, India) led by Prof. Nagasuma Chandra, the mathematician Prof. Gautam Menon (Institute of Mathematical Sciences, Chennai), and the applied mathematician Prof. Carmen Molina-Paris (University of Leeds, UK), represents a new technique for linking immunological information at the within-host level with infection dynamics at the population level. In particular, with this new methodology one can use existing genotype prevalence data available worldwide, regarding HLA class-I alleles prevalence among different individuals and ethnicities around the world, together with sequencing data for different viral (or bacterial) strains identified in different outbreaks in the past, in order to predict the epidemic spread potential of different pathogens (in this work, we focused on Influenza as a case study) among heterogeneous populations (in terms of individuals having different susceptibility profiles due to HLA class-I genetic heterogeneities). |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | The main output is the publication 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. at PLoS Computational Biology, which is a prestigious journal in Applied Mathematics, Biochemistry, and Computational Biology. Since the idea of linking immunological information at the individual level with epidemic dynamics at the population level has been recently identified in the literature as a current challenge in this area, I believe this will be a significant step forward in the field. Moreover, the publication has recently attracted media attention at Research Matters (https://researchmatters.in/news/diversity-our-genes-may-hold-key-spread-infections) and The Hindu (https://www.thehindu.com/sci-tech/science/genetic-diversity-can-prevent-rapid-spread-of-infectious-diseases/article23401491.ece) |
| Title | A new unified stochastic modelling framework for the spread of antibiotic resistant bacteria in hospital settings |
| Description | In this collaboration with Dr. Theodore Kypraios (University of Nottingham, UK), we have developed a new unified framework for the representation and analysis of stochastic models for the spread of hospital-acquired infections (and, in particular, antibiotic resistant bacteria) in hospital settings. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | This methodology allows one to incorporate into the mathematical/computational model spontaneous colonization of patients, patient-to-staff and staff-to-patient contamination/colonization, environmental contamination, patient cohorting, room configuration of the hospital ward, staff hand-washing compliance levels, the presence of different types of HCWs or specific staff-patient contact network structures. Moreover, we explain how to exactly compute the reproduction number of each agent at the hospital ward during the nosocomial outbreak. In this work, we make use of five representative case studies, regarding both hypothetical and real nosocomial outbreaks at hospital wards, to show how this unified modelling framework comprehend, as particular cases, many of the existing models in the field. We conduct several numerical studies and our results highlight the importance of maintaining high hand-hygiene compliance levels by healthcare workers, support control strategies including to improve environmental cleaning during nosocomial outbreaks and show the potential of some healthcare workers to act as super-spreaders during these outbreaks. The main output is the publication 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. |
| Title | Dataset associated with "Stochastic dynamics of Francisella Tularensis infection and replication" |
| Description | Python codes associated with "Stochastic dynamics of Francisella Tularensis infection and replication" |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | http://archive.researchdata.leeds.ac.uk/677/ |
| Description | A novel stochastic multi-scale model for bacterial infections: cellular, within-host and population scales |
| Organisation | Defence Science & Technology Laboratory (DSTL) |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | This is a collaboration with the Mathematical Biology & Medicine Group at Leeds (Prof. Carmen Molina-Paris, Prof. Grant Lythe, Mr Jonathan Carruthers) and the Defence Science & Technology Laboratory (DSTL; Dr. Joseph Gillard, Dr. Thomas Laws). As outlined in my Skills Development Fellowship proposal, one of the main aims was to develop multi-scale models that can account for bacterial infection dynamics occurring across scales (from the cellular, to the within-host and population levels). In this collaboration, we look at the particular case of the bacteria Francisella Tularensis (FT). For these bacteria, we developed a novel stochastic multi-scale model for the infection dynamics of FT across scales. My expertise, together with that of the Mathematical Biology & Medicine Group and our collaborators at DSTL, allowed us to (i) Incorporate non-Markovian events occurring in these systems (such as events related to the rupture of infected phagocytes in the lung of the infected host); (ii) Compute the rupture size distribution of a given infected phagocyte (that is, the amount of bacteria released upon rupture of the phagocyte); (iii) Compute the probability of an infected individual (who has inhaled a given dose of FT) showing symptoms after exposure, and the mean time until response; (iv) Calibrate, and qualitatively validate, our mathematical models with clinical and experimental data, by means of using Bayesian Statistical techniques; (v) Link our intra-cellular and within-host model with a population level model, to evaluate the risk of infection for individuals in a microbiology laboratory after an accidental release of FT. This is a central work within my fellowship, since the items above clearly account for several of the original objectives within my MRC Skills Development Fellowship proposal (developing models of bacterial infection across scales, using Bayesian Statistical techniques for linking these models with experimental and clinical data, and evaluating the spread of bacteria in healthcare-related facilities different than hospitals -in this case, a microbiology laboratory-). This collaboration is being continued currently, focused on analysing other bacterial pathogens of interest, and on showing how the novel multi-scale methodology developed for FT infection can be generalized to these other pathogens. |
| Collaborator Contribution | In this work, we collaborated with Dr. Joseph Gillard (modeller at DSTL), and Dr. Roman Lukaszewsky and Dr. Thomas Laws (experimentalists in DSTL). They provided us with expertise both from the modelling and the experimental sides, and specially regarding FT infection. For a second model, they provided us with some FT infection data. |
| Impact | Main output is the publication 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. This joint work has also enhanced our collaboration with DSTL. For example, I have been able to get a PhD studentship (CASE award) with DSTL as an industrial partner (see Awards & Recognition section). A second manuscript, 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. which incorporates migration of bacteria across organs within the host, has been recently published at PLOS Computational Biology. This second mathematical model has been calibrated with experimental data provided by DSTL. |
| Start Year | 2017 |
| Description | A unified stochastic modelling framework for the spread of nosocomial infections |
| Organisation | University of Nottingham |
| Department | School of Mathematics Nottingham |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | In this work, our aim was to try to unify most of the mathematical models that have been proposed in the literature so far for the spread of antibiotic resistant bacteria in healthcare settings, leading to a general framework for the modelling of nosocomial infections. Once this unified framework has been proposed, I designed a technique by which the reproduction number of the different agents in the hospital setting (e.g., contaminated surfaces, healthcare workers -HCWs- with contaminated hands, colonized patients, contaminated volunteers,...) can be quantified. This reproduction number helps us to identify the most probable routes of spread followed by antibiotic resistant bacteria during a nosocomial outbreak. Main clinical insights of this work are: - our results highlight the importance of maintaining high hand-hygiene compliance levels by HCWs, - support infection control strategies including to improve environmental cleaning during an outbreak; and - show the potential of some HCWs in particular hospital wards to act as super-spreaders during nosocomial outbreaks. |
