The MIT-BIH Arrhythmia Database contains 48 half-hour excerpts of two-channel ambulatory ECG recordings, obtained from 47 subjects studied by the BIH Arrhythmia Laboratory between 1975 and 1979. Twenty-three recordings were chosen at random from a set of 4000 24-hour ambulatory ECG recordings collected from a mixed population of inpatients (about 60%) and outpatients (about 40%) at Boston's Beth Israel Hospital; the remaining 25 recordings were selected from the same set to include less common but clinically significant arrhythmias that would not be well-represented in a small random sample.

The recordings were digitized at 360 samples per second per channel with 11-bit resolution over a 10 mV range. Two or more cardiologists independently annotated each record; disagreements were resolved to obtain the computer-readable reference annotations for each beat (approximately 110,000 annotations in all) included with the database.

This directory contains the entire MIT-BIH Arrhythmia Database. About half (25 of 48 complete records, and reference annotation files for all 48 records) of this database has been freely available here since PhysioNet's inception in September 1999. The 23 remaining signal files, which had been available only on the MIT-BIH Arrhythmia Database CD-ROM, were posted here in February 2005.

Much more information about this database may be found in the MIT-BIH Arrhythmia Database Directory.

Abstract

The COVID-19 Preventive Health Survey was designed to help policymakers and health researchers better monitor and understand people’s knowledge, attitudes and practices about COVID-19 to improve communications and their response to the pandemic. This survey is conducted in partnership between Facebook, the Massachusetts Institute of Technology (MIT), and Johns Hopkins University (JHU), with advice from the World Health Organization. Sampled users see the invitation at the top of their News Feed, but the surveys are collected off the Facebook app and the Facebook company does not collect or receive individual survey responses. The survey asks users to self-report their adherence to preventive measures, such as wearing masks and what they know about COVID-19, including symptoms of the disease, risk factors and how their community is handling the pandemic.

Geographic coverage

This survey was fielded in 67 countries and territories.

Wave Countries and Territories: Argentina, Bangladesh, Brazil, Colombia, Egypt, France, Germany, India, Indonesia, Italy, Japan, Malaysia, Mexico, Nigeria, Pakistan, Philippines, Poland, Romania, Thailand, Turkey, United Kingdom, United States, Vietnam

Snapshot Countries and Territories: Afghanistan, Algeria, Angola, Australia, Azerbaijan, Bolivia, Cambodia, Cameroon, Canada, Chile, Cote d’Ivoire, Ecuador, Estonia, Georgia, Ghana, Guatemala, Honduras, Iraq, Jamaica, Kazakhstan, Kenya, Mongolia, Morocco, Mozambique, Myanmar, Nepal, Netherlands, Peru, Portugal, Senegal, Singapore, South Africa, South Korea, Spain, Sri Lanka, Sudan, Taiwan, Tanzania, Trinidad & Tobago, Uganda, Ukraine, United Arab Emirates, Uruguay, Venezuela

Analysis unit

• Public Aggregate Data: Subnational levels
• Microdata through Facebook Data for Good program: Individual level

Universe

The target population consists of active Facebook users. The sampling frame is active Facebook users with ages 18+, which includes users living within 23 countries or territories. The sampling frame is restricted to people who use Facebook in one of the supported locales.

Kind of data

Sample survey data [ssd]

Sampling procedure

The target population consists of active Facebook users. The sampling frame is active Facebook users with ages 18+, which includes users living within 23 countries or territories. The sampling frame is restricted to people who use Facebook in one of the supported locales.

The Facebook app invites a sample of adult users to take an optional, off-Facebook survey through an invitation at the top of their Facebook News Feed. Users who click on the invitation are redirected to a Qualtrics page hosted by MIT where they are informed about the survey and can take the survey. While MIT designs, collects, and analyzes the survey data, Facebook provides assistance with questionnaire translation, survey sampling and recruitment, and statistical bias correction.

Mode of data collection

Internet [int]

Research instrument

The survey includes questions about self-reported preventive behaviors and knowledge and attitudes towards COVID-19 vaccines. The survey instrument is managed by MIT and available in more than 55 languages. Two versions of the survey were fielded across 67 countries and territories. Countries with sufficient sample sizes receive a “Wave Survey” that is fielded every 2 weeks between July 2020 and March 2021. The rest of the countries receive a periodic “Snapshot Survey”. Snapshot and wave surveys were developed based on feedback from global health partners so that information could be collected that is helpful to inform public health responses even in areas with fewer survey respondents. As of Spring 2021, some questions from the survey have been merged with the larger Covid-19 Trends and Impact Survey. The full survey instrument is available here.

The snapshot survey was fielded to 44 countries and territories with a one-time sample over a 2 week period. A follow up sample was done in late 2020 of snapshot countries and territories to provide updated information.

The wave survey was fielded to 23 countries and territories with repeated, bi-monthly cross-sections. Each of the 8 waves is two weeks long. Sampled users may be invited to take the survey again in subsequent weeks, depending on the density of their area. However, the responses of sampled users who participate more than once will not be linked longitudinally.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Facebook provides MIT (and other researchers) with analytic weights that adjust for non-response and coverage biases. Making adjustments using the weights ensures that the sample more accurately reflects the characteristics of the target population represented.

Data appraisal

Non-Response Bias This means that some sampled users are more likely to respond to the survey than others. To adjust for this, Facebook calculates the inverse probability that sampled users complete the survey using their self-reported age and gender as well as other characteristics known to correlate with nonresponse. Then these inverse probabilities are used to create weights for responses, after which the survey sample reflects the active adult user population on the Facebook app.

Coverage Bias This means not everyone in every country has a Facebook app account or uses their account regularly. To adjust for this, Facebook adjusts the weights created in the first step even further so that the distribution of age, gender, and administrative region of residence in the survey sample reflects that of the general population.

Seasonal environmental heterogeneity is cyclic, persistent and geographically widespread. In species that reproduce multiple times annually, environmental changes across seasonal time may create different selection regimes that may shape the population ecology and life history adaptation in these species. Here, we investigate how two closely related species of Drosophila in a temperate orchard respond to environmental changes across seasonal time. Natural populations of Drosophila melanogaster and D. simulans were sampled at four timepoints from June through November to assess seasonal change in fundamental aspects of population dynamics as well as life history traits. D. melanogaster exhibit pronounced change across seasonal time: early in the season, the population is inferred to be uniformly young and potentially represents the early generation following overwintering survivorship. D. melanogaster isofemale lines derived from the early population and reared in a common garden are characterized by high tolerance to a variety of stressors as well as a fast rate of development in the laboratory environment that declines across seasonal time. In contrast, wild D. simulans populations were inferred to be consistently heterogeneous in age distribution across seasonal collections; only starvation tolerance changed predictably over seasonal time in a parallel manner as in D. melanogaster. These results suggest fundamental differences in population and evolutionary dynamics between these two taxa associated with seasonal heterogeneity in environmental parameters and associated selection pressures.