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A Poisson Kalman filter for disease surveillance
- Source :
- Phys. Rev. Research 2, 043028 (2020)
- Publication Year :
- 2020
-
Abstract
- An optimal filter for Poisson observations is developed as a variant of the traditional Kalman filter. Poisson distributions are characteristic of infectious diseases, which model the number of patients recorded as presenting each day to a health care system. We develop both a linear and nonlinear (extended) filter. The methods are applied to a case study of neonatal sepsis and postinfectious hydrocephalus in Africa, using parameters estimated from publicly available data. Our approach is applicable to a broad range of disease dynamics, including both noncommunicable and the inherent nonlinearities of communicable infectious diseases and epidemics such as from COVID-19.<br />Comment: 19 Pages, 8 Figures
- Subjects :
- Statistics - Methodology
Quantitative Biology - Quantitative Methods
Subjects
Details
- Database :
- arXiv
- Journal :
- Phys. Rev. Research 2, 043028 (2020)
- Publication Type :
- Report
- Accession number :
- edsarx.2003.11194
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1103/PhysRevResearch.2.043028