| Collaborator Contribution | As part of this Skills Development Fellowship, my collaboration with Dr. Theodore Kypraios in this piece of research allowed me to learn more about the clinical side of antibiotic resistant bacteria in healthcare settings, and about the existing mathematical models that have been proposed so far for the analysis of these pathogens, since Dr. Kypraios is an expert in this area. He has a wide range of publications on the mathematical modelling of these outbreaks, in collaboration with clinicians and statisticians. Moreover, my collaboration with Dr. Kypraios has helped me to learn more about the usage of Statistical Bayesian techniques for parameter estimation in these models, which was one of the main skill development objectives of this fellowship, since he is an expert in this topic. |
| Impact | The main output of this collaboration is the manuscript 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. This work has been presented in a number of meetings already (Nottingham, Barcelona, Leeds,... etc), for which we have received very positive feedback from attendants. |
| Start Year | 2016 |
| Description | Analysing the impact of airflow on the spread of airborne infections in hospitals |
| Organisation | University of Leeds |
| Department | School of Civil Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | In this collaboration, the aim is to join the expertise by M. Lopez-Garcia -related to the development and analysis of mathematical/computational models for the spread of disease among individuals in a population- with the expertise by the research group of Prof. Catherine Noakes -related to the experimental measurement and the development of computational models for airflow dynamics- in order to analyse the role played by airflow and ventilation in the spread of airborne infections in hospital settings. M. Lopez-Garcia proposed this collaboration by showing, in the draft in [1], how techniques previously developed by him with collaborators [2-4] -related to the analysis of stochastic epidemic processes- can be put together with techniques previously developed by Prof. Noakes [5], in order to assess the role played by airflow dynamics and ventilation in the spread dynamics of nosocomial infections (such as resistant bacteria) in hospital wards. When an outbreak related to a nosocomial pathogen begins in a hospital ward, the ventilation regime in this hospital ward (rooms configurations, existence of corridors, windows and airflows,...) needs to be considered as a control strategy that is in place even if this outbreak has not been detected by the healthcare workers in this ward. Thus, it is to be expected that some ventilation regimes might help more to contain the spread of the pathogen than others. The aim of this collaboration is to identify ventilation regimes that should be avoided, and those ones that are to be recommended, as a control strategy to decrease the spread of nosocomial pathogens in the ward. [1] Lopez-Garcia M, King M-F, Noakes CJ (2019) A multi-compartment SIS stochastic model with zonal ventilation for the spread of nosocomial infections: detection, outbreak management and infection control. Risk Analysis, in press. [2] Gomez-Corral A, Lopez-Garcia M (2017) Perturbation analysis in finite LD-QBD processes and applications to epidemic models. Numerical Linear Algebra with Applications, DOI: 10.1002/nla.2160 [3] Lopez-Garcia M (2016) Stochastic descriptors in an SIR epidemic model for heterogeneous individuals in small networks. Mathematical Biosciences, 271, 42-61. [4] Lopez-Garcia M, Camacho A (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. [5] Noakes CJ, Sleigh PA (2009) Mathematical models for assessing the role of airflow on the risk of airborne infection in hospitals. Journal of the Royal Society Interface, rsif20090305. |
| Collaborator Contribution | Prof. Noakes and Dr King helped to incorporate the techniques developed by their group in Ref. [5] for linking airflow dynamics and ventilation regimes with infection rates in epidemic models. |
| Impact | This collaboration is multi-disciplinary, joining the mathematical techniques by M. Lopez-Garcia in the area of stochastic processes and mathematical epidemiology with the experimental knowledge by Prof. Noakes and their expertise in fluid-dynamics for modelling airflow and ventilation. Main outcome is the manuscript Lopez-Garcia M, King M-F, Noakes CJ (2019) A multi-compartment SIS stochastic model with zonal ventilation for the spread of nosocomial infections: detection, outbreak management and infection control. Risk Analysis, in press, which has been accepted for publication. The outcomes of this research can help to identify ventilation regimes to be avoided in hospital settings for controlling the spread of nosocomial pathogens. This has also been the seed for more collaborations with the HECOIRA project, for the modelling of the emergence and spread of antibiotic resistant bacteria in healthcare settings, during the last months. |
| Start Year | 2017 |
| Description | Analysing the importance of contact routes for bacterial spread in hospital settings: the impact of wearing hospital nitrile gloves |
| Organisation | University of Leeds |
| Department | School of Mechanical Engineering Leeds |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | In this collaboration with Prof. Catherine Noakes, Dr. Marco-Felipe King, Dr Stephanie Dancer (Consultant Microbiologist, NHS Lanarkshire) and others, within the HECOIRA project https://hecoira.leeds.ac.uk/meet-the-team/ our aim has been to look at the importance that hand-surface contact routes have in the spread of antibiotic resistant bacteria in healthcare facilities. In particular, we have looked in this collaboration at how much bacteria is spread during sequential hand-surface contacts. The main aim was to measure and model the viable concentration of Escherichia coli on fingertips after sequential contacts with inoculated plastic fomites, and assess the effect of nitrile gloves on the concentration. |
| Collaborator Contribution | In this work, a mixture of experimental work, modelling approaches and Bayesian Statistical methods has been used in order to assess the amount of bacteria transmitted during sequential hand-surface contacts. The group of Prof. Noakes, in close collaboration with Dr. Stephanie Dancer, carried out experiments where coupons of smooth laminate plastic, were inoculated with E. coli, allowed to dry for 60mins and 35 participants touched these sequentially up to 8 times using either a bare- or nitrile gloved finger. Fingers were swabbed, and colonies cultured on media for enumeration. Then, Dr. King in collaboration with Dr. Lopez-Garcia developed a linear mixed effects model in order to examine the effect of gloves as well as the individual participant's finger area and surface pressure. An Approximate Bayesian Computation (ABC) method was used to estimate transfer efficiency for a single contact from experimental data and compared against distributions from other literature sources. |
| Impact | This collaboration has led to the joint manuscript. 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, 30: 993-1004. |
| Start Year | 2017 |
| Description | Considering realistic inter-event time distributions in mathematical models for biological systems: an application to nosocomial infections |
| Organisation | Comillas Pontifical University |
| Country | Spain |
| Sector | Academic/University |
| PI Contribution | One of the main unrealistic assumptions that are considered when implementing epidemic mathematical/computational models for the spread of antibiotic resistant bacteria in hospital settings is the consideration that, from a computational perspective, events in these systems occur after Exponentially-distributed random times. This assumption is a common assumption made when analysing these systems, due to nice mathematical/computational features of this Exponential distribution. However, it is well-known that this assumption might be unrealistic in some situations, so that new methodologies are needed in order to make our computational models closer to reality by considering more realistic inter-event distributions. In this collaboration, M. Lopez-Garcia is contributing with his expertise in the usage of a number of probabilistic tools when analysing these stochastic processes in Medicine and Biology. The objective of this collaborative work is to show how more realistic distributions can be used when analysing these systems. We illustrate this new methodology by considering a computational model for the spread of a nosocomial pathogen in a hospital ward, and when focusing on the risk of infection of a particular healthcare worker in this ward. When the bacterial outbreak is detected, it is typical that the hospital workers implement screening policies in order to detect new infectious cases during the outbreak. We show how these screening policies (e.g., screening healthcare workers every X days since the outbreak is detected) can be incorporated into our computational models by means of replacing the Exponentially distributed inter-event times by more general distributions, while still being able to analyse the resulting process. |
