Model-based spatial access modelling of hospitalisation for severe acute febrile illness

The universal health coverage framework highlights the need for a broader approach to health and well-being transcending different aspects of population health and monitoring health gains. Hospitals represent one platform for measuring health gains in a population. However, surveillance data is biased by varying population access and health system variables that have, to date, been poorly quantified. For hospital data to be of utility for measuring effective health coverage and gain, it must be coupled with accurate parameters of access and related variables of referral care, hospital competition, and treatment-seeking behavior. These parameters have not been quantified in a framework combining clinical and spatial epidemiology to effectively quantify health outcomes and transform the use of surveillance data. In this proposal, I will focus on building knowledge on hospital access and health system variables using mathematical-spatial statistical approaches with an application to Acute Febrile Illness (AFI) in young children representing a majority of undifferentiated syndromes presenting at the hospital and forming a bulk of morbidity and mortality in children. My objectives will also aim to estimate the burden of AFI in communities served by the hospital and measure the influence of health system variables to health outcomes related to AFI.