Tracing and tracking the emergence, epidemiology and dispersal of Malaria and Dengue virus
The four mosquito-borne dengue virus serotypes (DENV1–DENV4) cause a high burden of disease throughout the tropical and sub-tropical regions of the world. Nevertheless, their precise epidemiological history in Africa – including when and where they originated and were distributed during the 20th century – remains unclear, stressing the need for One Health focused research.
The Sensoworks IIoT Platform (Intelligent Internet of Things) analyses a set of clinical data from a biochemical sensor (patch) for continuous patient monitoring.
The method is similar to Continuous Glucose Monitoring, which provides – at very short intervals -the values detected in the subcutaneous interstitial fluid, recording the variation of the parameters.
The biological element interacts with the substrate to be analysed and, thanks to the transduction system (sensor), it converts the biochemical response into an electrical signal.
Leveraging wireless radio frequency technology, the continuous monitoring system is equipped with a small and light sensor connected to a transmitter, which sends the data detected by the sensor to the patient’s smartphone on regular intervals during the 24 hours.
The smartphone sends data to the Sensoworks IIoT Platform in real-time, communicating the detected parameters. These parameters will be displayed and analysed by a health worker, in order to monitor the possible evolution of the infection.
In the hypothesis of a patient who develops the disease in the days following the return from a tropical country, the Sensoworks IIoT Platform will allow the healthcare professional to identify the patient for tracking purposes (contact tracing).
The Sensoworks IIoT Platform, therefore, acts as a centralised tool for the management of the eventual evolution of the disease, for all patients under observation to whom the biochemical sensor has been applied, effectively constituting a real centre for the management and tracking of a possible epidemic.
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