|Reference||Context||Aim||Method and sample||Types of outcomes||Modes of communication|
|Multiple information sources and channels||Lin et al. ||H1N1||To investigate the effect of socioeconomic status and health communication behaviours (including barriers) on people’s knowledge and misconceptions about pandemic influenza A(H1N1) (pH1N1) and adoption of prevention behaviours.||Cross sectional survey with a representative sample (response rate 66%) (N = 1569), > 18 years old. USA.||Socioeconomic status, health communication behaviours, knowledge, misconceptions, barriers to information processing. Sources of information.||
Multiple information sources.|
Multiple channels, local television news, national network news, internet, health care professionals, local newspapers, social media.
|Jardine et al. ||(SARS) and H1N1||Report on public information use, together with assessed usefulness and credibility, in the province of Alberta, Canada during both the SARS epidemic and H1N1 pandemic.||
Comparative survey study.|
Survey collecting data on the SARS epidemic, representative sample (response rate 47%) (N = 1209). Canada.
Survey collecting data about the H1N1 pandemic, representative sample (response rate 21%) (N = 1206). Canada.
|Information sources used (public information seeking), perceptions (usefulness and credibility of information sources).||Multiple information sources, traditional media, social media, friends, doctors, families.|
|Al-Hasan et al. ||COVID-19||
A comparative evaluation of citizens’ adherence process to COVID-19-relevant|
recommendations by the government.
Cross-sectional survey with a random sample (N = 482), 43% USA, 38%|
Kuwait, 20% South Korea.
|Self-adherence to COVID-19 recommendations, information channels reported.||Multiple information sources, newspapers, television, friends, doctors, families and social sources.|
|Alanezi et al. ||COVID-19||
To investigate the situational awareness about COVID-19 in Saudi Arabia and the|
importance of information sources, information types, and communication channels for creating awareness among the people in Saudi Arabia.
|Cross-sectional survey with a non-representative sample (response rate 39%). (N = 591), > 18 years old. Saudi Arabia.||Situational awareness (factual knowledge about transmission symptoms and treatment), information sources used, source credibility.||
Multiple information sources|
Online governmental portals and SMS.
The Ministry of Health, family and friends as sources of information.
|Ali et al. ||COVID-19||This study assessed sociodemographic predictors of the use and trust of different COVID-19 information sources, as well as the association between information sources and knowledge and beliefs about the pandemic.||Cross sectional survey study. Self-selected nonprobability sample (N = 11,242), > 18 years old. USA.||Source credibility, information sources reported.||Multiple communication channels. Government websites, television, radio, podcasts, or newspapers.|
|Lep et al. ||COVID-19||How people search for information, how they perceive its credibility, and how all this relates to their engagement in self-protective behaviours in the crucial period right after the onset of COVID-19.||Cross-sectional survey study. (response rate 43%), (N = 1718), 18–81 years old. Slovenia.||Self-protective behaviour and credibility of information sources.||Multiple information sources. Online news portals, television news, social media, official webpage for health risk information, radio. Officials and health care professionals as sources.|
|Meier et al. ||COVID-19||To describe the public belief in the effectiveness of protective measures, the reported implementation of these measures, and to identify communication channels used to acquire information on COVID-19 in European countries during the early stage of the pandemic.||Cross-sectional survey study. (N = 9796), Netherland (N = 8611), Germany (N = 604), Italy (N = 581). 20–70 years old.||Information channels most commonly reported. Accurate information and belief in the effectiveness of protective measures.||Multiple information sources most commonly reported included television newspapers, official health websites, and social media.|
|Parsons Leigh et al. ||COVID-19||
We assessed self-reported public perceptions related to|
COVID-19 including beliefs (e.g., severity, concerns, health), knowledge (e.g., transmission,
information sources), and behaviours (e.g., physical distancing) to understand perspectives in Canada and to inform future public health initiatives.