| Collaborator Contribution | This is a collaborative work with Prof. Mario Castro (Comillas Pontifical University, Madrid), Prof. Grant Lythe and Prof. Carmen Molina-Paris (University of Leeds) which resulted in the publication 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. Prof. Castro contributed with his expertise in the analysis of biological systems, the consideration of realistic distributions in these systems, and his expertise in the usage of R and Mathematica (software used in this collaborative work). In order to carry out this collaboration, Prof. Castro visited the University of Leeds for the 2016-2017 academic year, partially funded by the Spanish Ministry of Science. |
| Impact | Main output is the publication 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. From a methodological perspective, we expect these new techniques to be widely applied in the future for incorporating realistic inter-event time distributions when analysing Biological systems by means of mathematical/computational models. From a Mathematical Epidemiology perspective, the case study analysed in this manuscript for the spread of a bacteria in a hospital ward will allow us to identify optimum screening policies for detecting the infection of healthcare workers during these outbreaks, while keeping below some threshold the total amount of resources needed for the implementation of these screening policies. |
| Start Year | 2016 |
| Description | Health analytics and disease modeling for better understanding of healthcare-associated infections |
| Organisation | University of Pittsburgh |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | I was invited by Prof. Saumyadipta Pyne (Scientific Director, Public Health Dynamics Lab, University of Pittsburgh) to write a review on existing mathematical and computational modelling approaches for analysing the spread of antibiotic resistant bacteria, and more in general hospital-acquired pathogens, in healthcare facilities. This review was to be published in the BLDE University Journal of Health Sciences, for which he is an editor. As a result, I wrote a review paper in collaboration with Prof. Pyne and Dr. Meghana Aruru (Adjunct Professor, College of Pharmacy, California Northstate University) on this topic. This review allowed me to write about the recent advances within this Skills Development Fellowship, and in particular I was able to comment on the following pieces of work 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, 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, 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, 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, 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, which are directly related to this Skills Development Fellowship. |
| Collaborator Contribution | Prof. Pyne contributed in designing, writing and proof-reading the manuscript. In particular, he specially contributed in describing agent-based modelling approaches. Dr. Aruru did a similar contribution, specially focusing on policy-related aspects and the specific importance of hospital infection control in India. |
| Impact | Main output is the publication 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. |
| Start Year | 2017 |
| Description | Linking HLA class-I genetic heterogeneities at the individual (within-host) level with epidemic dynamics at the population level |
| Organisation | Indian Institute of Science Bangalore |
| Country | India |
| Sector | Academic/University |
| PI Contribution | This is a multi-disciplinary collaboration with Ms Narmada Sambaturu and Dr. Sumanta Mukherjee, who belong to the research group led by Prof. Nagasuma Chandra at the Department of Biochemistry at the Indian Institute of Science, together with Prof. Carmen Molina-Paris (University of Leeds) and Prof. Gautam Menon (Institute of Mathematical Sciences, Chennai). In this collaboration, the objective is to link heterogeneities at the individual level, in terms of HLA class-I genetic individual information, with the epidemic dynamics for the spread of a viral or bacterial strain in a given population. We have provided with expertise in the mathematical modelling of the spread of infection among individuals in a population, using epidemic compartmental-based models (such as the multi-type SIR model) for predicting the epidemic dynamics. |
| Collaborator Contribution | Our partners at the Indian Institute of Science (IISc) have provided their expertise with analysing HLA genetic data regarding the prevalence of different HLA alleles in different ethnicities around the world. This allows one to consider the spread of pathogens among individuals in a population when these individuals are heterogeneous in their susceptibility against a given viral or bacterial strain, due to existing HLA genetic heterogeneities among different individuals and ethnicities around the world. This work is directly relevant to this MRC research project since linking within-host individual dynamics with population-level epidemic dynamics was one of the main objectives listed in the fellowship, and is a well-known challenge in Mathematical Epidemiology. This collaboration arose as a perfect opportunity since our partners at IISc had access to sequencing data for different viral strains (in this work, Influenza is analysed as a case study, since data was available for this pathogen) identified around the world. Now that we have been able to develop this new technique, my aim is to analyse its potential applicability for -antibiotic resistant- bacteria in hospital settings, such as Mycobacterium Tuberculosis. |
| Impact | Main output is the publication 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. Our research has been recently featured in the media https://www.thehindu.com/sci-tech/science/genetic-diversity-can-prevent-rapid-spread-of-infectious-diseases/article23401491.ece https://researchmatters.in/news/diversity-our-genes-may-hold-key-spread-infections |
| Start Year | 2016 |
| Description | Modelling hand-surface transmission of bacteria - Pathogen Accretion Model |
| Organisation | University of Leeds |
| Department | Faculty of Medicine and Health |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | In this collaboration with Prof. Mark Wilcox (Faculty of Medicine and Health, University of Leeds), I have been learning about how to use the pathogen accretion model (originally developed by some other collaborators of mine, Prof. Catherine Noakes and Dr. Marco Felipe-King, School of Civil Engineering, University of Leeds) to model the transmission of bacteria from hand to surfaces and surfaces to hand, as a result of hand-surface contacts. This is part of the Skills Development part of this fellowship, since it was planned that within this fellowship I was planning to learn more about the clinical side of bacteria, and about how to model their transmission, by discussing, among others, with Prof. Wilcox. |
| Collaborator Contribution | My discussions during these months with Prof. Wilcox allowed me to learn more about this topic. Moreover, he was able to provide me with some data regarding the airborne spread of bacteria as a result of hand-drying episodes (following hand-hygiene), where different hand drying methods can lead to the spread of (potentially harmful) bacteria from hands to nearby surfaces. Then, the pathogen accretion model (PAM) can help to model how subsequent hand-surface contacts made by different people with these contaminated surfaces can trigger the spread of bacteria around other surfaces, and the hands of these individuals. |
| Impact | This is part of the Skills Development part of this fellowship. I have learned more about how to use the pathogen accretion model for modelling hand-to-surface and surface-to-hand spread of bacteria during hand-surface contacts, and about the clinical side of bacteria, by my discussions with Prof. Wilcox. Moreover, learning more about the pathogen accretion model has led me to closely engage with Prof. Catherine Noakes and Dr. Marco Felipe-King (School of Civil Engineering, University of Leeds), who are the original designers of the pathogen accretion model. This has allowed me to start new collaborations with these researchers, directly related to the topic of this fellowship (spread of antibiotic resistant bacteria in healthcare settings), which will continue during the course of the fellowship. In particular, this has led to my participation in the HECOIRA project, led by Prof. Catherine Noakes, in collaboration with other clinicians (e.g., Dr. Stephanie Dancer, Consultant Microbiologist, NHS Lanarkshire). |
| Start Year | 2016 |
| Description | Modelling transfer of bacteria during hand-surface contacts in healthcare settings |
