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Fig. 4 | Parasites & Vectors

Fig. 4

From: Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

Fig. 4

Multilevel Spearman’s correlation between the vectors’ biting rates and the meteorological variables (as cross-correlation maps). Biting rates were separated into presence/absence of bites (left) and abundance of bites (i.e. positive counts only) (right). Unit of biting rates: number of landings on human/person/night. Unit of meteorological variables: °C for land surface temperatures (LST), cumulative millimeters for rainfall. Meteorological variables were extracted on a weekly scale up to 6 weeks before the dates of collection for each main vector species. In each CCM, time lags are expressed in week(s) before the date of collection. The red-bordered square indicates the time lag interval that showed the highest correlation coefficient (absolute value) with the meteorological variable (the associated time lag interval and correlation coefficient are reported on the top-left corner of the CCM). The black-bordered squares indicate correlations close to the highest observed correlation (i.e. less than 10% of difference). Gray-filled squares indicate correlations with p-value > 0.2 or coefficient > 0.1

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