Comparative dimensions of COVID-19 visual health literacy: social media news imagery in Germany and China

The study investigates how national healthcare strategies are reflected in visual representations accompanying online news posts during the COVID-19 pandemic, and how these visuals differ across countries with distinct management strategies, languages, and cultural contexts. Focusing on Germany (mitigation) and China (elimination), the authors analyse image-led posts from major social news media accounts across German, Mandarin, and English in 2022, the transition period into the endemic phase. Motivated by the growing role of visual health literacy in conveying scientific knowledge, the study explores the composition and functions of visual content (photos, infographics) that shape public understanding, trust, and compliance with health policies. It introduces the concept of “visual dataset fingerprints” and employs metaphorical mapping to examine how visual narratives align with public health realities across cultural and linguistic audiences.

Theoretical and empirical work underscores the central role of visuals in health communication. Visual health literacy extends beyond textual skills to include pictographic and non-verbal elements that influence beliefs, emotions, and behaviours (Entwistle & Williams, 2008; Osborne, 2009). Innovative and interactive visualisations can enhance comprehension and decision-making (Ola & Sedig, 2017; Liu et al., 2016), while design collaborations can bridge communication gaps (Paulovich, 2012; Pratt & Searles, 2017). Visuals help overcome literacy barriers but require clarity to avoid misunderstanding (Saraiva & Ferreira, 2020; Garcia-Retamero & Galesic, 2010). During COVID-19, media ecosystems shaped public discourse and behaviour (Finset et al., 2020; MacKay et al., 2021; Mach et al., 2021; Van Dijck & Alinejad, 2020), with implications for trust (Bromme et al., 2022; Ternullo, 2022; Zhao et al., 2020). Country-specific research indicates contrasts: in China, visually appealing Weibo posters sometimes lacked substantive health information (Zhang & Zhang, 2023), and data visualisation carried power dynamics affecting policy and perception (Zhao & Ye, 2022); quality control and professional expertise were highlighted to prevent misinformation (Wang, 2023). In Germany, the pandemic accelerated telemedicine and audiovisual tools to reach disadvantaged groups (Burg et al., 2021; Schwarz, 2020; Wiesner et al., 2012), but visual literacy challenges persisted (Garcia-Retamero & Galesic, 2010). Comparative governance literature (e.g., Lu et al., 2021; Kuhlmann et al., 2021; Desson et al., 2020) contextualises differences in mitigation vs elimination strategies and federal vs centralised implementations. Historical crises (AIDS, SARS) illustrate evolving visual framings (Lupton, 1994; Wallis & Nerlich, 2005). Together, these studies motivate a comparative, culturally sensitive analysis of visual health communication in Germany and China.

Design and framework: A multifaceted qualitative-descriptive design focuses on photorealistic, licensed photographs shared by national social news media accounts. The analysis is anchored in visual discourse methods and metaphorical mapping to assess how visuals represent public health processes. Analytic lenses: - Visual Discourse Analysis (Albers et al., 2009) to decode narratives and stereotypes in context. - Grammar of Visual Design (Kress & van Leeuwen, 2020) to examine composition, focus, and perspective. - Representational Photography (Wells, 2015) to situate images within the history and theory of photographic communication. - Translational Pictography (Newton, 2009) to gauge how complex health information is rendered comprehensible. - Metaphorical Mapping (Ahmedien, 2023) to evaluate mappings from biological/public health realities to visual metaphors. Coding scheme: A manual content and categorical coding framework captures five core categories—People, Objects, Settings, Activities, Context—with subcoding of People into healthcare workers, politicians, executive state authorities (police/military), and civilians (Table 1). Each image could contain multiple coding elements. Data sources and period: Publicly available image-led posts from eight high-follower national media accounts on Twitter/X and Chinese microblogs, covering 1 January 2022 to 31 December 2022. Outlets: @CCTV (English), @ChinaDaily (English), China Daily (Mandarin, microblog), CCTVNEWS (Mandarin, microblog), @dwnews (English, Germany), @SPIEGEL_English (English, Germany), @SZ (German), @Tagesschau (German). Search strategy and inclusion: Native platform searches using “CORONA,” “COVID,” “COVID-19,” “新冠肺炎.” Inclusion criteria: (1) contains a visual; (2) focuses on COVID-19 public health implications; (3) publicly accessible without age/paywall restrictions; (4) original posts (no replies, no retweets/shares). Duplicates, replies/retweets, and many infographic-borderline cases were excluded per coder agreements. Data handling and reliability: Cultural- and language-proficient coders (BN, KQ) performed manual coding with iterative calibration via calls and emails; borderline cases discussed; exclusion agreements established. Visualisation conducted in R (JVR). For posts with multiple images, each visual counted as a standalone item. Scope and scale: Figure 1 indicates 3007 visuals were coded across platforms, with total coding elements tallied by category. Additional outlet-level and language-location totals describe broader posting volumes (e.g., English-China >4000 images in 2022, Mandarin-China ~1600, German-language ~2800, English-Germany ~1200). The analysis is descriptive; formal statistical tests were not performed due to sample structure and variance.

