Grupo de investigación en Biología Matemática y Computacional (BIOMAC), Departamento de Ingeniería Biomédica, Universidad de los Andes, Bogotá, Colombia.
Corporación colombiana de investigación agropecuaria, AGROSAVIA, Bogotá, Colombia.
PLoS Negl Trop Dis. 2023 Feb 6;17(2):e0011117. doi: 10.1371/journal.pntd.0011117. eCollection 2023 Feb.
Snakebite envenoming is a neglected tropical disease affecting deprived populations, and its burden is underestimated in some regions where patients prefer using traditional medicine, case reporting systems are deficient, or health systems are inaccessible to at-risk populations. Thus, the development of strategies to optimize disease management is a major challenge. We propose a framework that can be used to estimate total snakebite incidence at a fine political scale.
METHODOLOGY/PRINCIPAL FINDINGS: First, we generated fine-scale snakebite risk maps based on the distribution of venomous snakes in Colombia. We then used a generalized mixed-effect model that estimates total snakebite incidence based on risk maps, poverty, and travel time to the nearest medical center. Finally, we calibrated our model with snakebite data in Colombia from 2010 to 2019 using the Markov-chain-Monte-Carlo algorithm. Our results suggest that 10.19% of total snakebite cases (532.26 yearly envenomings) are not reported and these snakebite victims do not seek medical attention, and that populations in the Orinoco and Amazonian regions are the most at-risk and show the highest percentage of underreporting. We also found that variables such as precipitation of the driest month and mean temperature of the warmest quarter influences the suitability of environments for venomous snakes rather than absolute temperature or rainfall.
CONCLUSIONS/SIGNIFICANCE: Our framework permits snakebite underreporting to be estimated using data on snakebite incidence and surveillance, presence locations for the most medically significant venomous snake species, and openly available information on population size, poverty, climate, land cover, roads, and the locations of medical centers. Thus, our algorithm could be used in other countries to estimate total snakebite incidence and improve disease management strategies; however, this framework does not serve as a replacement for a surveillance system, which should be made a priority in countries facing similar public health challenges.
蛇伤中毒是一种被忽视的热带病，影响贫困人群，在一些地区，由于患者更倾向于使用传统医学、病例报告系统不足或高危人群无法获得卫生系统，其负担被低估。因此，制定优化疾病管理的策略是一项重大挑战。我们提出了一个可以用于在精细政治尺度上估计蛇伤总发病率的框架。
方法/主要发现：首先，我们根据哥伦比亚毒蛇的分布生成了精细尺度的蛇伤风险图。然后，我们使用广义混合效应模型，根据风险图、贫困程度和到最近医疗中心的旅行时间来估计总蛇伤发病率。最后，我们使用马尔可夫链-蒙特卡罗算法用 2010 年至 2019 年哥伦比亚的蛇伤数据对我们的模型进行校准。我们的结果表明，10.19%的蛇伤病例（每年 532.26 例中毒）未报告，这些蛇伤受害者没有寻求医疗救治，而奥里诺科和亚马逊地区的人口是最危险的，报告率最低。我们还发现，最具医学意义的毒蛇物种的存在位置、蛇伤发病率和监测数据、人口规模、贫困程度、气候、土地覆盖、道路以及医疗中心的位置等变量，影响着适合毒蛇生存的环境，而不是绝对温度或降雨量。
结论/意义：我们的框架允许使用蛇伤发病率和监测数据、最具医学意义的毒蛇物种的存在位置以及人口规模、贫困程度、气候、土地覆盖、道路和医疗中心位置等公开信息来估计蛇伤漏报率。因此，我们的算法可以在其他国家用于估计总蛇伤发病率，并改进疾病管理策略；然而，该框架不能替代监测系统，而监测系统应成为面临类似公共卫生挑战的国家的优先事项。
