Bettridge, Judy M.

Brena, C.

Christley, Robert M.

Dessie, Tadelle

Gutu, Z.

Hanotte, Olivier H.

Kaiser, P.

Lynch, Stacey E.

Melese, K.

Taye, T.

Wigley, Paul

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37.12 37.14 37.16 37.18 37.20 37.229.549.569.589.609.62Circle plot of 'z'X CoordY Coord0.00 0.02 0.04 0.06 0.08 0.100.000.050.100.15Variogram with tolerance limitsdistancesemivarianceInfectious bursal disease in Ethiopian village chickens J. Bettridge1,2, S. Lynch1,2, C. Brena1,2, K. Melese3, T. Dessie2, Z. Gutu1,2, T. Taye2,4,  O. Hanotte4,  P. Kaiser5, P. Wigley1 and R. Christley1   1. The Institute of Infection and Global Health, University of Liverpool, UK 2. International Livestock Research Institute, Addis Ababa, Ethiopia 3. Ethiopian Institute for Agriculture Research, Debre Zeit, Ethiopia  4. Centre for Genetics and Genomics, School of Biology, University of Nottingham 5. Infection and Immunity Division, The Roslin Institute and R(D) SVS, University of Edinburgh   Jarso Horro                                                                         Poultry production in Ethiopia and                                                                      Infectious bursal disease virus (IBDV)      • The majority of Ethiopian poultry are indigenous birds kept in small backyard flocks, belonging to rural smallholders, and are particularly important to landless in society, and also to women.  • Disease is reported by smallholders to be a major constraint to production, but most outbreaks are attributed to Newcastle disease without any investigation of the pathogens responsible.  • IBDV was first reported in Ethiopia in 2002 in a commercial flock, but the very virulent (vvIBDV) strain type has since been identified in all production systems. This strain is associated with high mortality in birds between 3 and 6 weeks of age.   • Only birds over 3 weeks and less than around 10 weeks of age will have clinical disease (diarrhoea, dehydration, echymotic haemorrhages). Adult birds will seroconvert without showing clinical signs. Chicks under 2 weeks do not normally develop disease, but become immunosuppressed, as the developing B-cells  are  depleted  by  the  virus,  impairing  the  bird’s  ability to produce antibodies.   4 Market sheds  (groups of villages dependent  on a single market) 2 Regions (Horro & Jarso) Both in highland areas, but with different  social demographics 8 Villages 2 birds of over 6 months of age were randomly  selected  from each household flock                                              Total: 1280 birds    Sampling Methods        Modelling risk factors  • Multi-level  intercept only models were fitted  to assess the variation in antibody levels (as measured by the S:P ratio) at each level of the dataset, and the amount of variation between different ELISA plates.   • Intraclass clustering coefficients indicated ~66% of variation was contributed by individual birds, and ~ 13% by  the farm. Market shed and region did not contribute significantly, however, the ELISA plate was an important source of variation. Household and plate were therefore fitted in the final  multilevel mixed model as random  effects, and village and season were included as fixed effects.  • Other household and bird level variables were screened for inclusion in the final model, and retained where there was evidence that they significantly (p<0.05) improved model fit (Table 1.)  • Due to the non-normality of the residuals, bootstrap estimates of the standard errors  (SE) were estimated.  The  simulated  SE’s  were  lower  for  the  effects  of  Salmonella  titre  and  outbreak  history and only slightly increased for the village effect without altering the significance, providing evidence that our estimates are generally robust, despite non-normality. However,     the bootstrapped model suggested that Season B was not significantly different to the other seasons (p=0.09).  • Bird-level residuals were examined for spatial clustering, by comparing them with simulated sets of residuals with no spatial correlation. The variogram shown below suggests that, in adjacent villages H1A and H1B, in Season D, there was more similarity between birds found close to each other, as we might expect with an infectious agent. However, spatial clustering of residuals was not evident for all villages in all seasons.  Conclusions  • Infectious bursal disease is or has been circulating in at least seven out of the eight villages in our study.   • The association of seropositivity in a household flock with recent deaths in growers, but not chicks or adults fits with the biology of the disease, and is consistent with IBDV  contributing to mortality in this population.  • All seropositive birds had moderate to high antibody levels to Salmonella, which makes it unlikely that they were infected as chicks. It is probable that all immunosuppressed birds have died by the age of 6 months.  • The differences  between and possibly within villages highlights the need for control strategies to be tailored to the local area, with regard to regional differences in the socio-economic importance of poultry, rather than blanket measures applied.  640 Households H1A H1B H2A H2B J1A J1B J2A J2B Total Season May 2011 25 25 25 25 25 25 25 25 200 Oct 2011 25 25 25 25 25 24 25 25 199 May 2012 15 15 14 16 15 15 15 15 120 Oct 2012 15 15 16 15 15 15 15 15 121   Total    80 80 80 81 80 79 80 80 640 Data was clustered at 4 levels Each village was visited 4 times, and different households were randomly selected   44 birds tested antibody positive    1180 birds tested antibody negative •  Management data  for the household were collected in a questionnaire • Blood was collected into an anticoagulant and transported to the laboratory, where samples were tested for antibodies to IBD using a FlockScreen Antibody ELISA (x-OvO, Inverkeithing,UK). Optical density is converted to a ratio to the positive control (S:P ratio). Birds with an S:P ratio > 0.285 are considered seropositive Variogram with tolerance limits of the residuals (from the  model in Table 1) for  villages H1A and H1B in Season D, showing evidence of spatial autocorrelation over short distances (p=0.02) Table  1:   Fixed effects Coefficient SE P Intercept 0.060 0.026 0.022 Continuous variables       Salmonella s:p ratio 0.012 0.003 0.000 Categorical variables       Season A Reference     Season B 0.040 0.018 0.028 Season C 0.031 0.027 0.242 Season D 0.033 0.027 0.230 Village H1A Reference     Village H1B -0.054 0.027 0.045 Village H2A -0.064 0.027 0.020 Village H2B -0.070 0.026 0.006 Village J1A -0.094 0.030 0.002 Village J1B -0.055 0.029 0.052 Village J2A -0.116 0.028 0.000 Village J2B -0.056 0.029 0.051 No outbreak in last 12 months Reference     Outbreak in chicks 0.014 0.024 0.556 Outbreak in growers 0.059 0.026 0.022 Outbreak in chicks and growers 0.097 0.043 0.025 Outbreak in adults 0.011 0.012 0.337 Outbreak in chicks and adults 0.001 0.025 0.978 Outbreak in growers and adults 0.040 0.028 0.152 Outbreak in all age groups -0.003 0.021 0.879 H1 H2 J1 J2 Seroprevalence by village and season, based on a cut-off S:P ratio value of 0.285 Distribution of S:P ratios. An S:P ratio of  0.285 equates to an antibody titre of ~2400    Residuals (from model in Table 1) for villages H1A and H1B H1A H1B This work is part of a larger collaborative project  looking at the infectious disease epidemiology, genetic and socio-economic aspects of  poultry keeping in Ethiopia.  Further information can be found at www.ch4d.wordpress.com   Funded by:       (Projects BB/H009396/1, BB/H009159/1 and BB/H009051/1) judybett@liv.ac.uk 

Infectious bursal disease in Ethiopian village chickens

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Infectious bursal disease in Ethiopian village chickens

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