Difference between revisions of "Team:Uppsala/Human Practices/Market Analysis"
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<p> <strong> Figure 2. </strong> Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers. </p> | <p> <strong> Figure 2. </strong> Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers. </p> | ||
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<p> <strong> Figure 2. </strong> Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers. </p> | <p> <strong> Figure 2. </strong> Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers. </p> | ||
Revision as of 19:44, 16 October 2018
Market Analysis
The iGEM project started with a brainstorm session to decide in which direction we wanted our project to go. But before starting with our project, we had some crucial questions that needed to be answered. What tools are accessible today and what are their limits? Is there a market for a new diagnostic tool with our approach? Is there a need for a new diagnostic tool for large strongyles as well? How do the potential stakeholder or customer feel about using a diagnostic tool based on GMO?
To answer these questions we chose to proceed by setting up a meeting up with the company Vidilab (a swedish company working with diagnostics of parasites such as strongyles). Vidilab are everyday users of the current diagnostic tools thus are deeply involved and experienced within the area of our project, making them great consultants. Today horse owners send a stool sample to companies such as Vidilab, who identifies certain parasitic species such as small strongyles found in the sample and counts eggs per gram.
From Vidilab we learnt that this method is not efficient and results vary between companies. All horses have parasites within their intestines, the question you need to answer is what amount of eggs are within the normal range? To get valid results you need to first diagnose a non-infected horse to get a baseline that will be used later on when the horse is more greatly infected. Vidilab uses the guidelines of finding less than 100 eggs per gram dung within a healthy horse corresponds to a low amount, while more than 1000 eggs per gram dung indicates that the horse is infected by a large amount of parasites. Horses with high baseline (more than 1000 eggs per gram dung) can live without symptoms, though they can infect other horses and the paddock with lower baseline (less than 100 eggs per gram dung), which is why you still might want to treat a horse without any symptoms (Vidilab, 2018).
Additionally, different companies are diagnosing during different time of the year, which Vidilab states provides a huge error in the results. The parasites go through different stages which includes one period were they stay encysted, that won’t show any result during a diagnosis (Vidilab, 2018). Thereby the results can be misleading if you diagnose your horse during this time of the year. Another factor to take into consideration is that you need to do follow-ups to be able to analyse whether the parasite are resistant to the anthelmintics used in the treatment plan.
Furthermore there is no existing quantitative and simple diagnostic tool that measures large strongyles efficiently. Thereby we chose to work on making a better system for detecting small strongyles and also looked into the possibility of designing a second worm buster, targeting large strongyles. Products like these could compete in the market of diagnostic tools for small and large strongyles or become a complement for companies working within the field of strongyle diagnostics.
In addition, we conducted a survey to receive greater understanding of the individual perspective of the respondents. The survey was translated into 10 different languages (english, swedish, russian, german, czech, spanish, french, estonian, latvian and italian) and distributed to the respective countries using social media. To make sure that we only would proceed with scientifically validated results, we had to determine how much error we would tolerate, in other words what our lowest limit of answers per survey would be to still have valid results. A good approximate sampling size is, as a rule of thumb at the very least 30 (J. Greenwood, 1950), since it translates well between T-distribution and normal distribution. To be more accurate, everything depends on the actual population we wish to approximate the expected value for. The larger sample size the better (J. Greenwood, 1950).
To be certain of only proceeding with scientifically validated values, we chose to only proceed with surveys which had gotten more than 50 answers. The amount of answers differed between the surveys and only the swedish and the czech versions surveys fulfilled the chosen scientifically validated value of at least 50 participants, see table 1.
Table 1. The table show the translational versions of the survey, sent in the market analysis, with highest amount of answers.
From the Swedish survey we learned that not everyone diagnoses their horses before treating them with anthelmintics. This could lead to an increment of the resistance towards anthelmintics, which is why we want to make it as easy as possible to diagnose horses in a quantitative manner. This would allow treatments to be customized based on the amount of strongyle burden. To assist this statement we simulated extension of strongyle infections upon anthelmintic treatments of different frequency. Comparing our model to the current average treatment frequency we could suggest treatment optimizations in order to decrease risk of resistance development. Read more about the model [here].
