Prevalence of Listeria monocytogenes in milk in Africa: a generalized logistic mixed-effects and meta-regression modelling.

Listeria outbreaks and food recalls is on the raise globally. Milk particularly is highly susceptible to Listeria as its production and storage adequately support Listeria growth. The extent of milk contamination with Listeria monocytogenes (Lm) and preventative actions to halt milk associated outbreaks in Africa are unknown. Hence, this study aimed at assessing the national and subregional prevalence of Lm in milk in Africa and identify impacting factors via generalized logistic mixed-effects (GLMEs) and meta-regression modelling. Lm-milk-specific data acquired from primary studies according to standard protocol were fitted using a GLMEs. The GLMEs was subjected to leave-one-study-out-cross-validation (LOSOCV). Factors impacting Lm prevalence in milk were assayed via a 1000-permutation-assisted meta-regression-modelling. The pooled prevalence of Lm in milk in Africa was 4.35% [2.73-6.86] with a prediction interval (PI) of 0.14-59.86% and LOSOCV value of 2.43% [1.62-3.62; PI: 0.32-16.11%]. Western Africa had the highest prevalence [20.13%, 4.13-59.59], then Southern Africa [5.85%, 0.12-75.72], Northern Africa [4.67%, 2.82-7.64], Eastern Africa [1.91%, 0.64-5.55], and there was no record from Central Africa. In term of country, Lm prevalence in milk significantly (p < 0.01) varied from 0.00 to 90.00%. Whereas the Lm prevalence was negligibly different (p = 0.77) by milk type, raw-milk had the highest prevalence [5.26%], followed by fermented-milk [4.76%], boiled-milk [2.90%], pasteurized-milk [1.64%], and powdered-milk [1.58%]. DNA extraction approach did not significantly (p = 0.07) affect Lm prevalence (Boiling [7.82%] versus Kit [7.24%]) as well as Lm detection method (p = 0.10; (ACP [3.64%] vs. CP [8.92%] vs. CS [2.27%] vs. CSP [6.82%]). Though a bivariate/multivariate combination of all tested variables in meta-regression explained 19.68-68.75% (R) variance in Lm prevalence in milk, N, nation, and subregion singly/robustly accounted for 17.61% (F = 7.5994; p = 0.005), 63.89% (F = 4.2028; p = 0.001), and 16.54% (F = 3.4743; p = 0.026), respectively. In conclusion, it is recommended that adequate sample size should be prioritized in monitoring Lm in milk to prevent spuriously high or low prevalence to ensure robust, plausible, and credible estimate. Also, national efforts/interests and commitments to Lm monitoring should be awaken.