Practical example of data triangulation to assess prevalence Practical example of data triangulation to assess prevalence. this example mostly relies on wastewater analysis and information from a web survey on drugs. But not sufficient…

What I’m going to present is a little part of a larger project which goal is to better understand a local illicit drugs market study. You can see that it’s a collaboration of 3 institution, 1 forensic institute, addiction switzerland and the institute for social and preventive medicine. This collab plays of course a key role because 1 single institution would not have.

More in details of this prevalence estimation The idea is to assess the n with wastewater and information issued from this web survey on drugs. As a very first step, a first attempt to see if we can go somewhere with it.

Usual equation when doing demand-based estimation of the volumes.

− 𝑙𝑜𝑎𝑑𝑠 𝐿𝑇𝐹 𝑢𝑠𝑒𝑟𝑠 ) There is a problem with our equation because the left side is related to integrated users and on the right side we have volumes (and we can not differentiate in the wastewater). So we have to find another way to estimate what is coming from this population.

Investigate methodological considerations on web surveys… real opportunity to get information but no perfect tool!

Thank you for your attention!