Healthcare-associated infections in a tunisian university hospital: From analysis to action

Introduction: our study was conducted, in university hospital center (UHC) Farhat Hached of Sousse (city in Tunisian center-east), within healthcare-associated infections (HAI) epidemiological surveillance (ES) program,  based, among others, on HAI regular prevalence surveys. Our objectives are to resituate HAI prevalence rate and to identify their risk factors (RF) in order to adjust, in our hospital, prevention programs.Methods: it is a transversal descriptive study, including all patients who had been hospitalized for at least 48 hours, measuring prevalence of HAI a “given day”, with only one passage by service. Risk factors were  determined using Epiinfo 6.0, by uni-varied analysis, then, logistic  regression stepwise descending for the variables whose pResults: the study focused on 312 patients. Infected patients prevalence was 12.5% and that of HAI was 14.5 %. Infections on peripheral venous catheter (PVC)  dominated (42.2%) among all HAI identified. HAI significant RF were neutropenia (p<10-4) for intrinsic factors, and PVC for extrinsic factors (p=0,003). Conclusion: predominance of infections on PVC should be subject of specific prevention actions, including retro-information strategy, prospective ES, professional practices evaluation and finally training and increasing awareness of health personnel with hygiene measures. Finally,  development of a patient safety culture with personnel ensures best adherence to hygiene measures and HAI prevention

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Exploring IoT Trickle-Based Dissemination Using Timed Model-Checking and Symbolic Execution

International audienceWe focus on studying an IoT algorithm called Trickle using a formal model-based approach. The algorithm has an essential role in traffic regulation across distributed networks of wireless sensors which are part of IoT. The algorithm allows efficient dissemination of information such as critical applicative data, firmware upgrades or security fixes. In this paper, we develop timed asynchronous computational models for Trickle. We show how reachability properties can be assessed on such models using an original combination of model-checking and symbolic execution implemented by the tools UPPAAL and DIVERSITY, respectively. Our experiments produce promising results on highlighting updated or outdated nodes situations during dissemination

Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines

In this paper we propose a new approach to conformance testing based on Abstract State Machine (ASM) model refinement. It consists in generating test sequences from ASM models and checking the conformance between code and models in multiple iterations. This process is applied at different models, starting from the more abstract model to the one that is very close to the code. The process consists of the following steps: (1) model the system as an Abstract State Machine, (2) generate test sequences based on the ASM model, (3) compute the code coverage using generated tests, (4) if the coverage is low refine the Abstract State Machine and return to step 2. We have applied the proposed approach to Antidote, an open-source implementation of IEEE 11073-20601 Personal Health Device (PHD) protocol which allows personal healthcare devices to exchange data with other devices such as small computers and smartphones