JMIR Publications

ABSTRACT

Background:

Infectious disease surveillance is difficult in many LMICs. Information market-based participatory surveillance (“IM surveillance) surveillance is a crowdsourcing method that encourages individuals to actively report health symptoms and trends by trading virtual “stocks” with payoffs tied to a future event.

Objective:

This study aimed to assess the feasibility and acceptability of a tailored IM surveillance system to monitor population-level COVID-19 outcomes in Accra, Ghana

Methods:

We designed and evaluated a collective intelligence-based IM system from October to December 2021 using a mixed method study approach. Healthcare workers and community volunteers aged ≥18 years living in Accra were invited to participate in the pilot trading. Data collected using an online self-administered questionnaire included age, occupation, and main sources of Covid-19 news, and participants’ trading frequency and rewards data was obtained from the system. Online-based in-depth interviews were conducted using a structured topic guide to explore reasons and factors associated with participants’ user-journey experience, barriers to the system use and willingness to use collective intelligence-based surveillance systems in future. Descriptive statistics summarized the baseline characteristics of participant, day-of-the-week effect per time of the day (average by day) on trading frequency was assessed using trend analysis, and ordinary least squares (OLS) regression analysis was conducted to determine the factors associated with trading at least once.

Results:

Of the invites sent to 105 eligible participants, 21 (84.0%) traded at least once on the platform. Across the 12 questions in the platform, estimating the number of Covid-19 cases for the Greater Accra region had the least number of trades (range: 6 -13 trades) and estimating the national level number of Covid-19 cases received the most trades (range: 13- 19 trades). Compared to social media/internet, obtaining Covid-19-related information mainly from TV/Radio was associated with less likelihood of trading (marginal effect: -0.184). However, those who got information from TV/Radio made more trades and earned more rewards when they did trade. Additionally, those aged <30 years made 7.5 times more trades and earned 11.7 USD more in rewards than those above 30 (marginal effect: 0.0135). Qualitative interview findings showed that implementing the prediction markets surveillance was feasible, all 21 participants who traded found the use of the approach for Covid-19 surveillance acceptable. Friends actively participated in the trading with communal discussion and a strong onboarding process facilitated participation. The barriers included the lack of bi-directional communication on social media and technical difficulties.

Conclusions:

The use of a collective intelligence-based participatory system for disease surveillance is feasible and acceptable in Ghana. This approach shows promise as a cost-effective source of information on disease trends in low- and middle-income countries where surveillance systems are underdeveloped, but further studies are needed to optimize its use.