Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.遥感技术可为受环境因素驱动的疾病提供早期预警支持，例如洪水可诱发钩端螺旋体病（leptospirosis）。本研究以钩端螺旋体病为案例研究对象，评估在柬埔寨境内，是否存在可用于研究已明确将洪水作为重要传播驱动因素的疾病的遥感洪水指标，以及具体可选用哪些此类指标。研究通过地面验证（ground truthing）对六种潜在洪水指标的性能进行了评估。修正归一化差异水体指数（Modified Normalized Difference Water Index, MNDWI）被用于估算暴露于其检测到的洪水环境时，感染钩端螺旋体病的风险比（Risk Ratio, RR），尤其在雨季期间。同时还开展了卡方（Chi-square）检验。研究还基于MNDWI值构建了另一项解释变量——当年首次发生洪水后的时长，并将其与其他解释变量一同纳入钩端螺旋体病感染的广义线性模型（Generalized Linear Model, GLM）与提升回归树模型（Boosted Regression Tree Model, BRT）中。值得注意的是，用于检测水体以及预测钩端螺旋体病血清转换风险的MNDWI阈值被独立确定为-0.3。当MNDWI值大于-0.3时，与钩端螺旋体病感染存在显著相关性（RR=1.61，95%置信区间[1.10–1.52]；χ²=5.64，p值=0.02），且在雨季期间该相关性更为显著（RR=2.03，95%置信区间[1.25–3.28]；χ²=8.15，p值=0.004）。当年首次洪水发生后的时长在广义线性模型中被证实为显著的风险因素（p值=0.042）。上述结果表明，MNDWI可作为早期预警遥感工具中的风险指标，用于东南亚地区以洪水为传播驱动因素的疾病（如钩端螺旋体病）的早期预警。