Next, the sounds of 20 species of mosquito that spread diseases to humans were recorded – more than in any previous study. First, techniques were developed that allow anybody to record mosquitoes on virtually any mobile phone model – including smartphones and basic flip-phones. now report that the microphones in ordinary mobile phones are sensitive enough to accurately record the whining buzz of a mosquito, even in the presence of background noise. The challenge was to find instruments that could record these sounds clearly enough to measure the pitch, but that were still cheap and sturdy enough to use in mosquito-infested environments. However, scientists have known for many decades that one can identify species of mosquito by the pitch of sound they make when they fly. This makes them less suitable for resource-poor areas, which typically have the highest levels of mosquito-borne diseases. Most current methods to monitor mosquitoes are laborious, and need expensive equipment and highly trained people. Yet, this kind of control strategy relies on knowing which species of mosquito that spread diseases to humans and where they are found.
As such, the most effective way to control these diseases is to reduce the number of mosquitoes in the affected area. Many of these diseases have no cure, and those that do often face the problem of drug resistance. Thus, we establish a new paradigm for mosquito surveillance that takes advantage of the existing global mobile network infrastructure, to enable continuous and large-scale data acquisition in resource-constrained areas.ĭiseases spread by mosquito bites – like malaria, dengue and Zika – kill over half a million people each year. As proof-of-concept, we carry out field demonstrations where minimally-trained users map local mosquitoes using their personal phones. We survey a wide range of medically important mosquito species, to quantitatively demonstrate how acoustic recordings supported by spatio-temporal metadata enable rapid, non-invasive species identification. We show that even low-cost mobile phones with very basic functionality are capable of sensitively acquiring acoustic data on species-specific mosquito wingbeat sounds, while simultaneously recording the time and location of the human-mosquito encounter. Here, we demonstrate that commercially available mobile phones are a powerful tool for acoustically mapping mosquito species distributions worldwide. The direct monitoring of mosquito populations in field settings is a crucial input for shaping appropriate and timely control measures for mosquito-borne diseases.
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