Killeen G F, McKenzie F E, Foy B D, Schieffelin C, Billingsley P F, Beier J C
Department of Tropical Medicine, School of Public Health and Tropical Medicine, Center for Infectious Diseases, Tulane University Health Sciences Center, New Orleans, Louisiana 70112-2824, USA.
Am J Trop Med Hyg. 2000 May;62(5):535-44. doi: 10.4269/ajtmh.2000.62.535.
Malaria transmission intensity is modeled from the starting perspective of individual vector mosquitoes and is expressed directly as the entomologic inoculation rate (EIR). The potential of individual mosquitoes to transmit malaria during their lifetime is presented graphically as a function of their feeding cycle length and survival, human biting preferences, and the parasite sporogonic incubation period. The EIR is then calculated as the product of 1) the potential of individual vectors to transmit malaria during their lifetime, 2) vector emergence rate relative to human population size, and 3) the infectiousness of the human population to vectors. Thus, impacts on more than one of these parameters will amplify each other's effects. The EIRs transmitted by the dominant vector species at four malaria-endemic sites from Papua New Guinea, Tanzania, and Nigeria were predicted using field measurements of these characteristics together with human biting rate and human reservoir infectiousness. This model predicted EIRs (+/- SD) that are 1.13 +/- 0.37 (range = 0.84-1.59) times those measured in the field. For these four sites, mosquito emergence rate and lifetime transmission potential were more important determinants of the EIR than human reservoir infectiousness. This model and the input parameters from the four sites allow the potential impacts of various control measures on malaria transmission intensity to be tested under a range of endemic conditions. The model has potential applications for the development and implementation of transmission control measures and for public health education.
疟疾传播强度是从单个媒介蚊子的起始角度进行建模的,并直接表示为昆虫接种率(EIR)。单个蚊子在其生命周期内传播疟疾的潜力以图形方式呈现,是其摄食周期长度、存活率、叮咬人类偏好以及寄生虫孢子增殖潜伏期的函数。然后,EIR通过以下三者的乘积来计算:1)单个媒介在其生命周期内传播疟疾的潜力;2)相对于人口规模的媒介出现率;3)人群对媒介的感染性。因此,对这些参数中不止一个的影响会相互放大彼此的作用。利用对这些特征的实地测量以及人类叮咬率和人类宿主感染性,预测了来自巴布亚新几内亚、坦桑尼亚和尼日利亚的四个疟疾流行地区的主要媒介物种传播的EIR。该模型预测的EIR(±标准差)是实地测量值的1.13±0.37倍(范围 = 0.84 - 1.59)。对于这四个地点,蚊子出现率和生命周期传播潜力是比人类宿主感染性更重要的EIR决定因素。该模型以及来自这四个地点的输入参数使得在一系列流行条件下能够测试各种控制措施对疟疾传播强度的潜在影响。该模型在传播控制措施的制定和实施以及公共卫生教育方面具有潜在应用价值。