|Cross-sectional survey with a representative sample (N = 1996), 18–65 years old. Canada.||Perceptions related to COVID-19, knowledge related to transmission, information sources, and physical distancing behaviour.||
Multiple information sources|
Traditional media sources, print, family, friends, scientific articles, non-government and government and public health websites and social media posts from private sources and from the government.
|Reddy et al. ||COVID-19||To assess South Africans’ understanding of and response to COVID-19 during the first week of the country’s lockdown period.||Cross-sectional survey (N = 55,823). (≥18 years old). South Africa.||Risk perception, knowledge, trust in information sources, access to information sources, opinions.||Multiple information sources. Government sources, scientific journals, personal doctors, satellite television, radio, local television, print, online news, family, friends, SMS and email.|
|Riiser et al. ||COVID-19||To describe adolescents’ health information sources and knowledge, health literacy, health protective measures, and health-related quality of life (HRQoL) during the initial phase of the Covid-19 pandemic in Norway. Second, to investigate the association between HL and the knowledge and behaviour relevant for preventing spread of the virus. Third, to explore variables associated with HRQoL in a pandemic environment.||Cross-sectional survey study. (N = 2205), 16–19 years old. Norway.||Information sources used. Health literacy (information that is easy to understand).||Multiple information sources, television and family.|
|Liao et al. ||H1N1||To examine how levels of trust in formal and informal sources of risk/prevention information associated with hand washing and social distancing.||Cross sectional survey study with a representative random sample (response rate 69%), (N = 1001), ≥18 years old. Hong Kong.||Source credibility, situational awareness (understanding the cause of H1N1), attitudes, risk perception, reported self-protective behaviour.||Multiple information sources, formal (government/media) information, informal (interpersonal) information.|
|Fridman et al. ||COVID-19||To investigate associations between public knowledge about COVID-19, adherence to social distancing, and public trust in government information sources and private sources (e.g., FOX and CNN), and social networks to inform future policies related to critical information distribution.||
Cross sectional survey study with representative sample|
(N = 1243), ≥18 years old USA.
|Source credibility, information sources reported, adherence to social distancing.||Multiple information sources, government sources (webpages), private sources (Twitter, social media, CNN).|
|King et al. ||H1N1||
This study aimed to gain an understanding of parental information seeking, trusted sources and needs in|
relation to pandemic influenza A 2009 (pH1N1) to inform future policy planning and resource development.
Mixed method study. Survey study (N = 431), (response rate 44%). Parents from 16 childcare centres in Sydney.|
Qualitative in-depth interviews with 42 parents. Sydney.
|Information seeking strategies, trusted sources.||Multiple information sources, mass media, hospital and governmental websites, doctors, childcare centres and schools, celebrities, anti-vaccination groups as source of information, mass media, WHO, CDC.|
|Liu et al. ||COVID-19||This study aimed to clarify the influencing factors for the anxiety level among the Chinese people during the COVID-19 pandemic, with a particular focus on the media exposure to different COVID-19 information.||Cross sectional survey with nonrepresentative sample (N = 4991), (response rate 18%), Age 18–61 years old. China.||Risk perception, media exposure, social and geographical proximity to COVID-19.||Multiple information sources. Television, radio, newspaper, interpersonal, weechat, weibo, tiktok, online news website, search engines.|
|Gesser-Edelsburg et al. ||COVID-19||To examine the response of the Israeli public to the government’s emergency instructions regarding the pandemic in terms of correlations between overall risk perception and crisis management; overall risk perception and economic threat perception; crisis management and compliance with behavioural guidelines; and crisis management and economic threat perception.||Cross sectional survey with nonprobability sampling (N = 1056), general public, 18–95 years old). Israel.||Spokesperson’s credibility, trust and health literacy.||Scientific articles, WHO websites, hospital websites.|
|Zhang et al. ||COVID-19||The objective of this paper is to illustrate the effective process and attention points of risk communication reflecting on the COVID-19 outbreak in Wuhan, China.||Qualitative case study consisting of document analysis and interviews and interviews with governmental officials and experts. China.||Lessons from Wuhan.||Chinese authoritative media and mainstream internet media, social media.|
