Foot and mouth disease (FMD) is an important livestock disease impacting mainly intensive production systems. In southern Africa, the FMD virus is maintained in wildlife and its control is therefore complicated. However, FMD control is an important task to allow countries access to lucrative foreign meat market and veterinary services implement drastic control measures on livestock populations living in the periphery of protected areas, negatively impacting local small-scale livestock producers. This study investigated FMD primary outbreak data in Zimbabwe from 1931 to 2016 to describe the spatio-temporal distribution of FMD outbreaks and their potential drivers. The results suggest that: (i) FMD outbreaks were not randomly distributed in space across Zimbabwe but are clustered in the Southeast Lowveld (SEL); (ii) the proximity of protected areas with African buffalos was potentially responsible for primary FMD outbreaks in cattle; (iii) rainfall per se was not associated with FMD outbreaks, but seasons impacted the temporal occurrence of FMD outbreaks across regions; (iv) the frequency of FMD outbreaks increased during periods of major socio-economic and political crisis. The differences between the spatial clusters and other areas in Zimbabwe presenting similar buffalo/cattle interfaces but with fewer FMD outbreaks can be interpreted in light of the recent better understanding of wildlife/livestock interactions in these areas. The types of wildlife/livestock interfaces are hypothesized to be the key drivers of contacts between wildlife and livestock, triggering a risk of FMD inter-species spillover. The management of wildlife/livestock interfaces is therefore crucial for the control of FMD in southern Africa.

Background: Studies have linked bats to outbreaks of viral diseases in human populations such as SARS-CoV-1 and MERS-CoV and the ongoing SARS-CoV-2 pandemic. Methods: We carried out a longitudinal survey from August 2020 to July 2021 at two sites in Zimbabwe with bat–human interactions: Magweto cave and Chirundu farm. A total of 1732 and 1866 individual bat fecal samples were collected, respectively. Coronaviruses and bat species were amplified using PCR systems. Results: Analysis of the coronavirus sequences revealed a high genetic diversity, and we identified different sub-viral groups in the Alphacoronavirus and Betacoronavirus genus. The established sub-viral groups fell within the described Alphacoronavirus sub-genera: Decacovirus, Duvinacovirus, Rhinacovirus, Setracovirus and Minunacovirus and for Betacoronavirus sub-genera: Sarbecoviruses, Merbecovirus and Hibecovirus. Our results showed an overall proportion for CoV positive PCR tests of 23.7% at Chirundu site and 16.5% and 38.9% at Magweto site for insectivorous bats and Macronycteris gigas, respectively. Conclusions: The higher risk of bat coronavirus exposure for humans was found in December to March in relation to higher viral shedding peaks of coronaviruses in the parturition, lactation and weaning months of the bat populations at both sites. We also highlight the need to further document viral infectious risk in human/domestic animal populations surrounding bat habitats in Zimbabwe.

Background: Glossina austeniandGlossina brevipalpis(Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique.Methodology/Principal findings: The present study used existing entomological survey data ofG.austeniandG.brevipalpisto develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species).Conclusions/Significance: The models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area.

Tsetse flies are the cyclic vectors of sleeping sickness and African animal trypanosomosis. The possibility to classify the natural habitat of riverine tsetse species is explored in the Mouhoun River basin, Burkina Faso: the objectives were to discriminate the riverine forests community types and their fragmentation levels by using Landsat 7 enhanced thematic mapper images, to map tsetse densities. Glossina palpalis gambiensis Vanderplank 1949 (Diptera: Glossinidae) and G. tachinoides Westwood, 1850 are the vectors of trypanosomoses in this area. After a supervised classification, the community types were discriminated using the water area in 400-m-wide polygons around the river. A fragmentation analysis of the swamp forest unit, cross-tabulated with the community types, lead to identification of the final landscapes where tsetse apparent densities (ADT) were implemented using a training data set of 608 trap locations. The predicted ADT were then compared with an independent validation data set of 78 trap locations. The correlation between the model predictions and the validation data set was high, validating this approach (P < 0.001). The riverine forest community type and fragmentation level are critical factors for riverine tsetse species, which should be taken into consideration to map their suitable habitat.

Landscape attributes driving avian influenza virus circulation in the Lake Alaotra region of Madagascar

Tsetse (Glossina sensu stricto) are cyclical vectors of human and animal trypanosomoses, that are presently targeted by the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) coordinated by the African Union. In order to achieve effective control of tsetse, there is need to produce elaborate plans to guide intervention programmes. A model intended to aid in the planning of intervention programmes and assist a fuller understanding of tsetse distribution was applied, in a pilot study in the Masoka area, Mid-Zambezi valley in Zimbabwe, and targeting two savannah species, Glossina morsitans morsitans and Glossina pallidipes. The field study was conducted between March and December 2015 in 105 sites following a standardized grid sampling frame. Presence data were used to study habitat suitability of both species based on climatic and environmental data derived from MODIS and SPOT 5 satellite images. Factors influencing distribution were studied using an Ecological Niche Factor Analysis (ENFA) whilst habitat suitability was predicted using a Maximum Entropy (MaxEnt) model at a spatial resolution of 250 m. Area Under the Curve (AUC), an indicator of model performance, was 0.89 for G. m. morsitans and 0.96 for G. pallidipes. We then used the predicted suitable areas to calculate the probability that flies were really absent from the grid cells where they were not captured during the study based on a probability model using a risk threshold of 0.05. Apart from grid cells where G. m. morsitans and G. pallidipes were captured, there was a high probability of presence in an additional 128 km² and 144 km² respectively. The modelling process promised to be useful in optimizing the outputs of presence/absence surveys, allowing the definition of tsetse infested areas with improved accuracy. The methodology proposed here can be extended to all the tsetse infested parts of Zimbabwe and may also be useful for other PATTEC national initiatives in other African countries. Tse-tse flies are vectors of human and animal trypanosomoses, that are presently targeted by the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) coordinated by the African Union. In Zimbabwe, the government has devoted a full section of the veterinary services to tsetse and trypanosomosis control but the delimitation of tsetse infested areas, which is a pre-requisite to achieve effective control still requires improvement. Here we present a methodology that could help delimit target areas throughout the country, in a pilot study area located in the Masoka area, Mid-Zambezi valley in Zimbabwe, and targeting two savannah species, Glossina morsitans morsitans and Glossina pallidipes. The study, which was carried out in preparation for a vector control campaign, allowed to discriminate areas where tsetse presence was certain, likely or unlikely Habitat degradation due to agricultural activities seemed to play a pivotal role in determining the infestation by tsetse since settled areas had low probabilities for both species which was expected in this group. Application of this model will help reduce the cost of delineating tsetse infested areas in other parts of Zimbabwe and may also be useful for other PATTEC national initiatives in other African countries at a time when funding for tsetse control programmes is reduced.