Battle Katherine E, Cameron Ewan, Guerra Carlos A, Golding Nick, Duda Kirsten A, Howes Rosalind E, Elyazar Iqbal R F, Price Ric N, Baird J Kevin, Reiner Robert C, Smith David L, Gething Peter W, Hay Simon I
Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford, UK.
Sanaria Institute for Global Health and Tropical Medicine, Rockville, MD, USA.
Malar J. 2015 May 7;14:191. doi: 10.1186/s12936-015-0706-3.
Though essential to the development and evaluation of national malaria control programmes, precise enumeration of the clinical illness burden of malaria in endemic countries remains challenging where local surveillance systems are incomplete. Strategies to infer annual incidence rates from parasite prevalence survey compilations have proven effective in the specific case of Plasmodium falciparum, but have yet to be developed for Plasmodium vivax. Moreover, defining the relationship between P. vivax prevalence and clinical incidence may also allow levels of endemicity to be inferred for areas where the information balance is reversed, that is, incident case numbers are more widely gathered than parasite surveys; both applications ultimately facilitating cartographic estimates of P. vivax transmission intensity and its ensuring disease burden.
A search for active case detection surveys was conducted and the recorded incidence values were matched to local, contemporary parasite rate measures and classified to geographic zones of differing relapse phenotypes. A hierarchical Bayesian model was fitted to these data to quantify the relationship between prevalence and incidence while accounting for variation among relapse zones.
The model, fitted with 176 concurrently measured P. vivax incidence and prevalence records, was a linear regression of the logarithm of incidence against the logarithm of age-standardized prevalence. Specific relationships for the six relapse zones where data were available were drawn, as well as a pooled overall relationship. The slope of the curves varied among relapse zones; zones with short predicted time to relapse had steeper slopes than those observed to contain long-latency relapse phenotypes.
The fitted relationships, along with appropriate uncertainty metrics, allow for estimates of clinical incidence of known confidence to be made from wherever P. vivax prevalence data are available. This is a prerequisite for cartographic-based inferences about the global burden of morbidity due to P. vivax, which will be used to inform control efforts.
尽管对于国家疟疾控制规划的制定和评估至关重要,但在地方监测系统不完整的疟疾流行国家,精确统计疟疾临床疾病负担仍具有挑战性。从寄生虫流行率调查汇编中推断年发病率的策略已被证明在恶性疟原虫的特定案例中有效,但间日疟原虫的此类策略尚未开发出来。此外,确定间日疟原虫流行率与临床发病率之间的关系,也可能有助于推断信息平衡相反地区(即发病病例数比寄生虫调查收集得更广泛的地区)的流行程度;这两种应用最终都有助于对间日疟原虫传播强度及其所致疾病负担进行地图学估计。
开展了主动病例检测调查,并将记录的发病率值与当地同时期的寄生虫率测量值进行匹配,并按不同复发表型的地理区域进行分类。对这些数据拟合了分层贝叶斯模型,以量化流行率与发病率之间的关系,同时考虑复发区域之间的差异。
该模型拟合了176个同时测量的间日疟原虫发病率和流行率记录,是发病率对数与年龄标准化流行率对数的线性回归。绘制了有数据可用的六个复发区域的具体关系以及汇总的总体关系。曲线斜率在不同复发区域有所不同;预测复发时间短的区域斜率比观察到包含长潜伏期复发表型的区域更陡。
拟合的关系以及适当的不确定性度量,使得可以从任何有间日疟原虫流行率数据的地方做出已知置信度的临床发病率估计。这是基于地图学推断间日疟原虫所致全球发病负担的先决条件,该负担将用于为控制工作提供信息。