Time series analysis of government information about COVID-19 on social media and the number of new cases during the first 6 months of the pandemic: the Brazil case

Authors

DOI:

https://doi.org/10.33448/rsd-v10i16.23797

Keywords:

COVID-19; Health education; Health communication; Access to information; Social networking.

Abstract

This retrospective study sought to assess the association between the evolution of the COVID-19 pandemic in Brazil and the quality of educational materials published in the official profiles of Brazilian government health agencies on Instagram. Posts about COVID-19, published between January 31 and August 15, 2021, were selected, dated, quantified and classified according to their content by three researchers. Public’s engagement was calculated by the number of likes, comments and views. The quality of the educational posts was assessed by two trained and calibrated researchers (Kappa intra and inter-examiners, k=0.96 and k=0.92, respectively), using the Brazilian version of the Clear Communication Index (BR-CDC-CCI), the number of new COVID-19 cases was collected using the COVID-19 epidemic calculator provided by PAHO at https://covid-calc.org/. The relationship between the evolution of the COVID-19 indicator and the quality of educational posts was calculated using the statistical model of a fortnightly time series. On average, educational posts reached 6.4 in the BR-CDC-CCI score (median = 6.5). In the multiple model adjusted for the amount of educational posts and public engagement, it was observed that for each increase of one point in the BR-CDC-CCI score, there was a reduction of 327,864 new cases of Covid-19 (p <0.001). It was concluded that there was a relationship between the low quality of posts and the greater number of new cases of the disease, indicating the need for greater attention from Brazilian government agencies with the quality of information made available on social networks to help control the COVID-19 pandemic.

References

Brazil. (1988). Constituição da República Federativa do Brazil (Senado Federal).

Centers for Disease Control and Prevention. (2009, April). Simply put; a guide for creating easy-to-understand materials (3rd ed.). https://stacks.cdc.gov/view/cdc/11938

Centers for Disease Control and Prevention. (2010). National Action Plan to Improve Health Literacy | Health Literacy. https://www.cdc.gov/healthliteracy/planact/national.html

Centers for Disease Control and Prevention. (2019). CDC clear communication index : a tool for developing and assessing CDC public communication products : user guide. https://stacks.cdc.gov/view/cdc/107490

COVID-19 in Brazil: “So what?” [Editorial]. (2020, May 9). The Lancet, 395(10235), 1461. https://doi.org/10.1016/S0140-6736(20)31095-3

Daraz, L., Morrow, A., Ponce, O., Farah, W., Katabi, A., Majzoub, A., Seisa, M., Benkhadra, R., Alsawas, M., Larry, P., & Murad, M. (2018). Readability of Online Health Information: A Meta-Narrative Systematic Review. American Journal of Medical Quality : The Official Journal of the American College of Medical Quality, 33(5), 487–492. https://doi.org/10.1177/1062860617751639

de Melo Cunha, M. A. G., Lino, P. A., Dos Santos, T. R., Vasconcelos, M., Lucas, S. D., & de Abreu, M. H. N. G. (2015). A 15-year time-series study of tooth extraction in Brazil. Medicine, 94(47).

Fleary, S., Joseph, P., & Pappagianopoulos, J. (2018). Adolescent health literacy and health behaviors: A systematic review. Journal of Adolescence, 62, 116–127. https://doi.org/10.1016/J.ADOLESCENCE.2017.11.010

Garcia, P., Fera, J., Mohlman, J., & Basch, C. H. (2021). Assessing the Readability of COVID-19 Testing Messages on the Internet. Journal of Community Health, 46, 913-917. https://doi.org/10.1007/S10900-021-00973-6

Geboers, B., Reijneveld, S., Jansen, C., & de Winter, A. (2016). Health Literacy Is Associated With Health Behaviors and Social Factors Among Older Adults: Results from the LifeLines Cohort Study. Journal of Health Communication, 21(sup2), 45–53. https://doi.org/10.1080/10810730.2016.1201174

Johns Hopkins University & Medicine. Coronavirus Resource Center.(2021). COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). https://coronavirus.jhu.edu/map.html

Korda, H., & Itani, Z. (2013). Harnessing social media for health promotion and behavior change. Health Promotion Practice, 14(1), 15–23. https://doi.org/10.1177/1524839911405850

Levin-Zamir D, Bertschi I. (2018) Media Health Literacy, eHealth Literacy, and the Role of the Social Environment in Context. Int J Environ Res Public Health, 15(8), 1643. https://doi.org/10.3390/ijerph15081643.

