The prevalence of brucellosis and bovine tuberculosis in ruminants in Sidi Kacem Province, Morocco.

Bovine tuberculosis (BTB) and brucellosis are major endemic zoonoses in ruminants in Morocco that impact on both animal and human health. This study presents an assessment of the epidemiological and socioeconomic burden of bacterial zoonoses in Sidi Kacem Province in Northern Morocco from a cross-sectional survey of 125 cattle and/or small ruminant-owning households. In total, 1082 sheep and goats were examined from 81 households. The single intradermal comparative cervical test to screen for bovine tuberculosis was undertaken on 1194 cattle from 123 households and all cattle were blood sampled. Cattle and small ruminant sera were tested for brucellosis using the standard Rose Bengal Test (sRBT) and the modified Rose Bengal Test (mRBT). Bacteriology was performed on 21 milk samples obtained from cattle that were seropositive for brucellosis for isolation and phenotyping of circulating Brucella strains. Individual and herd prevalence for BTB in cattle of 20.4% (95% CI 18%-23%) and 57.7% (95% CI 48%-66%), respectively, were observed in this study. The prevalence of brucellosis in cattle at individual and herd level was 1.9% (95% CI 1.2%-2.8%) and 9% (95% CI 4.5%-1.5%), respectively. Brucella pathogens were isolated from three cattle milk samples and were identified as B. abortus using Bruceladder® multiplex PCR and B. abortus biovar 1 by classical phenotyping. All small ruminants were seronegative to sRBT, two were positive to mRBT. A higher risk of BTB and brucellosis was observed in cattle in intensive livestock systems, in imported and crossed breeds and in animals from larger herds (>15). The three risk factors were usually present in the same herds, leading to higher transmission risk and persistence of both zoonoses. These results highlight the importance of implementing control strategies for both BTB and brucellosis to reduce productivity losses and the risk of transmission to humans. Prioritising control for BTB and brucellosis in intensive livestock production systems is essential for human and animal health.

Spatial clustering of pathology submissions during the initial introduction and spread of avian influenza H5N1 in poultry in Nigeria in 2006-2007.

Highly pathogenic avian influenza (HPAI) virus H5N1 spread throughout Nigeria between 2006 and 2007. Bird samples collected across the country were submitted through the free-of-charge (FOC) program to the National Veterinary Research Institute, Vom (NVRI-Vom) laboratory. The present article describes the spatial distributions and evaluated clustering of the FOC submissions from poultry farms at the global, local, and focal levels between 2006 and 2007 epidemic in Nigeria. Spatial statistics evaluating clustering of the FOC submissions were implemented using the Moran's I test, the purely spatial cluster analysis with the SaTScan Poisson model, and the Bithell's linear score test. A significant global clustering of the FOC submissions was observed. Significant local clusters of submissions were observed in the North-East, North-Central, and South-West zones. There was significant decline in FOC submissions with increasing distance from NVRI-Vom. These results indicated that the geographic area of influence of the FOC submission program in Nigeria was limited to regions closer to the diagnostic laboratory. This work provides a detailed insight into the surveillance activities during the HPAI outbreaks in Nigeria, and should assist policy-makers and field veterinarians to improve the effectiveness of national eradication plans in the face of any outbreak of animal diseases.

Current and future distribution of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in WHO Eastern Mediterranean Region.

BACKGROUND: Aedes-borne diseases as dengue, zika, chikungunya and yellow fever are an emerging problem worldwide, being transmitted by Aedes aegypti and Aedes albopictus. Lack of up to date information about the distribution of Aedes species hampers surveillance and control. Global databases have been compiled but these did not capture data in the WHO Eastern Mediterranean Region (EMR), and any models built using these datasets fail to identify highly suitable areas where one or both species may occur. The first objective of this study was therefore to update the existing Ae. aegypti (Linnaeus, 1762) and Ae. albopictus (Skuse, 1895) compendia and the second objective was to generate species distribution models targeted to the EMR. A final objective was to engage the WHO points of contacts within the region to provide feedback and hence validate all model outputs. METHODS: The Ae. aegypti and Ae. albopictus compendia provided by Kraemer et al. (Sci Data 2:150035, 2015; Dryad Digit Repos, 2015) were used as starting points. These datasets were extended with more recent species and disease data. In the next step, these sets were filtered using the Köppen-Geiger classification and the Mahalanobis distance. The occurrence data were supplemented with pseudo-absence data as input to Random Forests. The resulting suitability and maximum risk of establishment maps were combined into hard-classified maps per country for expert validation. RESULTS: The EMR datasets consisted of 1995 presence locations for Ae. aegypti and 2868 presence locations for Ae. albopictus. The resulting suitability maps indicated that there exist areas with high suitability and/or maximum risk of establishment for these disease vectors in contrast with previous model output. Precipitation and host availability, expressed as population density and night-time lights, were the most important variables for Ae. aegypti. Host availability was the most important predictor in case of Ae. albopictus. Internal validation was assessed geographically. External validation showed high agreement between the predicted maps and the experts' extensive knowledge of the terrain. CONCLUSION: Maps of distribution and maximum risk of establishment were created for Ae. aegypti and Ae. albopictus for the WHO EMR. These region-specific maps highlighted data gaps and these gaps will be filled using targeted monitoring and surveillance. This will increase the awareness and preparedness of the different countries for Aedes borne diseases.

