Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-28T13:41:21.625Z Has data issue: false hasContentIssue false
  • English
  • Français

Your Call Is Important to Us: COVID-19 and Trends in Public Health Unit Call Service Utilization

Published online by Cambridge University Press:  12 July 2021

Zachary B. Horn ,
Alexandra M. Uren  and
Megan K. Young
Zachary B. Horn*
Affiliation:
Griffith University School of Medicine, Queensland, Australia
Alexandra M. Uren
Affiliation:
Metro North Public Health Unit, Queensland, Australia
Megan K. Young
Affiliation:
Griffith University School of Medicine, Queensland, Australia Metro North Public Health Unit, Queensland, Australia University of Queensland School of Public Health, Queensland, Australia
*
Corresponding author: Zachary Horn, Email [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

The aim of this study was to analyze coronavirus disease 2019 (COVID-19) -related call data at Metro North Public Health Unit, Brisbane Australia, over the 2020 calendar year to assist surge preparedness.

Methods:

Call data were retrieved by call category or reference to “COVID” in summaries from the call management system at a large metropolitan public health service. Under a mixed-methods approach, qualitative data (caller, call purpose, and call outcome) were categorized with categories arising de novo. Resulting variables were numerically analyzed to identify trends by categories and time.

Results:

Of the 3468 calls retrieved, 160 duplicates and 26 irrelevant calls were excluded. Of 3282 included calls, general practitioners, followed by the public, contributed the greatest call volumes. Health-care–related callers and the public made 84.2% of calls. Calls most frequently related to patient testing (40.7%) and isolation/quarantine (23.2%). Education provision accounted for 29.4% of all outcomes. A total of 11.8% of all call outcomes involved applying relevant case definitions, and 49.1% of calls were identified as potentially preventable through effective emergency risk communication and targeted call-handling.

Conclusions:

This study identified key drivers of public health unit phone service use related to the COVID-19 pandemic throughout 2020. The results highlighted where risk perception influenced call volume and provided important insights for future public health preparedness.

Keywords

COVID-19disaster planninginformation-seeking behaviorpublic healthrisk communication
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 16 , Issue 6 , December 2022 , pp. 2583 - 2590
Copyright
© Society for Disaster Medicine and Public Health, Inc. 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

World Health Organization. Communicating risk in public health emergencies: a WHO guideline for emergency risk communication (ERC) policy and practice. World Health Organization. 2017. https://apps.who.int/iris/bitstream/handle/10665/259807/9789241550208-eng.pdf?sequence=2. Accessed January 13, 2020.Google Scholar
Constantino, C, Fiacchini, D. The rationale of the WHO document on Risk Communication and Community Engagement (RCCE) readiness and response to the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and of the Italian Decalogue for Prevention Departments. J Prev Med Hyg. 2020;61(1):e1-e2. doi: 10.15167/2421-4248/jpmh2020.61.1.1502 Google Scholar
Hsu, Y, Chen, Y, Wei, H, et al. Risk and outbreak communication: lessons from Taiwan’s experiences in the post-SARS era. Health Secur. 2020;13(2):165-169. doi: 10.1089/hs.2016.0111 Google Scholar
Abrams, E, Greenhawt, M. Risk communication during COVID-19. J Allergy Clin Immunol Pract. 2020;8:1791-1794. doi: 10.1016/j.jaip.2020.04.012 Google ScholarPubMed
Cucinotta, D, Vanelli, M. WHO declares COVID-19 a pandemic. Acta Biomed. 2020;91(1):157-160. doi: 10.23750/abm.v91i1.9397 Google ScholarPubMed
Garfin, D, Silver, R, Holman, A. The novel coronavirus (COVID-2019) outbreak: amplification of public health consequences by media exposure. Health Psychol. 2020;39(5):355-357. doi: 10.1037/hea0000875 Google ScholarPubMed
Bento, A, Nguyen, T, Wing, C, et al. Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases. Proc Natl Acad Sci U S A. 2020;117(21):11220-11222. doi: 10.1073/pnas.2005335117 CrossRefGoogle ScholarPubMed
Liebermann-Cribbin, W, Alpert, N, Gonzalez, A, et al. Three months of informational trends in COVID-19 across New York City. J Public Health. 2020;42(3):448-450. doi: 10.1093/pubmed/fdaa082 Google Scholar
Falcone, R, Sapienza, A. How COVID-19 changed the information needs of Italian citizen. Int J Environ Res Public Health. 2020;17:3988. doi: 10.3390/ijerph17196988 Google Scholar
Rovetta, A, Bhagavathula, A. COVID-19-related web search behaviours and infodemic attitudes in Italy: infodemiological study. J Med Internet Res. 2020;6(2):e19374. doi: 10.2196/19374 Google ScholarPubMed
Liu, P. COVID-19 information seeking on digital media and preventive behaviours: the mediation role of worry. Cyberpsychol Behav Soc Netw. 2020;23(10):677-682. doi: 10.1089/cyber.2020.025 CrossRefGoogle ScholarPubMed
Ning, L, Niu, K, Bi, X, et al. The impacts of knowledge, risk perception, emotion and information on citizens’ protective behaviours during the outbreak of COVID-19: a cross-sectional study in China. BMC Public Health. 2020;20(1):1751. doi: 10.1186/s12889-020-09892-y Google ScholarPubMed
Brennen, S, Simon, F, Howard, P, et al. Types, sources, and claims of COVID-19 misinformation. Oxford: Reuters Institute for the Study of Journalism. 2020. http://www.primaonline.it/wp-content/uploads/2020/04/COVID-19_reuters.pdf. Accessed January 13, 2020.Google Scholar
Barua, Z, Barua, S, Aktar, S, et al. Effects of misinformation on COVID-19 individual responses and recommendations for resilience of disastrous consequences of misinformation. Prog Disaster Sci. 2020;8:100119. doi: 10.1016/j.pdisas.2020.100119 Google ScholarPubMed
ABC News. Queensland’s coronavirus timeline: how COVID-19 cases spread around the state. ABC News. September 25, 2020. https://www.abc.net.au/news/2020-03-28/coronavirus-timeline-queensland-tracking-spread/12077602?nw=0. Accessed February 22, 2021.Google Scholar