The COVID-19 pandemic has heightened public awareness of infectious disease prevention. However, minors often lack fully developed hygiene awareness, making it difficult to enforce basic preventive measures such as handwashing and mask-wearing. In addition, their frequent close contact in enclosed environments, such as educational institutions, increases the risk of rapid disease transmission. As minors can serve as significant vectors of infection, understanding their movement patterns is essential for devising effective countermeasures. Despite this need, tracking minors using mobile device location data remains difficult due to the low smartphone ownership rate. Therefore, as a first step toward overcoming the limitations of mobile device tracking and enabling large-scale behavioural analysis of minors, this study developed a method for estimating their residential locations at a micro-scale, such as the building level, using various statistical datasets. Furthermore, it estimated their daily commuting destinations—such as schools and kindergartens—as well as their daily schedules and commuting routes, in order to project their routine behavioural patterns and spatial activity ranges on a nationwide scale. This approach enables a more comprehensive understanding of minors’ daily movements and supports the planning and implementation of more effective infectious disease prevention strategies.

Recent social media data analysis suggests that children from low-income families are more likely to exceed their parents’ income if exposed to interactions with high-income individuals. This highlights the potential of understanding parental behavior to break the cycle of poverty. Using detailed human mobility data, this study estimated the movements of parents with young children, extracted by focusing on drop-off activities in childcare facilities. The differences between parents and non-parents were analyzed with respect to time spent at home, visiting tendencies, and frequency of visits to various locations. It was shown that parents raising children spend significantly more time at home and explored new locations less frequently than non-parents. Budget-conscious dining patterns were also observed, with parents visiting establishments such as restaurants and bars less frequently while frequenting supermarkets and fast food outlets more. Additionally, parents operated within a smaller activity radius. These findings provide a foundation for understanding parental social interactions and offer insights for improving urban support policies for low-income families, contributing to data-driven approaches to social inclusion.

As dynamic accessibility depends on the interplay of opportunities and travel impedance, available General Transit Feed Specification data and mobile phone data offer new opportunities to enhance the temporal sensitivity of accessibility. This paper utilizes a mobile phone-based origin-destination (OD) matrix and dynamic travel time via public transport to explore spatial and temporal patterns of accessibility measures. Four scenarios are constructed and compared to illustrate the relative accessibility. The results show that the impact of the public transport system changes progressively depending on the cut-off time considered, and average accessibility gains could vary four-fold between the city centre and suburban zones. Besides, the exploration of the relationship between land use, mobile phone-based attractiveness, and dynamic accessibility underlines the time-dependent effect of land use. Further research should focus on the development of advanced accessibility-based travel models.