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# 3. Economic considerations

Understanding those factors that are associated with a lower rate of loss may provide potential treatment options for beekeepers.

However, just because a practice appears to be effective in reducing loss does not mean that it is necessarily in the beekeeper’s best interest to adopt it. An additional piece of information for apiary managers is how much the treatment will cost and how much money the producer will likely save with its application.

Calculating the costs of practices in beekeeping is relatively straight forward, in that it includes the purchase cost of treatment and any labour or materials costs associated with its application. While each producer can calculate their costs, accurate aggregate data are more difficult to obtain, particularly for labour costs, or for   applications where producers use their own recipe. Thus, the true costs of treatment may vary from producer to producer, and individual managers can be guided to compare their own costs to the average  for a better cost estimate.

Calculating the benefit from reducing disease is more nuanced. One simple approach is to use the replacement cost of a hive as an estimate for the benefit of losing one less colony. To be as close as possible to the actual cost, one would like to find the replacement process that most closely replicates the scenario of having not lost the colony in the first place, such as a nuclear colony. Thus, one would  not simply want to use the cost of splitting a hive, but would want a replacement that would be as productive as quickly as an existing colony while not reducing the productivity of surviving colonies. The true replacement costs would include extra feeding and labour costs associated with getting that colony to productivity (Equations 3.0).

Equation 3.0.a

Benefit of saving one colony = Replacement cost

Where replacement cost = cost of nuclear colony + cost of feed + cost of labour

Once one has a measure of the benefit of saving one colony, one can determine the expected net benefit of treatment for a disease.

Equation 3.0.b

Expected net benefit of treatment =

Replacement cost x (mean survival of untreated colonies – mean survival of treated colonies)

Where mean survival = 100 - Average Loss

If the cost of treatment exceeds the expected benefit, generating a negative expected net benefit, then despite the fact that the treatment may reduce colony loss, it may not be in the producer’s best interest to use that treatment.

Note that the above calculation, even if all treatment and replacement costs are included, will tend to underestimate the  benefits associated with treatment.  Disease not only affects mortality, it also affects productivity, which is not captured in the above calculation. Thus, the above calculation should be thought of as generating a lower bound on expected net benefit. A more nuanced approach would be to estimate the effect of treatment on disease  load, and the effect of disease load on productivity of honey production, pollination or other revenue-generating activities. Further, some beekeepers may place personal value on not losing a colony,  and for them, their expected benefit of treatment may be higher still. These data are more difficult to collect, and will likely vary greatly  from producer to producer.  Nonetheless, giving beekeepers an estimate of the net benefit of treatment should allow them to   compare the pure monetary costs and benefits to any other idiosyncratic costs of colony loss and help them in their management decisions.

 Box 8. Using the numbers from the average winter loss determined by a management survey given in Box 6, we observed that beekeepers that used a known varroa mite control product lost 7.2 percentage points (or 20%) fewer colonies than beekeepers that did not use a product. To calculate the 95% CI for the difference in the mean, we need to add and subtract 1.96 × sed, where sed is the standard error of the difference in means. The standard error of the difference, sed is defined as where se1 is the standard error of the mean for sample 1, and se2 is the standard error of the mean for sample 2. (The standard error calculations come from the confidence interval calculations in box 6 above.) The standard error for the sample using treatment is 1.02 and the standard error for the control sample (or no-treatment sample) is 0.92. Thus, the standard error of the difference in means is . Thus, we get a 95% confidence interval of the difference in means of 7.2 plus or minus 1.96 × 1.37, or 4.51 to 9.89. If the replacement costs of a hive, including labor and feeding are \$150, then the expected benefit of the treatment is the change in probability of loss times the replacement costs, or 0.07 × \$150 = \$10.80 (with a 95% CI of \$6.77 to \$14.83). Assume the cost of treatment is \$7.50 per colony. Thus the expected net benefits would be \$10.80 - \$7.50 = \$3.30 (with a 95% CI of -\$0.78 to \$7.33) per hive. Thus, on average the producer is expected to benefit from the treat- ment, but could in fact lose from treatment.  Net gains are expected to range from a loss of \$0.78 per colony to a gain of \$7.33 per colony, 95 times out of 100.

Note that the above calculation, even if all treatment and replacement costs are included, will tend to underestimate the benefits associated with treatment.  Disease not only affects mortality, it also affects productivity, which is not captured in the above calculation. Thus, the above calculation should be thought of as generating a lower bound on expected net benefit. A more nuanced approach would be to estimate the effect of treatment on disease load, and the effect of disease load on productivity of honey production, pollination or other revenue-generating activities. Further, some beekeepers may place personal value on not losing a colony, and for them, their expected benefit of treatment may be higher still. These data are more difficult to collect, and will likely vary greatly from producer to producer.  Nonetheless, giving beekeepers an estimate of the net benefit of treatment should allow them to compare the pure monetary costs and benefits to any other idiosyncratic costs of colony loss and help them in their management decisions.