Population health informatics to counter epidemic threats: data integration and epidemic simulation
Many valuable datasets that could be used to counter epidemic threats are not used due to challenges in accessing and standardizing datasets, and in integrating data into novel analyses such as epidemic simulation. Our research aims to improve the acquisition, standardization, and integration of information about epidemic threats. We digitized and integrated a century of public health data for the United States to demonstrate that vaccines prevented 100 million disease cases and we used data on dengue fever from 8 countries in Southeast Asia to find that synchronous dengue transmission in this region coincided with elevated temperatures caused by El Niño. We are now improving the availability and usability of these, and other, data for epidemic simulation by re-representing datasets in a machine-readable format defined by the Apollo XML Schema Document. So far, we have re-represented information on Chikungunya virus epidemics from the scientific literature and from country epidemic reports using a combination of manual and automated data standardization methods. Based on this experience, we aim to standardize data for additional diseases, such as Zika virus, Dengue virus, HIV, and Cholera, towards a standard, global information system for epidemic simulation.