估计 2007 年恶性疟原虫疟疾的全球临床负担。

Estimating the global clinical burden of Plasmodium falciparum malaria in 2007.

机构信息

Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.

出版信息

PLoS Med. 2010 Jun 15;7(6):e1000290. doi: 10.1371/journal.pmed.1000290.

Abstract

BACKGROUND

The epidemiology of malaria makes surveillance-based methods of estimating its disease burden problematic. Cartographic approaches have provided alternative malaria burden estimates, but there remains widespread misunderstanding about their derivation and fidelity. The aims of this study are to present a new cartographic technique and its application for deriving global clinical burden estimates of Plasmodium falciparum malaria for 2007, and to compare these estimates and their likely precision with those derived under existing surveillance-based approaches.

METHODS AND FINDINGS

In seven of the 87 countries endemic for P. falciparum malaria, the health reporting infrastructure was deemed sufficiently rigorous for case reports to be used verbatim. In the remaining countries, the mapped extent of unstable and stable P. falciparum malaria transmission was first determined. Estimates of the plausible incidence range of clinical cases were then calculated within the spatial limits of unstable transmission. A modelled relationship between clinical incidence and prevalence was used, together with new maps of P. falciparum malaria endemicity, to estimate incidence in areas of stable transmission, and geostatistical joint simulation was used to quantify uncertainty in these estimates at national, regional, and global scales. Combining these estimates for all areas of transmission risk resulted in 451 million (95% credible interval 349-552 million) clinical cases of P. falciparum malaria in 2007. Almost all of this burden of morbidity occurred in areas of stable transmission. More than half of all estimated P. falciparum clinical cases and associated uncertainty occurred in India, Nigeria, the Democratic Republic of the Congo (DRC), and Myanmar (Burma), where 1.405 billion people are at risk. Recent surveillance-based methods of burden estimation were then reviewed and discrepancies in national estimates explored. When these cartographically derived national estimates were ranked according to their relative uncertainty and replaced by surveillance-based estimates in the least certain half, 98% of the global clinical burden continued to be estimated by cartographic techniques.

CONCLUSIONS AND SIGNIFICANCE

Cartographic approaches to burden estimation provide a globally consistent measure of malaria morbidity of known fidelity, and they represent the only plausible method in those malaria-endemic countries with nonfunctional national surveillance. Unacceptable uncertainty in the clinical burden of malaria in only four countries confounds our ability to evaluate needs and monitor progress toward international targets for malaria control at the global scale. National prevalence surveys in each nation would reduce this uncertainty profoundly. Opportunities for further reducing uncertainty in clinical burden estimates by hybridizing alternative burden estimation procedures are also evaluated.

摘要

背景

疟疾的流行病学使得基于监测的方法来估计其疾病负担变得很复杂。制图方法提供了替代疟疾负担估计的方法,但对其推导和保真度仍存在广泛的误解。本研究的目的是提出一种新的制图技术,并应用于 2007 年全球恶性疟原虫疟疾的临床负担估计,同时比较这些估计及其可能的精度与现有的基于监测的方法所得到的估计及其精度。

方法和发现

在 87 个恶性疟原虫流行的国家中的 7 个国家中,卫生报告基础设施被认为足够严格,可以逐字使用病例报告。在其余国家中,首先确定不稳定和稳定的恶性疟原虫疟疾传播的映射范围。然后在不稳定传播的空间范围内计算可能的临床病例发生率范围的估计。使用临床发病率和流行率之间的模型关系,以及新的恶性疟原虫疟疾流行图,估计稳定传播地区的发病率,并使用地质统计学联合模拟来量化这些估计在国家、区域和全球尺度上的不确定性。将所有传播风险地区的这些估计结合起来,导致 2007 年发生了 4.51 亿(95%可信区间 3.49-5.52 亿)例恶性疟原虫疟疾。这种发病率几乎全部发生在稳定传播的地区。在印度、尼日利亚、刚果民主共和国(DRC)和缅甸(缅甸),超过一半的所有估计的恶性疟原虫临床病例和相关不确定性发生在这些国家,这些国家有 14.05 亿人面临风险。然后,对最近的基于监测的负担估计方法进行了审查,并探讨了国家估计之间的差异。当根据相对不确定性对这些地图绘制的国家估计进行排名,并在最不确定的一半中用基于监测的估计取代时,98%的全球临床负担继续通过地图绘制技术来估计。

结论和意义

负担估计的制图方法提供了已知保真度的疟疾发病率的全球一致衡量标准,并且它们是在那些国家监测功能失调的疟疾流行国家中唯一可行的方法。在仅四个国家中,疟疾临床负担的不确定性很大,这使我们无法在全球范围内评估需求并监测实现疟疾控制国际目标的进展。每个国家的全国患病率调查将大大降低这种不确定性。通过混合使用替代负担估计程序,还有机会进一步降低临床负担估计的不确定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0249/2885984/6f8626dac90d/pmed.1000290.g001.jpg

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