|Mass media||Hall and Wolf ||H1N1||To examine the projected expectations towards the behaviour of the audiences and the projected ways of information circulation informing public health communication strategies during a pandemic.||Qualitative interviews with 31 participants across sectors, including public health agencies. Germany.||Content and framing of messages.||Mass media.|
|Rossmann et al. ||H1N1||To determine whether media did amplify the A/H1N1- related risks as they were accused of.||A quantitative content analysis of 243 press releases, 1243 quality press and 834 tabloid press articles from WHO, CDC, ECDC, EU Public Health and health ministries in the 10 selected EU countries, between March 2009 and March 2011. Global.||Content of the message, framing of messages.||Newspapers, press releases.|
|Basnyat et al. ||H1N1||To understand how public health messages provided by the government in Singapore during an Influenza.||Qualitative thematic analysis of 308 government-issued press releases disseminating public health information about H1N1 that was directly linked to news stories (N = 56) and news stories about H1N1 generated by the newspaper (N = 253). Singapore.||News coverage (framing).||Press releases, newspapers|
|Cloes et al. .||H1N1||We aimed to assess professional stakeholders’ perceptions of the risk-communication difficulties faced during the 2009 influenza A pandemic in Europe.||Qualitative interviews with 25 experts from 8 European countries were interviewed: 9 from the micro-level, 10 from the meso-level, and 6 from the macro-level of employment.||Trust, perception of risk communication.||Mass media.|
|Luth et al. ||H1N1||We analyse (1) the content of television news about the H1N1 pandemic and vaccination campaign in Alberta, Canada; (2) the extent to which television news content conveyed key public health agency messages; (3) the extent of discrepancies in audio versus visual content.||Qualitative grounded theory analysis of 47 news clips sampled from the CTV online video archive, and semi-structured interviews with five journalists. Canada.||
Content of news, discrepancies in audio|
versus visual content.
|Television news, video and audio content.|
|Websites and online platforms||Khan et al. ||COVID-19||To investigate the readability and presence of translated online information readily available to the British public during COVID-19.||
Cross sectional web study of google search hits. National Health Service and government websites.|
Assessed for readability using multiple validated scales. UK.
|Readability, health literacy.||Websites.|
|Szmuda et al. ||COVID-19||To assess the readability of online information regarding the novel coronavirus disease and establish whether they follow the patient educational information reading level recommendations.||Cross sectional web study of google search hits. Websites related to governments, hospitals and health organizations (such as WHO). Assessed for readability using multiple validated scales. Global.||Readability, health literacy.||Websites.|
|Lagassé et al. ||H1N1||To assess the literacy level and readability of online communications about H1N1/09 influenza issued by the CDC during the first month of outbreak.||Prospective web study. Documents issued by the CDC, USA and Prevention during the first month of outbreak. Assessed for readability using multiple validated scales (i.e., Suitability Assessment of Materials (SAM). USA.||Readability, health literacy.||Websites,|
|Fernández-Díaz et al. ||COVID-19||To determine whether the content offered to inform about the disease is prepared so that any person can access it, regardless of their technology (hardware, software, or network infrastructure), language, culture, or disability, whether physical or mental, as determined by the Worldwide Web Consortium (W3C).||Web study. Analyses the web accessibility of the WHO website based on guidelines. Six representative pages from the WHO website were selected for in-depth analysis. WHO.||Accessibility of information.||Websites.|
|Ringel et al. .||H1N1||To assess whether state and local health departments were able to provide online information to their constituents within twenty-four hours of this declaration.||Cross sectional web study. Websites from the health departments of all fifty states, the District of Columbia, USA, and a sample of local U.S. health departments. Assessment of timeliness, how easy it was to find information and the content of the information. USA.||Timeliness (Online information within 24 h).||Websites.|
|Hu et al. ||COVID-19||
To describe and compare the officially released content regarding local epidemic|
situations as well as analyse the characteristics of information disclosure through local communication in major cities
|Cross sectional web study. Analysis of COVID-19 information on official websites of 31 cities. Descriptive statistical analysis. China.||Timely reporting and transparency.||Websites.|
|Social media platforms||Sutton et al. ||COVID-19||
To examine message retransmission on Twitter, focusing on original messages posted by public agencies|
responding to COVID-19.
