PhD Student (M/F) in Mathematics with Applications to Epidemiology

Job Description

Thesis Subject

Mathematical Modeling of Epidemic Circulation in Mayotte: Projective and Retrospective Analyses

CONTEXT
Mayotte, a French island and archipelago in the Indian Ocean located near the Comoros Islands, has experienced several epidemics in recent years. Four dengue epidemics were recorded in Mayotte in 2010, 2012, 2014, and 2019–2020, prior to the SARS-CoV-2 epidemic on the island.
Coincidentally, two population-based surveys were conducted in 2019 (Unono Wa Maoré) and 2021 (MayCov), respectively before and after the 2019–2020 dengue epidemic—the largest to date in terms of reported cases on the island.
Additionally, Mayotte has also been affected by chikungunya epidemics in 2005–2006 and 2025, with new cases reported in early 2026. Post-epidemic serological surveys were also carried out in 2006, and during the peak of the epidemic in June 2025 (EpiMay).

OBJECTIVES
The primary objective of this PhD thesis is to compile existing data of various types (reported case numbers, serological survey results) and to develop existing and/or original models to provide a comprehensive overview of the epidemiological situation of arboviral diseases in Mayotte and to better anticipate future risks.
To refine this assessment of the current situation and risks, we also plan to examine the following two points in detail:


A comparative analysis with Réunion Island, which has experienced similar crises in recent years. We are particularly interested in comparing healthcare systems based on the results of modeling past epidemics (especially chikungunya in 2025). Indeed, we have obtained surprising preliminary results for Mayotte, with a very low detection rate (approximately 1 reported case for every 50 actual cases), despite a disease with a high expected rate of symptomatic cases. In this regard, the a posteriori analysis of sociocultural factors from the survey conducted by the ARS (Regional Health Agency) could be highly informative. It is worth noting that the detection rate estimate for dengue was of the same order of magnitude.


A methodological comparison between mechanistic vector control models and macroscopic SIR-type models calibrated on serological survey data. Currently, risk indicators (e.g., R₀ estimation) derived from mosquito population prediction models and their impact on the epidemic differ significantly from indicators (R₀ estimation) based on simple ODE models calibrated on general population sampling data (approximately 1,000 individuals), which provide a reliable estimate of the infected population proportion.

The PhD candidate will also need to be responsive to the needs of the ARS in the event of an epidemic peak, producing rough estimates in the early stages of a crisis and progressively refining them as the epidemic evolves.

ENVIRONMENT
This PhD thesis is part of a collaboration between the ARS and the CNRS, which began during the SARS-CoV-2 health crisis and continued with the modeling of dengue circulation (retrospective) and chikungunya (prospective). The ARS has already funded a one-year postdoctoral position (2024–2025) at the Laboratoire de Mathématiques de Bretagne Atlantique (LMBA, UMR 6205 CNRS UBO).

The thesis will be co-supervised by:

Julien Balicchi (Engineer, Head of the Studies and Statistics Department at ARS Mayotte)
Vincent Calvez (CNRS Senior Researcher, LMBA)
The supervision will also benefit from the risk analysis expertise of Franck Vermet, Director of EURIA and a lecturer-researcher at LMBA.

Your Work Environment

The successful candidate will be integrated into the LMBA at the Brest campus. They will participate in scientific activities, including lab seminars, team seminars, and PhD student seminars. They will also organize regular meetings with the ARS Mayotte teams to present their findings and develop their research project. Additionally, they will have the opportunity to engage with national networks in mathematical epidemiology modeling.

Constraints and risks

Not applicable

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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