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19 November 2025

CerMapp: A Cloud-Based Geospatial Prototype for National Wildlife Disease Surveillance

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1
Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”, 64100 Teramo, Italy
2
Azienda Sanitaria Locale della Valle d’Aosta—AUSL Aosta—SC Sanità Animale, Località Amerique 7/L, 11020 Quart, Italy
3
Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta—S.C Valle d’Aosta—CeRMAS (National Reference Center for Wildlife Diseases), Località Amerique 7/G, 11020 Quart, Italy
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Author to whom correspondence should be addressed.

Abstract

CerMapp is a multi-platform and system application designed to address a critical gap in veterinary public health: the lack of a standardized, national-scale geodatabase for wildlife diseases. This gap has long hindered the effective application of GIS and remote sensing in spatial epidemiology. Currently deployed at the prototype level in Aosta Valley, NW Italy, the application’s core innovation is its ability to generate a structured, analysis-ready data repository, which serves as a foundational resource for One Health initiatives. Developed by the National Reference Center for Wildlife Diseases on the ESRI ArcGIS Survey123 platform v.3.24, CerMapp enables veterinarians, foresters, and wildlife professionals to easily collect and georeference field data, including species, health status, and photographic evidence using flexible methods such as Global Navigation Satellite System or manual map entry. Data collected via CerMapp are stored in a centralized geodatabase, facilitating risk analyses and detailed geospatial studies. This data can be integrated with remote sensing information processed on cloud platforms like Google Earth Engine or within traditional GIS software, contributing to a comprehensive and novel wildlife health registry. By promoting the rational and standardized collection of essential geospatial data, CerMapp data may support predictive disease modeling, risk assessment, and habitat suitability mapping for wildlife diseases, zoonoses, and vector-borne pathogens. Its scalable, user-friendly design ensures alignment with existing national systems like the Italian Animal Disease Information System (SIMAN), making advanced geospatial analysis accessible without requiring specialized digital skills from field operators or complex IT maintenance from institutions.

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