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At present, many countries around the world have significantly invested in sustainable transportation systems, especially for high-speed rail (HSR) infrastructures, since they are believed to improve economies, and regenerate regional and business growth. In this study, we focus on economic growth, dynamic land use, and urban mobility. The emphasis is placed on testing a hypothesis about whether HSRs can enable socio-economic development. Real case studies using big data from large cities in China, namely Shanghai province and Minhang districts, are taken into account. Socio-technical information such as employment rate, property pricing, and agglomeration in the country's economy is collected from the China Statistics Bureau and the China Academy of Railway Sciences for analyses. This research aims to re-examine practical factors resulting from HSR's impact on urban areas by using ANOVA analysis and dummy variable regression to analyse urban dynamics and property pricing. In addition, this study enhances the prediction outcomes that lead to urban planning strategies for the business area. The results reveal that there are various effects (i.e., regional accessibility, city development plans, and so on) required to enable the success of HSR infrastructure in order to enrich urban dynamics and land pricing. This paper also highlights critical perspectives towards sustainability, which are vital to social and economic impacts. In addition, this study provides crucial perspectives on sustainable developments for future HSR projects.

Vaccination has been proven to be the most effective method to prevent infectious diseases.However, in many low and middle-income countries with geographically dispersed and nomadic populations, last-mile vaccine delivery can be extremely complex. Because newborns in remote locations within these countries often do not have direct access to clinics and hospitals, they face significant risk from diseases and infections. An approach known as outreach is typically utilized to raise immunization rates in these situations. A set of these remote population centers is chosen, and over an appropriate time horizon, teams of clinicians and support personnel are sent from a depot to set up mobile clinics at these locations to vaccinate people there and in the immediate surrounding area. In this paper, we model the problem of optimally designing outreach efforts as a mixed integer program that is a combination of a set covering problem and a vehicle routing problem. In addition, because elements relevant to outreach (such as populations and road conditions) are often unstable and unpredictable, we incorporate uncertainty to study the robustness of the worst-case solutions and the related issue of the value of information.

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