Simplified binomial estimation of human malaria transmission exposure distributions based on hard classification of where and when mosquitoes are caught: statistical applications with off-the-shelf tools.
Simplified binomial estimation of human malaria transmission exposure distributions based on hard classification of where and when mosquitoes are caught: statistical applications with off-the-shelf tools.
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DOI：
10.1186/s13071-021-04884-2
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发表时间：
2021-08-03
影响因子：
3.2
通讯作者：
Govella NJ
中科院分区：
文献类型：
--
作者：
Killeen GF;Monroe A;Govella NJ
防止接触疟疾病媒和其他蚊媒病原体的个人防护措施的影响和局限性取决于人与蚊子之间的行为相互作用。因此，了解它们在时间和空间上何时何地重叠是至关重要的。计算人类接触分布的行为调整估计值的常用方法故意对人们在何处和何时花费时间进行软分类，以产生整个人口或人口群体中蚊子叮咬平均接触的细微和代表性分布。然而，这些加权平均依赖于汇总个人层面的数据，以获得每个时间增量在相关行为类别中的平均人口分布，因此它们不能用于测试个体之间的差异。此外，这些汇总结果是分解数据的相当复杂的函数，因此它们与常规的现成统计工具可以自信地应用的标准二项或计数分布不匹配。幸运的是，在室内或睡眠时暴露于蚊虫叮咬的比例也可以用简单的二项法来估计，这是基于在给定时间增量内对人类位置的严格分类，即完全在室内或完全在室外。这种简化的二项方法允许使用标准的现成逻辑回归工具进行方便的分析，以统计评估个体人类，人类种群子集或媒介物种之间的差异。这种对人与蚊子之间行为相互作用的简化二项估计应该更广泛地用于估计这些指标均值周围的置信区间，比较不同的病媒种群和人群群体，以及评估个体行为对暴露模式和感染风险的影响。此外，标准样本量估计技术可以很容易地用于估计必要的最小实验规模和现场研究的数据收集目标，将这些指标记录为关键结果。实地研究的样本量计算应考虑到自然地理变化和季节性，利用滚动横断面设计以后勤可行的方式调查和重新调查大量单独的研究地点。在线版本包含补充材料，可在10.1186/s13071-021-04884-2获得。
The impacts and limitations of personal protection measures against exposure to vectors of malaria and other mosquito-borne pathogens depend on behavioural interactions between humans and mosquitoes. Therefore, understanding where and when they overlap in time and space is critical. Commonly used approaches for calculating behaviour-adjusted estimates of human exposure distribution deliberately use soft classification of where and when people spend their time, to yield nuanced and representative distributions of mean exposure to mosquito bites across entire human populations or population groups. However, these weighted averages rely on aggregating individual-level data to obtain mean human population distributions across the relevant behavioural classes for each time increment, so they cannot be used to test for variation between individuals. Also, these summary outcomes are quite complex functions of the disaggregated data, so they do not match the standard binomial or count distributions to which routine off-the-shelf statistical tools may be confidently applied. Fortunately, the proportions of exposure to mosquito bites that occur while indoors or asleep can also be estimated in a simple binomial fashion, based on hard classification of human location over a given time increment, as being either completely indoors or completely outdoors. This simplified binomial approach allows convenient analysis with standard off-the-shelf logistic regression tools, to statistically assess variations between individual humans, human population subsets or vector species. Such simplified binomial estimates of behavioural interactions between humans and mosquitoes should be more widely used for estimating confidence intervals around means of these indicators, comparing different vector populations and human population groups, and assessing the influence of individual behaviour on exposure patterns and infection risk. Also, standard sample size estimation techniques may be readily used to estimate necessary minimum experimental scales and data collection targets for field studies recording these indicators as key outcomes. Sample size calculations for field studies should allow for natural geographic variation and seasonality, taking advantage of rolling cross-sectional designs to survey and re-survey large numbers of separate study locations in a logistically feasible manner. The online version contains supplementary material available at 10.1186/s13071-021-04884-2.
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影响因子：
8.1
作者：
Killeen GF;Marshall JM;Kiware SS;South AB;Tusting LS;Chaki PP;Govella NJ
通讯作者：
Govella NJ
影响因子：
3.3
作者：
Kiware, Samson S.;Chitnis, Nakul;Killeen, Gerry F.
通讯作者：
Killeen, Gerry F.
影响因子：
7.7
作者：
Huho, Bernadette;Briet, Olivier;Killeen, Gerry
通讯作者：
Killeen, Gerry
影响因子：
3
作者：
Monroe, April;Moore, Sarah;Killeen, Gerry F.
通讯作者：
Killeen, Gerry F.
DOI：
10.1093/infdis/jiab004
发表时间：
2021-04-27
期刊：
The Journal of infectious diseases
影响因子：
--
作者：
Hii J;Hustedt J;Bangs MJ
通讯作者：
Bangs MJ