Computational epidemiology is a multidisciplinary field that uses techniques from

computer science Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, ...

mathematics Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many ar ...

geographic information science Geographic information science (GIScience, GISc) or geoinformation science is a scientific discipline at the crossroads of computational science, social science, and natural science that studies geographic information, including how it represe ...

and

public health Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals". Analyzing the de ...

to better understand issues central to

epidemiology Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and Risk factor (epidemiology), determinants of health and disease conditions in a defined population, and application of this knowledge to prevent dise ...

such as the spread of diseases or the effectiveness of a public health intervention. Computational epidemiology traces its origins to mathematical epidemiology, but began to experience significant growth with the rise of

big data Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data processing, data-processing application software, software. Data with many entries (rows) offer greater statistical power, while data with ...

and the democratization of high-performance computing through

cloud computing Cloud computing is "a paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources with self-service provisioning and administration on-demand," according to International Organization for ...

Introduction

In contrast with traditional

, computational epidemiology looks for patterns in unstructured sources of data, such as social media. It can be thought of as the hypothesis-generating antecedent to hypothesis-testing methods such as national surveys and randomized controlled trials. A mathematical model is developed which describes the observed behavior of the viruses, based on the available data. Then simulations of the model are performed to understand the possible outcomes given the model used. These simulations produce as results projections which can then be used to make predictions or verify the facts and then be used to plan interventions and meters towards the control of the disease's spread.

References

External links

Sax Institute - Decision Analytics

Computational Epidemiology Lab
Computational science Epidemiology {{med-stub