Digital platforms have been inundated with COVID-19-related information since the pandemic began in late 2019. Information about the virus has been shared and viewed over 270 billion times online and mentioned almost 40 million times on Twitter and web-based news sites in the 47 countries of the WHO African Region between February and November 2020, according to UN Global Pulse, the United Nations’ Secretary-General’s initiative on big data and artificial intelligence.

A large proportion of this information is inaccurate and misleading and continues to be shared by social media users intentionally or unknowingly everyday. The COVID-19 infodemic is amplified online through social media but health misinformation is also circulating offline.

Measuring precisely how much of what is circulating is misinformation is difficult, but fact-checking organizations in Africa say they have debunked more than 1000 of such misleading reports since the onset of the pandemic. Some of the widely shared misinformation include conspiracies around unproven treatments, false cures and anti-vaccine messages.

"In health emergencies, misinformation can kill and ensure diseases continue to spread. People need proven, science-based facts to make informed decisions about their health and well-being, and a glut of information - an infodemic - with misinformation in the mix makes it hard to know what is right and real. This crucial new alliance brings unique reach, knowledge and skills to help stop the impact of dangerous misinformation," said Dr Matshidiso Moet, WHO Regional Director for Africai.

Among others, the Africa Infodemic Response Alliance will work collaboratively to counter false information around COVID-19 vaccines and complement on the ground public health awareness raising and community engagement efforts by creating demand for vaccines in the region.

The network is the first initiative of its kind and it brings together 13 international and regional organizations and fact-checking groups with expertise in data and behavioural science, epidemiology, research, digital health, and communications to detect, disrupt and counter damaging misinformation on public health issues in Africa.

The Alliance will encourage proactive disclosure by data holders and support journalists and media outlets to effectively share lifesaving information based on scientific evidence and debunk disinformation on health issues. It also aims to support individual African countries in developing tailored infodemic management strategies, including analysing trends and behaviours, recruiting specialists and refining systematic engagement strategies rooted in research and analytics.

This initiative puts into practice key recommendations on infodemic management that were developed by over 1300 experts from across disciplines in early 2020 under the auspices of WHO’s global Information Network for Epidemics (EPI-WIN).

The Alliance members are Africa CDC, the International Federation of the Red Cross and Red Crescent Societies (IFRC), the United Nations Verified initiative, the United Nations Children’s Fund (UNICEF), The United Nations Educational, Scientific and Cultural Organization (UNESCO) and United Nations Global Pulse. Participating and supporting bodies include Africa Check, Agence France-Presse Fact Check, PesaCheck, Dubawa and Meedan.

"Close coordination among fact-checkers, public health institutions and other communications stakeholders is essential for addressing the unique midinformation challenges we face today, where informational ambiguity based on scant or conflicting evidence, or emerging scientific knowledge can exacerbate the spread of disease," said Nat Gyenes, Director Meedan’s Digital Health Lab.
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Footnotes
  1. Online conversations are heavily influenced by news coverage, like the 2022 Supreme Court decision on abortion. The relationship is less clear between big breaking news and specific increases in online misinformation.
  2. The tweets analyzed were a random sample qualitatively coded as “misinformation” or “not misinformation” by two qualitative coders trained in public health and internet studies.
  3. This method used Twitter’s historical search API
  4. The peak was a significant outlier compared to days before it using Grubbs' test for outliers for Chemical Abortion (p<0.2 for the decision; p<0.003 for the leak) and Herbal Abortion (p<0.001 for the decision and leak).
  5. All our searches were case insensitive and could match substrings; so, “revers” matches “reverse”, “reversal”, etc.
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Published on
December 3, 2020
April 20, 2022