| Organisation | University of Arizona |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | This is a collaboration with the research group of Kelly Reynolds, Robert Canales and collaborators. PhD student Amanda Wilson visited Leeds and worked with Dr Lopez-Garcia, Dr King and Prof Noakes in a project related to modelling the bacterial transfer between finger and surfaces during several hand-surface contacts. The group at University of Arizona provided some hand-surface transfer contact data, while the group at Leeds contributed with the modelling and computational expertise. Ms Wilson led the work in close collaboration with Dr King and Dr Lopez-Garcia. |
| Collaborator Contribution | The group at University of Arizona provided some hand-surface transfer contact data, while the group at Leeds contributed with the modelling and computational expertise, and Ms Wilson led the work in close collaboration with Dr King and Dr Lopez-Garcia. The research group has also engaged with Dr Tim Julian (Group Leader of Pathogens and Human Health, Department Environmental Microbiology, Eawag), who is an expert in this area. |
| Impact | This collaboration has led to two manuscripts recently published: 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. 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, 30: 993-1004. |
| Start Year | 2019 |
| Description | New tools for analysing epidemics on contact networks: an application to a nosocomial outbreak in an Intensive Care Unit |
| Organisation | University of Leeds |
| Department | School of Mathematics Leeds |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This is a collaboration with Dr. Jonathan Ward at the Department of Applied Mathematics, University of Leeds. We have jointly developed a new framework for the analysis of epidemic processes on contact networks. We have shown how the explosive number of states of the underlying continuous-time Markov chain can be reduced by generalising the Graph Automorphism Lumping methodology. We have shown the applicability of this technique by implementing it to the spread of an antibiotic resistant bacteria in the Intensive Care Unit considered by Laura Temime (PNAS, 2009). |
| Collaborator Contribution | Dr Ward has brought expertise in the theory of graph automorphisms, and the graph automorphism lumping methodology. He is joint first author of the resulting manuscript Ward JA, 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. |
| Impact | Manuscript: Ward JA, 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. Invitation to speak and present this work at the workshop "Mathematical Modeling and Statistical Analysis of Infectious Disease Outbreaks", CIRM, Marseille, France. https://conferences.cirm-math.fr/2303.html Presenting at this workshop was by invitation only |
| Start Year | 2018 |
| Description | On the reinfection of individuals in stochastic epidemic models |
| Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | M. Lopez-Garcia visited MSF Epicentre in February-March 2017 (2 weeks) in order to collaborate with Dr. Anton Camacho (MSF, London School of Hygiene and Tropical Medicine). This collaboration is part of the skills development part of this fellowship. In particular, one of the objectives of this fellowship is that M. Lopez-Garcia can be trained in the application of Bayesian statistical techniques in order to calibrate mathematical/computational models in Mathematical Epidemiology by means of using infection longitudinal clinical data, as planned within this Skills Development Fellowship. In order to do this, and as a training-oriented collaboration, M. Lopez-Garcia designed during this visit a number of simple mathematical epidemic models (SIS, SIRS, SIRI,..) that account for reinfection of individuals. For these models, M. Lopez-Garcia implemented a number of techniques (usage of first-step arguments, auxiliary absorbing continuous-time Markov chains,..) in order to compute the probability that a given individual in the population gets reinfected by a propagating pathogen [1]. One of the questions is how to use this probability as the likelihood when applying Bayesian Statistical Techniques for calibrating the models with longitudinal clinical data. Working in this area with Dr. Camacho also allowed me also to visit in 2018 the research group of Dr. Joshua Ross in Adelaide. Dr Ross is a world leader in the area of Mathematical Epidemiology. All of this has resulted into a joint manuscript in preparation [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. |
| Collaborator Contribution | During the research visit to MSF, A. Camacho trained M. Lopez-Garcia in the usage of a number of statistical techniques in order to estimate model parameters from longitudinal data. In particular, in this collaborative work [1] which is in preparation, we use longitudinal clinical data related to a two-wave epidemic of flu that occurred in 1971 in the Tristan da Cunha island [2], in order to calibrate the epidemic models developed and analysed by M. Lopez-Garcia. From an epidemiological perspective, this will help to understand the reinfection dynamics in a wide range of epidemic scenarios. From a skills development perspective, this collaborative work represents a simple and effective way in which M. Lopez-Garcia is being able to learn about the statistical techniques for estimating parameters in epidemic models by using clinical data. [2] A Camacho, S Ballesteros, AL Graham, F Carrat, O Ratmann, and B Cazelles. Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study. In Proc. R. Soc. B, volume 278, pages 3635-3643. The Royal Society, 2011. Also, visiting the research group of Dr. Ross in Adelaide has allowed me to collaborate with these world-recognised researchers as well. A joint publication is in preparation. |
| Impact | Main output is the manuscript [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. which is in preparation. This collaboration is a fundamental part of the Skills Development part of this fellowship. One of the aims of the fellowship is that M. Lopez-Garcia is trained in the usage of statistical techniques in order to estimate parameters in epidemic models by using infection longitudinal data. Dr. Anton Camacho, who works at MSF Epicentre and belongs to the research group led by Dr. Sebastian Funk at the London School of Hygiene and Tropical Medicine, is an expert in the usage of these techniques [3-5], representing the perfect researcher who can help M. Lopez-Garcia with this training. [3] Camacho, A., Kucharski, A. J., Funk, S., Breman, J., Piot, P., & Edmunds, W. J. (2014). Potential for large outbreaks of Ebola virus disease. Epidemics, 9, 70-78. [4] Henao-Restrepo, A. M., Longini, I. M., Egger, M., Dean, N. E., Edmunds, W. J., Camacho, A., ... & Enwere, G. (2015). Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial. The Lancet, 386(9996), 857-866. [5] Camacho, A., Kucharski, A., Aki-Sawyerr, Y., White, M. A., Flasche, S., Baguelin, M., ... & Tiffany, A. (2015). Temporal Changes in Ebola Transmission in Sierra Leone and Implications for Control Requirements: a Real-time Modelling Study. PLoS Curr, 7. |
| Start Year | 2016 |
| Description | On the reinfection of individuals in stochastic epidemic models |
| Organisation | Médecins Sans Frontières (MSF) |
| Department | Epicentre - Médecins Sans Frontières (MSF Epicentre) |
| Country | France |
| Sector | Charity/Non Profit |
| PI Contribution | M. Lopez-Garcia visited MSF Epicentre in February-March 2017 (2 weeks) in order to collaborate with Dr. Anton Camacho (MSF, London School of Hygiene and Tropical Medicine). This collaboration is part of the skills development part of this fellowship. In particular, one of the objectives of this fellowship is that M. Lopez-Garcia can be trained in the application of Bayesian statistical techniques in order to calibrate mathematical/computational models in Mathematical Epidemiology by means of using infection longitudinal clinical data, as planned within this Skills Development Fellowship. In order to do this, and as a training-oriented collaboration, M. Lopez-Garcia designed during this visit a number of simple mathematical epidemic models (SIS, SIRS, SIRI,..) that account for reinfection of individuals. For these models, M. Lopez-Garcia implemented a number of techniques (usage of first-step arguments, auxiliary absorbing continuous-time Markov chains,..) in order to compute the probability that a given individual in the population gets reinfected by a propagating pathogen [1]. One of the questions is how to use this probability as the likelihood when applying Bayesian Statistical Techniques for calibrating the models with longitudinal clinical data. Working in this area with Dr. Camacho also allowed me also to visit in 2018 the research group of Dr. Joshua Ross in Adelaide. Dr Ross is a world leader in the area of Mathematical Epidemiology. All of this has resulted into a joint manuscript in preparation [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. |
