An assessment of the operationality and factors influencing the effectiveness of rabies surveillance in Gombe State, Nigeria.

Rabies remains a burden in Africa, disproportionately affecting the most vulnerable despite the availability of effective vaccines. Nigeria, the most populous African country, needs rapid disease control actions and commitments to achieve the goal of eliminating dog-mediated rabies by 2030. Surveillance is an essential element of effective disease control strategies.

Prospects for dog rabies elimination in Nigeria by 2030.

The attainment of the global target of zero dog-mediated human rabies by 2030 depends on functional rabies programmes. Nigeria, a rabies-endemic country, and the most populous country in Africa has a very poor rabies control strategy with a score of 1.5 out of 5 based on the Stepwise Approach towards Rabies Elimination (SARE).

Whole Genome Sequencing for Rapid Characterization of Rabies Virus Using Nanopore Technology.

Genomic data can be used to track the transmission and geographic spread of infectious diseases. However, the sequencing capacity required for genomic surveillance remains limited in many low- and middle-income countries (LMICs), where dog-mediated rabies and/or rabies transmitted by wildlife such as vampire bats pose major public health and economic concerns. We present here a rapid and affordable sample-to-sequence-to-interpretation workflow using nanopore technology.

Rabies virus infection is associated with variations in calbindin D-28K and calretinin mRNA expression levels in mouse brain tissue.

Rabies virus (RABV) infection leads to a fatal neurological outcome in humans and animals and is associated with major alterations in cellular gene expression. In this study, we describe the effects of RABV infection on the mRNA expression levels of two genes, encoding the Ca-binding proteins (Ca-BPs) calbindin D-28K (Calb1) and calretinin (Calb2), in the brains of BALB/c mice. Sixty 4-week-old mice were divided into two test groups and one control group.

Toward Accurate Indoor Positioning: An RSS-Based Fusion of UWB and Machine-Learning-Enhanced WiFi.

A wide variety of sensors and devices are used in indoor positioning scenarios to improve localization accuracy and overcome harsh radio propagation conditions. The availability of these individual sensors suggests the idea of sensor fusion to achieve a more accurate solution. This work aims to address, with the goal of improving localization accuracy, the fusion of two conventional candidates for indoor positioning scenarios: Ultra Wide Band (UWB) and Wireless Fidelity (WiFi).