An evaluation of the COVID-19 self-service digital contact tracing system in New Zealand.

Background: Digital contact tracing (DCT) aims to improve time-to-isolation (timeliness) and find more potentially exposed individuals (sensitivity) to enhance the utility of contact tracing. The aim of this study was to evaluate the public uptake of a DCT self-service survey and its integration with the Bluetooth exposure notification system within the New Zealand Covid Tracer App (NZCTA).

Methods: We adopted a retrospective cohort study design using community COVID-19 cases from February 2022 to August 2022 in New Zealand (1.

Exploring the drivers and barriers to uptake for digital contact tracing.

Digital contact tracing has been deployed as a public health intervention to help suppress the spread of Covid-19 in many jurisdictions. However, most governments have struggled with low uptake and participation rates, limiting the effectiveness of the tool. This paper characterises a number of systems developed around the world, comparing the uptake rates for systems with different technology, data architectures, and mandates.

Should policy makers trust composite indices? A commentary on the pitfalls of inappropriate indices for policy formation.

Background: This paper critically discusses the use and merits of global indices, in particular, the Global Health Security Index (GHSI; Cameron et al. https://www.ghsindex.

Fusing Appearance and Spatio-Temporal Models for Person Re-Identification and Tracking.

Knowing who is where is a common task for many computer vision applications. Most of the literature focuses on one of two approaches: determining who a detected person is (appearance-based re-identification) and collating positions into a list, or determining the motion of a person (spatio-temporal-based tracking) and assigning identity labels based on tracks formed. This paper presents a model fusion approach, aiming towards combining both sources of information together in order to increase the accuracy of determining identity classes for detected people using re-ranking.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target.