Dynamics of influenza A (avian influenza) virus in poultry in the Greater Accra region of Ghana amongst the production levels.

This research explores, through active surveillance, influenza A prevalence at different production levels in the Greater Accra region of Ghana, a study area with previous outbreak of highly pathogenic avian influenza H5N1 virus. The prevalence of influenza A was determined by rtRTPCR. This was achieved by screening 2040 samples comprising tracheal and cloacal swabs from chicken, ducks, pigeons, guinea fowls, and turkeys. Influenza A prevalence by production levels and species was computed at 95% confidence interval (CI) using the exact binomial interval. Structured questionnaires were also administered to 50 randomly selected poultry traders in the live bird markets. The overall influenza A prevalence was 7.7% (95% CI, 6.6, 8.9). Live bird market recorded 13.5% (n = 139, 95% CI, 11.5, 15.7), backyard poultry was 1.4% (95% CI, 0.6, 2.7), and commercial poultry 2.4% (95% CI, 1.2, 4.3). There was evidence of influenza A in all the poultry species sampled except for turkey. Subtyping of the M-gene has revealed the circulation of H9 in the three production levels. Live bird market has demonstrated high prevalence coupled with low level of biosecurity consciousness among the poultry operators. This is suggestive of live bird market serving as a potential basket for genetic reassortment with unpredictable future consequences.

Disaggregating Tropical Disease Prevalence by Climatic and Vegetative Zones within Tropical West Africa.

Tropical infectious disease prevalence is dependent on many socio-cultural determinants. However, rainfall and temperature frequently underlie overall prevalence, particularly for vector-borne diseases. As a result these diseases have increased prevalence in tropical as compared to temperate regions. Specific to tropical Africa, the tendency to incorrectly infer that tropical diseases are uniformly prevalent has been partially overcome with solid epidemiologic data. This finer resolution data is important in multiple contexts, including understanding risk, predictive value in disease diagnosis, and population immunity. We hypothesized that within the context of a tropical climate, vector-borne pathogen prevalence would significantly differ according to zonal differences in rainfall, temperature, relative humidity and vegetation condition. We then determined if these environmental data were predictive of pathogen prevalence. First we determined the prevalence of three major pathogens of cattle, Anaplasma marginale, Babesia bigemina and Theileria spp, in the three vegetation zones where cattle are predominantly raised in Ghana: Guinea savannah, semi-deciduous forest, and coastal savannah. The prevalence of A. marginale was 63%, 26% for Theileria spp and 2% for B. bigemina. A. marginale and Theileria spp. were significantly more prevalent in the coastal savannah as compared to either the Guinea savanna or the semi-deciduous forest, supporting acceptance of the first hypothesis. To test the predictive power of environmental variables, the data over a three year period were considered in best subsets multiple linear regression models predicting prevalence of each pathogen. Corrected Akaike Information Criteria (AICc) were assigned to the alternative models to compare their utility. Competitive models for each response were averaged using AICc weights. Rainfall was most predictive of pathogen prevalence, and EVI also contributed to A. marginale and B. bigemina prevalence. These findings support the utility of environmental data for understanding vector-borne disease epidemiology on a regional level within a tropical environment.