1Australian Institute of Health Service Management, College of Business and Economics, University of Tasmania, Sydney, Australia
2School of Population Health, Faculty of Medicine & Health, University of New South Wales, Sydney, Australia
3School of Psychological Sciences, College of Health and Medicine, University of Tasmania, Hobart, Australia
4Department of Marketing, College of Business and Economics, University of Tasmania, Hobart, Australia
© 2023 Korea Disease Control and Prevention Agency.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Ethics Approval
Not applicable.
Conflicts of Interest
The authors have no conflicts of interest to declare.
Funding
None.
Availability of Data
All data generated and analyzed during this study are included in this published article. Other data may be requested through the corresponding author.
Authors’ Contributions
Conceptualization: all authors, AH; Design: all authors; Methodology: all authors; Supervision: AH, NK, LY, MA; Literature review: BAB, AH; Validation: all authors; Visualization: BAB; Writing–original draft: BAB; Writing–review & editing: all authors. All authors read and approved the final manuscript.
Additional Contributions
The authors are grateful to the librarians at the University of Tasmania who provided guidance on the use of the SPIDER tool and electronic database search.
Serial no. | Infectious diseases |
PHEIC status |
Pandemic statusa) | ||
---|---|---|---|---|---|
Considered | Announced | Duration (d) | |||
1 | Poliomyelitis | Yes | Yes | 3,303 (ongoing) | No |
2 | COVID-19 | Yes | Yes | 1,192 | Yes |
3 | Ebola (first outbreak) | Yes | Yes | 600 | Yes |
4 | H1N1 influenza | Yes | Yes | 473 | Yes |
5 | Ebola (third outbreak) | Yes | Yes | 346 | No |
6 | Zika | Yes | Yes | 292 | Yes |
7 | Monkeypox | Yes | Yes | 293 | No |
8 | SARSb) | No | No | - | Yes |
9 | MERS | Yes | No | - | Yes |
10 | Ebola (second outbreak) | Yes | No | - | No |
11 | Yellow fever | Yes | No | - | No |
PHEIC, public health emergency of international concern; SARS, severe acute respiratory syndrome; MERS, Middle East respiratory syndrome.
a) The authors used the definition of Doshi [4] as a criterion.
b) SARS did not undergo a PHEIC evaluation as it predates the revised International Health Regulations policy of the World Health Organization. It was called “a worldwide health threat” instead.
Theoretical frameworks used for data analysis | No. of studies |
---|---|
Crisis and emergency risk communication model [15,18,29,37−40] | 7 |
Health belief model [41−45] | 5 |
Media richness theory [46,47] | 2 |
Social amplification of risks framework [48,49] | 2 |
Agenda-setting theory [50] | 1 |
Dialogic accounting framework [27] | 1 |
Dialogic communication theory [46] | 1 |
Disaster communication ecology framework [51] | 1 |
Extended parallel process model [52] | 1 |
Frame theory [53] | 1 |
Mixed game model [54] | 1 |
Public value theory [47] | 1 |
Socially mediated crisis communication model [49] | 1 |
Total | 25a) |
Level of PHA |
Focus of study |
||
---|---|---|---|
Single PHA | Multiple PHAs (one country) | Multiple PHAs (multiple countries) | |
Global | 4 | 7 | 4 |
National | 24 | 19 | 10 |
State | 0 | 14 | 0 |
Local | 3 | 10 | 0 |
Total | 31 | 30 | 12 |
Serial no. | Infectious diseases | PHEIC status |
Pandemic status |
||
---|---|---|---|---|---|
Considered | Announced | Duration (d) | |||
1 | Poliomyelitis | Yes | Yes | 3,303 (ongoing) | No |
2 | COVID-19 | Yes | Yes | 1,192 | Yes |
3 | Ebola (first outbreak) | Yes | Yes | 600 | Yes |
4 | H1N1 influenza | Yes | Yes | 473 | Yes |
5 | Ebola (third outbreak) | Yes | Yes | 346 | No |
6 | Zika | Yes | Yes | 292 | Yes |
