3.3.7 Data analysis
Flea data were recorded in Microsoft Excel 2016 and prepared in a
readable data set format, data set were imported in R programming
language (R Core Team version 4.2.2 of 2022) from which all statistical
analyses were conducted with a significance level (α) of 0.05. Data were
tested for normality before analyzed and were found not normally
distributed (Shapiro-Wilk test p <.05) leading us to use
non-parametric test for inferential statistics. Rodent’s flea load on
examined rodents were evaluated by assessing total flea indices and
specific flea indices (Zimba et al ., 2012). Percentage prevalence
of rodents infested with fleas (proportion of examined rodents positive
for fleas) were computed with 95 % confidence interval for proportion
and multiplied by 100%.
Chi-square χ2 test of association was applied to
examine the relationship of abundance of species of fleas with rodent
species, plague and non-plague foci villages, season, habitat type and
rodent sex. The nature of association was further analyzed to find the
contribution of level of factors to the Chi-square result using absolute
standardized residuals and the relationship were presented in balloon
chart (Kassambara, 2022). Flea biased parasitism on rodent’s sex and
weight was analyzed by assessing the variation of flea abundance between
sexes using Wilcoxon rank sum test and through evaluation of correlation
between flea abundance and rodent’s weigh using Spearman rank
correlation test (rho) respectively; these factors were further analyzed
in generalized linear model (GLM) to assess their influence on flea
abundance. The GLM was used to establish the model variables that
described the influence of predictors of abundance of flea. Model was
selected based on AIC in which model with possible lowest AIC was
selected with help of step-AIC function in MASS package of R programming
language (Venables and Ripley, 2002). Predictor variables were both
numerical and categorical variables that include, host characteristics
(rodent species, sex and weight), habitats, season and plague locations.