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Updated: Jul 19, 2026
09:49
Investigation of Microbial Cooperation via Imaging Mass Spectrometry Analysis of Bacterial Colonies Grown on Agar and in Tissue During Infection
Published on: November 18, 2022
Joint spatial analysis of gastrointestinal infectious diseases
Leonhard Held1, Giusi Graziano, Christina Frank
1Department of Statistics, University of Munich, Ludwigstr. 33, 80539 Munich, Germany. leonhard.held@stat.uni-muenchen.de
Statistical Methods in Medical Research
|November 9, 2006
Summary
This study infers infectious disease reporting rates using joint statistical modeling. This method helps reveal geographic risk patterns for foodborne illnesses by accounting for under-reporting variations.
Area of Science:
- Epidemiology
- Biostatistics
- Spatial Analysis
Background:
- Under-reporting is a major challenge in infectious disease surveillance.
- Accurate spatial analysis requires understanding and estimating reporting variations.
Purpose of the Study:
- To develop a method for inferring reporting rates from infectious disease surveillance data.
- To enable the discernment of geographic risk patterns for foodborne infections.
Main Methods:
- Adoption and extension of the shared component model for joint statistical modeling of multiple infectious diseases.
- Estimation of a shared spatial component representing reporting rate variation.
- Adjustment for local outbreaks using a time series method.
Main Results:
- The shared component model successfully estimates spatial variation in reporting rates.
- Geographic risk patterns for specific foodborne diseases can be discerned after accounting for under-reporting.
Conclusions:
- Joint statistical modeling offers a robust approach to address under-reporting in infectious disease surveillance.
- This methodology enhances the accuracy of spatial risk assessment for foodborne diseases.
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