|Quantitative analysis of content and structure. Twitter messages from 690 accounts representing U.S. public health, emergency management and elected officials. USA.||Retransmission of messages and engagement (variation in message content and structure).||Twitter, textual messages, and video.|
|Sutton et al. ||COVID-19||To identify, and describe the patterns of longitudinal risk communication from public health communicating agencies on Twitter during the first 60 days of the response to the COVID-19 pandemic.||Quantitative content analyses of textual content. 138,546 Twitter messages from 696 U.S. Public health agencies’ accounts. USA.||Content of messages.||Twitter.|
|Kamiński et al. ||COVID-19||To explore the number of reactions to and sentiments of tweets on coronavirus coming from scientific institutions, governmental authorities, and celebrities.||A retrospective infodemiology study. Sentiment analysis. 17,331 COVID-19-related tweets posted by 338 Twitter accounts of health agencies, governmental authorities, universities, scientific journals, medical associations and celebrities in > 4 months since the virus began to spread. Global.||Post impact (number of likes, retweets, and nominal and relative % followers.||Twitter.|
|Wang et al. .||COVID-19||To investigate the actors’ risk and crisis communication on Twitter regarding message types, communication sufficiency, timeliness, congruence, consistency and coordination.||Quantitative content analysis. 13,598 pandemic-relevant tweets posted over January to April from 67 federal and state-level agencies and stakeholders in USA.||
Message types, communication sufficiency, timeliness, congruence, consistency and|
|Chen et al. ||COVID-19||Investigates how Chinese central government agencies used social media to promote citizen engagement during the COVID-19 crisis.||Quantitative content analysis. 1441 Sina Weibo posts. User rating assessment and automated algorithmic text analysis. China.||Emotional valence, engagement, media richness, content type, dialogic loop.||Sina Weibo.|
|Liao et al. ||COVID-19||To examine public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage based on an analysis of data from Sina Weibo, a major social media platform in China.||Infodemiology study.Cross-sectional study. Sina Weibo Posts relevant to COVID-19 from Chinese government agency accounts. China.||Public engagement (likes, comments, shares, and followers).||Sina Weibo.|
|Ngai et al. ||COVID-19||To develop an integrated framework to examine the content, message style, and interactive features of COVID-19-related posts and determine their effects on public engagement in the largest social media network in China.||Infodemiology study. Quantitative content analysis of 608 Sina Weibo posts. China.||Content, message style, and interactive features, engagement.||Sina Weibo.|
|Zhang et al. .||COVID-19||To illustrate the process of how a piece of information becomes a health rumour. Furthermore, we identify factors that cause people to believe rumours and conduct behaviour that leads to a purchase craze.||Qualitative study. Interviews with 30 participants. Process tracing of media involved in generating misinformation. China.||Perception and behaviour, misinformation.||News report from the authoritative central, official media. Social media.|
|Videos||Li et al. ||COVID-19||
To evaluate the|
accuracy, usability and quality of the most widely viewed
YouTube videos on COVID-19.
|Content analysis of 75 top viewed YouTube videos. Global.||Usability (quality of video content), reliability of videos.||YouTube videos.|
|Dutta et al. ||COVID-19||To analyse the usefulness of YouTube as a web-based platform for medical and epidemiological information.||Cross-sectional study. YouTube search results analysed for content. 240 videos from non-governmental sources and from government and health agencies. 40 videos in six languages (English, Arabic, Bengali, Dutch, Hindi, and Nigerian Pidgin). Global.||Misinformation.||YouTube videos.|
|D’Souza et al. ||COVID-19||To assess the most viewed YouTube videos on COVID-19 for medical content.||Coding of video characteristics, source, and medical content. 113 most-widely viewed videos about COVID-19. Global.||Number of views, content of the messages.||YouTube videos.|
|Moon and Lee ||COVID-19||To compare the reliability, overall quality, title–content consistency, and content coverage of Korean-language YouTube videos on COVID-19, which have been uploaded by different sources.||
200 of the most viewed YouTube videos in Korean language from January 1, 2020, to April 30, 2020. South Korea.