First study on domestic dog ecology, demographic structure and dynamics in Bamako, Mali.

BACKGROUND: For the planning of an effective dog mass vaccination campaign against rabies in Africa, it is crucial to know more about the dog population. In this paper we describe for the first time the dog ecology, demographic structure and population dynamics of a domestic dog population in Bamako, Mali. In 2010 and 2011, we visited 2956 randomly selected compounds. Questionnaire data was collected on the compound and household level and on each dog individually. Dog-owning households were followed every six months during one (dog-owning households identified in 2011) or two years (dog-owning households identified in 2010) for the successive collection of dog demography data. RESULTS: We recorded 379 dogs in 279 compounds. The dog human ratio was estimated at 1:121, and the extrapolation of the domestic dog population in Bamako results in an estimate of 14 906 dogs (95% CI 13 041-17 037). The female male ratio was 1:2.8. A high proportion of young dogs was found as a result of a high turnover rate in the population. Mortality within the first year of life was high, and dogs had a life expectancy at birth of 2.5 years. Using a Leslie matrix, we estimated the annual dog population growth to be 20%. Christians were more likely to be dog owners than Muslims. Another factor favouring dog ownership was belonging to the ethnic group of Bobo or Malinke. Dogs were mainly used as watchdogs and fed with household leftovers and garbage. They were most often obtained and given away without remuneration. CONCLUSIONS: This work contributes vital information towards planning effective and sustainable dog rabies control programmes for the district of Bamako. Due to the high turnover rate, we recommend repeated mass-vaccination campaigns of at least 70% of the owned dogs at yearly intervals. In addition, dog-owners need to be educated on good dog management.

The dog and cat population on Maio Island, Cape Verde: characterisation and prediction based on household survey and remotely sensed imagery.

The objective was to estimate and characterise the dog and cat population on Maio Island, Cape Verde. Remotely sensed imagery was used to document the number of houses across the island and a household survey was carried out in six administrative areas recording the location of each animal using a global positioning system instrument. Linear statistical models were applied to predict the dog and cat populations based on the number of houses found and according to various levels of data aggregation. In the surveyed localities, a total of 457 dogs and 306 cats were found. The majority of animals had owners and only a few had free access to outdoor activities. The estimated population size was 531 dogs [95% confidence interval (CI): 453-609] and 354 cats (95% CI: 275-431). Stray animals were not a concern on the island in contrast to the rest of the country.

Narrative overview of animal and human brucellosis in Morocco: intensification of livestock production as a driver for emergence?

Brucellosis is one of the most widespread zoonoses in the world caused by several species of the genus Brucella. The disease, eradicated in many developed countries, is a re-emerging neglected zoonosis endemic in several zones especially in the Mediterranean region, impacting on human health and livestock production. A One Health approach could address brucellosis control in Morocco but scarcity of reliable epidemiological data, as well as underreporting, hinders the implementation of sustainable control strategies. Surveillance and control policies implemented by the Moroccan government in domestic animals (cattle and small ruminants) in the last few decades are assessed for disease impact. This study considers the origins of animal brucellosis in Morocco and the potential for emergence of brucellosis during a shift from extensive to intensive livestock production.

Phenotypic and genotypic characterization of Brucella strains isolated from autochthonous livestock reveals the dominance of B. abortus biovar 3a in Nigeria.

Brucellosis is a worldwide widespread zoonosis caused by bacteria of the genus Brucella. Control of this disease in a given area requires an understanding of the Brucella species circulating in livestock and humans. However, because of the difficulties intrinsic to Brucella isolation and typing, such data are scarce for resource-poor areas. The paucity of bacteriological data and the consequent imperfect epidemiological picture are particularly critical for Sahelian and Sub-Sahara African countries. Here, we report on the characterization of 34 isolates collected between 1976 and 2012 from cattle, sheep and horses in Nigeria. All isolates were identified as Brucella abortus by Bruce-ladder PCR and assigned to biovar 3 by conventional typing. Further analysis by enhanced AMOS-ERY PCR showed that all of them belonged to the 3a sub-biovar, and MLVA analysis grouped them in a cluster clearly distinct from that formed by European B. abortus biovar 3b strains. Nevertheless, MLVA detected heterogeneity within the Nigerian biovar 3a strains. The close genetic profiles of the isolates from cattle, sheep and horses, suggest that, at least in some parts of Nigeria, biovar 3a circulates among animal species that are not the preferential hosts of B. abortus. Consistent with previous genetic analyses of 7 strains from Ivory Cost, Gambia and Togo, the analysis of these 34 Nigerian strains supports the hypothesis that the B. abortus biovar 3a lineage is dominant in West African countries.

