Molecular identification of cattle ticks in the Greater Accra Region of Ghana: a high occurrence of Rhipicephalus microplus.

Ticks are competent vectors of a wide range of pathogens. They are of veterinary and public health importance as they affect both animal and human health. Transhumance and the transboundary movements of cattle within the West African Sub-region have facilitated the spread of ticks which threatens the introduction of invasive species. Currently, Rhipicephalus microplus have been identified in the Upper East Region of Ghana which could mean a wider distribution of the species across the country due to livestock trade. This study focused on three sites in the Greater Accra Region, which serves as the gateway to receiving most of the cattle transported from the northern regions of Ghana. Ticks were sampled from August 2022 in the wet season to January 2023 in the dry season. Three tick genera were identified: Amblyomma (19.5%), Hyalomma (1.1%), and Rhipicephalus (79.3%) from the 1,489 feeding ticks collected from cattle. Furthermore, Rhipicephalus microplus, Hyalomma rufipes and Amblyomma variegatum were identified molecularly using primers that target the mitochondrial COI gene. There was a significant association between the tick species and seasons (p < 0.001). Finding R. microplus in this study indicates the extent of the spread of this invasive tick species in Ghana and highlights the need for efficient surveillance systems and control measures within the country.

Predicting the environmental suitability for Anopheles stephensi under the current conditions in Ghana.

Vector-borne diseases emergence, particularly malaria, present a significant public health challenge worldwide. Anophelines are predominant malaria vectors, with varied distribution, and influenced by environment and climate. This study, in Ghana, modelled environmental suitability for Anopheles stephensi, a potential vector that may threaten advances in malaria and vector control. Understanding this vector's distribution and dynamics ensures effective malaria and vector control programmes implementation. We explored the MaxEnt ecological modelling method to forecast An. stephensi's potential hotspots and niches. We analysed environmental and climatic variables to predict spatial distribution and ecological niches of An. stephensi with a spatial resolution of approximately 5 km2. Analysing geospatial and species occurrence data, we identified optimal environmental conditions and important factors for its presence. The model's most important variables guided hotspot prediction across several ecological zones aside from urban and peri-urban regions. Considering the vector's complex bionomics, these areas provide varying and adaptable conditions for the vector to colonise and establish. This is shown by the AUC = 0.943 prediction accuracy of the model, which is considered excellent. Based on our predictions, this vector species would thrive in the Greater Accra, Ashanti Central, Upper East, Northern, and North East regions. Forecasting its environmental suitability by ecological niche modelling supports proactive surveillance and focused malaria management strategies. Public health officials can act to reduce the risk of malaria transmission by identifying areas where mosquitoes may breed, which will ultimately improve health outcomes and disease control.