title: Automatic infection detection system.
abstract: An infected person may be contagious already before the first symptoms appear. This person can, in the period of disease evolution, infect several associated citizens before consulting a general practitioner (GP). Early detection of contagion is therefore important to prevent spreading of diseases. The Automatic Infection Detection (AID) System faces this problem through investigating the hypothesis that the blood glucose (BG) level increases when a person is infected. The first objective of the prototyped version of the AID system was to identify possible BG elevations in the incubation time that could be related to the spread of infectious diseases. To do this, we monitored two groups of people, with and without diabetes mellitus. The AID system analyzed the results and we were able to detect two cases of infection during the study period. The time of detection occurred simultaneous or near the time of onset of symptoms. The detection did not occur earlier for a number of reasons. The most likely one is that the evolution process of an infectious disease is both complicated and involves the immune system and several organs in the body. The investigation with regard to isolating the key relations is therefore considered as a very complex study. Nevertheless, the AID system managed to detect the infection much earlier than what is possible with today's early warning systems for infectious diseases.
authors.affiliation: Department of Computer Science, Faculty of Science, University of Tromsø, Norway.
authors.forename: Ove
authors.initials: O
authors.lastname: Granberg
authors.forename: Johan Gustav
authors.initials: JG
authors.lastname: Bellika
authors.forename: Eirik
authors.initials: E
authors.lastname: Arsand
authors.forename: Gunnar
authors.initials: G
authors.lastname: Hartvigsen
mesh_terms: D001786:Blood Glucose / Q000032:analysis*; D003141:Communicable Diseases / Q000097:blood / Q000175:diagnosis*; D003920:Diabetes Mellitus / Q000097:blood; D004196:Disease Outbreaks; D005873:Giardiasis / Q000175:diagnosis / Q000453:epidemiology; D006801:Humans; D008491:Medical Informatics Applications; D008991:Monitoring, Physiologic / Q000379:methods; D011159:Population Surveillance / Q000379:methods*
chemical_list: D001786:Blood Glucose