| Collaborator Contribution | During the research visit to MSF, A. Camacho trained M. Lopez-Garcia in the usage of a number of statistical techniques in order to estimate model parameters from longitudinal data. In particular, in this collaborative work [1] which is in preparation, we use longitudinal clinical data related to a two-wave epidemic of flu that occurred in 1971 in the Tristan da Cunha island [2], in order to calibrate the epidemic models developed and analysed by M. Lopez-Garcia. From an epidemiological perspective, this will help to understand the reinfection dynamics in a wide range of epidemic scenarios. From a skills development perspective, this collaborative work represents a simple and effective way in which M. Lopez-Garcia is being able to learn about the statistical techniques for estimating parameters in epidemic models by using clinical data. [2] A Camacho, S Ballesteros, AL Graham, F Carrat, O Ratmann, and B Cazelles. Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study. In Proc. R. Soc. B, volume 278, pages 3635-3643. The Royal Society, 2011. Also, visiting the research group of Dr. Ross in Adelaide has allowed me to collaborate with these world-recognised researchers as well. A joint publication is in preparation. |
| Impact | Main output is the manuscript [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. which is in preparation. This collaboration is a fundamental part of the Skills Development part of this fellowship. One of the aims of the fellowship is that M. Lopez-Garcia is trained in the usage of statistical techniques in order to estimate parameters in epidemic models by using infection longitudinal data. Dr. Anton Camacho, who works at MSF Epicentre and belongs to the research group led by Dr. Sebastian Funk at the London School of Hygiene and Tropical Medicine, is an expert in the usage of these techniques [3-5], representing the perfect researcher who can help M. Lopez-Garcia with this training. [3] Camacho, A., Kucharski, A. J., Funk, S., Breman, J., Piot, P., & Edmunds, W. J. (2014). Potential for large outbreaks of Ebola virus disease. Epidemics, 9, 70-78. [4] Henao-Restrepo, A. M., Longini, I. M., Egger, M., Dean, N. E., Edmunds, W. J., Camacho, A., ... & Enwere, G. (2015). Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial. The Lancet, 386(9996), 857-866. [5] Camacho, A., Kucharski, A., Aki-Sawyerr, Y., White, M. A., Flasche, S., Baguelin, M., ... & Tiffany, A. (2015). Temporal Changes in Ebola Transmission in Sierra Leone and Implications for Control Requirements: a Real-time Modelling Study. PLoS Curr, 7. |
| Start Year | 2016 |
| Description | On the reinfection of individuals in stochastic epidemic models |
| Organisation | University of Adelaide |
| Country | Australia |
| Sector | Academic/University |
| PI Contribution | M. Lopez-Garcia visited MSF Epicentre in February-March 2017 (2 weeks) in order to collaborate with Dr. Anton Camacho (MSF, London School of Hygiene and Tropical Medicine). This collaboration is part of the skills development part of this fellowship. In particular, one of the objectives of this fellowship is that M. Lopez-Garcia can be trained in the application of Bayesian statistical techniques in order to calibrate mathematical/computational models in Mathematical Epidemiology by means of using infection longitudinal clinical data, as planned within this Skills Development Fellowship. In order to do this, and as a training-oriented collaboration, M. Lopez-Garcia designed during this visit a number of simple mathematical epidemic models (SIS, SIRS, SIRI,..) that account for reinfection of individuals. For these models, M. Lopez-Garcia implemented a number of techniques (usage of first-step arguments, auxiliary absorbing continuous-time Markov chains,..) in order to compute the probability that a given individual in the population gets reinfected by a propagating pathogen [1]. One of the questions is how to use this probability as the likelihood when applying Bayesian Statistical Techniques for calibrating the models with longitudinal clinical data. Working in this area with Dr. Camacho also allowed me also to visit in 2018 the research group of Dr. Joshua Ross in Adelaide. Dr Ross is a world leader in the area of Mathematical Epidemiology. All of this has resulted into a joint manuscript in preparation [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. |
| Collaborator Contribution | During the research visit to MSF, A. Camacho trained M. Lopez-Garcia in the usage of a number of statistical techniques in order to estimate model parameters from longitudinal data. In particular, in this collaborative work [1] which is in preparation, we use longitudinal clinical data related to a two-wave epidemic of flu that occurred in 1971 in the Tristan da Cunha island [2], in order to calibrate the epidemic models developed and analysed by M. Lopez-Garcia. From an epidemiological perspective, this will help to understand the reinfection dynamics in a wide range of epidemic scenarios. From a skills development perspective, this collaborative work represents a simple and effective way in which M. Lopez-Garcia is being able to learn about the statistical techniques for estimating parameters in epidemic models by using clinical data. [2] A Camacho, S Ballesteros, AL Graham, F Carrat, O Ratmann, and B Cazelles. Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study. In Proc. R. Soc. B, volume 278, pages 3635-3643. The Royal Society, 2011. Also, visiting the research group of Dr. Ross in Adelaide has allowed me to collaborate with these world-recognised researchers as well. A joint publication is in preparation. |
| Impact | Main output is the manuscript [1] M Lopez-Garcia, P Ballard, JV Ross, A Camacho (2019) On the reinfection of individuals in stochastic epidemic models. In preparation. which is in preparation. This collaboration is a fundamental part of the Skills Development part of this fellowship. One of the aims of the fellowship is that M. Lopez-Garcia is trained in the usage of statistical techniques in order to estimate parameters in epidemic models by using infection longitudinal data. Dr. Anton Camacho, who works at MSF Epicentre and belongs to the research group led by Dr. Sebastian Funk at the London School of Hygiene and Tropical Medicine, is an expert in the usage of these techniques [3-5], representing the perfect researcher who can help M. Lopez-Garcia with this training. [3] Camacho, A., Kucharski, A. J., Funk, S., Breman, J., Piot, P., & Edmunds, W. J. (2014). Potential for large outbreaks of Ebola virus disease. Epidemics, 9, 70-78. [4] Henao-Restrepo, A. M., Longini, I. M., Egger, M., Dean, N. E., Edmunds, W. J., Camacho, A., ... & Enwere, G. (2015). Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial. The Lancet, 386(9996), 857-866. [5] Camacho, A., Kucharski, A., Aki-Sawyerr, Y., White, M. A., Flasche, S., Baguelin, M., ... & Tiffany, A. (2015). Temporal Changes in Ebola Transmission in Sierra Leone and Implications for Control Requirements: a Real-time Modelling Study. PLoS Curr, 7. |
| Start Year | 2016 |
| Description | Perturbation analysis of stochastic processes: application to a two-strains bacterial outbreak in a hospital ward |
| Organisation | Complutense University of Madrid |
| Country | Spain |
| Sector | Academic/University |
| PI Contribution | This collaboration relates to a new computational & analytical method that has been included in the Research Databases & Models section. It relates to the publication Gómez-Corral A, López-García M, (2018). Perturbation analysis in finite LD-QBD processes and applications to epidemic models. Numerical Linear Algebra with Applications, which is a collaborative work with Dr. Antonio Gomez-Corral (Complutense University of Madrid, Spain). When analysing a mathematical model for the spread dynamics of a pathogen among a population, such as patients and healthcare workers among a hospital ward, a typical difficulty that arises is to estimate the parameter values of this model (the infection rates between patients and healthcare workers, the average infectious period of each individual,...), and also to estimate how much each of these parameters affect the outputs of the model (e.g., how much the recovery period length of each individual affects the total number of infected patients at the end of the outbreak? When a bacterial outbreak arises in a hospital ward, how much the average length of stay of patients in this ward affects the disease spread dynamics?,...). This impact can be estimated by carrying out a perturbation analysis of the computational model. However, a typical difficulty that arises is that the number of parameters in these computational/mathematical models combinatorially increases with the number of individuals (i.e., patients and healthcare workers) in the hospital ward. In this manuscript, we develop a new analytical and computational methodology that allows for an efficient and comprehensive perturbation analysis of the epidemic model under study. We illustrate this methodology by applying it to a computational model for the spread of two bacterial strains (an antibiotic-susceptible, AS, and an antibiotic-resistant AR, strain) within a hospital ward. The perturbation analysis allows to obtain the following clinical insights: (i) Implementing control strategies against the AS strain can be counter-productive, since the AS strain competes with the AR strain for infecting patients; (ii) The rate at which patients are discharged as well as the infectiousness of the AS and AR bacterial strains are the most important factors affecting the dynamics of these infections; (iii) The usage of antibiotics which are effective against both strains of bacteria is specially effective for reducing the length of the outbreak. This control strategy also seems to play a significant role in reducing the peak of the outbreak; (iv) The usage of antibiotics which are only effective against the strain of AS bacteria can have a negative impact for controlling the AR bacterial strain outbreak. This is related to the fact that these antibiotics have no direct impact on the recovery of patients infected by AR bacterial strain, but at the same time it helps to remove from the system its direct competitor (i.e., the AS bacterial strain). |