- Overall emphasis by language/location: China/Mandarin outlets emphasised Context images most strongly (49% of all images; Table 3 Panel B), while Germany/English used images of People most frequently (39%). Germany/German and China/English showed similar overall shares of Context (~34–35%) and People (~29–31%). - People subcategories (proportions among People; Table 3 Panel D): - China/Mandarin: Politicians 0.46; Civilians 0.34; Healthcare 0.18; Executive authorities 0.02. Politicians dominated People images. - China/English: Civilians 0.56; Healthcare 0.37; Politicians 0.06; Executive authorities 0.01. Civilians and healthcare workers dominated. - Germany/German: Civilians 0.49; Healthcare 0.25; Politicians 0.21; Executive authorities 0.06. Balanced between civilians and healthcare with notable politicians. - Germany/English: Civilians 0.61; Healthcare 0.20; Politicians 0.09; Executive authorities 0.11. Civilians most prominent; comparatively higher executive authority share among German/English. - Cross-language contrasts within countries: - China: Civilians appear 22% more often in China/English than China/Mandarin; Healthcare workers 19% more often in China/English (37% vs 18%). Politicians appear 40% more often in China/Mandarin (46% vs 6%). - Germany: Civilians appear 10% more often in Germany/English than Germany/German; Healthcare workers differ by 5% (Germany/English 20% vs Germany/German 25%). Politicians appear 12% more often in Germany/German than Germany/English. - Outlet-level patterns: @ChinaDaily (Twitter) used the largest number of images (reported >4000 in 2022), while @SPIEGEL_English had very few (≈11). CCTVNEWS showed the largest share of Context images among outlets; German-based outlets showed larger proportions of People images. - Topic composition: Mandarin-language (China) outlets focus heavily on contextualising the pandemic environment; China/English and Germany/German give more prominence to Objects and Settings; German outlets show a relatively balanced mix of Settings, Objects, People, and Activities. - Descriptive only: Due to limited observations per category/outlet and uneven distributions, results are presented as descriptive patterns without inferential statistics.

The findings indicate that visual representations in social news media reflect national health strategies, communication norms, and audience targeting across languages and cultures. In China, Mandarin-language outlets prioritise contextual framing and political leadership, consistent with centrally coordinated crisis narratives and policy communication. In contrast, English-language outlets from China foreground healthcare workers and civilians, suggesting a strategy aimed at international audiences emphasising care delivery and societal impact. German outlets—especially in German—balance civilians, healthcare workers, and politicians, consistent with federal, multi-actor governance and mitigation strategies. These patterns align with the proposed concept of “visual dataset fingerprints,” wherein the composition of non-verbal elements (People, Objects, Settings, Activities, Context) metaphorically maps onto underlying public health processes and governance approaches. They also highlight the importance of language and audience: official-language channels in both countries tend to feature politicians more than English-language channels, pointing to distinct intra- vs extra-national communication objectives. Understanding such visual fingerprints can inform design of culturally sensitive, trust-enhancing public health messaging, guide platform strategies during endemic transitions, and complement textual analyses in health communication research.

Analysing image-led social news posts from China and Germany throughout 2022, the study identifies distinct, country- and language-specific visual strategies in public health communication. Mandarin outlets in China emphasised Context and politicians, while English-language outlets in both countries highlighted civilians and healthcare workers; German-language outlets showed a balanced distribution across categories. These descriptive patterns suggest that visual health communication responds to governance structures, cultural contexts, and intended audiences. Focusing on the endemic phase provides an understudied perspective on how strategies evolve beyond acute crisis. The study proposes “visual dataset fingerprints” and metaphorical mapping as tools for comparative visual health communication research. Future work should expand datasets, standardise sampling across outlets and platforms, and apply robust quantitative tests to evaluate causal impacts of visual strategies on public perceptions and behaviours.

- Descriptive analysis only; no inferential statistical testing due to limited observations within categories and uneven distributions across outlets and languages. - High variance in image counts across outlets and languages (e.g., far more images in China/English than in Germany/English or China/Mandarin) may bias proportional comparisons. - Manual coding is resource-intensive and subject to coder interpretation despite calibration; exclusion of borderline infographics may affect representativeness. - Selection limited to eight high-follower outlets and a single year (2022, endemic transition), restricting generalisability across platforms, time periods, and other countries. - Potential confounding by political climate, socio-economic conditions, and platform-specific affordances that were not controlled for.