A team at the Stanford Medicine School has perfected a number of technologies for detecting a variety of bio-substances, including cells, bacteria and viruses.
So far the detection required expensive equipment and skilled professionals, something that is not affordable/available in many parts of the world.
They are using flexible polyester chips with electrodes that can be connected to a measuring device (including a smartphone). When an appropriate reagent gets in contact with a fluid, like blood from a fingerprick, it aggregates the specific cells it has been targeted to. The solution is smeared on the chip and the measuring device can detect the variation in resistance characterising the presence/absence of a specific cell or virus, like HIV.
This approach turns out to be very cheap (a single measure including the disposable chip and the reagent cost about 2$) and the measurement itself is easy to perform.
A further bonus is the possibility for earlier detection than using conventional methods. As an example the conventional way to detect HIV is to look for antibodies in the blood but they take a few months to develop. On the contrary, this method detects the virus directly, hence it is viable also in the first phase of the infection.
The technologies developed are both in the manufacturing of the chip and in the creation of the reagents. They change significantly since each one is specific to a particular cell. In some cases the reagent does not change the resistivity of the chip circuit but changes the colour of some spots in the chip (in this case it is a different sort of chip) and a cellphone camera is used to pick up the intensity of the colour change thus allowing an app to evaluate the concentration of some bacteria.
Clearly these set of technologies are very important for poorer areas but they are likely to find a place in our homes in the next decade (at least this is my feeling). I am pretty sure that just brushing your teeth will provide plenty of information on your health, well before any clinical signs become apparent. And, as I pointed out in previous posts on data economics in health care, they will change our perception of medicine.