|Misleading information (usefulness), overall quality, title-content consistency, source, video popularity.||YouTube video.|
|Bekalu et al. .||Pandemic influenza||To examine if effects of message format vary across audiences of different socio-demographic groups – age, gender, race/ethnicity, education and income.||
Experimental study. 627 American adults. Participants were randomly assigned to view either a narrative (N = 322) or a non-narrative|
(N = 305) video clip. Pre- and post-viewing questions assessing knowledge and perceived response. USA.
|Knowledge, perceived response.||Video.|
|Information leaflet||Krajcovic et al. ||H1N1||
To analyse the effectiveness of the information leaflet Personal measures during pandemic|
flu A(H1N1) 2009 with the focus on its design, contents, and distribution
|Cross sectional survey. 200 persons in 5 different age groups. Undisclosed response rate. Slovakia.||Reading literacy, comprehensibility.||Information leaflet.|
|Graphs||Banerjee et al. ||COVID-19||
To investigate the importance of an exponential-growth prediction bias in understanding why the COVID-19 outbreak|
|Quasi-experimental design. Participants from 43 countries. Global.||Bias.||Graphs, numbers.|
|Written messages||Okuhara et al. ||COVID-19||To examine the most persuasive message type in terms of narrator difference in encouraging people to stay at home during the COVID-19 pandemic and social lockdown.||
RCT. (N = 1980). Participants were randomly assigned to five intervention messages (from a governor, a public|
health expert, a physician, a patient, and a resident of an outbreak area) and a control message. Japan.
|Behavioural change (stay at home).||Written messages.|
|Mowbray et al. ||Pandemic influenza||
To examine the persuasiveness of messages promoting vaccination and antiviral use either as health-enhancing or|
as risk-reducing, as well as messages which conveyed evidence-based information about the costs and benefits of vaccination, or which applied anticipated regret as a motivator for vaccine uptake.
|11 focus groups 41 participants from England, including young and older adults, those with lower education, parents, and those with elevated health risk. England.||Persuasiveness, experiences, feelings.||Messages were designed for dissemination through Twitter and social media networks.|
|Shulman and Bullock ||COVID-19||To address whether the convention to avoid jargon in science communication generalizes to crisis communication as well.||
Experimental design with survey. 393 American participants recruited from Mturk Comparing the effects of messages containing jargon (N = 197) versus no jargon (N = 196) across three topic conditions that vary in situational urgency: COVID-19 (high urgency) flood risk (low urgency, and policy information about how the|
United States handles national emergencies (control). USA.
|Jargon, motivation to process.||Written messages.|
|Communication with ethnic minority groups||Kavaliunas et al. ||COVID-19||Our aim is to describe and analyse the Swedish approach in combating the pandemic.||Policy analysis. Data collated from various sources: published scientific studies, pre-print material, agency reports, media communication, public surveys. Sweden.||COVID-19 trends, healthcare system response, policy and measures overview, and implications.||Migrant community leaders to reach out to ethnic groups.|
|Driedger et al. .||H1N1||How First Nations and Metis people in Manitoba, Canada, responded to the public health management of pandemic H1N1.||Qualitative study. 23 focus groups with 193 people, Aboriginal people in Canada.||Experiences of stigma and trust.||Different formats (radio, television, print, on-line, community sessions).|
|Moyce et al. ||COVID-19||
The purpose of our study was to understand the perception of the Latino community in a rural state|
|Qualitative study with 14 semi structured interviews with Spanish speaking Latino population in US.||Risk perception and communication needs.||Social media, television, Spanish-language news stations, Facebook.|