ANTON  CAMACHO

26 years old

Paris, France

Curriculum Vitae


LAB

UMR 7625: Ecology & Evolution

CNRS-ENS-AgroParisTech-UPMC


Unit: Eco-Evolutionary Mathematics

46 rue d’Ulm

75005 Paris, France


+33 1 44 32 36 97

camacho@biologie.ens.fr



THESIS

Supervisors:

Pr Bernard CAZELLES

& Pr Amaury LAMBERT


Title: «Stochastic modeling in epidemiology with applications to influenza»


Keywords:

-Markov processes

-Demographic stochasticity

-State-space models

-Statistical inference

-Influenza

-Numerical simulations

-Linear noise approximation

-Moment closure approximations





 

WORKSHOPS


2011

  1. -Dynamical Systems Applied to Biology and Natural Sciences (Lisbon, Fev. 2011)
       
    Talk: «Estimating variability in stochastic nonlineat epidemiological models: an application to the transition from invasion to long-term persistence of emerging pathogens.» PDF



2010

  1. -COMMISCO: Conférence Modélisation Mathématique et Informatique des Systèmes Complexes (Bondy, Oct. 2010)
       
    Talk: «Analyse de séries temporelles par maximisation de la vraissemblance: étude et sélection de modèle.» PDF

  2. -Ecology, Epidemiology and Evolution: Biological Processes and Artificial Analogues
    (Warwick, Sept. 2010)
       
    Talk: «Rapid Influenza Reinfection: Likely Mechanisms and Potential Impacts during a Pandemic.» PDF

  3. -Journées MAS
    (Bordeaux, Sept. 2010)
       
    Talk: «Time Series Analysis via Maximum Likelihood. From theory to practice.» PDF

  4. -CMPD3: Computational and Mathematical Population Dynamics
    (Bordeaux, June 2010)
       
    Talk: «Gradual & Punctuated Antigenic Drift for Influenza Evolution. A quantitative approach based on time series analysis.» PDF

  5. -Chaos and dynamics in biological networks
    (Cargèse May 2010)
       
    Talk: «Assessing the use of Phenomenological Transmission Functions to Model Disease Spread on Contact Networks.» PDF


2009

  1. -Multiply Structured Populations in Biology
    (Bath July 2009)
       
    Talk: «Disentangling Between Different Mechanisms for Explaining Observed Two-Wave Influenza Epidemics.» PDF


2008

  1. -R0 and Related Concepts: Methods and Illustrations
    (Paris Oct. 2008)
       
    Poster: «Limitations of the van Kampen Approach for Stochastic Epidemiological Models.» PDF

PUBLICATIONS


A. Camacho, S. Ballesteros, A.L. Graham, F. Carrat, O. Ratmann & B. Cazelles  2011.

Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study.  Proceedings of the Royal Society B (in press). PDF  Supp. Material


S. Ballesteros, L. Stone, A. Camacho, E. Vergu & B. Cazelles.

Fundamental irregularity of regular seasonal influenza epidemics: from theory to observation (in revision).


A. Camacho, S. Ballesteros, A. Lambert & B. Cazelles.

Assessing the use of the linear noise approximation for nonlinear stochastic epidemiological models (in preparation).


I am a Ph.D student in Applied Mathematics, under the 

supervision of Bernard Cazelles and Amaury Lambert,

at the Biological department of the Ecole Normale

Supérieure in Paris.


Our aim is to developp:

  1. 1) analytical tools for studying stochastic
    epidemiological models without resorting to
    computationally intensive numerical simulations.


  1. 2) statistical tools for interfacing theoretical models
    with epidemiological data in order to quantitatively
    evaluate the biological mechanisms underlying the
    spread of influenza among humans.


TEACHING

  1. -Calcul vectoriel et matriciel (LM 121, L1, UPMC):
    tutorials, 64 hours/year from 2008 to 2011

  2. -Ecologie et dynamique des populations structurées (STRU, M2, ENS) : seminar, 3 hours/year from 2009 to 2011

EDUCATION

Since 2008: Ph.D student in Applied Mathematics


2007-2008: Master’s Degree in Mathematics & Applications; specialization in Mathematical Modeling.

Graduated Summa Cum Laude from Univ. Paris 6 UPMC.

   

2003-2008: Engineer from Institut National des Sciences Appliquées (INSA) de Lyon; specialization in Bioinformatic & Modeling.