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Related Concept Videos

Data Collection by Observations01:08

Data Collection by Observations

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Naturalistic Observations02:30

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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Updated: Jul 18, 2025

Visualizing Efficacy of Pesticides Against Disease Vector Mosquitoes in the Field
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Process and Methodological Considerations for Observational Analyses of Vector Control Interventions in Sub-Saharan

Sarah M Burnett1, Kelly M Davis1, Gudissa Assefa2

  • 1U.S. President's Malaria Initiative (PMI) VectorLink Project, PATH, Washington, District of Columbia.

The American Journal of Tropical Medicine and Hygiene
|August 21, 2023
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Summary
This summary is machine-generated.

National malaria control programs need better data for insecticide resistance and new tools. This guidance helps use routine health, entomological, and program data for effective vector control deployment decisions.

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Area of Science:

  • Public Health
  • Epidemiology
  • Vector Biology

Background:

  • Malaria control progress has stalled globally.
  • Insecticide resistance and new products necessitate data-driven vector control deployment.
  • National malaria control programs (NMCPs) require subnational decision-making frameworks.

Purpose of the Study:

  • Provide practical guidance for designing vector control evaluations.
  • Recommend key data variables and sources for subnational decision-making.
  • Propose methods to overcome data quality challenges in malaria control.

Main Methods:

  • Integrated observational longitudinal analyses of routine health, entomological, and program data.
  • Experience from 22 vector control evaluations across 14 sub-Saharan African countries.
  • Review of published and gray literature on vector control impact evaluations.

Main Results:

  • Key recommendations for parameterizing impact and coverage indicators.
  • Incorporation of diverse covariates: RDT stockouts, insecticide susceptibility, vector density, climate.
  • Emphasis on pre-evaluation data quality assessment (on-ground or remote).

Conclusions:

  • Enhanced utilization of routine data can improve malaria vector control strategies.
  • Data-driven subnational stratification is crucial for effective intervention deployment.
  • Strengthened data quality and integration support evidence-based national malaria control programs.