Geospatial modelling and univariate analysis of commensal rodent-borne cestodoses: the case of invasive spp. of Rattus and indigenous Mastomys coucha from South Africa

• Published in: Frontiers in Veterinary Science
• Main Authors: Julius, R.S., Zengeya, T.A., Schwan, E.V., Chimimba, C.T.
• Format: Other/Unknown Material
• Language: unknown
• Published: 2021
• Subjects: ecological niche modelling; Hymenolepis diminuta; Hymenolepis nana; inermicapsifer madagascariensis; parasites; invasive; indigenous murid rodents; species distribution models; South Africa; Rattus rattus
• Online Access: http://hdl.handle.net/10019.1/111873

Poor socio-economic and unsanitary conditions are conducive to commensal rodent infestations, and these conditions are widespread in South Africa. Cestode species of zoonotic interest are highly prevalent in commensal rodents, such as invasive Rattus norvegicus, Rattus rattus, Rattus tanezumi, and indigenous Mastomys coucha, and have been frequently recovered from human stool samples. These cestode species have similar transmission dynamics to traditional soil-transmitted helminths (STHs), which ties them to infections associated with poverty and poor sanitation. Univariate analysis was used in the present study to determine the association between rodent-related factors and cestode prevalence, while ecological niche modelling was used to infer the potential distribution of the cestode species in South Africa. Cestode prevalence was found to be associated with older rodents, but it was not significantly associated with sex, and ectoparasite presence. The predicted occurrence for rodent-borne cestodes predominantly coincided with large human settlements, typically associated with significant anthropogenic changes. In addition, cestode parasite occurrence was predicted to include areas both inland and along the coast. This is possibly related to the commensal behaviour of the rodent hosts. The study highlights the rodent-related factors associated with the prevalence of parasites in the host community, as well as the environmental variables associated with parasite infective stages that influence host exposure. The application of geospatial modelling together with univariate analysis to predict and explain rodent-borne parasite prevalence may be useful to inform management strategies for targeted interventions.