Biomedical
Using Nonprobabilistic Surveys to Measure COVID-19 Incidence
Jacob E. Simmering
Peer Reviewed
Abstract
Summary:
The article discusses the potential of nonprobability online surveys as an efficient and timely method for measuring COVID-19 incidence. These surveys, when integrated with wastewater surveillance data, provide useful estimates of disease spread, particularly in the absence of precise official case counts. They offer demographic insights and can be rapidly deployed, but they face challenges such as increased sampling noise in state-level data. The study highlights the importance of these surveys in public health decision-making and pandemic response.Key Questions
How do nonprobability online surveys compare to traditional COVID-19 case counts?
Nonprobability surveys correlate well with official case counts and wastewater data, particularly when traditional case counts became less reliable due to widespread home testing.
What are the advantages of using online surveys for disease monitoring?
Online surveys can be quickly deployed, provide demographic insights, and help identify affected populations more precisely than wastewater surveillance or clinical case counts.
What challenges are associated with using online surveys for public health data collection?
Survey data faces challenges such as sampling noise, particularly at state levels, and the need for strategies to maintain accurate demographic subgroup analysis.
How can nonprobability surveys enhance public health decision-making?
These surveys allow for real-time insights into disease spread and the identification of specific high-risk populations, informing timely public health interventions.
