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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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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...
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Cluster Sampling Method01:20

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Appropriate sampling methods ensure 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.
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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. 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.
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Systematic Sampling Method01:17

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Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
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Related Experiment Video

Updated: Nov 28, 2025

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A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited

Alexander T Yu1, Rajani Shakya2, Bikram Adhikari2

  • 1Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, Stanford, California, USA.

Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
|December 1, 2020
PubMed
Summary

A new geographic information system (GIS) geosurvey simplified healthcare surveys in Nepal by eliminating the need for pre-enumeration. This innovative approach enhances population health research logistics and can be replicated for future community health studies.

Keywords:
SEAPcluster samplinggeospatial samplinghealthcare utilization surveytyphoid

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Area of Science:

  • Public Health
  • Epidemiology
  • Geographic Information Systems

Background:

  • Population-based surveys are resource-intensive and logistically complex, particularly in areas with dynamic demographics and incomplete population data.
  • Traditional methods often require pre-enumeration, adding significant time and cost.

Purpose of the Study:

  • To simplify field logistics for healthcare utilization surveys in Nepal for the Surveillance for Enteric Fever in Asia Project.
  • To remove the need for pre-enumeration of households in survey areas.

Main Methods:

  • Implemented a geographic information system (GIS)-based geosurvey and field mapping system.
  • Utilized a single-stage cluster sampling approach with digitally created grids from satellite imagery.
  • Developed a tablet-compatible geosurvey system for data syncing, functional in areas without cellular data.

Main Results:

  • Surveyed 25,521 households (84,202 individuals) in urban Kathmandu and periurban Kavrepalanchok between January 2017 and November 2018.
  • Achieved a high overall survey participation rate of 90.9%.
  • Observed geographic heterogeneity in participation rates, with lower rates in wealthier areas.

Conclusions:

  • A GIS-based geosurvey and field mapping system enabled virtual household mapping during survey administration.
  • This facilitated a single-stage cluster sampling method for assessing healthcare utilization in Nepal.
  • The system simplified logistics, eliminated pre-enumeration, and is replicable for future community surveys.