Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Single Nucleotide Polymorphisms-SNPs

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Residuals and Least-Squares Property

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

Pareto Chart

Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Business forecasting methods: Impressive advances, lagging implementation.

PloS one·2023

Same author

Improving the forecasting performance of temporal hierarchies.

PloS one·2019

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 25, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

Forecasting the novel coronavirus COVID-19.

Fotios Petropoulos¹, Spyros Makridakis²

¹School of Management, University of Bath, Bath, United Kingdom.

|April 2, 2020

Summary

Forecasting COVID-19 spread requires reliable data and historical patterns. Our objective method predicts continued case increases, highlighting the severe risks of underestimating this pandemic.

Area of Science:

Epidemiology
Public Health
Data Science

Background:

Accurate forecasting of COVID-19 spread, deaths, and recoveries is crucial for understanding global impact.
Forecasting relies on historical data, but predictions are uncertain due to past unpredictability and influencing factors.
Psychological responses to disease danger and personal risk perception significantly impact public reactions.

Purpose of the Study:

To introduce an objective methodology for predicting the continuation of COVID-19.
To provide reliable forecasts for confirmed COVID-19 cases.
To inform planning and decision-making through a live forecasting exercise.

Main Methods:

Utilizing a simple yet powerful objective approach for COVID-19 prediction.

More Related Videos

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Published on: November 5, 2021

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

Related Experiment Videos

Last Updated: Dec 25, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Live Imaging and Quantification of Viral Infection in K18 hACE2 Transgenic Mice Using Reporter-Expressing Recombinant SARS-CoV-2

Published on: November 5, 2021

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

Assuming data reliability and that future disease patterns will mirror past trends.

Conducting a live forecasting exercise to assess pandemic progression.

Main Results:

Forecasts indicate a continuing increase in confirmed COVID-19 cases.
Significant associated uncertainty accompanies the case increase predictions.
The study emphasizes the asymmetric risks of underestimating pandemic spread versus over-preparation.

Conclusions:

Objective forecasting of COVID-19 is achievable with reliable data and consistent patterns.
Underestimating the pandemic poses a far greater risk than over-conservatism in containment efforts.
The described forecasting exercise offers valuable insights for public health planning and policy.