Fig. 4: Longitudinal analysis of malaria parasitism in the Kanyawara cohort of wild chimpanzees. | Communications Biology

Fig. 4: Longitudinal analysis of malaria parasitism in the Kanyawara cohort of wild chimpanzees.

From: The ecology and epidemiology of malaria parasitism in wild chimpanzee reservoirs

Fig. 4

a The proportion of chimpanzee fecal samples (N = 878) that tested positive for malaria parasites varied by month of sampling (dashed line corresponds to dataset mean). Bar length corresponds to proportion of samples that tested positive during a given month of sampling (monthly mean is listed in parentheses). Samples collected between November and May tended to be more likely to test positive for malaria parasites, while samples collected between June and October tended to be less likely. b Demographic variables also influenced infection probability. Samples collected from younger chimpanzees were generally more likely to test positive for malaria parasites than were samples collected from older chimpanzees. This result highlights the early age of infection onset (including the youngest sample in the dataset, collected from a 3-month-old female), indicative of a high magnitude of ongoing transmission. Despite this observation, a subset of chimpanzees (e.g., NT) deviated from this trend, potentially indicative of resistance to infection. c Predicted infection probabilities, derived from the Kanyawara GLMM (Table 2), demonstrate that seasonality of infection is partially driven by variation in mean ambient temperature. Mean ambient temperature (measured directly via weather monitoring stations) was positively correlated with infection probability across the range of temperature values observed at this sampling site (20.0–23.0 °C; p < 0.0001). Raw data (binary) are plotted as dots and stratified vertically for visualization. d Infection probabilities predicted by the Kanyawara GLMM also demonstrated that the youngest study subjects tended to be the most likely to test positive for malaria parasites (p < 0.0001). Raw data (binary) are plotted as dots and stratified vertically for visualization.

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