Introduction

Passive surveillance systems are thought to under-estimate the true incidence of American cutaneous leishmaniasis (ACL) by two- to five-fold. Ecological niche models based on remotely sensed data can identify environmental factors which favor phlebotomine vectors. Here we report an integrated approach to identifying areas at risk of cutaneous leishmaniasis by applying spatial analysis methods to niche model results, and local surveillance data, in two locations in Colombia with differing vector ecology. The objective was to identify townships in which later phases of the project could implement community-based surveillance to obtain direct estimates of under-reporting.

Materials and methods

The study was carried out in one municipality in each of two departments of the Andean region of Colombia: Pueblo Rico in Risaralda, and Rovira in Tolima. Niche mapping by maximum entropy, based on published and unpublished existing locations of Pintomyia (Pifanomyia) longiflocosa and Psychodopygus panamensis, and using variables on land cover, climate and elevation. Field catches were done in each municipality to test predictions of high relative probability of presence. The niche model results were included as a predictor in a conditional autoregressive spatial model, in which the outcome variable was the number of cases by township, as detected by passive surveillance.

Results

Having rarefied 173 geolocated records, 46 of Pi. longiflocosa and 57 of Ps. panamensis were used for the niche modelling. At the national level, both species had high relative probability of presence on parts of the slopes of the three Andean cordilleras. Pi. longiflocosa also has a high relative probability of presence in the higher parts of the Magdalena valley, as does Ps. panamensis in some areas close to the Caribbean coast. At the local level, field catches confirmed that Pi. longiflocosa was the most abundant species in Rovira, and likewise Ps. panamensis in Pueblo Rico. The spatial regression showed that the incidence of ACL, according to surveillance, was positively, but not statistically significantly, associated with the relative probability of presence from the risk model.

Conclusions

These niche maps bring together published and unpublished results on phlebotomine species which are important vectors in Colombia. Maps of the fitted values of incidence were used to guide the selection of townships in which further phases of the study will attempt to quantify the extent of under-estimation of ACL incidence.

中文翻译：

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整合白血球碱生态位模型和皮肤利什曼病监测数据绘图，以确定存在低估风险的区域

 介绍

人们认为被动监测系统低估了美国皮肤利什曼病 (ACL) 的真实发病率两到五倍。基于遥感数据的生态位模型可以识别有利于白蛇毒载体的环境因素。在这里，我们报告了一种综合方法，通过将空间分析方法应用于哥伦比亚两个具有不同媒介生态的地点的生态位模型结果和当地监测数据，来识别皮肤利什曼病风险区域。目标是确定项目后期可以实施基于社区的监测的乡镇，以获得漏报情况的直接估计。

 材料和方法

这项研究是在哥伦比亚安第斯地区两个省的一个市镇进行的：里萨拉尔达的普韦布洛里科和托利马的罗维拉。根据已发表和未发表的Pintomyia ( Pifanomyia ) longiflocosa和Psychodopygus panamensis的现有位置，并使用土地覆盖、气候和海拔等变量，通过最大熵进行生态位映射。在每个城市进行了实地捕获，以测试对存在的高相对概率的预测。生态位模型结果被作为条件自回归空间模型的预测因子，其中结果变量是通过被动监测检测到的乡镇病例数。

 结果

已稀有 173 条地理定位记录，其中 46 条为Pi。 longiflocosa和诗篇 57 篇。巴拿马用于利基建模。在国家层面上，这两个物种在三个安第斯山脉的部分斜坡上存在的相对概率较高。圆周率。 longiflocosa也有较高的相对概率存在于马格达莱纳山谷的较高地区， Ps 也是如此。巴拿马在靠近加勒比海岸的一些地区。在当地，现场捕获证实了Pi。 longiflocosa是罗维拉最丰富的物种， Ps.同样如此。普韦布洛里科的巴拿马。空间回归显示，根据监测，ACL 的发生率与风险模型中存在的相对概率呈正相关，但没有统计学意义。

 结论

这些生态位图汇集了已发表和未发表的白荠属物种的结果，白苓属是哥伦比亚的重要载体。发病率拟合值地图用于指导乡镇的选择，研究的进一步阶段将尝试量化 ACL 发病率低估的程度。