By giving the possibility to perform this at home and interpret the result yourself, we believe that we would make the diagnosing procedure easier. We believe that a more user friendly method would contribute to a increment in the amount of diagnosting.
Results from the survey
From the surveys we also concluded that a strong majority within both countries (Sweden & Czech Republic) was positive towards the use of a GMO based diagnostic tool, whereas in Sweden the percentage was 83,2% at a total of 370 participants. This is crucial information since, otherwise, there would not be a market for our worm buster.
Another factor we wanted to analyse with our survey was the kind of anthelmintics being used by the recipients. Are the treatments similar across the country? Are people aware of what kind of treatment they use? The result showed that the majority uses a combination of several anthelmintics, and that the combination of anthelmintics varies. In Sweden all anthelmintics needs prescription provided by a veterinarian, which means that the individual horse owners cannot treat their horses without a veterinarians approval (Tove Forslund, 2018). This indicates that each treatment plan is unique, and thereby there are existing restrictions to the spread of resistance towards anthelmintics.
From the results it was clear that the three most popular anthelmintics in Sweden are Noromectin (77 people), Ivermectin (59 people) and Cydectin (22 people). The results also showed that out of 300 individual horse owners up to 128 people (42.7 %) didn’t know what kind of treatment they used. This indicates that those individuals trust their veterinarians completely and blindly accept their professional directions. This could be somewhat alarming due to the ongoing spread of resistance towards anthelmintics. To eliminate the risk of spreading the resistance, each horse owners should critically review the kind of treatment plan for their horses.
Another aspect we wanted to analyse was to see the correlations between the following questions:
- How often do the horse owners diagnose their horse(s) for parasitic infections per year?
- How often do the horse owners treat their horse(s) for parasitic infections?
Figure 1. Correlations between the “frequency of diagnoses done for parasitic infections each year” against the “frequency of treatments done for parasitic infections each year”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers.
We were interested in studying the correlations between the amount of treatments and diagnoses the horse owners provide for their horses each year. Do they treat their horse(s) without diagnosing them first or are the treatments specific for the horses? The result shown in figure 1 indicates that the majority of the treatments are done after a diagnosis. The factor of having 2 diagnoses for the horses might be a follow up diagnosis to see whether the treatment worked or not. Moreover figure 1 also shows that a minority treat their horses without having a diagnose on their horses first. This could be due to the individual not being the one in charge of ordering a diagnose or not realising they are doing it, since today it is common to have the diagnosis as a routine (Lind EO et. al, 2007).
Another aspect we wanted to analyse was to see the correlations between the following questions:
- How often do the horse owners treat their horse(s) for parasitic infections?
- Would the horse owners be open to a diagnosis method that involves genetically modified bacteria if it was proven to be cost-effective, safe and approved by the appropriate agency?
Bigass heading
By studying how often horses are treated per year against respondents attitudes towards GMO, we set out to see if there is any correlation between these factors. The result shown in figure 2 indicates that there is no distinct dependence between these variables. We were expecting that eventually more frequent treatments would correlate to bigger acceptance of GMO suggesting possible wish for more effective/conclusive diagnostics. However it is suggested that openness for GMO is generally high irrespective of the chosen treatment frequency.
…………
Figure 2. Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers.
Another aspect we wanted to analyse was to see the correlations between the following questions:
- How often do the horse owners diagnose their horse(s) for parasitic infections per year?
- Would the horse owners be open to a diagnosis method that involves genetically modified bacteria if it was proven to be cost-effective, safe and approved by the appropriate agency?
By studying how often horses are treated per year against respondents attitudes towards GMO, we set out to see if there is any correlation between these factors. The result shown in figure 2 indicates that there is no distinct dependence between these variables. We were expecting that eventually more frequent treatments would correlate to bigger acceptance of GMO suggesting possible wish for more effective/conclusive diagnostics. However it is suggested that openness for GMO is generally high irrespective of the chosen treatment frequency.
Figure 2. Correlation between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. Number of treatments have the parameter <1 that corresponds to treatments occurring less often than once per year. NA stands for not applicable and are not numeric answers.
Figure 3. >/strong> Correlations between the “frequency of diagnoses done for parasitic infections each year” towards “Their attitudes to using a GMO based diagnosis tool”. NA stands for not applicable and are not numeric answers.