Limaye, R., Sauer, M., Ali, J., Bernstein, J., Wahl, B., Barnhill, A., & Labrique, A. (2020). Building trust while influencing online COVID-19 content in the social media world. The Lancet. Digital Health, 2(6), e277–e278. https://doi.org/10.1016/S2589-7500(20)30084-4

Liu, Y., Liu, L., Li, Y., & Chen, Y. (2015). Relationship between Health Literacy, Health-Related Behaviors and Health Status: A Survey of Elderly Chinese. International Journal of Environmental Research and Public Health, 12(8), 9714–9725. https://doi.org/10.3390/IJERPH120809714

Loeb, S., Taylor, J., Borin, J., Mihalcea, R., Perez-Rosas, V., Byrne, N., Chiang, A. L., & Langford, A. (2020). Fake News: Spread of Misinformation about Urological Conditions on Social Media. European Urology Focus, 6(3), 437–439. https://doi.org/10.1016/J.EUF.2019.11.011

Marinho, A., Faur, C., Ferreira, F., Borges-Oliveira, A., & Abreu, M. (2020). Cross-cultural adaptation of the Clear Communication Index to Brazilian Portuguese. Revista de Saude Publica, 54(26). https://doi.org/10.11606/S1518-8787.2020054001561

McClure, E., NG, J., Vitzthum, K., & Rudd, R. (2016). A Mismatch Between Patient Education Materials About Sickle Cell Disease and the Literacy Level of Their Intended Audience. Preventing Chronic Disease, 13(5). https://doi.org/10.5888/PCD13.150478

Pang, P., Cai, Q., Jiang, W., & Chan, K. (2021). Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao. International Journal of Environmental Research and Public Health, 18(7), 3508. https://doi.org/10.3390/IJERPH18073508

Park, C.L., Russell, B.S., Fendrich, M., Finkelstein-Fox, L., Hutchison, M., Becker, J. (2020) Americans' COVID-19 Stress, Coping, and Adherence to CDC Guidelines. J Gen Intern Med , 35(8), 2296-2303. https://doi.org/0.1007/s11606-020-05898-9.

R Core Team. (2020). R: The R Project for Statistical Computing. (Version 4.0.3) [Computer Software]. https://www.r-project.org/

Roberts, M., Callahan, L., & O’Leary, C. (2017). Social Media: A Path to Health Literacy . Stud Health Technol Inform, 240, 464–475. https://pubmed.ncbi.nlm.nih.gov/28972534/

Schillinger, D., Chittamuru, D., & Ramírez, A. S. (2020). From “Infodemics” to Health Promotion: A Novel Framework for the Role of Social Media in Public Health. American Journal of Public Health, 110(9), 1393. https://doi.org/10.2105/AJPH.2020.305746

Sørensen, K., Pelikan, J., Röthlin, F., Ganahl, K., Slonska, Z., Doyle, G., Fullam, J., Kondilis, B., Agrafiotis, D., Uiters, E., Falcon, M., Mensing, M., Tchamov, K., van den Broucke, S., Brand, H., HLS-EU Cosortium. (2015). Health literacy in Europe: comparative results of the European health literacy survey (HLS-EU).

European Journal of Public Health, 25(6), 1053–1058. https://doi.org/10.1093/EURPUB/CKV043

Shumway, R. H. & Stoffer, D. S. (2010). Time series analysis and its applications (Vol. 3). New York: springer.

Takla M, Jeevaratnam K. (2020) Chloroquine, hydroxychloroquine, and COVID-19: Systematic review and narrative synthesis of efficacy and safety. Saudi Pharm J, 28(12), 1760-1776. https://doi.org/10.1016/j.jsps.2020.11.003.

United States Government. (2010). An act to enhance citizen access to Government information and services by establishing that Government documents issued to the public must be written clearly, and for other purposes. https://www.govinfo.gov/content/pkg/PLAW-111publ274/html/PLAW-111publ274.htm

Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe. https://edoc.coe.int/en/media/7495-information-disorder-toward-an-interdisciplinary-framework-for-research-and-policy-making.html

Wojtowicz, A. (2020). Addressing Health Misinformation with Health Literacy Strategies: Proceedings of a Workshop—in Brief. National Academies of Sciences, Engineering, and Medicine. Washington, DC: The National Academies Press. https://doi.org/10.17226/26021

World Health Organization. (2020). 1st WHO Infodemiology Conference. How infodemics affect the world & how it can be managed. https://www.who.int/news-room/events/detail/2020/06/30/default-calendar/1st-who-infodemiology-conference

Downloads

Published

17/12/2021

How to Cite

SILVA, L. da .; MARINHO, A. M. C. L.; BRAGA, N. S. .; SANTOS , T. R. dos; ABREU, M. H. N. G. de .; ASSUNÇÃO, C. M.; FERREIRA , F. M. Time series analysis of government information about COVID-19 on social media and the number of new cases during the first 6 months of the pandemic: the Brazil case . Research, Society and Development, [S. l.], v. 10, n. 16, p. e501101623797, 2021. DOI: 10.33448/rsd-v10i16.23797. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/23797. Acesso em: 14 nov. 2024.

Issue

Section

Health Sciences