2010/09/24 by Ashok Krishnamurthy, Loren Cobb, Krishnamurthy, Ashok +5
Biochemistry, Genetics and Molecular Biology · Environmental Science · Mathematics · Medicine · #60H30 #62L12 #COVID-19 epidemiological studies #Computation (stat.CO) #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Species Distribution and Climate Change #Yersinia bacterium, plague, ectoparasites research #Zoonotic diseases and public health #msc:60H30 #msc:62L12 #stat.CO
paper · pdf · doi:10.48550/arxiv.1009.4959
15 pages, 5 figures. JSM 2010
openalex publication_date 2010/09/24 · arxiv created 2010/09/25 · arxiv updated 2010/10/04 · openalex created_date 2022/09/11 · openalex updated_date 2026/07/28
We explore the use of the optimal statistical interpolation (OSI) data assimilation method for the statistical tracking of emerging epidemics and to study the spatial dynamics of a disease. The epidemic models that we used for this study are spatial variants of the common susceptible-infectious-removed (S-I-R) compartmental model of epidemiology. The spatial S-I-R epidemic model is illustrated by application to simulated spatial dynamic epidemic data from the historic "Black Death" plague of 14th century Europe. Bayesian statistical tracking of emerging epidemic diseases using the OSI as it unfolds is illustrated for a simulated epidemic wave originating in Santa Fe, New Mexico.