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An exploration of the disease burden due to Cryptosporidium in consumed surface water for sub-Saharan Africa

机译:撒哈拉以南非洲地表水消费中隐孢子虫引起的疾病负担的探索

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The protozoan pathogen Cryptosporidium is an important cause of diarrhoeal disease, but in many contexts its burden remains uncertain. The Global Waterborne Pathogen model for Cryptosporidium (GloWPa-Crypto) predicts oocyst concentrations in surface water at 0.5 by 0.5 degrees (longitude by latitude) resolution, allowing us to assess the burden specifically associated with the consumption of contaminated surface water at a large scale. In this study, data produced by the GloWPa-Crypto model were used in a quantitative microbial risk assessment (QMRA) for sub-Saharan Africa, one of the regions most severely affected by diarrhoeal disease. We first estimated the number of people consuming surface water in this region and assessed both direct consumption and consumption from a piped (treated) supply. The disease burden was expressed in disability adjusted life years (DALYs). We estimate an annual number of 4.3 x 10(7) (95% uncertainty interval [UI] 7.4 x 10(6)-5.4 x 10(7)) cases which represent 1.6 x 10(6) (95% UI 3.2 x 10(5)-2.3 x 10(6)) DALYs. Relative disease burden (DALYs per 100,000 persons) varies widely, ranging between 1.3 (95% UI 0.1-5.7) for Senegal and 1.0 x 10(3) (95% UI 4.2 x 10(2)-1.4 x 10(3)) for Eswatini. Countries that carry the highest relative disease burden are primarily located in south and south-east sub-Saharan Africa and are characterised by a relatively high HIV/AIDS prevalence. Direct surface water consumption accounts for the vast majority of cases, but the results also point towards the importance of stable drinking water treatment performance. This is, to our knowledge, the first study to utilise modelled data on pathogen concentrations in a large scale QMRA. It demonstrates the potential value of such data in epidemiological research, particularly regarding disease aetiology.
机译:原生动物病原体隐孢子虫是腹泻病的重要原因,但在许多情况下其负担仍不确定。隐孢子虫的全球水生病原体模型(GloWPa-Crypto)预测地表水中的卵囊浓度为0.5 x 0.5度(经度),这使我们能够评估与大规模消耗受污染地表水有关的负担。在这项研究中,GloWPa-Crypto模型产生的数据被用于撒哈拉以南非洲的定量微生物风险评估(QMRA),该地区是受腹泻病影响最严重的地区之一。我们首先估算了该地区消耗地表水的人数,并评估了直接消耗量和管道(处理过的)供水量。疾病负担以残疾调整生命年(DALYs)表示。我们估计每年有4.3 x 10(7)(95%不确定区间[UI] 7.4 x 10(6)-5.4 x 10(7))代表1.6 x 10(6)(95%UI 3.2 x 10 (5)-2.3 x 10(6))天。相对疾病负担(每100,000人的DALY)差异很大,介于塞内加尔1.3(95%UI 0.1-5.7)和1.0 x 10(3)(95%UI 4.2 x 10(2)-1.4 x 10(3))之间对于Eswatini。相对疾病负担最高的国家主要位于撒哈拉以南非洲的南部和东南部,其特点是艾滋病毒/艾滋病的患病率较高。绝大多数情况下,直接地表水消耗量很大,但结果也指出了稳定饮用水处理性能的重要性。据我们所知,这是第一项利用大规模QMRA中病原体浓度建模数据的研究。它证明了此类数据在流行病学研究中的潜在价值,特别是在疾病病因学方面。

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