2020-01-012024-05-17https://scholars.lib.ntu.edu.tw/handle/123456789/671623摘要：過去研究發現高血壓在男女及停經前後有顯著變異，並發展個人化高血壓風險模式，以提供降低不同危險因子策略之評估。其他慢性病(如糖尿病)之個人風險模式的預防也有相同的發現。本計畫依據不同慢性病自然病史，包括代謝症候群、失智等，探討各層級因子對於不同慢性病疾病進展階段影響，並據以發展個人化慢性病風險評估模式，利用實證醫學方法評估個人化多層次多因子慢性病預防介入策略之效益。除了利用多層次風險評估及評估架構發展個人化疾病預測模式外，此預測模式亦需利用其他來源資料做外部驗證。 感染防治系統需納入宿主-環境之互動與平衡之監測、個人與病原因素造成傳播機率的不同外、接觸頻率、可傳染期間對於社區傳染病散佈亦有重要影響。此外亦應考慮巨觀因子(環境暴露、宿主特性、共同生活之接觸頻率)、家戶接觸，以及微觀因子(抗藥特性)、傳染病之多重疾病進程等對於染患疾病或形成帶原狀態的影響。藉由社區健康行為介入中心之架構將可建立包含上述完整多層次之傳染病監測體系，以結核病、C型肝炎等傳染病為目標，透過族群在傳染病傳播動力了解，達到早期偵測流行發生、評估介入策略效益，提供族群傳染病防治之目的。本計畫藉由世代研究設計評估相關疫苗、抗病毒藥物以及篩檢對於個案之發生、偵測以及相關併發症及死亡作為定義事件，評估各種政策對於社區民眾之保護效益<br> Abstract: Previous study found that the risk of hypertension was significantly different between men and women and before and after menopause, and then developed a personalized risk model for hypertension to provide an assessment of strategies to reduce risk factors. The personalized prevention of other chronic diseases such as diabetes has the same findings. The project is based on the natural history of each chronic disease, including metabolic syndrome, dementia, etc., to explore the impact of various levels of factors on the progression of different chronic diseases, and to develop a personalized risk assessment model for chronic diseases. The benefits of personalized multi-level, multi-factor chronic disease prevention intervention strategies will be evaluated with an empirical medical approach. This sub-project is using metabolic syndrome as a pilot research on chronic disease prevention and control models, and gradually expand to other chronic diseases, using community health platforms and health big data to explore important chronic disease burdens and epidemics trends in Taiwan. It will further develop a personalized disease risk prediction model. Such personalized risk predictions help community members to stratify and manage disease risk and apply personalized chronic disease prevention intervention strategies. In addition to developing a personalized disease prediction model using a multi-level risk assessment, this forecasting model also requires external validation, by using the information from other communities. The infection control system has to comprise the host-environment interaction and balance monitoring. The individual and pathogen factors cause different transmission rates, and the frequency of exposure and the infectious period also have an important impact on the spread of community infectious diseases. In addition, macroscopic factors (environmental exposure, host characteristics, frequency of contact with common life), household exposure, and microscopic factors (drug resistance), multiple diseases of infectious diseases should be considered for the impact on the carrier state or the symptomatic state. Through the framework of the community health intervention center, a comprehensive multi-level infectious disease surveillance system can be established. It can achieve the goal of early detection of epidemics, evaluate the effectiveness of intervention strategies, and provide prevention and treatment of population infectious diseases for tuberculosis, hepatitis C infection through the understanding the dynamics of disease transmission in population. This subproject is aim to establish a monitoring platforms for infectious diseases (such as tuberculosis) in communities and medical institutions. We evaluates the effectiveness of vaccination strategies for community populations by identifying the relevant vaccines, antiviral drugs, and screening agents for the occurrence, detection, and associated complications and deaths through cohort study. The project evaluates the benefits of vaccines, antiviral drugs, and rapid screening agents in a cohort or case-control study design.慢性病傳染病個人化評估模式Chronic DiseaseInfection DiseasePersonalized risk assessment model