Mosquito borne diseases such as malaria, dengue, chikungunya and zika cause huge suffering in tropical regions of the world. One of the main approaches to controlling these diseases is to use insecticides to kill mosquitoes and prevent them from transmitting the infection from person to person. Millions of pounds are spent on mosquito control each year though surprisingly there is no simple method for evaluating the ability of these interventions to kill mosquitoes or prevent them from transmitting disease. The number of biting mosquitoes in an area fluctuates substantially from day to day due to local weather patterns so the number of mosquitoes caught in traps is a poor predictor of the size of the population. More importantly the number of mosquitoes in itself is not a good predictor of risk as many diseases take several days to develop inside the mosquito and find their way to the mouthparts. This means that only older mosquitoes can pass on the infection. Mosquito age is therefore very important for assessing the effectiveness of anti-mosquito interventions but currently, there is no easy, accurate way of assessing the age of a mosquito population. Near-Infrared Spectroscopy (NIRS) is a new age-grading and species identification technique that has been developed in the laboratory. It predicts the age of the mosquito by measuring how a beam of light is reflected differently from the bodies of mosquitoes as they get older. Unlike other methods NIRS doesn't require costly chemicals or procedures and it can be carried out by anybody with minimal training. This makes it feasible for use as a routine method for monitoring mosquito age in the field. Currently NIRS cannot predict the age of an individual mosquito very accurately and tests have only been done on mosquitoes reared in the laboratory which are likely to be more uniform (and therefore give more accurate results) than those caught in the wild. However, for disease control it is more important to know the average age of the mosquito population than the age of individuals. Our preliminary work suggests that if we change the way we analyse NIRS outputs we can generate highly precise predictions of the average age of the mosquito population. The project intends to take NIRS from the laboratory to the field and test whether it is good enough to be able to be used in the routine monitoring of mosquito populations. The project will use semi-field and field data to operationalise the technique and outline how many mosquitoes need to be caught (and over how many days) to generate estimates accurate enough to guide the deployment of mosquito control. The work will concentrate on the two most important mosquito borne infections: malaria (which kills 438,000 people in 2015) and dengue (which infects 400 million people annually). However the technique developed here can be applied to other diseases and mosquito species. NIRS can also be used to differentiate closely-related mosquito species that are indistinguishable by eye. That is important, as not all of these mosquitoes have the same ability to transmit disease and are affected by control interventions differently. Similarly to age-grading, the capacity of NIRS to differentiate species needs to be more rigorously tested in the field. There is also evidence to suggest that NIRS might be able to detect whether a mosquito is infected with the virus that causes dengue disease. This will be tested for malaria, first in the laboratory in Burkina Faso and then in the field. Currently mosquito species, age and infection status are estimated using a variety of laborious and costly procedures that preclude their use as routine monitoring tools in poorer parts of the world. A single, inexpensive method for doing all three tests simultaneously would have significant public health impact: we could describe the risks of disease transmission and evaluate the efficacy of control programs far more cheaply and quickly.