7 | Monkeypox | Yes | Yes | 293 | No |
8 | SARS |
No | No | - | Yes |
9 | MERS | Yes | No | - | Yes |
10 | Ebola (second outbreak) | Yes | No | - | No |
11 | Yellow fever | Yes | No | - | No |
1 | AB=(("social media" OR "social networking site*" OR Facebook OR Twitter OR YouTube OR Weibo OR Instagram OR WeChat OR TikTok OR "online social network*") OR ti("social media" OR "social networking site*" OR Facebook OR Twitter OR YouTube OR Weibo OR Instagram OR WeChat OR TikTok OR "online social network*") OR if("social media" OR "social networking site*" OR Facebook OR Twitter OR YouTube OR Weibo OR Instagram OR WeChat OR TikTok OR "online social network*")) |
2 | AB=(("health messag*" OR "public health" OR "health policy" OR "health campaign" OR "health promotion" OR "health information" OR "false health information" OR misinformation OR disinformation OR "health behavio?r" OR "health literacy" OR "health communication") OR ti("health messag*" OR "public health" OR "health policy" OR "health campaign" OR "health promotion" OR "health information" OR "false health information" OR misinformation OR disinformation OR "health behavio?r" OR "health literacy" OR "health communication") OR if("health messag*" OR "public health" OR "health policy" OR "health campaign" OR "health promotion" OR "health information" OR "false health information" OR misinformation OR disinformation OR "health behavio?r" OR "health literacy" OR "health communication")) |
3 | AB=((pandemic* OR MERS OR Zika OR SARS* OR H1N1 OR Ebola OR COVID* OR coronavirus OR "acute communicable disease*" OR "emerging communicable disease*" OR "acute infectious disease*" OR "acute communicable disease*") OR ti(pandemic* OR MERS OR Zika OR SARS* OR H1N1 OR Ebola OR COVID* OR coronavirus OR "acute communicable disease*" OR "emerging communicable disease*" OR "acute infectious disease*" OR "acute communicable disease*") OR if(pandemic* OR MERS OR Zika OR SARS* OR H1N1 OR Ebola OR COVID* OR coronavirus OR "acute communicable disease*" OR "emerging communicable disease*" OR "acute infectious disease*" OR "acute communicable disease*")) |
4 | 1 AND 2 AND 3 |
Characteristic | No. of papers (%) |
---|---|
Publication year | |
2010−2014 | 2 (2.7) |
2015−2019 | 16 (21.9) |
2020−2022 | 55 (75.3) |
Pandemic of focus | |
COVID-19 | 54 (74.0) |
Ebola | 9 (12.3) |
Zika | 7 (9.6) |
H1N1 | 3 (4.1) |
SARS, MERS | 0 (0) |
Country of study | |
USA | 31 (42.5) |
China | 9 (12.3) |
Canada, Singapore | 5 (6.8) |
India, Italy, Norway | 3 (4.1) |
Saudi Arabia, Spain, UK | 2 (2.7) |
Australia, Denmark, Finland, Israel, UAE, Philippines, Portugal, Romania | 1 (1.4) |
Social media data source | |
66 Single sources (90%) | |
26 (39.4) | |
25 (37.9) | |
Sina Weibo | 4 (6.1) |
Instagram, WeChat, YouTube | 3 (4.5) |
TikTok | 2 (3.0) |
7 Multiple sources (10%) | |
7 (100) | |
5 (71.4) | |
Instagram, YouTube | 3 (42.9) |
LinkedIn, Pinterest | 1 (14.3) |
Study methodological approach/design | |
Mixed | 15 (20.5) |
Qualitative | 27 (37.0) |
Quantitative | 31 (42.5) |
Country of focus (multiple countries=12) | |
USA | 32 (43.8) |
WHO | 15 (20.5) |
China | 8 (11.0) |
Singapore | 7 (9.6) |
Canada | 6 (8.2) |
Italy, England | 4 (5.5) |
Norway, India | 3 (4.1) |
Saudi Arabia, Denmark, Brazil, Australia, Nigeria, South Africa, New Zealand | 2 (2.7) |
UAE, Spain, Romania, Philippines, Macao, Israel, Portugal, Sweden, Gambia, Chile, South Sudan, Namibia, Germany, Botswana, Ethiopia, Kenya, Liberia, Malawi, Rwanda, Sierra Leone, Zimbabwe, Sudan, Ghana, Tanzania, Uganda, Zambia, UK | 1 (1.4) |
Theoretical frameworks used for data analysis | No. of studies |
---|---|
Crisis and emergency risk communication model [15,18,29,37−40] | 7 |
