Collective Intelligence-Based Participatory COVID-19 Surveillancein Accra, Ghana:Pilot Mixed Methods Study

被引:0
作者
Marley, Gifty [1 ]
Dako-Gyeke, Phyllis [2 ]
Nepal, Prajwol [1 ]
Rajgopal, Rohini [1 ]
Koko, Evelyn [3 ]
Chen, Elizabeth [3 ]
Nuamah, Kwabena [4 ]
Osei, Kingsley [4 ]
Hofkirchner, Hubertus [5 ]
Marks, Michael [6 ,7 ]
Tucker, Joseph [6 ,8 ]
Eggo, Rosalind [6 ]
Ampofo, William [9 ]
Ylvia, Sean [1 ]
机构
[1] Univ N Carolina, Dept Hlth Policy & Management, 1101D McGavran Greenberg Hall,CB 7411, Chapel Hill, NC 27599 USA
[2] Univ Ghana, Sch Publ Hlth, Dept Social & Behav Sci, Accra, Ghana
[3] Univ N Carolina, Gillings Sch Global Publ Hlth, Dept Hlth Behav, Chapel Hill, NC USA
[4] Cognate Syst Co Ltd, Accra, Ghana
[5] Prediki Predict Markets GmbH, Vienna, Austria
[6] London Sch Hyg & Trop Med, Clin Res Dept, London, England
[7] UCL, Div Infect & Immun, London, England
[8] Univ N Carolina, Inst Global Hlth & Infect Dis, Chapel Hill, NC USA
[9] Univ Ghana, Noguchi Mem Inst Med Res, Accra, Ghana
来源
JMIR INFODEMIOLOGY | 2024年 / 4卷
关键词
information markets; participatory disease surveillance; collective intelligence; community engagement; the wisdom of thecrowds; Ghana; mobile phone; PREDICTION MARKETS;
D O I
10.2196/50125
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Infectious disease surveillance is difficult in many low- and middle-income countries. Information market(IM)-based participatory surveillance is a crowdsourcing method that encourages individuals to actively report health symptomsand observed trends by trading web-based virtual "stocks" with payoffs tied to a future event. Objective: This study aims to assess the feasibility and acceptability of a tailored IM surveillance system to monitorpopulation-level COVID-19 outcomes in Accra, Ghana. Methods: We designed and evaluated a prediction markets IM system from October to December 2021 using a mixed methodsstudy approach. Health care workers and community volunteers aged >= 18 years living in Accra participated in the pilot trading.Participants received 10,000 virtual credits to trade on 12 questions on COVID-19-related outcomes. Payoffs were tied to thecost estimation of new and cumulative cases in the region (Greater Accra) and nationwide (Ghana) at specified future time points.Questions included the number of new COVID-19 cases, the number of people likely to get the COVID-19 vaccination, and thetotal number of COVID-19 cases in Ghana by the end of the year. Phone credits were awarded based on the tally of virtual creditsleft and the participant's percentile ranking. Data collected included age, occupation, and trading frequency. In-depth interviewsexplored the reasons and factors associated with participants' user journey experience, barriers to system use, and willingness touse IM systems in the future. Trading frequency was assessed using trend analysis, and ordinary least squares regression analysiswas conducted to determine the factors associated with trading at least once. Results: Of the 105 eligible participants invited, 21 (84%) traded at least once on the platform. Questions estimating thenational-level number of COVID-19 cases received 13 to 19 trades, and obtaining COVID-19-related information mainly fromtelevision and radio was associated with less likelihood of trading (marginal effect: -0.184). Individuals aged <30 years traded7.5 times more and earned GH cent 134.1 (US $11.7) more in rewards than those aged >30 years (marginal effect: 0.0135).Implementing the IM surveillance was feasible; all 21 participants who traded found using IM for COVID-19 surveillanceacceptable. Active trading by friends with communal discussion and a strong onboarding process facilitated participation. Thelack of bidirectional communication on social media and technical difficulties were key barriers. Conclusions: Using an IM system for disease surveillance is feasible and acceptable in Ghana. This approach shows promiseas a cost-effective source of information on disease trends in low- and middle-income countries where surveillance isunderdeveloped, but further studies are needed to optimize its use
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页数:17
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