Disease transmission and control in complex, structured populations
Lead Research Organisation:
University of Manchester
Department Name: Mathematics
Abstract
Infectious disease is the main thing that kills people. Some of the greatest improvements to human health have involved improvements in our understanding and control of germs - from John Snow's pioneering work on cholera in the 19th century to the eradication of smallpox in the 20th century. The 21st century sees a new set of challenges in the understanding and control of infections - while the eradication of polio progresses, we see new influenza strains causing or threatening pandemics, the continued progression of HIV and a massive health burden of often simply but expensively preventable diseases in the developing world.Epidemiology - the science of looking for significant patterns in cases of disease - has always been at the heart of controlling infectious diseases, and mathematics has always been central epidemiology.This project applies advanced mathematics to the science of epidemiology, making use of the large datasets and modern computational resources that are available. New insights about the structure of complex systems offer the promise of making massive advances in this field, through enhanced understanding of transmission routes of infection, risk factors and changes in the disease over time. These insights can in turn be combined with mathematical methods to design optimised interventions against infection so that diseases can be controlled in the most effective way.
Planned Impact
The ultimate aim for impact from my research is to reduce the burden of infectious disease on the human population - quantitative epidemiology has always been at the centre of efforts to control pathogens.Infectious disease remains the main cause of human mortality. This means that major advances in our understanding of them can revolutionise public health, while even minor improvements in science can have highly significant effects on the general health and well-being of the general population.The intermediate beneficiaries of my work are the Health Protection Agency (HPA), which is the body responsible for public health - including infection control - in England, the medical research institute KEMRI in Kenya, and also the Department of Health and associated scientific advisory bodies. Through working with these bodies as detailed in the Pathways to Impact document I will ensure that any policy-relevant conclusions from my work are swiftly disseminated.
People |
ORCID iD |
Thomas House (Principal Investigator / Fellow) |
Publications
Thompson RN
(2020)
Key questions for modelling COVID-19 exit strategies.
in Proceedings. Biological sciences
Sprague D
(2016)
Assessing delivery practices of mothers over time and over space in Uganda, 2003-2012
in Emerging Themes in Epidemiology
Schultz D
(2020)
Weather Patterns Associated with Pain in Chronic-Pain Sufferers
in Bulletin of the American Meteorological Society
Pouwels KB
(2021)
Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey.
in The Lancet. Public health
Pellis L
(2015)
Exact and approximate moment closures for non-Markovian network epidemics.
in Journal of theoretical biology
Pellis L
(2020)
Systematic selection between age and household structure for models aimed at emerging epidemic predictions.
in Nature communications
Pellis L
(2015)
Eight challenges for network epidemic models
in Epidemics
Pellis L
(2015)
Real-time growth rate for general stochastic SIR epidemics on unclustered networks.
in Mathematical biosciences
Parra-Rojas C
(2016)
Stochastic epidemic dynamics on extremely heterogeneous networks.
in Physical review. E
Overton CE
(2020)
Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example.
in Infectious Disease Modelling
Description | The discoveries arising from this fellowship were extremely wide-ranging, particularly as regards population structure and infectious disease, and extending to more general issues in complex data and epidemiology. Some recent highlights are: results on the emergence of pandemic influenza; new mathematical techniques for network epidemics; understanding social effects in giving birth in facilities in Uganda; statistical tests for the epidemiological relevance of the tail of a contact distribution; vaccine policy relevant modelling for RSV in developed countries; that depression does not spread in social networks but health mood does; and many technical results that support these conclusions. |
Exploitation Route | Public Health Policy. |
Sectors | Healthcare Government Democracy and Justice |
URL | http://personalpages.manchester.ac.uk/staff/thomas.house |
Description | The impacts from this fellowship have been both immediate and longer-term. Highlights include: > Impact of work on 2009 data on pandemic preparedness policy, including for schools and households. > Work on mood and complex contagion was extremely widely reported in public and had a large impact on discussions of these issues > Work on Ebola was widely cited and used as part of evidence synthesis by the Government. > Analysis techniques for complex data picked up by Industry, leading to founding of companies and collaborations with large companies. > Extensive impact on study design, modelling and data analysis during the current coronavirus pandemic. It is almost uncanny how much of the research supported under this award had at times during the pandemic played an absolutely central role in determination of national policy and scientific understanding during the pandemic, made possible by a follow-on "Impact" fellowship. |
First Year Of Impact | 2011 |
Sector | Communities and Social Services/Policy,Digital/Communication/Information Technologies (including Software),Education,Financial Services, and Management Consultancy,Healthcare,Government, Democracy and Justice |
Impact Types | Cultural Societal Economic Policy & public services |
Description | Industrially Funded MPhil |
Amount | £26,900 (GBP) |
Organisation | Autotrader |
Sector | Private |
Country | United Kingdom |
Start | 01/2017 |
End | 12/2017 |
Description | Industrially Funded MSc project |
Amount | £3,000 (GBP) |
Organisation | Autotrader |
Sector | Private |
Country | United Kingdom |
Start | 04/2016 |
End | 09/2016 |