Comparison of GARP and Maxent in modelling the geographic distribution of Bacillus anthracis in Zimbabwe

A number of presence-only models can be used in the prediction of the geographic distribution of diseases and/or their vectors. The predictive performance of these models differs depending on a number of factors but primarily the modeled species’ ecological traits. In this study, the performance of GARP and Maxent, two of the most commonly used modelling methods were compared in predicting presence and absence of anthrax in Zimbabwe using accuracy, sensitivity, specificity, Kappa statistic and the Jaccard coefficient as measures of model performance. The results showed that GARP had higher accuracy than Maxent (GARP = 0.70, Maxent = 0.67). Both methods had equal sensitivity (sensitivity = 0.71), but GARP had higher specificity (GARP=0.70, Maxent=0.67). Both Kappa and the Jaccard coefficient were also higher for GARP (0.335; 0.36) than for Maxent (0.295; 0.34). The results imply that GARP has superior performance over Maxent and is recommended for modelling species habitat suitability.Keywords: ENMs, GARP, Maxent, Anthra

Modelling climate change impacts on the spatial distribution of anthrax in Zimbabwe

Abstract Background In Zimbabwe, anthrax is endemic with outbreaks being reported almost annually in livestock, wildlife, and humans over the past 40 years. Accurate modelling of its spatial distribution is key in formulating effective control strategies. In this study, an Ensemble Species Distribution Model was used to model the current and future distribution of anthrax occurrence in Zimbabwe. Methods Bioclimatic variables derived from the Beijing Climate Centre Climate System Model were used to model the disease. Collinearity testing was conducted on the 19 bioclimatic variables and elevation to remove redundancy. Variables that had no collinearity were used for anthrax habitat suitability modelling. Two future climate change scenarios for different Representative Concentration Pathways (RCP), RCP4.5 and RCP8.5 were used. Model evaluation was done using true skill, Kappa statistics and receiver operating characteristics. Results The results showed that under current bioclimatic conditions, eastern and western districts of Zimbabwe were modelled as highly suitable, central districts moderately suitable and southern parts marginally suitable for anthrax occurrence. Future predictions demonstrated that the suitable (8%) and highly suitable (7%) areas for anthrax occurrence would increase under RCP4.5 scenario. In contrast, a respective decrease (11%) and marginal increase (0.6%) of suitable and highly suitable areas for anthrax occurrence were predicted under the RCP8.5 scenario. The percentage contribution of the predictors varied for the different scenarios; Bio6 and Bio18 for the current scenario, Bio2, Bio4 and Bio9 for the RCP4.5 and Bio3 and Bio15 for the RCP8.5 scenarios. Conclusions The study revealed that areas currently suitable for anthrax should be targeted for surveillance and prevention. The predicted future anthrax distribution can be used to guide and prioritise surveillance and control activities and optimise allocation of limited resources. In the marginally to moderately suitable areas, effective disease surveillance systems and awareness need to be put in place for early detection of outbreaks. Targeted vaccinations and other control measures including collaborative ‘One Health’ strategies need to be implemented in the predicted highly suitable areas. In the southern part where a high decrease in suitability was predicted, continued monitoring would be necessary to detect incursions early

A study on the prevalence of dog erythrocyte antigen 1.1 and detection of canine Babesia by polymerase chain reaction from apparently healthy dogs in a selected rural community in Zimbabwe

A study was carried out to determine the prevalence of blood group antigen dog erythrocyte antigen (DEA) 1.1 in mixed breed dogs in rural Chinamhora, Zimbabwe. DEA 1.1 is clinically the most important canine blood group as it is the most antigenic blood type; hence, DEA 1.1 antibodies are capable of causing acute haemolytic, potentially life-threatening transfusion reactions. In this study, blood samples were collected from 100 dogs in Chinamhora, and blood typing was carried out using standardised DEA 1.1 typing strips with monoclonal anti–DEA 1.1 antibodies (Alvedia® LAB DEA 1.1 test kits). Polymerase chain reaction for detecting Babesia spp. antigen was carried out on 58 of the samples. Of the 100 dogs, 78% were DEA 1.1 positive and 22% were DEA 1.1 negative. A significantly (p = 0.02) higher proportion of females (90.5%) were DEA 1.1 positive than males (69.0%). The probability of sensitisation of recipient dogs following first-time transfusion of untyped or unmatched blood was 17.2%, and an approximately 3% (2.95%) probability of an acute haemolytic reaction following a second incompatible transfusion was found. Babesia spp. antigen was found in 6.9% of the samples. No significant relationship (χ2 = 0.56, p = 0.45) was found between DEA 1.1 positivity and Babesia spp. antigen presence. Despite a low probability of haemolysis after a second incompatibility transfusion, the risk remains present and should not be ignored. Hence, where possible, blood typing for DEA 1.1 is recommended. A survey of DEA 3, 4, 5 and 7 in various breeds is also recommended