Palabras clave
pruebas masivas; COVID-19 Costa Rica; RT-qPCR; pruebas de antígenos; RT-LAMP; agrupamiento; estrategias de detección
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Resumen
Introducción: En este artículo, derivamos el comportamiento de cuatro diferentes estrategias de pruebas masivas, basadas en las directrices y políticas de salud pública emitidas por el sistema de salud pública de Costa Rica. Objetivos: Desarrollar formalmente los cambios de cada estrategia de pruebas masivas estudiada bajo diferentes contextos relacionados con riesgo de las personas, costos de la prueba y acceso a tecnologías alternativas de pruebas. Métodos: Asumimos un pre-clasificador aplicado a individuos, capaz de dividir a los sospechosos en grupos de bajo riesgo y alto riesgo. Consideramos el impacto de tres tecnologías de prueba: RT-qPCR, pruebas basadas en antígenos y pruebas de saliva (RT-LAMP). Cuando estuvo disponible, introdujimos una categoría de trabajadores esenciales. Resultados: Los resultados de simulaciones numéricas confirman que las estrategias que utilizan únicamente pruebas RT-qPCR no pueden lograr una capacidad de existencias suficiente para proporcionar una detección eficiente, independientemente de la prevalencia, sensibilidad o especificidad. Las estrategias que aprovechan el poder tanto del agrupamiento (pooling) como del RT-LAMP maximizan la capacidad de existencias o la eficiencia de detección, o ambos. Conclusiones: Invertir en la calidad de los datos como en la precisión de la clasificación puede mejorar las probabilidades de lograr el control y la mitigación de la pandemia. El trabajo futuro se concentrará, basándonos en nuestros hallazgos, en construir datos sintéticos representativos a través de modelado basado en agentes y estudiar las propiedades de pre-clasificadores específicos bajo varios escenarios.
Citas
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