DetectImports

DetectImports implements methods in R to identify imported infectious disease cases using genomic data from a single geographic location to distinguish importation from local transmission.

Key Features:

• Localized genomic comparison: Compares new cases with historical cases from the same region using genomic data to detect imported infections without multi-location sampling.
• Genealogical distribution assessment: Evaluates genealogical distributions to identify discrepancies between locally acquired and imported cases.
• Population size adjustment: Accounts for variation in the size of the local population to improve import detection sensitivity and specificity.
• Validation under structured coalescent: Performance has been tested using data simulated under the structured coalescent model.
• Application to pathogens: Demonstrated on genomic datasets from both bacterial and viral pathogens.
• Computational efficiency: Capable of delivering results on the number of imported cases within seconds to minutes.

Scientific Applications:

• Epidemiological inference: Distinguishes imported versus local transmission to inform analyses of outbreak origin and spread.
• Public health response: Informs targeted control strategies by identifying likely importation events in geographically limited sampling.
• Pathogen-agnostic genomic surveillance: Applicable to both bacterial and viral genomic surveillance datasets for import detection.

Methodology:

Compares new versus historical regional genomes, assesses genealogical distributions to detect discrepancies, adjusts for local population size, and has been validated using simulations under the structured coalescent model and applied to bacterial and viral genomic datasets.