Health belief model [41−45] | 5 |
Media richness theory [46,47] | 2 |
Social amplification of risks framework [48,49] | 2 |
Agenda-setting theory [50] | 1 |
Dialogic accounting framework [27] | 1 |
Dialogic communication theory [46] | 1 |
Disaster communication ecology framework [51] | 1 |
Extended parallel process model [52] | 1 |
Frame theory [53] | 1 |
Mixed game model [54] | 1 |
Public value theory [47] | 1 |
Socially mediated crisis communication model [49] | 1 |
Total | 25 |
Level of PHA | Focus of study |
||
---|---|---|---|
Single PHA | Multiple PHAs (one country) | Multiple PHAs (multiple countries) | |
Global | 4 | 7 | 4 |
National | 24 | 19 | 10 |
State | 0 | 14 | 0 |
Local | 3 | 10 | 0 |
Total | 31 | 30 | 12 |
Serial no. | Themes/sub-themes (% of reported paper) | Description of sub-themes |
---|---|---|
1 | Origin of health information (85) | |
1.1 | Status (59) | Experience and reputation of pandemic or public health crisis management |
1.2 | Tactics (59) | Granular approach adopted for social media communication |
1.3 | Policy (40) | Use of guidelines and regulation for social media communication |
1.4 | Personnel (12) | Those responsible for content creation and sharing, and resource management |
2 | Topical issues addressed (85) | |
2.1 | Education (73) | Public awareness about the pandemic and subsequent actions to take |
2.2 | Government efforts (37) | Communication of specific actions by (health) authorities |
2.3 | Collaboration (36) | Call for concerted support to tackle the pandemic |
2.4 | News update (34) | Highlights and breaking stories about the pandemic spread |
2.5 | Misinformation (33) | Communication addressing the menace of inaccurate information |
2.6 | Ancillary messages (29) | Non-pandemic related messages important for sustaining public health |
3 | Structure and style of messaging (75) | |
3.1 | Dialogue tools (63) | Incorporation of dialogic elements to trigger feedback and engagement |
3.2 | Media richness (44) | Incorporation of enriching elements to trigger feedback and engagement |
3.3 | Tone (23) | Incorporation of emotional tone to trigger feedback and engagement |
4 | Diversity of platforms and audience profile (68) | |
4.1 | Platforms (58) | Relevant summary attributes of social media platforms for health information |
4.2 | Community (53) | Followers, subscribers, and users of PHAs’ social media accounts |
5 | Timeliness and relevance (67) | |
5.1 | Milestones and phases (66) | Messaging in accordance with specific pandemic events and stages |
5.2 | Frequency (10) | Regularity of messaging |
6 | Content credibility and reliability (62) | |
6.1 | Congruence (41) | Collaboration among PHAs to share similar messages |
6.2 | Consistency (16) | Coherence of a PHA’s health messages to meet public information demands |
6.3 | Transparency (15) | Perceived openness and forthrightness in communication |
PHEIC, public health emergency of international concern; SARS, severe acute respiratory syndrome; MERS, Middle East respiratory syndrome. The authors used the definition of Doshi [ SARS did not undergo a PHEIC evaluation as it predates the revised International Health Regulations policy of the World Health Organization. It was called “a worldwide health threat” instead.
*, allows for different search term endings; ?, allows for both British and American spelling.
SARS, severe acute respiratory syndrome; MERS, Middle East respiratory syndrome; USA, United States of America; UK, United Kingdom; UAE, United Arab Emirates; WHO, World Health Organization.
Three studies used 2 frameworks each for data analysis.
PHA, public health agency.
PHA, public health agency.