ABSTRACT
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.
ABSTRACT
Development of protein 3-D structural comparison methods is essential for understanding protein functions. Some amino acids share structural similarities while others vary considerably. These structures determine the chemical and physical properties of amino acids. Grouping amino acids with similar structures potentially improves the ability to identify structurally conserved regions and increases the global structural similarity between proteins. We systematically studied the effects of amino acid grouping on the numbers of Specific/specific, Common/common, and statistically different keys to achieve a better understanding of protein structure relations. Common keys represent substructures found in all types of proteins and Specific keys represent substructures exclusively belonging to a certain type of proteins in a data set. Our results show that applying amino acid grouping to the Triangular Spatial Relationship (TSR)-based method, while computing structural similarity among proteins, improves the accuracy of protein clustering in certain cases. In addition, applying amino acid grouping facilitates the process of identification or discovery of conserved structural motifs. The results from the principal component analysis (PCA) demonstrate that applying amino acid grouping captures slightly more structural variation than when amino acid grouping is not used, indicating that amino acid grouping reduces structure diversity as predicted. The TSR-based method uniquely identifies and discovers binding sites for drugs or interacting proteins. The binding sites of nsp16 of SARS-CoV-2, SARS-CoV and MERS-CoV that we have defined will aid future antiviral drug design for improving therapeutic outcome. This approach for incorporating the amino acid grouping feature into our structural comparison method is promising and provides a deeper insight into understanding of structural relations of proteins.