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Poisson-Gamma and Spatial-Temporal Models: with Application to Cervical Cancer in Kenya's Counties

机译:泊松 - 伽玛和空间 - 时间模型:在肯尼亚县的宫颈癌应用

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In Africa, Cancer is an emerging health problem where in 2012 new cancer cases were about 847,00 and around 519,00 deaths, three quarters of those deaths occurred in sub-Saharan region. In 2018, cancer was ranked as the third leading cause of deaths in Kenya after infectious and cardiovascular diseases. In 2018 cancer incidences were estimated to be 47,887 new cancer cases and 32,987 deaths. According to data from World Health Organization in 2020, cervical cancer is the second most prevalent cancer among women while breast cancer is the first. In this study, data collected by the Nairobi Cancer Registry (NCR) was used to produce spatial-temporal distribution of the cervical cancer in counties in Kenya. The results showed that counties where data was available among them Embu, Meru, Machakos, Mombasa, Nyeri, Kiambu, Kakamega, Nairobi and Bomet respectively had high risk of cervical cancer. Availability of county-based estimates and spatial-temporal distribution of cervical cancer cases will aide development of targeted county strategies, enhance early detection, promote awareness and implementation of universal coverage of major control interventions which will be crucial in reducing and halting the rising burden of the cancer cases in Kenya. In counties where data was not available the model showed relative risks for cervical cancer disease was minute but it was present, therefore spatial temporal models are very appropriate to estimate relative risks of diseases even when there is a small sample (and possibly without a sample) in a given area by borrowing information from other neighboring regions.
机译:在非洲,癌症是一个新兴的健康问题,在2012年,新的癌症病例约为847,00和约519,00人死亡,在撒哈拉地区发生了四分之三的死亡。 2018年,癌症被排名为肯尼亚发生传染病和心血管疾病后的肯尼亚死亡原因。 2018年癌症发病率估计为47,887个新癌症病例和32,987人死亡。根据2020年世界卫生组织的数据,宫颈癌是女性中最普遍的癌症,而乳腺癌是第一个。在这项研究中,由内罗毕癌症登记处(NCR)收集的数据用于在肯尼亚县产生宫颈癌的空间分布。结果表明,县中可用的县,Meru,Machakos,Mombasa,Nyeri,Kiambu,Kakamega,Nairobi和Bomet分别具有高风险的宫颈癌。县级估计和宫颈癌患者的空间分布的可用性将融合有针对性的县策略的发展,提高早期检测,提高认识和实施普遍覆盖的主要控制干预措施,这将在减少和停止负担的负担至关重要肯尼亚的癌症病例。在县的数据不可用,模型显示出宫颈癌疾病的相对风险是微小的,但存在,因此即使存在小样品(并且可能没有样品),空间时间模型也非常合适地估计疾病的相对风险在给定区域通过从其他邻居区域借用信息。

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