computational epidemiology

USAGE SUMMARY

The phrase "computational epidemiology" is correct and usable in written English.
It can be used in contexts related to the study of disease patterns, causes, and effects using computational methods and data analysis. Example: "Researchers in computational epidemiology are using advanced algorithms to predict the spread of infectious diseases."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

9 human-written examples

Spergel suggested computational epidemiology and public health.

The New Yorker

Dr. Polgreen and collaborators in his computational epidemiology group at University of Iowa started gathering the anonymous ads to see what they could learn about patterns of sexual behavior in different regions.

The New York Times - Health

Epitrack is a Recife-based startup that uses crowdsourced data, AI and predictive analysis to combat outbreaks and epidemics through computational epidemiology.

TechCrunch

If you are a biological scientist with interest in this work, you may find the move into mathematical and computational epidemiology a bit more difficult; the best advice is to collaborate with someone who has a strong mathematical background.

Science Magazine

Two specific problems, computational epidemiology and human immune system modeling, are given as examples.

BMC Genomics

Below, we describe one of these domains, Computational Epidemiology, in greater detail.

BMC Genomics

Human-verified similar examples from authoritative sources

Similar Expressions

50 human-written examples

Mathematics, Computation, and Epidemiology Computational and mathematical epidemiology offers new and stimulating training and career opportunities, many of which are available at Rutgers Center for Discretee Mathematics and Theoretical Computer Science (DIMACS), notes Rutgers professor Fred Roberts.

Science Magazine

Publication charges for this article have been funded by the Training grant in Computational Genomic Epidemiology of Cancer (CoGE) (R25 CA094186-06).

BMC Genomics

While our results thus avoid these criticisms, since Levine et al.'s criticisms were meant to illustrate the general shortcomings of computer modeling, our results also argue against excessive skepticism about computational approaches in epidemiology.

Plosone

DIMACS has several postdoctoral fellowships available for work in computational and mathematical epidemiology.

Science Magazine

What kind of background do you need to work in computational and mathematical epidemiology?

Science Magazine

Expert writing Tips

Best practice

When writing about "computational epidemiology", clearly define the specific computational methods or models used in your study or analysis to provide clarity and context.

Common error

Avoid using "computational epidemiology" when simply referring to traditional epidemiological methods. Ensure your work incorporates significant computational techniques, data analysis, or modeling to warrant the term.

Linguistic Context

The phrase "computational epidemiology" functions as a noun phrase identifying a specific field of study. It combines the term "epidemiology" with the modifier "computational", indicating the use of computational methods in this field. Ludwig AI confirms its usability in written English.

Expression frequency: Uncommon

Frequent in

Science

60%

News & Media

40%

Formal & Business

0%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "computational epidemiology" is a term used to describe the application of computational methods to the study of epidemiology. Ludwig AI confirms this phrase is grammatically correct and usable in written English. The field involves using computational models and data analysis to understand disease patterns, predict outbreaks, and evaluate intervention strategies. It is most commonly found in scientific and news media contexts. While less frequent, its presence in these domains signifies its relevance in both research and public discourse. Key skills in this field include expertise in epidemiology, statistics, computer science, and mathematical modeling.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

digital epidemiology

This term highlights the use of digital tools and data in epidemiological studies.

data-driven epidemiology

This alternative emphasizes the importance of data in modern epidemiological studies, particularly those involving computational techniques.

epidemiological modeling

This alternative focuses on the modeling aspect used within epidemiology, rather than the computational methods themselves.

predictive epidemiology

This phrase highlights the predictive capabilities enabled by computational methods in epidemiology.

quantitative epidemiology

This term emphasizes the use of quantitative methods in epidemiology, which includes but isn't limited to computational approaches.

epidemiological informatics

This option emphasizes the use of informatics tools in the field of epidemiology.

simulation epidemiology

This emphasizes the use of simulation techniques to model disease spread and dynamics.

mathematical epidemiology

This phrase highlights the mathematical aspect of epidemiology, which is a close relative but doesn't necessarily imply computational implementation.

systems epidemiology

This suggests a more holistic, systems-based approach to epidemiological studies.

statistical epidemiology

This alternative focuses on the statistical methods used in epidemiological studies, but computational methods are a subset.

FAQs

How does "computational epidemiology" differ from traditional epidemiology?

"Computational epidemiology" uses computational methods, such as modeling and simulation, to study disease patterns, while traditional epidemiology relies more on observational studies and statistical analysis. However, modern epidemiology increasingly integrates "computational approaches".

What are some practical applications of "computational epidemiology"?

Practical applications include predicting disease outbreaks, simulating intervention strategies, and understanding the spread of infectious diseases. It's used to inform public health decisions and resource allocation.

What skills are needed to work in "computational epidemiology"?

Skills in epidemiology, statistics, computer science, and mathematical modeling are essential. Familiarity with programming languages and data analysis tools is also important.

What is the role of data in "computational epidemiology"?

Data is crucial for building and validating computational models. It provides insights into disease dynamics and informs the development of effective intervention strategies. "Data-driven epidemiology" enables more accurate predictions and informed decision-making.