MRC Centre for Global Infectious Disease Analysis, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom.
PLoS Comput Biol. 2021 Feb 16;17(2):e1008658. doi: 10.1371/journal.pcbi.1008658. eCollection 2021 Feb.
During sporogony, malaria-causing parasites infect a mosquito, reproduce and migrate to the mosquito salivary glands where they can be transmitted the next time blood feeding occurs. The time required for sporogony, known as the extrinsic incubation period (EIP), is an important determinant of malaria transmission intensity. The EIP is typically estimated as the time for a given percentile, x, of infected mosquitoes to develop salivary gland sporozoites (the infectious parasite life stage), which is denoted by EIPx. Many mechanisms, however, affect the observed sporozoite prevalence including the human-to-mosquito transmission probability and possibly differences in mosquito mortality according to infection status. To account for these various mechanisms, we present a mechanistic mathematical model, which explicitly models key processes at the parasite, mosquito and observational scales. Fitting this model to experimental data, we find greater variation in the EIP than previously thought: we estimated the range between EIP10 and EIP90 (at 27°C) as 4.5 days compared to 0.9 days using existing statistical methods. This pattern holds over the range of study temperatures included in the dataset. Increasing temperature from 21°C to 34°C decreased the EIP50 from 16.1 to 8.8 days. Our work highlights the importance of mechanistic modelling of sporogony to (1) improve estimates of malaria transmission under different environmental conditions or disease control programs and (2) evaluate novel interventions that target the mosquito life stages of the parasite.
在孢子生殖期间，引起疟疾的寄生虫感染蚊子，繁殖并迁移到蚊子的唾液腺，在下一次吸血时可以传播。孢子生殖所需的时间，即外潜伏期（EIP），是疟疾传播强度的一个重要决定因素。EIP 通常被估计为特定百分比，x，的受感染蚊子发育成唾液腺孢子虫（感染性寄生虫生命阶段）的时间，用 EIPx 表示。然而，许多机制会影响观察到的孢子虫流行率，包括人向蚊子的传播概率，以及根据感染状态可能存在的蚊子死亡率差异。为了考虑这些不同的机制，我们提出了一种机制数学模型，该模型明确地在寄生虫、蚊子和观察尺度上建模了关键过程。通过将该模型拟合到实验数据，我们发现 EIP 的变化比以前认为的要大：我们估计在 27°C 下，EIP10 和 EIP90 之间的范围为 4.5 天，而使用现有统计方法为 0.9 天。这种模式在数据集中包含的研究温度范围内保持不变。将温度从 21°C 升高到 34°C，将 EIP50 从 16.1 天降低到 8.8 天。我们的工作强调了对孢子生殖进行机制建模的重要性，以（1）在不同的环境条件或疾病控制计划下改善疟疾传播的估计，以及（2）评估针对寄生虫蚊子生命阶段的新干预措施。