| Collaborator Contribution | Dr. Antonio Gomez-Corral is an expert in the analysis of stochastic processes and their application in Mathematical Epidemiology. He has contributed to this work by developing part of the analysis corresponding to this methodology, as well as by helping with the design of the computational model for the spread of two bacterial strains within a hospital ward. |
| Impact | The main output is the publication 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. We hope that this new methodology will be broadly used in the area of computational/mathematical epidemiology in the mid-future, not only for analysing the spread dynamics of bacterial outbreaks within hospital wards, but more generally when analysing compartmental epidemic models related to different diseases and populations. We will be able to address if this impact is achieved by tracking the amounts of citations of this manuscript once published, in the mid-future. To maximise the probabilities of delivering this impact, Dr. Antonio Gomez-Corral presented this work in the "Probability in the North-East" that took place at Leeds on April 2017. Moreover, we recently sent this manuscript to Prof. Peter Taylor (University of Melbourne, Australia) and Prof. Hal Caswell (University of Amsterdam), who are experts in the area of Mathematical Epidemiology and perturbation analysis of mathematical/computational models. Replies received from them were very encouraging and we will keep in touch with these and others researchers in the area related to this new methodology. |
| Start Year | 2016 |
| Title | Hospital Infections: Scenario 1 |
| Description | As part of the Impact and Public Engagement activities within this fellowship, M Lopez-Garcia has recently developed a series of video games called "Hospital Infections". These are a series of video games, developed in Actionscript2, where the player becomes the director of a hospital ward, who has to make some policy-making decisions during the course of an outbreak by an antibiotic resistant bacteria. In "Hospital Infections Scenario 1", the player can choose how to allocate patients among the different available rooms in this hospital ward, this rooms configuration having an impact on the spread dynamics of the nosocomial pathogen. A histogram plotting the probabilities related to the total number of individuals suffering the infection during the outbreak helps to identify the best strategies for controlling the outbreak. Moreover, an interactive panel allows the player to learn more about these infection processes. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The main objectives of these video games are: (i) To increase the awareness among the general public about the problem of antimicrobial resistance. One of the main aims is that this could help to improve the appropriate use of antibiotics among the general public; (ii) To create an interactive platform that can be used to publicise and show the research carried out within this fellowship to the general public; (iii) To show the usefulness of developing mathematical/computational models when analysing the spread of nosocomial infections in hospital settings; (iv) To encourage students in Schools and Colleges to carry out studies in the area of Mathematics applied to the Natural Sciences, Biology and Medicine, helping to reduce the problem of STEM skills shortage in the UK http://www.telegraph.co.uk/business/ready-and-enabled/stem-skills-shortfall/ ; (v) To help the general public to understand the main concepts of random processes and their applications in the area of Mathematical Epidemiology and Public Health. To this aim, M Lopez-Garcia has designed a specific web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html where these video games are publicly and freely available. This web-site also contains information related to some of the research carried out by the MRC in this area, and some explanations about the basic concepts related to antibiotic resistance. Moreover, these video games are being used in a number of public engagement activities being carried out by M Lopez-Garcia during the period of this fellowship, in order to maximise the chances of achieving objectives (i)-(v). For the same aim, these video games are also being presented in different scientific meetings to show the usefulness of this type of software for training, educational and public engagement purposes. Finally, more "Hospital Infections" video game scenarios will be developed during the course of this fellowship, improving as well the playability of the newly developed and the currently existing scenarios. The web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html that contains these video games will be also improved, in order to increase the visibility of these video games, to help to fulfil the objectives (i)-(v). |
| URL | https://matml.github.io/#videogames |
| Title | Hospital Infections: Scenario 2 |
| Description | As part of the Impact and Public Engagement activities within this fellowship, M Lopez-Garcia has recently developed a series of video games called "Hospital Infections". These are a series of video games, developed in Actionscript2, where the player becomes the director of a hospital ward, who has to make some policy-making decisions during the course of an outbreak by an antibiotic resistant bacteria. In "Hospital Infections Scenario 2", the player must now allocate two types of patients: patients suffering or not a chronic disease. It is explained to this player that suffering a chronic disease can mean that the immune system of this individual is weaker than usual, so that his/her susceptibility against the nosocomial pathogen might be higher. Thus, the decision about how to allocate these two types of patients among the available rooms needs now to take into account these individual heterogeneities, which will affect the spread dynamics of the nosocomial pathogen. Again, histograms and text explanations allow the player to look for the best strategy and to better understand these processes. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2017 |
| Impact | The main objectives of these video games are: (i) To increase the awareness among the general public about the problem of antimicrobial resistance. One of the main aims is that this could help to improve the appropriate use of antibiotics among the general public; (ii) To create an interactive platform that can be used to publicise and show the research carried out within this fellowship to the general public; (iii) To show the usefulness of developing mathematical/computational models when analysing the spread of nosocomial infections in hospital settings; (iv) To encourage students in Schools and Colleges to carry out studies in the area of Mathematics applied to the Natural Sciences, Biology and Medicine, helping to reduce the problem of STEM skills shortage in the UK http://www.telegraph.co.uk/business/ready-and-enabled/stem-skills-shortfall/ ; (v) To help the general public to understand the main concepts of random processes and their applications in the area of Mathematical Epidemiology and Public Health. To this aim, M Lopez-Garcia has designed a specific web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html where these video games are publicly and freely available. This web-site also contains information related to some of the research carried out by the MRC in this area, and some explanations about the basic concepts related to antibiotic resistance. Moreover, these video games are being used in a number of public engagement activities being carried out by M Lopez-Garcia during the period of this fellowship, in order to maximise the chances of achieving objectives (i)-(v). For the same aim, these video games are also being presented in different scientific meetings to show the usefulness of this type of software for training, educational and public engagement purposes. Finally, more "Hospital Infections" video game scenarios will be developed during the course of this fellowship, improving as well the playability of the newly developed and the currently existing scenarios. The web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html that contains these video games will be also improved, in order to increase the visibility of these video games, to help to fulfil the objectives (i)-(v). |
