Disease Mapping with Spatially Uncertain Data
نویسندگان
چکیده
منابع مشابه
Disease Mapping with Spatially Uncertain Data
Objective Uncertainty regarding the location of disease acquisition, as well as selective identification of cases, may bias maps of risk. We propose an extension to a distance-based mapping method (DBM) that incorporates weighted locations to adjust for these biases. We demonstrate this method by mapping potential drug-resistant tuberculosis (DRTB) transmission hotspots using programmatic data ...
متن کاملMaking Decisions with Spatially and Temporally Uncertain Data
We consider a decision-making problem where the environment varies both in space and time. Such problems arise naturally when considering e.g., the navigation of an underwater robot amidst ocean currents or the navigation of an aerial vehicle in wind. To model such spatiotemporal variation, we extend the standard Markov Decision Process (MDP) to a new framework called the Time-Varying Markov De...
متن کاملAdversarial patrolling with spatially uncertain alarm signals
When securing complex infrastructures or large environments, constant surveillance of every area is not affordable. To cope with this issue, a common countermeasure is the usage of cheap but wide–ranged sensors, able to detect suspicious events that occur in large areas, supporting patrollers to improve the effectiveness of their strategies. However, such sensors are commonly affected by uncert...
متن کاملA hierarchical aggregate data model with spatially correlated disease rates.
The aggregate data study design (Prentice and Sheppard, 1995, Biometrika 82, 113-125) estimates individual-level exposure effects by regressing population-based disease rates on covariate data from survey samples in each population group. In this work, we further develop the aggregate data model to allow for residual spatial correlation among disease rates across populations. Geographical varia...
متن کاملOptimization with uncertain data
6 Chance constraints and the choice of uncertainty sets 15 6.1 Value at risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 6.2 Safe convex approximations for chance constraints . . . . . . . . . . . . . . . 17 6.3 Tightest convex bounds and conditional value at risk . . . . . . . . . . . . . 18 6.4 Analytic approximation using moment generating functions . . . . . ....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Online Journal of Public Health Informatics
سال: 2013
ISSN: 1947-2579
DOI: 10.5210/ojphi.v5i1.4380