SimonAB/DL-MIRS_Siria_et_al

Code repository for Siria et al. # Rapid age-grading and species identification of natural mosquitoes for malaria surveillance Doreen J. Siria, Roger Sanou, Joshua Mitton, Emmanuel P. Mwanga, Abdoulaye Niang, Issiaka Sare, Paul C.D. Johnson, Geraldine Foster, Adrien M.G. Belem, Klaas Wynne, Roderick Murray-Smith, Heather M. Ferguson, Mario González-Jiménez, Simon A. Babayan, Abdoulaye Diabaté, Fredros O. Okumu, and Francesco Baldini **The malaria parasite, which is transmitted by several _Anopheles_ mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We developed a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40,000 ecologically and genetically diverse _An. gambiae_, _An. arabiensis_, and _An. coluzzii_ females, we developed a deep transfer learning model that learned and predicted the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model was able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.** ## Resources - Code for converting spectra - Code for UMAP Clustering - Code for convolutional neural net - Code for power analyses - Code and instructions for calculating age structure proportions based on gonotrophic cycles ## General system requirements Developed on: - Operating systems: macOS 10-12; Windows 7; Linux Ubuntu - Hardware: CPU Intel Core i7, 16-64 GB RAM - Specialised hardware for deep learning: GPU - TITAN Xp 12GB ## Installation guide …