This challenge was designed specifically as a #ZindiWeekendz hackathon (To Vaccinate or Not to Vaccinate: It’s not a Question). We are re-opening the hackathon as a Knowledge Challenge, to allow the Zindi community to learn and test their skills. To help you all out, we’ve created a new Tutorials tab with helpful resources from the community. We encourage Zindians to share their code on the discussion board so that everyone in our community can learn from and support one another.
Work has already begun towards developing a COVID-19 vaccine. From measles to the common flu, vaccines have lowered the risk of illness and death, and have saved countless lives around the world. Unfortunately in some countries, the 'anti-vaxxer' movement has led to lower rates of vaccination and new outbreaks of old diseases.
Although it may be many months before we see COVID-19 vaccines available on a global scale, it is important to monitor public sentiment towards vaccinations now and especially in the future when COVID-19 vaccines are offered to the public. The anti-vaccination sentiment could pose a serious threat to the global efforts to get COVID-19 under control in the long term.
The objective of this challenge is to develop a machine learning model to assess if a Twitter post related to vaccinations is positive, neutral, or negative. This solution could help governments and other public health actors monitor public sentiment towards COVID-19 vaccinations and help improve public health policy, vaccine communication strategies, and vaccination programs across the world.
The Zindi community is joining the fight against COVID-19! #ZindiWeekendz are virtual weekend hackathons hosted by Zindi. This series of #ZindiWeekendz throughout April and May 2020 focuses specifically on COVID-19.
In a time of lockdowns, remote work, and general uncertainty, #ZindiWeekendz offer data scientists the opportunity to continue to develop their skills while contributing to practical, open-source AI solutions to help in the battle against COVID-19.
All winning solutions will be shared as a public good on GitHub. We are committed to supporting partners implement these solutions and encourage anyone who is interested to reach out to us at firstname.lastname@example.org.