Forecasting infectious diseases: Improved prediction could transform treatment
Infectious disease is a leading cause of death worldwide, especially among children, according to the World Health Organization. Children in developing nations are particularly vulnerable, and while substantial progress has been made in reducing the childhood mortality rate, disparities still exist across regions, countries, and socioeconomic statuses.
As a pediatric neurosurgeon, Penn State’s Steven Schiff has dedicated a significant portion of his career to the study and treatment of infectious disease, particularly brain diseases in children. Now, Dr. Schiff aims to apply innovative prediction models, similar to those used in forecasting the weather, in order to provide improved personalized treatment to patients battling infectious disease. Ultimately, the same strategies can be used for targeted prevention strategies for such infections.
Today, patients suffering from symptoms of infectious disease such as sepsis, flu-like illness, fever with rash, or meningitis, are typically all treated alike: By drawing samples for laboratory analysis, starting antibiotic therapy with the physician’s best guess as to the likely causes, and then hoping to learn the causative reason for the infection over a period of days from laboratory analysis.
Dr. Schiff’s vision is to move from reactive, delayed diagnoses to real-time treatment guidance using predictive models that incorporate historical microbiological surveillance data, geographic location of the patients, as well as environmental and climatic factors to determine the likely pathogens in order to narrow down the best treatment choices at the point of care.
“We have demonstrated that it is feasible to predict epidemic disease outbreaks from retrospective seasonal and geographical case data and have shown that we can take climate factors into account in our predictive models,” says Dr. Schiff. “But such predictive strategies have never been used in treatment of individual patients. We believe our approach to predictive personalized public health has the potential to substantially improve patient outcomes.”
This vision builds off of an extensive body of work by Dr. Schiff in infant hydrocephalus, which is fluid build-up in the brain as a result of infection that can lead to brain damage and death. In areas like Uganda and sub-Saharan Africa, infectious disease is the cause for the majority of cases of hydrocephalus which are estimated at about 100,000 to 200,000 cases each year. Factors such as rainfall play a significant role in the prevalence of many infectious diseases, so linking observations in weather patterns to patterns of epidemics and outbreaks seems logical.
