A high immunity status is the best way to keeping healthy poultry flocks. Using baselines for ELISA serology is a useful tool to monitoring this status.
By Louise Dufour-Zavala, Georgia Poultry Lab Network
Poultry health reality is variable in different poultry producing areas of the world. However, the diagnostic tools veterinarians use to understand and measure different aspects of poultry health (serology, virology, bacteriology) are similar. The use of ELISA technology is quite universal and there are ways to manipulate data to make it useful for day to day decision making. The objective of this text is to describe a manner to analyze ELISA serology data and make it more useful to the poultry producer wherever ELISA serology is used.
Use of ELISA and definition of baseline
ELISA technology used in avian serology has many advantages: low cost, specificity and sensitivity, ease of use, and generation and tabulation for analysis of large amounts of computer generated data. It is relatively easy and probably recommendable for high throughput laboratories to produce yearly baselines for their poultry industry user base. Short of that service, companies themselves should monitor their own baselines. Baselines are very useful, as they represent titer values that can be expected for certain types of poultry at certain ages for certain disease agents based on historical data. When new laboratory data is generated in the form of ELISA titers, it can be compared to baseline titers for the bird, age and agent in one geographical location, or to baselines of a company’s own historical data.
There are 3 main objectives for ELISA testing: monitoring birds for natural exposure to disease, monitoring them for response to vaccination, and diagnostic support. It is for the second objective, monitoring for response to vaccination, that baselines are most used, although they will also clearly show exposure when analyzed over time.
In broilers, it is not necessary to test birds every week. Although weekly testing yields an interesting and typical U shape curve, the only valuable data points are the day old and the processing age numbers: the protection titers of the chicks hatched, and the combination of the response to vaccines and field exposure by the time they are marketed.
The line graph in Figure 1 starts with a certain level of maternal antibodies (A) that disappear by the third week of age (B), only to increase again and reach a certain level by processing age (C), as a result of a combination of vaccination and field exposure. The same graph shape is observed for all common poultry diseases observed in broilers that elicit a humoral immune response (production of serum antibodies). It is because of the predictability of this curve that weekly testing is unnecessary. The use of inactivated vaccines in broilers may change the shape of this curve.
Two good examples of this U shape curve are the GA IBV titers and the GA IBD titers in broilers for 2013-2015 are shown in Figures 2 and 3.
Breeders have a more complex vaccination schedule, but within a region, will also show a “typical” baseline curve over time. It is not necessary to sample breeders every 5-10 weeks, but if one did, one would find that the breeder baseline curve shows levels of waning maternal antibodies, followed by a response to live vaccination in the pullet stage. By the time the birds have received 2 inactivated vaccines as is typical in the US (at 12 and 18 weeks of age), their titer response markedly increases to a peak about 6 weeks after the second inactivated vaccine is given. That peak is followed by either maintenance of the titers or waning of the titers over time, depending on the vaccines used and field challenges.
As can be seen in Figure 4, the maternal antibodies (A) disappear by week 3-4 (B), followed by a moderate response to multiple live vaccines (C), a strong response to the first inactivated vaccine (D), another strong anamnestic response to the second inactivated vaccine (E). The titers maintain themselves or decrease slightly by the time the breeders are processed as fowl (F, G) at 65 weeks of age.
A good example of breeder baselines illustrating this effect is the reovirus baseline for 2013-2015 is shown in figure 5.
For diseases where no inactivated vaccines are used, but where field challenge is constantly present, such as for infectious bronchitis, the curve may not show a peak titer and the titers may maintain themselves during the production cycle due to constant challenge (figure 6).
The most important sample age in breeders is the peak titer, at 24 weeks of age. This is the optimal result of every vaccine that has been given to the flock. The response to the first inactivated vaccine, at 16-18 weeks of age, would be second in importance. At that age, it is also important to look for positivity to AE and CAV and make sure the birds have seroconverted to these 2 agents before the onset of production. Third in importance is a 45 week titer determination, as this one indicates how much antibody the flock still has to pass on to the progeny, and also whether the flock is getting a field challenge to any of the agents analyzed.
Any of the other monitoring ages (including day old to look for maternal antibody levels, 10 weeks to look for the response to live vaccine primers in pullets, and 65 weeks to look for end-of-production titers) can also be done depending on the particular company’s priorities.
How to use baselines
At GPLN, we publish our 2-year baseline every year. The full report has a broiler breeder section and a broiler section. After screening, the data is then separated by age range and bird type. All flock GMTs and CVs falling within the bird type and age range are then collated together, averaged, and graphed.
Poultry producers not only can compare their results to others, but they can also look at their data for one age range, a particular farm, or several farms over time for any particular test. We had noticed that many producers did this manually from their lab reports anyway. The laboratory providing this service saves the producers valuable time and enhances the value of the ELISA service considerably.
Example of uses: IBD titers after a vaccine change
If a company baseline for IBD-XR in 24 week old breeder flocks is 9,000, with a cv of 30, and they make a vaccine change (vaccine type, vaccine manufacturer, mixing the vaccine with another, changing the site of administration, changing the number of doses given), and the first few flocks analyzed after the change have a titer of 5,000-6,000 with no other parameter changes, the company can use that data to reconsider the vaccine decision.
In the first example (figure 7), company A IBD-XR titers were below GA average. After they made a change, their titers were above GA average (figure 8).
Another interesting way to use the data once compiled in such a manner is to look at trends over time. The reovirus problems that manifested themselves in the poultry industry of many countries during the past few years (2012-2014) can be looked at using baseline data in breeders and broilers. The problem lead to higher titers due to field challenge in broilers, and higher titers due to more vaccination and field challenge in pullets and breeders, as seen in the following 2 graphs. In figure 9, the increase in market age reovirus titers indicate that the broilers were challenged, and the decrease in broiler titers tell us that the problem is not as prevalent in 2015. In figure 10, it can be observed that the breeder titers maintain themselves since many flocks still in the field have been vaccinated aggressively against reovirus.
Baselines have many uses, and are mostly useful to the poultry producer and poultry health manager. It enables those persons to look at trends instead of piles of individual flock data sheets, understand the results generated by the laboratory much better, make decisions based on strong valid data, and measure the result of interventions such as vaccination changes very readily. Although the laboratory can be central in providing the bank of data and analyses, it falls back to the poultry managers to find the best uses for baselines in their own field situation(s).
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