Brucellosis as an emerging threat in developing economies: lessons from Nigeria.

Nigeria is the most populous country in Africa, has a large proportion of the world's poor livestock keepers, and is a hotspot for neglected zoonoses. A review of the 127 accessible publications on brucellosis in Nigeria reveals only scant and fragmented evidence on its spatial and temporal distribution in different epidemiological contexts. The few bacteriological studies conducted demonstrate the existence of Brucella abortus in cattle and sheep, but evidence for B. melitensis in small ruminants is dated and unclear. The bulk of the evidence consists of seroprevalence studies, but test standardization and validation are not always adequately described, and misinterpretations exist with regard to sensitivity and/or specificity and ability to identify the infecting Brucella species. Despite this, early studies suggest that although brucellosis was endemic in extensive nomadic systems, seroprevalence was low, and brucellosis was not perceived as a real burden; recent studies, however, may reflect a changing trend. Concerning human brucellosis, no studies have identified the Brucella species and most reports provide only serological evidence of contact with Brucella in the classical risk groups; some suggest brucellosis misdiagnoses as malaria or other febrile conditions. The investigation of a severe outbreak that occurred in the late 1970s describes the emergence of animal and human disease caused by the settling of previously nomadic populations during the Sahelian drought. There appears to be an increasing risk of re-emergence of brucellosis in sub-Saharan Africa, as a result of the co-existence of pastoralist movements and the increase of intensive management resulting from growing urbanization and food demand. Highly contagious zoonoses like brucellosis pose a threat with far-reaching social and political consequences.

Optimizing denominator data estimation through a multimodel approach.

To assess the risk of (zoonotic) disease transmission in developing countries, decision makers generally rely on distribution estimates of animals from survey records or projections of historical enumeration results. Given the high cost of large-scale surveys, the sample size is often restricted and the accuracy of estimates is therefore low, especially when spatial high-resolution is applied. This study explores possibilities of improving the accuracy of livestock distribution maps without additional samples using spatial modelling based on regression tree forest models, developed using subsets of the Uganda 2008 Livestock Census data, and several covariates. The accuracy of these spatial models as well as the accuracy of an ensemble of a spatial model and direct estimate was compared to direct estimates and "true" livestock figures based on the entire dataset. The new approach is shown to effectively increase the livestock estimate accuracy (median relative error decrease of 0.166-0.037 for total sample sizes of 80-1,600 animals, respectively). This outcome suggests that the accuracy levels obtained with direct estimates can indeed be achieved with lower sample sizes and the multimodel approach presented here, indicating a more efficient use of financial resources.

Prevalence and significant geospatial clusters of bovine tuberculosis infection at livestock-wildlife interface ecosystem in Eastern Tanzania.

Bovine tuberculosis (BTB) is an important neglected zoonosis that affects livestock, wildlife and human. A study to determine prevalence and geospatial clusters for BTB was conducted from June 2010 to March 2012 at livestock-wildlife interface areas (LWIA). A total of 1,288 cattle located in vicinity of Mikumi-Selous ecosystem Tanzania were tested. Single Intradermal Comparative Tuberculin Test and spatial scan statistic analysis were applied to establish the status of the disease and identify significant spatial BTB clusters. Overall individual prevalence was 3.7 % (n=1,288) (95 % CI=2.8-4.9) and 7.8 % (95 % CI=6.4-9.4) with cut-off of >4 and >2 mm, respectively. Villages with at least one reactor were 55.8 % (n=43). Reactivity was significantly higher in Mvomero and Kilosa districts compared with Kilombero and Ulanga districts (χ (2) =15.9; P<0.001). Significant spatial BTB clusters were revealed at 11 villages. BTB clustering was significant in Kilosa and Mvomero districts compared with Kilombero and Ulanga districts. There was overlap and aggregation of BTB clusters covering south and south-east of Kilosa district bordering Mikumi National Park (MNP) and Mvomero. Generally, clustering occurred around major rivers. The current study provides useful information on the dynamics and epidemiological status of BTB around the wildlife-livestock-human interface, it reveals that the wildlife are at risk of BTB from infected livestock. The study revealed hotspots for BTB that can be applied to guide implementation of participatory intervention at LWIA and control strategies in marginalised pastoralist communities. This study calls for similar studies in other Tanzania's LWIA for efficient intervention of BTB countrywide.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.