Financial support through the following projects:
UID/MAT/00297/2019
UID/MAT/00297/2013
PEstOE/MAT/UI0297/2014
PEstOE/MAT/UI0297/2011
Mathematical Biology  Mathematics for Health 
Data Knowledge 
Ecology 
Care and Ageing  Big Data 
Epidemiology 

Machine Learning 
Evolution & Genetics 
Projects:

Project: Modelling dengue fever epidemiology, prevention, and control: insights for public health intervention measures
Description: In recent years, mathematical modeling became an important tool for understanding infectious disease epidemiology and dynamics, leading to great advances for disease control, providing tools for assessing the potential impact of different public health intervention measures. M. Aguiar has large experience in modeling infectious diseases dynamics with special focus in dengue fever epidemiology. Multistrain dengue dynamics have been modeled with extended SusceptibleInfectedRecovered (SIR)type models including immunological aspects of the disease such as the Antibody DependentEnhancement (ADE) phenomenology; Aguiar et al. have investigated a minimalist twoinfection dengue model, with at least two different dengue serotypes to describe differences between primary and secondary infections. Deterministic chaos was found in much wider parameter regions (not predicted by previous models), no longer needing to restrict the infectivity on a secondary infection to be much larger than the infectivity on primary infection. The minimalist model successfully described large fluctuations observed in empirical outbreak data, estimating lower infection rate for secondary dengue infections than for primary infections, anticipating results published recently in Duong et al. PNAS 2015. Aguiar has also shown that the combination of immunological aspects of the disease such as temporary crossimmunity (TCI) and ADE are the most important features to drive the complex dynamics in the system, more than the detailed number of serotypes to be added in the model. However, this work is focusing on the multistrain aspect of the disease and its effects on the host population only, taking effects of the vector dynamics into account only by the model parameters. Regarding the newly licensed dengue vaccine, opposing the predictions made by other groups, Aguiar et al. have discussed the risks behind this vaccine recommendation, after analyzing an agestructured model. Using the public available vaccine trial data, vaccine efficacy was estimated via the Bayesian approach, predicting a significant reduction of hospitalizations only when the vaccine is given to seropositive individuals. This work is still ongoing.
Methods: Differential Equations  Bifurcation analysis  Bayesian Analysis  Epidemiological data analysis
CMA Researchers: Maíra Aguiar
Selected Pubications:

Project: Vaccination models and human behavior
Description: This project results from the effort we started, some years ago, to find a research topic that would bring together the expertise and interests of the elements of the group, in particular, game theory and epidemiology. An increasing effort has been made to include human behavior in epidemiological models. One way to model this behavior is through game theory, which assumes that individuals make their decisions in order to maximize their gain or minimize a particular risk. We started by studying the impact of individual decision for diseases with seasonal transmission and vaccination and, more recently we have studied the impact of voluntary vaccination on childhood diseases with increased risk in adulthood.
Methods: Theory of games  Differential Equations
CMA Researchers: Fabio A. C. C. Chalub, Paulo Doutor, Paula Patrício, Maria do Céu Soares
Funding: Project EXPL/MATCAL/0794/2013. Game theory and epidemiology; PI: Paula Rodrigues (CMA); Total funding: 25.000,00 €
Pubications:

Project: Transmission and control models of tuberculosis
Description: A model for tuberculosis transmission is analyzed to better understand the transmission dynamics of tuberculosis. The model is changed to accommodate different treatment strategies and to evaluate its impact on tuberculosis transmission in the population.
Methods: Differential Equations  Optimal Control
CMA Researchers: Paula Patrício
Publications: