Centre for Health Information Computation and Statistics (CHICAS), Furness Building, Lancaster University, Lancaster, LA1 4YG, UK.
Department of Biochemistry and Immunology, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 30270-901, Brazil.
Parasit Vectors. 2018 Feb 2;11(1):79. doi: 10.1186/s13071-018-2662-6.
Dengue is a vector-borne disease caused by the dengue virus (DENV). Despite the crucial role of Aedes mosquitoes in DENV transmission, pure vector indices poorly correlate with human infections. Therefore there is great need for a better understanding of the spatial and temporal scales of DENV transmission between mosquitoes and humans. Here, we have systematically monitored the circulation of DENV in individual Aedes spp. mosquitoes and human patients from Caratinga, a dengue endemic city in the state of Minas Gerais, in Southeast Brazil. From these data, we have developed a novel stochastic point process pattern algorithm to identify the spatial and temporal association between DENV infected mosquitoes and human patients.
The algorithm comprises of: (i) parameterization of the variogram for the incidence of each DENV serotype in mosquitoes; (ii) identification of the spatial and temporal ranges and variances of DENV incidence in mosquitoes in the proximity of humans infected with dengue; and (iii) analysis of the association between a set of environmental variables and DENV incidence in mosquitoes in the proximity of humans infected with dengue using a spatio-temporal additive, geostatistical linear model.
DENV serotypes 1 and 3 were the most common virus serotypes detected in both mosquitoes and humans. Using the data on each virus serotype separately, our spatio-temporal analyses indicated that infected humans were located in areas with the highest DENV incidence in mosquitoes, when incidence is calculated within 2.5-3 km and 50 days (credible interval 30-70 days) before onset of symptoms in humans. These measurements are in agreement with expected distances covered by mosquitoes and humans and the time for virus incubation. Finally, DENV incidence in mosquitoes found in the vicinity of infected humans correlated well with the low wind speed, higher air temperature and northerly winds that were more likely to favor vector survival and dispersal in Caratinga.
We have proposed a new way of modeling bivariate point pattern on the transmission of arthropod-borne pathogens between vector and host when the location of infection in the latter is known. This strategy avoids some of the strong and unrealistic assumptions made by other point-process models. Regarding virus transmission in Caratinga, our model showed a strong and significant association between high DENV incidence in mosquitoes and the onset of symptoms in humans at specific spatial and temporal windows. Together, our results indicate that vector surveillance must be a priority for dengue control. Nevertheless, localized vector control at distances lower than 2.5 km around premises with infected vectors in densely populated areas are not likely to be effective.
登革热是一种由登革病毒（DENV）引起的虫媒病。尽管埃及伊蚊在 DENV 传播中起着至关重要的作用，但单纯的媒介指数与人类感染的相关性很差。因此，需要更好地了解蚊子和人类之间 DENV 传播的时空尺度。在这里，我们从巴西东南部米纳斯吉拉斯州卡塔林加市的一个登革热流行城市中，对个体埃及伊蚊和人类患者中的 DENV 循环进行了系统监测。从这些数据中，我们开发了一种新的随机点过程模式算法，以确定 DENV 感染蚊子与人类患者之间的时空关联。
该算法包括：（i）为蚊子中每种 DENV 血清型的发病率参数化；（ii）确定在感染登革热的人类附近的蚊子中 DENV 发病率的时空范围和方差；（iii）使用时空附加的地统计线性模型分析与感染登革热的人类附近蚊子中一组环境变量与 DENV 发病率之间的关联。
血清型 1 和 3 是在蚊子和人类中最常见的病毒血清型。单独使用每种病毒血清型的数据，我们的时空分析表明，当在人类症状出现前 2.5-3 公里和 50 天（置信区间 30-70 天）内计算发病率时，感染的人类位于蚊子中 DENV 发病率最高的区域。这些测量结果与蚊子和人类的预期覆盖距离以及病毒潜伏期一致。最后，在感染人类附近发现的蚊子中 DENV 的发病率与低风速、较高的空气温度和北风密切相关，这些因素更有利于在卡塔林加传播媒介的生存和扩散。
我们提出了一种新的方法，用于在后者感染部位已知的情况下，对节肢动物传播病原体在媒介和宿主之间的二元点模式进行建模。这种策略避免了其他点过程模型所做的一些强烈而不现实的假设。关于卡塔林加的病毒传播，我们的模型显示了蚊子中高 DENV 发病率与人类特定时空窗口中症状出现之间的强烈和显著关联。总之，我们的结果表明，必须优先进行媒介监测以控制登革热。然而，在人口稠密地区，距离感染媒介不到 2.5 公里的局部媒介控制不太可能有效。