| URL | https://matml.github.io/#videogames |
| Title | Hospital Infections: Scenario 3 |
| Description | As part of the Impact and Public Engagement activities within this fellowship, M Lopez-Garcia has recently developed a series of video games called "Hospital Infections". These are a series of video games, developed in Actionscript2, where the player becomes the director of a hospital ward, who has to make some policy-making decisions during the course of an outbreak by an antibiotic resistant bacteria. In "Hospital Infections Scenario 3", the player can choose among a range of ventilation systems to be placed in a hospital ward, in order to avoid the spread of an airborne pathogen. The decision about which ventilation system is best to avoid the spread of this pathogen needs to take into account the extract ventilation rates in each room, the location of the different patients among different rooms, or the protocol in place in this hospital ward for the detection and declaration of a nosocomial outbreak. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2018 |
| Impact | The main objectives of these video games are: (i) To increase the awareness among the general public about the problem of antimicrobial resistance. One of the main aims is that this could help to improve the appropriate use of antibiotics among the general public; (ii) To create an interactive platform that can be used to publicise and show the research carried out within this fellowship to the general public; (iii) To show the usefulness of developing mathematical/computational models when analysing the spread of nosocomial infections in hospital settings; (iv) To encourage students in Schools and Colleges to carry out studies in the area of Mathematics applied to the Natural Sciences, Biology and Medicine, helping to reduce the problem of STEM skills shortage in the UK http://www.telegraph.co.uk/business/ready-and-enabled/stem-skills-shortfall/ ; (v) To help the general public to understand the main concepts of random processes and their applications in the area of Mathematical Epidemiology and Public Health. To this aim, M Lopez-Garcia has designed a specific web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html where these video games are publicly and freely available. This web-site also contains information related to some of the research carried out by the MRC in this area, and some explanations about the basic concepts related to antibiotic resistance. Moreover, these video games are being used in a number of public engagement activities being carried out by M Lopez-Garcia during the period of this fellowship, in order to maximise the chances of achieving objectives (i)-(v). For the same aim, these video games are also being presented in different scientific meetings to show the usefulness of this type of software for training, educational and public engagement purposes. Finally, more "Hospital Infections" video game scenarios will be developed during the course of this fellowship, improving as well the playability of the newly developed and the currently existing scenarios. The web-site https://www1.maths.leeds.ac.uk/~lopezgarcia/Bacteria.html that contains these video games will be also improved, in order to increase the visibility of these video games, to help to fulfil the objectives (i)-(v). |
| URL | https://matml.github.io/#videogames |
| Description | Article at the national magazine Muy Interesante ("Very Interesting"), Spain |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | As a result of receiving the "Vicent Caselles" research prize by the Spanish Royal Mathematical Society and the BBVA Foundation in Spain (see Awards & Recognition section), the research carried out by M Lopez-Garcia attracted a lot of attention. I was interviewed by a journalist from the Muy Interesante (Very Interesting) Spanish magazine, and an article was published in this journal on December 2016. The article can be found at https://www.pressreader.com/spain/muy-interesante/20161221 where the research carried out by this fellowship and the funding received by the MRC can be found specifically mentioned within the article. This kind of media attention is important for increasing the awareness of the problem of antibiotic resistance among the general public, but also to increase the awareness among the general public about the need for allocating funds for this type of research. The Muy Interesante magazine is the most read magazine in Spain according to the Spanish Media Research Association http://www.aimc.es/-What-is-AIMC-.html and in December 2016 had around 7.000.000 visits to its web-site, according to available data http://www.ojdinteractiva.es/medios-digitales/muy-interesante-evolucion-audiencia/totales/anual/529/trafico-global/ |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://www.pressreader.com/spain/muy-interesante/20161221 |
| Description | Article at the national newspaper ABC, Spain |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The "Vicent Caselles" research prize that M. Lopez-Garcia, together with other 5 young Spanish researchers, was awarded by the Spanish Royal Mathematical Society and the BBVA Foundation in Spain (see Awards & Recognition section) attracted a lot of media attention. A press release can be found at the ABC newspaper (Spain), http://www.abc.es/ciencia/abci-seis-jovenes-espanoles-reciben-premios-investigacion-matematica-vicent-caselles-201610042052_noticia.html about this research prize and the research that M Lopez-Garcia carries out (a video in Spanish with a short interview can also be found at that web-site). ABC is one of the most read newspapers in Spanish both online and printed (e.g., ABC sells more than 100.000 newspapers in Spain every day according to available data). |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.abc.es/ciencia/abci-seis-jovenes-espanoles-reciben-premios-investigacion-matematica-vicen... |
| Description | Article at the national newspaper El Pais, Spain |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The "Vicent Caselles" research prize that M. Lopez-Garcia, together with other 5 young Spanish researchers, was awarded by the Spanish Royal Mathematical Society and the BBVA Foundation in Spain (see Awards & Recognition section) attracted a lot of media attention. A press release can be found at the El Pais newspaper (Spain, South America and the USA), http://elpais.com/elpais/2016/10/04/ciencia/1475571372_487081.html about this research prize. El Pais is one of the most read newspapers in Spanish both online and printed (e.g., selling more than 100.000 units per day in Spain according to available data). |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://elpais.com/elpais/2016/10/04/ciencia/1475571372_487081.html |
| Description | Leeds Festival of Science 2019 - Schools roadshow |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I am participating in March 2019 in the Leeds Festival of Science 2019. In particular, I am carrying out talks at different Schools explaining how mathematical modelling can be used to study the spread of antibiotic resistant bacteria in hospital settings. I will be giving talks at: Bradford Girls' Grammar School Leeds City College (Park Lane Campus), two sessions to two different groups of students Notre Dame Catholic Sixth Form College Benton Park School I have already delivered this type of talks in many schools in the past. Students show surprise about the potential of using mathematics in this clinical area. Also, they realise about the importance of hand-hygiene, and an appropriate use of antibiotics. Teachers in these schools have also reported very good feedback, explaining to me that they are planning to use the videogames "Hospital Infections!" that I have developed in order to explain concepts related to probability theory, random variables and random processes. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://matml.github.io/#videogames |
