Currently I am working on mathematical and statistical models for estimating infectious diseases parameters based on serological and social contact data. We have seen that infectious diseases are raising concerns among scientists due to their negative consequences to social health, quality of life and economic cost. My research focuses on the analysis of data on pertussis, social contact data in developing countries and data on influenza in Vietnam. Pertussis (also known as whooping cough) is a highly transmissible respiratory disease that might cause severe symptoms in infants and children. Within the last 15 years, pertussis has come back in many developed countries. This brought our attention to. Many countries have their vaccination program against pertussis during pregnancy on the mothers and during early ages of the infants. In our research, we would like to investigate the blunting effect of the immune response after being vaccinated in infants born by vaccinated pregnant women and the time frame which is best to vaccinate the mother in order to achieve the highest benefit in their offspring. This is done in collaboration with colleagues from Antwerp University. Moreover, we want to use serial serological data on pertussis in order to study the transmission of this diseases. We aim to employ the stochastic modelling in order to estimate important parameters, especially the force of infection. The motivation to use a stochastic modelling approach is that stochastic is the most natural way to depict the spread of a disease, and as pointed out by Andersson and Britton (2000), stochastic models are to be preferred whenever their analysis is manageable. Beside the FOI, another important feature in studying infectious diseases is to understand how the disease is spread in the community. The widening of an infectious diseases depends on the mixing patterns between infected and susceptible individuals in a population. In Europe, there was a large project named POLYMOD conducted in eight countries (Belgium, Germany, Finland, Great Britain, Italy, Luxembourg, The Netherlands and Poland) with the aim to provide a quantitative solution to mixing patterns for airborne infectious diseases (Mossong et al., 2008). However, there is a noticeable gap in contact data for developing countries. In the literature, contact data collected from a diary based survey is only available for Vietnam until now. To fill in this gap, a large-scale multicountry survey of human-human and human-animal contact patterns was conducted in the South East Asia. Analyzing these data will contribute to a more complete picture of mixing patterns in many countries. This is done in combination with Infectious Disease Epidemiology Unit – Department of Epidemiology and Population Health from London School of Hygiene and Tropical Medicine. Influenza has been considered as a problem of developed countries with supporting data for preventive actions but less attention had been paid to the developing and tropical countries. This has changed since the re-emerging of influenza H5N1 in 2004 (Horby et al., 2012). The disease had been spread from Asia to Europe and Africa. In 15 countries with reported influenza A (H5N1) in humans all over the world, there were 4 countries in South East Asia (WHO, 2016). However, there is little data available on influenza transmission at the community level. In this part, we continue the data analysis of a household cohort study conducted in Ha Nam, a province in Vietnam on epidemiology of interpandemic and pandemic influenza from 2007-2010. The first analysis was published in 2012 (Horby et al., 2012). It will contribute to the understanding of the transmission in one of countries in South East Asia.