Exploring the Use of Wireless Emergency Alerts for Notifications Regarding Covid-19
Initial Lines of Inquiry
Bibliographic Data
| ID | 21738641 |
|---|---|
| Authors | Hamilton Bean (0000-0002-0987-4076, University of Denver), Nels Grevstad (0000-0002-6084-4956, Metropolitan State University of Denver), Alex Koutsoukos (University of Denver), Abigail Meyer (0000-0003-4202-6877, University of Denver) |
| Year | 2021 |
| Volume | 22 |
| Issue | 2 |
| Publication date | 2021-05-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Natural Hazards Review (JOURNAL) |
| Journal identifiers | ISSN: 1527-6988 • E-ISSN: 1527-6996 |
| Publisher | American Society of Civil Engineers (ASCE) (PUBLISHER • US) |
| DOI | 10.1061/(asce)nh.1527-6996.0000472 |
| OpenAlex | W3129006524 |
| Language | EN |
| Citations received | 4 |
| References cited | 10 |
US and international officials have sought ways to effectively use mobile technology to communicate health information to help thwart the spread of coronavirus disease 2019 (COVID-19). This study offers a preliminary exploration into the use of the state-level (N=6) and local-level (N=53) Wireless Emergency Alert (WEA) for notifications regarding COVID-19 in the US. The study compares changes in reported rates of infections and deaths between states and localities that issued WEA messages in March and April of 2020 with states that did not. Small sample sizes and differences in the rates of COVID-19 spread prohibit robust statistical analysis and detection of clear effect sizes, but estimated effects are generally in the right direction. Combining statistical analysis with preliminary categorization of both WEA message content and social media themes suggests that WEA messages might play an important role in instructing people to take protective in response to COVID-19. These initial lines of inquiry will be further developed in subsequent research
2019-20 coronavirus outbreak · Business · Categorization · Computer security · Data science · Disease · Internet privacy · Mobile device · Pathology · Social media · Statistical analysis · Statistics · Telecommunications · Wireless · World Wide Web · Computer Science · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · Mathematics · Medicine · Public Relations and Crisis Communication · Artificial Intelligence · Virology
| Unique citing works | 4 |
|---|---|
| Citations per year | 1,33 |
| Citation span | 2023 - 2025 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |