Predictive Personalized Public Health (P3H)

Hydrocephalus is one of the most common neurosurgical disorders in children, resulting in abnormal expansion of the cerebral ventricles. Given the severity of the disease and the requirement of surgery for treatment, timely and accurate diagnosis are important, particularly in resource-limited settings such as Uganda. We consider three categories of hydrocephalus:

  1. hydrocephalus due to myelomeningocele (spina bifida)
  2. post-infectious hydrocephalus (PIH), and
  3. non-post-infectious hydrocephalus (NPIH), which is caused by neural defects at birth other than myelomeningocele.

This project aims to predict the incidence of each category of hydrocephalus cases among children in Uganda. This is a collaborative effort that includes researchers with a wide range of expertise from Penn State University, Yale University, and the National Planning Authority of Uganda.

We develop inhomogeneous Poisson point process models, using the data collected over a 20-year period by the CURE Children’s Hospital of Uganda in Mbale on infants with hydrocephalus. The spatiotemporal distribution of cases within the population shows evidence of inhomogeneity. For PIH, an observed increase in cases during the rainy season leads to the hypothesis that the distribution of the bacteria is related to rainfall. For myelomeningocele, folate deficiency during pregnancy has been previously identified as a risk factor. It is suspected that crop failure in Uganda may be associated with folate deficiency. Our work investigates the association between the spatio-temporal pattern of hydrocephalus cases and several such environmental and socio-demographic factors to test these hypotheses. Ultimately, we aim to use our model to instruct policy on preventative measures for areas identified as high-risk, and to identify the most probable cause of disease to inform treatment at point-of-care using real-time data.