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Incidence estimation using a single cross-sectional age-specific prevalence survey with differential mortality

机译:使用具有不同死亡率的单个横断面年龄特定患病率调查来估计发病率

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Here, we present a method for incidence estimation of a curable, non-recurring disease when data from a single cross-sectional survey are used together with population-level mortality rates and an assumption of differential mortality of diseased versus non-diseased individuals. The motivating example is cataract, and the VISION2020 goal to eliminate avoidable blindness globally by 2020. Reliable estimates of current and future cataract disease burden are required to predict how many surgeries would need to be performed to meet the VISION2020 goals. However, incidence estimates, needed to derive future burden, are not as easily available, due to the cost of conducting cohort studies. Disease is defined at the person-level in accordance with the WHO person-level definition of blindness. An extension of the standard time homogeneous illness-death model to a four-state model is described, which allows the disease to be cured, whereby surgery is performed on at least one diseased eye. Incidence is estimated, and the four-state model is used to predict disease burden assuming different surgical strategies whilst accounting for the competing risk of death. The method is applied to data from approximately 10000 people from a survey of visual impairment in Nigeria.
机译:在这里,我们提供了一种将单一横断面调查的数据与人群水平的死亡率以及患病与未患病个体的死亡率差异假设一起使用时可治愈的非复发性疾病的发病率估算方法。激励措施的例子是白内障,而VISION2020目标是到2020年在全球范围内消除可避免的失明。需要对当前和未来的白内障疾病负担进行可靠的估算,才能预测需要进行多少手术才能达到VISION2020的目标。然而,由于进行队列研究的成本,很难估算出未来负担所需的发病率估计值。根据世卫组织对失明的人的定义在人的层面上定义疾病。描述了将标准时间均质疾病死亡模型扩展为四状态模型,该模型可以治愈疾病,从而对至少一只患病的眼睛进行手术。估计发病率,并采用四状态模型来预测疾病负担,并假设不同的手术策略,同时考虑竞争性死亡风险。该方法应用于尼日利亚视力障碍调查中约10000人的数据。

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