Instituto Leônidas e Maria Deane - Fiocruz Amazônia, Manaus, Amazonas, Brazil.
PLoS Negl Trop Dis. 2010 Mar 2;4(3):e620. doi: 10.1371/journal.pntd.0000620.
Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae), the most important vectors of Chagas disease (CD) in northern South America.
METHODOLOGY/PRINCIPAL FINDINGS: The probability of detecting triatomines in infested palms is estimated by repeatedly sampling each palm. This knowledge is used to derive an unbiased estimate of the biologically relevant probability of palm infestation. We combine maximum-likelihood analysis and information-theoretic model selection to test the relationships between environmental covariates and infestation of 298 Amazonian palm trees over three spatial scales: region within Amazonia, landscape, and individual palm. Palm infestation estimates are high (40-60%) across regions, and well above the observed infestation rate (24%). Detection probability is higher ( approximately 0.55 on average) in the richest-soil region than elsewhere ( approximately 0.08). Infestation estimates are similar in forest and rural areas, but lower in urban landscapes. Finally, individual palm covariates (accumulated organic matter and stem height) explain most of infestation rate variation.
CONCLUSIONS/SIGNIFICANCE: Individual palm attributes appear as key drivers of infestation, suggesting that CD surveillance must incorporate local-scale knowledge and that peridomestic palm tree management might help lower transmission risk. Vector populations are probably denser in rich-soil sub-regions, where CD prevalence tends to be higher; this suggests a target for research on broad-scale risk mapping. Landscape-scale effects indicate that palm triatomine populations can endure deforestation in rural areas, but become rarer in heavily disturbed urban settings. Our methodological approach has wide application in infectious disease research; by improving eco-epidemiological parameter estimation, it can also significantly strengthen vector surveillance-control strategies.
未能在实际发生疾病的地方检测到病原体或媒介构成了流行病学中的一个严重缺陷。在采样技术并不完美的普遍情况下，明确分析检测失败成为估计流行病学参数的关键步骤。我们用一项关于 Attalea 棕榈树被 Rhodnius spp.（Triatominae）感染的研究来说明这种方法，Rhodnius spp. 是南美洲北部恰加斯病（CD）最重要的传播媒介。
方法/主要发现：通过反复对每棵棕榈树进行采样，估计在受感染的棕榈树上检测到三锥虫的概率。这一知识被用于推导出对棕榈树受感染的生物学相关概率的无偏估计。我们结合最大似然分析和信息论模型选择，测试了环境协变量与 298 棵亚马逊棕榈树的感染之间的关系，涉及三个空间尺度：亚马逊地区内、景观和个体棕榈树。在整个地区，棕榈树的感染率估计值很高（40-60%），远远高于观察到的感染率（24%）。在土壤最肥沃的地区，检测概率较高（平均约为 0.55），而其他地区则较低（平均约为 0.08）。森林和农村地区的感染估计值相似，但城市景观中的感染估计值较低。最后，个体棕榈树的属性（积累的有机物和茎干高度）解释了感染率变化的大部分。
结论/意义：个体棕榈树的属性似乎是感染的关键驱动因素，这表明 CD 监测必须纳入地方尺度的知识，并且家庭周围棕榈树的管理可能有助于降低传播风险。在土壤肥沃的亚区，媒介种群可能更密集，而那里的 CD 流行率往往更高；这表明需要研究大范围的风险制图。景观尺度的影响表明，棕榈树三锥虫种群可以在农村地区的森林砍伐中生存下来，但在受严重干扰的城市环境中变得更为罕见。我们的方法在传染病研究中有广泛的应用；通过改进生态流行病学参数估计，它还可以显著加强媒介监测控制策略。
