Descripción del proyecto
Desvelar el lado oculto de las enfermedades infecciosas
El período de incubación es el intervalo temporal que transcurre entre la exposición a un agente infeccioso causante de una enfermedad y la aparición del primer síntoma. Aunque puede exhibir variedad interindividual, la tasa de replicación, así como el tipo y la duración de los síntomas suprimidos, también varían considerablemente entre patógenos. En este contexto, el proyecto DCUBATION, financiado con fondos europeos, investigará la aparición real de los síntomas. En concreto, se llevará a cabo una evaluación en tiempo real del riesgo previo de infecciones respiratorias al combinar modelos de transmisión con datos individuales de la historia médica electrónica de 4,5 millones de personas. El equipo del proyecto identificará microcambios en el comportamiento de los pacientes durante la fase inicial de una infección mediante el análisis de datos sensoriales digitales de dispositivos ponibles.
Objetivo
Infectious diseases pose one of the greatest risks for a global catastrophe. Just like controlling the spread of wildfires, an early detection of infectious diseases is instrumental to containing outbreaks. Nearly all infections start silently, and gradually progress until clinical symptoms appear. In this silent period, the incubation period (IP), pathogens inhibit major pathways of the innate immune system, allowing an extended period of unhindered replication. The rate of replication, as well as the type and length of suppressed symptoms vary considerably between pathogens, creating a unique signature for each pathogen. Thus, improved understanding of the IP is pivotal for early detection, prevention and control of infectious diseases. Previous studies estimating IPs have used aggregated retrospective data, and are subject to the biases of patient self-reporting. I hypothesise that the actual onset of clinical symptoms occurs earlier than previously known, can be identified more accurately, and can be used in real-time for patient empowerment. Focusing on respiratory infections, my methodological approach includes: 1) real-time evaluation of the prior risk for respiratory infections by integrating transmission models with individual-level data from electronic medical records of 4.5 Million individuals, 2) identification of micro-changes in patients’ behaviour during the early phase of an infection by prospectively analysing digital sensory data from wearable devices and mobile phones of 5000 selected participants, 3) early detection of the causing pathogen validated with self-swab kits that are tested using RT-PCR. Our preliminary work that combined an analysis of EMR and transmission modelling led to a change in public health policy in Israel. The proposed study has the potential to open new research directions on the hidden side of infectious diseases and to initiate a new era of personalized medicine through dramatic changes in patient-doctor interaction.
Ámbito científico
- natural sciencescomputer and information sciencesinternetinternet of things
- medical and health scienceshealth sciencespublic health
- medical and health scienceshealth sciencesinfectious diseases
- medical and health sciencesbasic medicineimmunology
- medical and health scienceshealth sciencespersonalized medicine
Palabras clave
Programa(s)
Régimen de financiación
ERC-STG - Starting GrantInstitución de acogida
69978 Tel Aviv
Israel