Before revision: Neonatal sepsis (NS) and resulting complications, such as postinfectious hydrocephalus (PIH), are a significant cause of neonatal and infant mortality throughout the developing world. Addressing this problem requires dynamical modeling and estimation of the true state of the disease using realistic data collection schemes, followed by optimal allocation of resources to control the disease with a combination of prevention and treatment. To address these issues, we first develop a compartmental model for non-communicable infections, which are especially common with NS. Then, we develop a novel optimal linear filterfor Poisson observations, characteristic of infectious diseases, which model the number of patients recorded as presenting each day at hospitals.
After revision: An optimal filter for Poisson observations is developed as a variant of the traditional Kalman filter. Poisson distributions are characteristic of infectious diseases, which model the number of patients recorded as presenting each day at hospitals.