AIMS/INTRODUCTION: Coronavirus disease 2019 (COVID-19) vaccinations have been proven to be generally safe in healthy populations. However, the data on vaccine safety in patients with type 1 diabetes are scarce. This study aimed to evaluate the frequency and severity of short-term (<7-day) adverse vaccination events (AEs) and their risk factors among type 1 diabetes patients.

MATERIALS AND METHODS: This study analyzed data from the COVID-19 vaccination in Autoimmune Diseases (COVAD) survey database (May to December 2021; 110 collaborators, 94 countries), comparing <7-day COVID-19 vaccine AE among type 1 diabetes patients and healthy controls (HCs). Descriptive statistics; propensity score matching (1:4) using the variables age, sex and ethnicity; and multivariate analyses were carried out.

RESULTS: This study analyzed 5,480 completed survey responses. Of all responses, 5,408 were HCs, 72 were type 1 diabetes patients (43 females, 48.0% white European ancestry) and Pfizer was the most administered vaccine (39%). A total of 4,052 (73.9%) respondents had received two vaccine doses. Patients with type 1 diabetes had a comparable risk of injection site pain, minor and major vaccine AEs, as well as associated hospitalizations to HCs. However, type 1 diabetes patients had a higher risk of severe rashes (3% vs 0.4%, OR 8.0, 95% confidence interval 1.7-36), P = 0.007), although reassuringly, these were rare (n = 2 among type 1 diabetes patients).

CONCLUSIONS: COVID-19 vaccination was safe and well tolerated in patients with type 1 diabetes with similar AE profiles compared with HCs, although severe rashes were more common in type 1 diabetes patients.

Multi-threading is a methodology that has been extremely used. Modern software depends essentially on multi-threading. Operating systems, famous examples, are based on multi-threading; a user can write his document, play an audio file, and downloading a file from internet at the same time. Each of these tasks called a thread. A common problem occurs when implementing multi-threaded programs is a data-race. Data race occurs when two threads try to access a shared variable at the same time without a proper synchronization. A detector is software that determines if the program contains a data-race problem or not. In this paper, we develop a detector that has the form of a type system. We present a type system which discovers the data-race problems. We also prove the soundness of our type system.

The most common form of computers today is the hand held form and
specially smart phones and tablets. The platform for the majority of
smart phones is the Android operating system. Therefore analyzing
and verifying the Android applications become an issue of extreme
importance. However classical techniques of static analysis are not
applicable directly to Android applications. This is so because
typically Android applications are developed using Java code that is
translated into Java bytecode and executed using Dalvik virtual
machine. Also developing new techniques for static analysis of
Android applications is an involved problem due to many facts such
as the concept of gestures used in Android interaction with users.

One of the main tools of analyzing and verifying programs is types
systems~\cite{el2012heap}. This paper presents a new type system,
Android$\mathcal{T}$, which is specific to Android applications. The
proposed type system ensures the absence of errors like "method is
undefined". Also the type system is applicable to check the
soundness of static analyses of Android applications.