El avance de la tecnología digital ha permitido concebir Sistemas de Vigilancia Epidemiológicos (SVE) automatizados con un enfoque <em>holístico-sistémico</em> favoreciendo la planeación, operación, gestión y procesamiento de datos fitosanitarios de manera efectiva y oportuna para toma de decisiones en la prevención y manejo regional de plagas. Este tipo de sistemas se enfocan en la salud del cultivo superando la visión reduccionista de plaga en la vigilancia normativa convencional. Un SVE web implica la definición clara del marco regional, objetivos, plaga(s) en su amplia acepción, recursos humanos/financieros, contexto normativo, líneas de investigación de soporte, estructura operativa y modelos de innovación. Estos elementos determinan la precisión, frecuencia y tipo de muestreo y monitoreo, así como las variables de medición relativas a un novel<em> sistema epidemiológico</em>. A diferencia de la vigilancia normativa, un SVE web <em>holístico-sistémico</em> tiene capacidad descriptiva y de pronóstico de riesgos, incluyendo alertas tempranas a partir de análisis espaciales y temporales. La interfaz web SVE asegura la generación flexible y dinámica de reportes y/o análisis automatizados. Un SVE operado en plataformas web, con énfasis en lenguajes de programación y herramientas de uso libre puede ser alojado en servidores genéricos o dedicados para almacenamiento de metadatos configurados con tecnologías Linux/Apache y funcionalidad 24/7 (h día-1). Programas de uso libre incluyen MySQL/MariaDB y otros como gestores de bases de datos; PHP / Node.js, y JavaScript, Ajax, HTML5 y CSS, como tecnologías web de maquetado base ‘back-end’ y ‘front-end’, respectivamente. Esta revisión se enfoca en principios, atributos conceptuales, enfoques metodológicos generales y objetivos de SVE base web. Aplicaciones generales se ilustran con un SVE desarrollado en México para el cafeto (<em>Coffea</em> spp.), el cual permitió operar la vigilancia de 19 plagas, nueve con estatus cuarentenario, mediante la generación, gestión y análisis de 87.4 y 15.7 millones de registros climáticos y epidemiológicos, respectivamente, obtenidos entre 2013-2019.

This study provides a safe and low-cost in-house protocol for RT-qPCR-based detection of SARS-CoV-2 using mouthwash–saliva self-collected specimens to achieve clinical and epidemiological surveillance in a real-time web environment applied to ambulatory populations. The in-house protocol comprises a mouthwash–saliva self-collected specimen, heat virus inactivation, and primers to target virus N-gene region and the human RPP30-gene. Aligning with 209 SARS-CoV-2 sequences confirmed specificity including the Alpha variant from the UK. Development, validation, and statistical comparison with official nasopharyngeal swabbing RT-qPCR test were conducted with 115 specimens of ambulatory volunteers. A web–mobile application platform was developed to integrate a real-time epidemiological and clinical core baseline database with mouthwash–saliva RT-qPCR testing. Nine built-in algorithms were generated for decision-making on testing, confining, monitoring, and self-reports to family, social, and work environments. Epidemiological and clinical follow-up and SARS-CoV-2 testing generated a database of 37,351 entries allowing individual decision-making for prevention. Mouthwash–saliva had higher sensitivity than nasopharyngeal swabbing in detecting asymptomatic and mild symptomatic cases with 720 viral copy number (VCN)/mL as the detection limit (Ct = 37.6). Cycling threshold and viral loading were marginally different (p = 0.057) between asymptomatic (35 Ct ± 2.8; 21,767.7 VCN/mL, range 720–77,278) and symptomatic (31.3 Ct ± 4.5; 747,294.3 VCN/mL, range 1433.6–3.08 × 106). We provided proof-of-concept evidence of effective surveillance to target asymptomatic and moderate symptomatic ambulatory individuals based on integrating a bio-safety level II laboratory, self-collected, low-risk, low-cost detection protocol, and a real-time digital monitoring system. Mouthwash–saliva was effective for SARS-CoV-2 sampling for the first time at the community level.

App-ExploraCitricos v2.0 is an application for assessing epidemiological variables with a spatio-temporal, multicrop, multivariety-species, multivariable, multi-pest, multi-user and multi-criteria approach for risk analysis in the citrus productive chain. This work aimed to develop an application for Android® mobile devices higher than 5.0, allowing in situ evaluations associated with epidemiological or phytosanitary processes through a flexible design customized to the user's criteria. The process is initiated by logging into the application with passwords, previously registered, for authentication. Before an assessment, users are required to register only once n-pests and/or n-diseases associated with the citrus crop(s)/species concerned, providing the common and scientific name, and organism type (fungus, virus, bacterium, etc.). Entries are stored locally available for future assessments. Later, set up assessment n-scales with n-classes to quantify damage/severity. Versatility allows entry of qualitative (e.g. healthy, sick, dead) or quantitative scales (e.g. 0, <25%, 25-50% and >50%). It also enables to assess presence/absence and quantify vector if required. By customizing the assessment, choose the pest(s) concerned and associated scale. At the moment of evaluation, a plantation is parameterized by 26 epidemiological-productive variables, e.g., agronomic condition, age, crop, variety/cultivar, irrigation type, nutrition, management, etc. Assessment is performed for n-plants defined by the user. Per plant, the selected pathogen-pest(s) and scale class is assessed. Optionally, up to three geo-referenced photographs of symptoms or other aspect of concern can be taken. At the end, assessment(s) are sent to a database web platform. Assessments per planting are exported in MS-Excel for sharing via email, bluetooth, social networks or other device tools.