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Two cum laude PhDs in one day at Spatial Sciences

20 June 2022

On Monday 20 June, Alyona Artamonova and Mindra Jaya defended their theses at the Faculty of Spatial Sciences. Both were assessed cum laude. A unique event for the faculty; cum laude twice in one day has never happened before.

Family proximity and relocations in older adulthood
Family proximity and relocations in older adulthood

Family proximity and relocations in older adulthood

Alyona Artamonova was the first to defend her thesis. In her research she addresses the following question: How are needs-related life circumstances of older people associated with their own and their relatives’ migration and immobility (including older adults’ moves into institutionalized care facilities)? the roles that various care-related living conditions of older people play in their own location choice and that of their relatives.

The family remains one of the most important sources of support for older adults. Geographic proximity between family members has important implications for the growing demand for formal and informal care. As people age, their own and their family members’ residential (im)mobility may be a strategy to facilitate the exchange of care. The roles of a range of needs-related life circumstances of older adults in their own and their family members’ locational choice are documented: needs for formal care, severe health problems, the absence of core family members, or losing a partner recently. The overall answer to the research question is that older adults’ needs-related life circumstances deter intergenerational geographic divergence, and inspire moves toward adult children, siblings, and into institutionalized residential care. This research project is part of the FamilyTies ERC project of Prof. Dr. Claartje Mulder.

The thesis is particularly strong because of the thorough and innovative way of conducting research, and the concrete way in which important questions in the field of migration are answered.

Bayesian Spatiotemporal Modeling and Mapping of Infectious Diseases
Bayesian Spatiotemporal Modeling and Mapping of Infectious Diseases

Bayesian spatiotemporal modeling and mapping of infectious diseases

The ceremony of Mindra Jaya, who works as a statistics teacher at Padjadjaran University in Bandung, Indonesia, followed later the same morning. He develops methods for analysis, prediction and mapping of the spread of infectious diseases, with applications to dengue fever in Bandung and COVID-19 in West Java. His findings enable us to predict the risk of these (and other) infectious diseases, in various neighbourhoods, municipalities or regions at different future times with minimal data.

Dengue disease is among the biggest health hazards in the twenty-first century. It is endemic to more than one hundred tropical and subtropical countries and affects hundreds of  millions of  people. South Asia and Southeast Asia have the highest levels of vulnerability to Dengue disease. However, it  continues to spread and increase worldwide. Dengue and COVID-19 have serious public health and socioeconomic implications. To prevent disease transmission and mitigate health and socioeconomic consequences, an effective and efficient early warning system (EWS) is required. To this end, adequate understanding of the spatiotemporal development of diseases is needed. The main objective of this thesis is to develop methodologies for the analysis, prediction, and mapping of the spatiotemporal distribution of infectious diseases at various spatiotemporal scales, with applications to Dengue disease in Bandung and COVID-19 in West Java.

This research presents several innovative methods to predict the spread of infectious diseases. Moreover, these methods are easily applicable worldwide.


Both theses are available online:

Last modified:20 June 2022 1.55 p.m.
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