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Epidemiological Surveillance System for Coffee Rust Disease (Hemileia vastatrix) in Mexico: A Regional Approach
Abstract
The Mexican approach to face the recent coffee rust epidemic outbreak was to establish a
Regional Surveillance System operated by specifically trained personal at state level and
centrally coordinated by phytosanitary officials. The System integrates in a web platform field
monitoring and restricted-moving sampling with spatial and temporal data analysis based on
simple algorithms. In 342 sites, a total of 12 variables are weekly/biweekly measured related
to disease intensity, plant phenology and clime. Upon these variables, 12 indexes are
estimated to define early warnings at county level. Restricted spatial interpolations to coffee
growing sub-regions and four related indexes are also generated to identify risk-management
areas. In addition to the official scheme, spore trapping and disease assessment are also
conducted in selected areas using a research approach for purposes of data validation and
forecasting modeling. The web platform allows certified official to generated customized
graphics at all time to establish the epidemic status at state, county and site level. In addition,
indexes per county are weakly estimated to alert officials and state policy makers. In 2014,
nine additional coffee pests were included in the surveillance system.
The advancement of digital technology has made it possible to conceive automated Epidemiological Surveillance Systems (ESS) with a holistic-systemic approach allowing effective operation, management, and processing of phytosanitary data for fast decision making applied to regional prevention and pest management. This surveillance type focuses on plant health, overcoming the reductionist pest vision of the conventional normative surveillance. An ESS implies the precise definition of the regional framework, objectives, pest(s) in a wide sense, human/financial resources, regulatory context, support research planning, operational structure, and innovation models. These elements determine the precision, frequency, and type of sampling and monitoring and the selection of variables related to a novel epidemiological system. In contrast to the normative surveillance, a systemic ESS has descriptive and risk forecasting capabilities, including early warnings, based on spatial and temporal analyses. A web-based ESS assures a flexible-dynamic generation of reports and automated analysis. An ESS operated on web platforms, emphasizing open source software and tools, can be hosted on generic or dedicated servers for metadata storage configured with Linux / Apache technologies with 24/7 (h day-1) functional capabilities. Open source tools include MySQL / MariaDB and other systems as database managers; PHP / Node.js, and JavaScript, Ajax, HTML5 and CSS as web design base ‘back-end’ and ‘front-end’ programs, respectively. This review focuses on principles, conceptual attributes, general methodological approaches, and objectives of web-based ESS. An overview is presented with an ESS developed in Mexico for coffee plantations (Coffea spp.), which allowed the surveillance of 19 pests, nine under quarantine status, through the generation, management, and analysis of 87.4 million climatic data and 15.7 million epidemiological records over 2013-2019.
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