| Description | Medicine - not just about medics! |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I participated in the programme "Medicine - not just about medics!", delivering a session in my institution (University of Leeds). Around 40 students from Schools around Yorkshire attended, where the aims it show how we as academics can carry out research in clinical topics while not being clinicians (in my case, using mathematics). This programme is very popular across schools, and carry out activities at the University of Leeds several times during the year. I am being asked to repeat the activity this year, due to the interest shown by the Schools. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Piece of news at a TV news programme in the regional Madrid TV channel "TeleMadrid" (Spain) |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The "Vicent Caselles" research prize that M. Lopez-Garcia, together with other 5 young Spanish researchers, was awarded by the Spanish Royal Mathematical Society and the BBVA Foundation in Spain (see Awards & Recognition section) attracted a lot of media attention. A piece of news during the TV news programme at the regional TV channel "TeleMadrid" (Madrid, Spain) was released http://www.telemadrid.es/noticias/sociedad/noticia/analizan-la-propagacion-de-bacterias-en-los-hospitales-con-modelos-matemat about this research prize and the research carried out within this fellowship. |
| Year(s) Of Engagement Activity | 2016 |
| URL | http://www.telemadrid.es/noticias/sociedad/noticia/analizan-la-propagacion-de-bacterias-en-los-hospi... |
| Description | School Visit |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I visited the Giggleswick School, in February 2018. During this activity, I presented the seminar "Playing Dice with Epidemics", where I explain how probability theory and the theory of random processes can be used in order to virtually simulate epidemics in real life, and in particular how to predict the infection dynamics of outbreaks of antibiotic resistant bacteria in hospital settings. During this workshop, I make use of the original series of video games "Hospital Infections", which have been tailor-designed for this purpose. These video games allow one to visually simulate the spread of an antibiotic resistant bacteria within a hospital ward. These video games allow the user -here, students- to make some decisions in terms of how to allocate patients across different rooms in the hospital ward, or how to design the ventilation system of the ward, and where the main aim is to avoid the spread of the bacteria in the ward. Thus, the workshop becomes a hands-on session where students can use laptops/computers to use these video games. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www.stem.leeds.ac.uk/maths/talks/ |
| Description | School Visit |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I visited the Crossley Heath School in Halifax in 2017. During this activity, I presented the seminar "Playing Dice with Epidemics", where I explain how probability theory and the theory of random processes can be used in order to virtually simulate epidemics in real life, and in particular how to predict the infection dynamics of outbreaks of antibiotic resistant bacteria in hospital settings. During this workshop, I make use of the original series of video games "Hospital Infections", which have been tailor-designed for this purpose. These video games allow one to visually simulate the spread of an antibiotic resistant bacteria within a hospital ward. These video games allow the user -here, students- to make some decisions in terms of how to allocate patients across different rooms in the hospital ward, or how to design the ventilation system of the ward, and where the main aim is to avoid the spread of the bacteria in the ward. Thus, the workshop becomes a hands-on session where students can use laptops/computers to use these video games. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://www.stem.leeds.ac.uk/maths/talks/ |
| Description | School Visit - Leeds Festival of Science |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I visited the John Smeaton Academy in Leeds, in March 2018, as part of the Leeds Festival of Science. During this activity, I presented the seminar "Playing Dice with Epidemics", where I explain how probability theory and the theory of random processes can be used in order to virtually simulate epidemics in real life, and in particular how to predict the infection dynamics of outbreaks of antibiotic resistant bacteria in hospital settings. During this workshop, I make use of the original series of video games "Hospital Infections", which have been tailor-designed for this purpose. These video games allow one to visually simulate the spread of an antibiotic resistant bacteria within a hospital ward. These video games allow the user -here, students- to make some decisions in terms of how to allocate patients across different rooms in the hospital ward, or how to design the ventilation system of the ward, and where the main aim is to avoid the spread of the bacteria in the ward. Thus, the workshop becomes a hands-on session where students can use laptops/computers to use these video games. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www.stem.leeds.ac.uk/maths/talks/ |
| Description | School Visit - Leeds Festival of Science |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I visited the Selby College, in March 2018, as part of the Leeds Festival of Science. During this activity, I presented the seminar "Playing Dice with Epidemics", where I explain how probability theory and the theory of random processes can be used in order to virtually simulate epidemics in real life, and in particular how to predict the infection dynamics of outbreaks of antibiotic resistant bacteria in hospital settings. During this workshop, I make use of the original series of video games "Hospital Infections", which have been tailor-designed for this purpose. These video games allow one to visually simulate the spread of an antibiotic resistant bacteria within a hospital ward. These video games allow the user -here, students- to make some decisions in terms of how to allocate patients across different rooms in the hospital ward, or how to design the ventilation system of the ward, and where the main aim is to avoid the spread of the bacteria in the ward. Thus, the workshop becomes a hands-on session where students can use laptops/computers to use these video games. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www.stem.leeds.ac.uk/maths/talks/ |
| Description | Surfaces and hand-hygiene: washing away fluorescent "germs"! |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | I carried out the activity Surfaces and hand-hygiene: washing away fluorescent "germs"! together with Dr. Marco-Felipe King (University of Leeds), at the Thackray Medical Museum, and as part of the MRC Festival 2018 (I got an award of 1200GBP for this activity from the MRC). The aim of the activity was to show to participants (general public and schools visiting the museum) the importance of hand hygiene for decreasing bacterial contamination levels on hands and surfaces, and the link to infections occurring by antibiotic resistant bacteria in hospital settings. We used different approaches for showing this (videogames on mathematical modelling in this area, shown on a big screen; swabs from hands and contamination level measured by a monitoring device; fluorescent gel to show good hand-hygiene practice,...etc). We got good feedback from participants, who showed interest in the research being carried out and funded by the MRC, and surprise about the potential use of mathematics in this area. Also, many participants told us that they were now more aware of the importance of hand-hygiene. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://www.leeds.ac.uk/forstaff/news/article/6223/mrc_festival_of_medical_research_2018_experiences |
| Description | Talk at Sixth Form Conference - School of Mathematics - University of Leeds |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I gave a talk within the Sixth Form Conference which is held every year at the School of Mathematics, at the University of Leeds. This is an opportunity for Sixth Form students to visit the School and learn more about the research that we do here. During this activity, I presented the seminar "Playing Dice with Epidemics", where I explain how probability theory and the theory of random processes can be used in order to virtually simulate epidemics in real life, and in particular how to predict the infection dynamics of outbreaks of antibiotic resistant bacteria in hospital settings. During this workshop, I make use of the original series of video games "Hospital Infections", which have been tailor-designed for this purpose. These video games allow one to visually simulate the spread of an antibiotic resistant bacteria within a hospital ward. These video games allow the user -here, students- to make some decisions in terms of how to allocate patients across different rooms in the hospital ward, or how to design the ventilation system of the ward, and where the main aim is to avoid the spread of the bacteria in the ward. Thus, the workshop becomes a hands-on session where students can use laptops/computers to use these video games. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://www.stem.leeds.ac.uk/maths/talks/ |