RESUMEN
In this paper, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is widely used to represent the stochastic spread of infectious diseases, such as COVID-19. While Markov Decision Processes (MDP) offers a mathematical framework for identifying optimal actions, such as vaccination and transmission-reducing intervention, to combat disease spreading according to the SEIR model. However, uncertainties in these scenarios demand a more robust approach that is less reliant on error-prone assumptions. The primary objective of our study is to introduce a new DRMDP framework that allows for an ambiguous distribution of transition dynamics. Specifically, we consider the worst-case distribution of these transition probabilities within a decision-dependent ambiguity set. To overcome the computational complexities associated with policy determination, we propose an efficient Real-Time Dynamic Programming (RTDP) algorithm that is capable of computing optimal policies based on the reformulated DRMDP model in an accurate, timely, and scalable manner. Comparative analysis against the classic MDP model demonstrates that the DRMDP achieves a lower proportion of infections and susceptibilities at a reduced cost. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
RESUMEN
The COVID-19 pandemic has impacted the global society and human life profoundly. Many countries have launched COVID-19 mobile apps with a wide range in how these apps work. While it is hoped that these apps can assist in the fight against COVID-19, many are worried about user privacy. China implemented “health code” systems, which assigned neighborhoods and citizens a specific health code, meant to indicate their risk of having been exposed to COVID-19. The most widely used health code systems were hosted on the popular apps WeChat and Alipay, each with billions of users. Some experts argued that China's use of mobile applications was essential to its successful combat against COVID-19. Included in this study are a summary of mobile technology usage in China, a review of previous studies of mobile technology in healthcare, and a brief survey of some existing mobile applications for COVID-19 that were implemented. Also included are outcomes of interviews with healthcare and public safety experts and a public survey to understand how mobile applications were used in China's response to COVID-19. The interviews revealed four important themes: personal privacy, community involvement, government involvement, and situational specificity. It was found that a key concern was maintaining a balance between collecting and utilizing personal information, as well as protecting this information. In addition, close collaboration between local communities and the national government was essential. Mobile applications assisted in communication and coordination but did not replace the work of people such as delivery drivers and contact tracers. Our results also showed that there was room for improvement, especially accessibility for the elderly or those unfamiliar with technology. Similar results were obtained from our survey. It was interesting to find that the apps were mostly used for “accessing information on COVID-19.” In addition, respondents overwhelmingly identified “information” as the most valuable feature of COVID-19 apps. Both interview and survey results revealed the importance of providing information as a primary function of COVID-19 apps. Based on our findings we distilled four main lessons: mobile applications should assist in existing COVID-19 responses, inform users, protect users’ personal information, and adapt to users’ environments. We recommend that public health officials and app developers take these lessons into consideration when developing COVID-19-related mobile applications. In addition, we encourage researchers to utilize this report as a jumping off point for further research.