2025-26 Project (Kucharski & Lowe)

Combining epidemiological, immunological and climatic data to understand and predict vector-borne epidemics

SUPERVISORY TEAM

Supervisor

Prof Adam Kucharski at LSHTM
Email: adam.kucharski@lshtm.ac.uk

Co-Supervisor

Prof Rachel Lowe at LSHTM
Email: rachel.lowe@lshtm.ac.uk

PROJECT SUMMARY

Project Summary

Climate sensitive infections such as dengue, Zika and chikungunya cause substantial burden in island populations, but the causes and predictability of outbreaks are not well understood. This project will combine mathematical and statistical models with a range of novel data sources – including surveillance data, community serological surveys, and climate indicators – to investigate the dynamics of vector-borne disease outbreaks in Pacific and Caribbean islands and territories, to develop better methods for understanding and forecasting these outbreaks. This work will involve close collaboration with partners working on surveillance and outbreak response in these regions.

Project Key Words

Dengue, vector-borne, climate, modelling, immunity, forecasting

MRC LID Themes

  1. Infectious Disease
  2. Global Health
  3. Health Data Science

Skills

MRC Core Skills

  1. Quantitative skills
  2. Interdisciplinary skills

Skills we expect a student to develop/acquire whilst pursuing this project

Modelling of infectious diseases, Bayesian inference, as well as quantitative analysis of climate and epidemiological data sets, evidence synthesis, and forecasting techniques.

Routes

Which route/s are available with this project?

  • 1+4 = Yes
  • +4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

  • LSHTM – MSc Control of Infectious Diseases
  • LSHTM – MSc Epidemiology
  • LSHTM – MSc Health Data Science

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Location & Travel

Students funded through MRC LID are expected to work on site at their primary institution, meeting – at the minimum – the institutional research degree regulations and expectations. Students may also be required to travel for conferences (up to 3 over the duration of the studentship), and for any required training (for research degree study). Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Primary location for duration of this research degree: LSHTM, London

Travel requirements for this project: Travel to collaborators at Institut Louis Malardé in French Polynesia and CIMH and CARPHA in the Caribbean

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • Minimum LSHTM institutional eligibility criteria for doctoral study.
  • The project will require some prior knowledge of epidemiology and statistics.
  • Experience of programming, for example with R, and of using mathematical and/or statistical models would also be beneficial.

Other useful information

  • Potential Industrial CASE (iCASE) conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

1. Project objectives:
– Combine surveillance data, novel serological surveys and climate data to quantify drivers of arbovirus transmission in Pacific Islands (e.g. French Polynesia, Fiji) and Caribbean (e.g. Dominican Republic, Barbados, Jamaica).    
– Compare possible explanations for recent shifts to multi-year circulation of dengue serotypes in isolated populations
– Develop and evaluate forecasting methodology that combines transmission mechanisms with spatiotemporal statistical analysis of arboviruses in epidemic-prone settings

2. Techniques to be used:
The project will use Bayesian inference methods such as MCMC and integrated nested Laplace approximation (INLA) to combine mechanistic transmission processes (e.g. defined by renewal equations) with spatiotemporal methodology for inferring predictors of incidence. We will also build on temperature-sensitive laboratory modelling approaches, which are already implemented as a prototype R package (github.com/epiverse-trace/climateR0).

3. Confirmed availability of any required databases or specialist materials: Surveillance and serological data will come from ongoing funded projects in Fiji and French Polynesia (Kucharski has an honorary research post at Institut Louis Malardé, which is leading this work, and has full access to data – he will be visiting in November 2024 and will discuss the project aims in detail). Climate data will be compiled using meteorological stations obtained via Lowe’s existing collaborators (e.g. with the Caribbean Institute for Meteorological and Hydrology) and from online sources including the Copernicus Climate Data Store.

4. Potential risks to the project and plans for their mitigation:
– Delays in data sharing agreements could slow research. Mitigation: Data sharing is in place for core studies and surveillance in Pacific Islands and the Dominican Republic, enabling research to commence while additional data use agreements are finalised. 
– Model performance may be limited at fine spatial scales. Mitigation: We will adjust the resolution of research questions if needed (e.g. focusing on regions rather than small areas) and make use of complementary data (serology, surveillance) to reduce dependence on a single data source. 
– Extreme events damaging/interrupting surveillance streams during the project. Mitigation: Focus on multiple settings will reduce this risk, as will availability of data sources already collected.

Further reading

Relevant preprints and/or open access articles:
(DOI = Digital Object Identifier)

Additional pre-application materials:

Additional information from the supervisory team

The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.

Kucharski-Lowe recording

MRC LID LINKS

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