I am looking for a prospective PhD student in computational modeling of infectious disease transmission. The position is funded by GSK Vaccines and the candidate will work between ISI Foundation in Torino, under my supervision, and the Exploratory Data Analytics (EDA) team of GSK in Siena.

The assignment of the scholarship is conditional on the admission to the PhD program in Complex Systems for Life Sciences of the University of Torino. The call for application can be found here

Interested candidates are invited to send me their CV.
Deadline for application: March 24, 2017.

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PhD Project
Mathematical modeling and simulations of invasive meningococcal disease dynamics and vaccination strategies

Invasive meningococcal diseases (IMD), as meningitis and septicemia, are rare but tremendous diseases, whose most common cause is a bacterium called N. meningitidis. IMD is a vaccine preventable disease, however, vaccines targeting serogroup B meningococcal strains have been developed only recently, and they represent a completely new type of vaccine. Evaluating their effectiveness when employed in immunization campaigns is challenging, but of major importance for vaccine research and development and for public health.

Mathematical models of meningococcal asymptomatic carriage, contagion, disease emergence and vaccination have been developed to evaluate impact of mass immunization campaigns. The Exploratory Data Analytics (EDA) team has developed a novel reverse approach based on a computational epidemic model of meningococcal disease transmission combined with real-time surveillance data (Argante L et al. 2016). This model-based inferential methodology has been proven to provide precise estimates of vaccine effectiveness in field immunization studies, disentangling the direct vaccine effect in protecting from IMD and the herd immunity effect.

The use of computer simulations can provide novel insights into the extremely high degree of complexity that characterizes the epidemiology of meningococcal disease, which is due to several factors: i) the meningococcal strains diversity and their continuous evolutionary adaptation to humans, ii) the complexity of the human immune systems, iii) the impact of different human habits in different countries and settings (e.g. rural vs. metropolitan areas) that drastically influence individual contact patterns and the contagion processes. These factors are especially relevant when considering a pathogen like N. meningitidis that is asymptomatically carried by up to 25% of the population, depending on age.

Moreover, the novel serogroup B vaccine Bexsero includes antigens that mimicry surface-exposed meningococcal proteins, to protect from the most prevalent world-wide circulating serogroup B strains, but nevertheless characterized by high levels of variability. A major challenge is faced when evaluating the fraction and the degree of coverage conferred by the Bexsero vaccine against meningococcal strains of a given country.

Building upon previous works developed by the EDA team, the candidate will work to extend and improve the computational methods described in Argante et al. 2016, to tackle the above mentioned challenges. More specifically, the main goal of the project will be to develop a multi-strain model to characterize the different strains given their antigenic genotype or phenotype profiles and evaluate strain-based effectiveness in field study.

The main research objectives will be:

  1. Development of stochastic mathematical models to computationally simulate the spread of meningococcal asymptomatic infection, the emergence of meningococcal invasive disease and the implementation of immunization interventions. The model will be able to account for multiple strains of N. meningitidis, demographic changes, between-humans contact patterns and contagion dynamics.

  2. Use simulations to infer epidemiological quantities of interest, such as the probability of infection and recovery from meningococcal carriage and the risk of disease, as well as vaccinological quantities, to detect differential vaccine effects against genetically and/or antigenically different meningococcal strains and herd immunity effects.

  3. Apply the methodologies to different real case studies, corresponding to mass immunization campaigns in different countries.

  4. Extend the above methodologies to other infectious diseases and vaccination scenarios.

References:

  • Argante L, Tizzoni M, Medini D - Fast and accurate dynamic estimation of field effectiveness of meningococcal vaccines – BMC Med. Jun 2016;

  • Trotter CL, Gay NJ, Edmunds WJ - Dynamic Models of Meningococcal Carriage Disease and the Impact of Serogroup C Conjugate Vaccination – Am J Epidemol. 2005;

  • Christensen H, Hickman M, et al. - Introducing vaccination against serogroup B meningococcal disease: an economic and mathematical modelling study of potential impact. – Vaccine 2013;

  • Donnelly J, Medini D, et al. - Qualitative and quantitative assessment of meningococcal antigens to evaluate the potential strain coverage of protein-based vaccines. – PNAS 2010;