Strategies to Increase Response Rate and Reduce Nonresponse Bias in Population Health Research: Analysis of a Series of Randomized Controlled Experiments during a Large COVID-19 Study.

Background: High response rates are needed in population-based studies, as nonresponse reduces effective sample size and bias affects accuracy and decreases the generalizability of the study findings.

Objective: We tested different strategies to improve response rate and reduce nonresponse bias in a national population-based COVID-19 surveillance program in England, United Kingdom.

Methods: Over 19 rounds, a random sample of individuals aged 5 years and older from the general population in England were invited by mail to complete a web-based questionnaire and return a swab for SARS-CoV-2 testing.

Release of mineral-bound water prior to subduction tied to shallow seismogenic slip off Sumatra.

Plate-boundary fault rupture during the 2004 Sumatra-Andaman subduction earthquake extended closer to the trench than expected, increasing earthquake and tsunami size. International Ocean Discovery Program Expedition 362 sampled incoming sediments offshore northern Sumatra, revealing recent release of fresh water within the deep sediments. Thermal modeling links this freshening to amorphous silica dehydration driven by rapid burial-induced temperature increases in the past 9 million years.

The effect of mode and context on survey results: analysis of data from the Health Survey for England 2006 and the Boost Survey for London.

Background: Health-related data at local level could be provided by supplementing national health surveys with local boosts. Self-completion surveys are less costly than interviews, enabling larger samples to be achieved for a given cost. However, even when the same questions are asked with the same wording, responses to survey questions may vary by mode of data collection.

The effect of survey method on survey participation: analysis of data from the Health Survey for England 2006 and the Boost Survey for London.

Background: There is a need for local level health data for local government and health bodies, for health surveillance and planning and monitoring of policies and interventions. The Health Survey for England (HSE) is a nationally-representative survey of the English population living in private households, but sub-national analyses can be performed only at a regional level because of sample size. A boost of the HSE was commissioned to address the need for local level data in London but a different mode of data collection was used to maximise participant numbers for a given cost.