Leptospirosis in American Samoa--estimating and mapping risk using environmental data.
Leptospirosis in American Samoa--estimating and mapping risk using environmental data.
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DOI：
10.1371/journal.pntd.0001669
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发表时间：
2012
影响因子：
3.8
通讯作者：
Weinstein P
中科院分区：
文献类型：
--
作者：
Lau CL;Clements AC;Skelly C;Dobson AJ;Smythe LD;Weinstein P
最近出现的钩端螺旋体病与疾病传播的许多环境驱动因素有关。由于诊断不足、实验室能力差和监测不足，缺乏准确的流行病学数据。已经为许多疾病制作了预测性风险图，以确定感染的高风险地区，并指导公共卫生资源的分配，在疾病监测不力的情况下尤其有用。到目前为止，还没有制作出钩端螺旋体病的预测性风险地图。这项研究的目的是根据环境因素估计地理位置的钩端螺旋体病血清阳性率，制作美属萨摩亚的预测性疾病风险地图，并评估地图在预测感染风险方面的准确性。有关血清阳性率和危险因素的数据来自最近在美属萨摩亚进行的一项钩端螺旋体病研究。有关环境变量的数据来自当地来源，包括降雨量、海拔、植被、土壤类型和后院养猪场的位置。采用多变量Logistic回归分析血清阳性与危险因素之间的关系。使用多变量模型，根据环境变量预测地理位置的血清阳性率。模型的拟合优度用受试者操作特征曲线下的面积和正确归类为血清阳性的病例的百分比来衡量。血清感染率的环境预测因素包括居住在村庄、农业区、粘土土壤中的中等海拔以下，以及房屋上方较高密度的养猪场。模型具有可接受的拟合度，并正确分类了84%的∼病例。环境变量可以用来确定钩端螺旋体病的高危地区。环境监测可能是钩端螺旋体病控制的一项有价值的战略，并使我们能够从疾病监测转向环境健康危害监测，作为指导公共卫生干预的更具成本效益的工具。钩端螺旋体病是最常见的从动物传播给人类的细菌感染。受感染的动物在尿液中排泄细菌，人类可能通过接触动物或受污染的环境(如水和土壤)而感染。环境因素在决定人类感染风险方面很重要，并且在不同的生态环境中有所不同。广泛的风险因素包括高降雨量和洪水；恶劣的卫生和个人卫生；城市化和过度拥挤；接触动物(包括啮齿动物、牲畜、宠物和野生动物)；户外娱乐和生态旅游；以及环境退化。已经为许多传染病制作了预测性风险图，以确定传播的高风险地区，并指导公共卫生资源的分配。在疾病监测和流行病学数据不佳的情况下，地图特别有用。这项研究的目的是根据环境因素估计地理位置的钩端螺旋体病血清阳性率，制作美属萨摩亚的预测性疾病风险地图，并评估地图在预测感染风险方面的准确性。这项研究证明了地理信息系统和疾病地图在确定钩端螺旋体病的环境危险因素和加强我们对疾病传播的了解方面的价值。类似的原则也可用于调查其他地区的钩端螺旋体病的流行病学。
The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ∼84% of cases. Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions. Leptospirosis is the most common bacterial infection transmitted from animals to humans. Infected animals excrete the bacteria in their urine, and humans can become infected through contact with animals or a contaminated environment such as water and soil. Environmental factors are important in determining the risk of human infection, and differ between ecological settings. The wide range of risk factors include high rainfall and flooding; poor sanitation and hygiene; urbanisation and overcrowding; contact with animals (including rodents, livestock, pets, and wildlife); outdoor recreation and ecotourism; and environmental degradation. Predictive risk maps have been produced for many infectious diseases to identify high-risk areas for transmission and guide allocation of public health resources. Maps are particularly useful where disease surveillance and epidemiological data are poor. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. This study demonstrated the value of geographic information systems and disease mapping for identifying environmental risk factors for leptospirosis, and enhancing our understanding of disease transmission. Similar principles could be used to investigate the epidemiology of leptospirosis in other areas.
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影响因子：
3.8
作者：
Maciel EA;de Carvalho AL;Nascimento SF;de Matos RB;Gouveia EL;Reis MG;Ko AI
通讯作者：
Ko AI
影响因子：
64.8
作者：
Keesing F;Belden LK;Daszak P;Dobson A;Harvell CD;Holt RD;Hudson P;Jolles A;Jones KE;Mitchell CE;Myers SS;Bogich T;Ostfeld RS
通讯作者：
Ostfeld RS
影响因子：
11.8
作者：
Brooker S;Leslie T;Kolaczinski K;Mohsen E;Mehboob N;Saleheen S;Khudonazarov J;Freeman T;Clements A;Rowland M;Kolaczinski J
通讯作者：
Kolaczinski J
影响因子：
11.8
作者：
Katz AR;Buchholz AE;Hinson K;Park SY;Effler PV
通讯作者：
Effler PV
影响因子：
9.6
作者：
Brooker S;Hay SI;Bundy DA
通讯作者：
Bundy DA