Early estimation of the number of hidden HIV infected subjects: An extended Kalman filter approach

Paolo Di Giamberardino; Daniela Iacoviello

doi:10.1016/j.idm.2023.03.001

Early estimation of the number of hidden HIV infected subjects: An extended Kalman filter approach

Infect Dis Model. 2023 Mar 11;8(2):341-355. doi: 10.1016/j.idm.2023.03.001. eCollection 2023 Jun.

Authors

Paolo Di Giamberardino¹, Daniela Iacoviello¹

Affiliation

¹ Dept. of Computer, Control and Management Engineering, Sapienza, University of Rome, Via Ariosto 25, 00185, Rome, Italy.

Abstract

In the last decades several epidemic emergencies have been affecting the world, influencing the social relationships, the economics and the habits. In particular, starting in the early '80, the Acquired Immunodeficiency Syndrome, AIDS, is representing one of the most worrying sanitary emergency, that has caused up to now more than 25 million of dead patients. The infection is caused by the Human Immunodeficiency Virus, HIV, that may be transmitted by body fluids; therefore with wise behaviours the epidemic spread could rapidly be contained. This sanitary emergency is peculiar for the long incubation time: it can reach even 10 years, a long period in which the individual can unconsciously infect other subjects. The identification of the number of infected unaware people, mandatory to define suitable containment measures, is here obtained by using the extended Kalman filter applied to a noisy model in which, reasonably, only the number of infected diagnosed patients is available. Numerical simulations and real data analysis support the effectiveness of the approach.

Keywords: Epidemic modeling; Extended Kalman filter; HIV-AIDS; Infection spread.