Fredros O. Okumu

This study validates the Polovodova method for mosquito age-grading, finding high accuracy for parity but declining precision for later gonotrophic cycles in both lab and field settings.

The paper introduces TAUS, a survival analysis method that avoids proportional hazards and parametric assumptions, enabling comparison of survival probabilities across populations with different age structures and life histories.

This study characterizes a new Anopheles funestus colony (FUTAZ) established in Tanzania, comparing its fitness traits and genetic markers to wild and existing colonies.

The paper analyzes genomic diversity in Anopheles funestus across Africa, identifying genetic variation, adaptation signals, and conservation of a gene drive target.

The paper analyzes the population genetics of Anopheles funestus in Tanzania, identifying two distinct genetic populations with different resistance backgrounds and suggesting geographic barriers to gene flow.

The paper discovers knock-down resistance (kdr) mutations in Anopheles funestus, a major malaria vector, showing resistance to DDT but not deltamethrin.

This study improves mosquito age prediction from mid-infrared spectra using transfer learning and dimensionality reduction, achieving high accuracy across different populations.

This paper develops an autoencoder and ANN model to estimate parity status of wild mosquitoes using NIR spectra, achieving high accuracy across multiple datasets.

This paper uses mid-infrared spectroscopy and machine learning to accurately predict malaria mosquito species and age structure, offering a fast and cost-effective alternative to traditional methods.