Background Ticks transmit several diseases that result in high morbidity and mortality in livestock. Tick-borne diseases are an economic burden that negatively affect livestock production, cost countries billions of dollars through vaccine procurement and other disease management efforts. Thus, understanding the spatial distribution of tick hotspots is critical for identifying potential areas of high tick-borne disease transmission and setting up priority areas for targeted tick disease management. In this study, optimised hotspot analysis was applied to detect hotspots and coldspots of 14 common tick species in Zimbabwe. Data on the spatial distribution of tick species were obtained from the Epidemiology Unit of the Division of Veterinary Field Services of Zimbabwe. Results A total of 55,133 ticks were collected with Rhipicephalus decoloratus being the most common species (28.7%), followed by Amblyomma hebraeum (20.6%), and Rhipicephalus sanguineus sensu lato (0.06%) being the least common species. Results also showed that tick hotspots are species-specific with particular tick species occupying defined localities in the country. For instance, Amblyomma variegatum, Rhipicephalus appendiculatus, Rhipicephalus decoloratus, Rhipicephalus compostus, Rhipicephalus microplus, Rhipicephalus pravus, and Rhipicephalus simus were concentrated in the north and north eastern districts of the country. In contrast, Amblyomma hebraeum, Hyalomma rufipes, Hyalomma trancatum and Rhipicephalus evertsi evertsi were prevalent in the southern districts of Zimbabwe. Conclusion The occurrence of broadly similar hotspots of several tick species in different districts suggests presence of spatial overlaps in the niche of the tick species. As ticks are vectors of several tick-borne diseases, there is high likelihood of multiple disease transmission in the same geographic region. This study is the first in Zimbabwe to demonstrate unique spatial patterns in the distribution of several tick species across the country. The results of this study provide an important opportunity for the development of spatially-targeted tick-borne disease management strategies.

Road asset mapping has the potential of reducing: costs in keeping all assets data, time-consuming activities like retrieving asset attribute from large files, risks associated with losing all the data by using Geographic Information Systems (GIS). Traditional road data has been stored in the form of hard copy maps showing the different road infrastructure. The World Wide Web (WWW), has revolutionized the provision, dissemination, and data access to people in different geographical locations. Web-GIS based applications have gained popularity because their low cost, ease of use and availability to a large population – that is anyone with a web-browser. Through browsers, web-GIS based applications can display a map with useful information. The design and development of an interactive web-GIS based digital road infrastructure management tool not only allows users to visualize the road infrastructure content but also help in decision making. It makes use of open source GIS tools, PostgreSQL and PostGIS (to manage spatial and non-spatial data), Geoserver (to connect the database to the client mapping application) and Apache Tomcat (to build and deploy the application). The maps are published through Geoserver with their associated information using JavaScript libraries (Open Layers and Geoext). Further spatial analysis (attribute queries) can be done online. Results show that a web-GIS was developed that manages road asset infrastructure like road signs, bridges, animal grids, rest areas. A user can query precise assets they want to visualize for instance damaged bridges. HoweGIS:here is still need to further improve the application for instance allowing user to put complaints about damaged road assets. Thus, the development of the application will help decision makers as well as other users to utilize the information for the benefit of the country.

This study quantified the spatial and temporal variation of aquatic weeds in two lakes in an urban catchment of Zimbabwe using the automatic water extraction index (AWEI) and normalised difference vegetation index (NDVI) derived from Landsat satellite data from 1986 to 2020. Extent of aquatic weeds estimated using AWEI in Lake Chivero increased from less than 1 km2 (4%) in 1986 to 7 km2 (27%) in 2020. NDVI-based aquatic weed estimation gave the least spatial extent in the first few years. Similarly, in Lake Manyame aquatic weeds occupied ~62 ha (<1% in 1986) before reaching a peak extent of 60 km2 (~70%) in 1995, based on AWEI estimates. NDVI-derived aquatic weed extent ranged from less than 2 km2 in 1997 to a maximum of 56.12 km2 in 1994. Although AWEI and NDVI estimated similar extents, NDVI had higher estimates than AWEI. A non-significant positive trend in aquatic weed extent was detected for Lake Manyame based on AWEI (Mann-Kendal tau = 0.139, s = 69, p = 0.27) and NDVI (Mann-Kendal tau = 0.129, s = 64, p = 0.307). In Lake Chivero, a non-significant negative trend was observed in aquatic weed extent based on NDVI (Mann-Kendal tau = −0.06, s = −30, p = 0.6382), while a positive trend was detected using AWEI (tau = 0.0036, s = 18, p = 0.7827). Results of the regression analysis indicate that phosphorus (R2 = 0.7957, p = 0.00122) and nitrogen (R2 = 0.8992, p = 0.0011) significantly explained variations in aquatic weed infestation in Lake Chivero. These results suggest that phosphorus and nitrogen enrichment are key drivers of aquatic weed proliferation in the two lakes. Thus, sustainable management of water resources in the catchment hinges on reducing the amount of nutrients released into the lakes from sewage treatment plants and croplands.