Related Experiment Video
Updated: Sep 23, 2025
07:13
Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
Published on: April 9, 2021
4.3K
Sampling Inspection Plan to Test Daily COVID-19 Cases Using Gamma Distribution under Indeterminacy Based on Multiple
Muhammad Aslam1, Gadde Srinivasa Rao2, Mohammed Albassam1
1Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia.
Summary
This study introduces a new multiple dependent state (MDS) sampling plan for COVID-19 case data using time-truncated schemes and gamma distribution under indeterminacy. The proposed plan requires a smaller sample size than existing methods.
Area of Science:
- Statistics
- Epidemiology
- Public Health
Background:
- The daily number of COVID-19 cases exhibits variability and uncertainty.
- Accurate and efficient sampling plans are crucial for monitoring disease spread.
- Existing sampling plans may not fully account for indeterminacy in case data.
Purpose of the Study:
- To develop a novel multiple dependent state (MDS) sampling plan for COVID-19 daily cases.
- To incorporate time-truncated sampling schemes and gamma distribution under indeterminacy.
- To compare the efficiency of the proposed plan with existing single sampling plans (SSP) and MDS plans.
Main Methods:
- Development of a multiple dependent state (MDS) sampling plan.
- Application of time-truncated sampling schemes.
- Utilizing gamma distribution under conditions of indeterminacy.
- Calculation of average sample number (ASN) and accept/reject criteria.
Main Results:
- The proposed MDS sampling scheme effectively handles indeterminacy in COVID-19 case data.
- Average sample number (ASN) decreases as indeterminacy values increase, highlighting the parameter's importance.
- The proposed MDS plan requires a smaller sample size compared to SSP and existing MDS plans.
Conclusions:
- The developed MDS sampling plan under indeterminacy is more efficient for COVID-19 surveillance.
- Indeterminacy is a significant factor influencing the average sample number (ASN).
- The proposed plan offers a more sample-size-efficient approach for monitoring daily COVID-19 cases.
Related Concept Videos
01:09Censoring Survival Data
259
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
259
01:23Sampling Plans
300
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
300
01:19Testing a Claim about Standard Deviation
2.5K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.5K
01:18Steps in Outbreak Investigation
225
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:
225
01:09Random Sampling Method
12.6K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
12.6K
01:17Wald-Wolfowitz Runs Test II
331
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
331