IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v38y2018i3p377-389.html
   My bibliography  Save this article

Are Perceived Prevalences of Infection also Biased and How? Lessons from Large Epidemics of Mosquito-Borne Diseases in Tropical Regions

Author

Listed:
  • Jocelyn Raude

    (EHESP Rennes, Université Sorbonne Paris Cité, France
    Aix Marseille University, IRD French Institute of Research for Development, EHESP French School of Public Health, UMR_D 190 Emergence des Pathologies Virales, Marseille, France
    UMR PIMIT, INSERM 1187, CNRS 9192, IRD 249. Plateforme Technologique CYROI, Université de La Réunion, Réunion, France)

  • Patrick Peretti-Watel

    (Aix Marseille Univ, IRD, AP-HM, SSA, VITROME, IHU-Méditerranée Infection, Marseille, France
    ORS PACA, Southeastern Health Regional Observatory, Marseille, France)

  • Jeremy Ward

    (Aix Marseille Univ, IRD, AP-HM, SSA, VITROME, IHU-Méditerranée Infection, Marseille, France
    ORS PACA, Southeastern Health Regional Observatory, Marseille, France
    Université Paris-Diderot, CNRS, LIED, Interdisciplinary Laboratory of Tomorrow's Energies, Paris, France)

  • Claude Flamand

    (Institut Pasteur de Guyane, Unité d’Epidémiologie, Cayenne, France)

  • Pierre Verger

    (Aix Marseille Univ, IRD, AP-HM, SSA, VITROME, IHU-Méditerranée Infection, Marseille, France
    ORS PACA, Southeastern Health Regional Observatory, Marseille, France)

Abstract

Background. Although people are likely to underestimate the frequencies of risks to health from common diseases and overestimate those from rare diseases, we still do not know much about reasons for this systematic bias, which is also referred to as “primary bias†in the literature. In this study, we take advantage of a series of large epidemics of mosquito-borne diseases to examine the accuracy of judgments of risk frequencies. In this aim, we assessed the perceived v. observed prevalence of infection by Zika, chikungunya or dengue fever during these outbreaks, as well as their variations among different subpopulations and epidemiological settings. Methods. We used data drawn from 4 telephone surveys, conducted between 2006 and 2016, among representative samples of the adult population in tropical regions (Reunion, Martinique, and French Guiana). The participants were asked to estimate the prevalence of these infections by using a natural frequency scale. Results. The surveys showed that 1) most people greatly overestimated the prevalence of infection by arbovirus, 2) these risk overestimations fell considerably as the actual prevalence of these diseases increased, 3) the better-educated and male participants consistently yielded less inaccurate risk estimates across epidemics, and 4) these biases in the perception of prevalence of these infectious diseases are relatively well predicted by the probability weighting function developed in the field of behavioral decision making. Conclusions. These findings suggest that the primary bias, which has been found in laboratory experiments to characterize a variety of probabilistic judgments, equally affects perception of prevalence of acute infectious diseases in epidemic settings. They also indicate that numeracy may play a considerable role in people’s ability to transform epidemiological observations from their social environment to more accurate risk estimates.

Suggested Citation

  • Jocelyn Raude & Patrick Peretti-Watel & Jeremy Ward & Claude Flamand & Pierre Verger, 2018. "Are Perceived Prevalences of Infection also Biased and How? Lessons from Large Epidemics of Mosquito-Borne Diseases in Tropical Regions," Medical Decision Making, , vol. 38(3), pages 377-389, April.
    • Handle: RePEc:sae:medema:v:38:y:2018:i:3:p:377-389
    DOI: 10.1177/0272989X17750845
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17750845
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X17750845?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lundborg, Petter & Lindgren, Bjorn, 2002. "Risk Perceptions and Alcohol Consumption among Young People," Journal of Risk and Uncertainty, Springer, vol. 25(2), pages 165-183, September.
    2. W. Kip Viscusi & Jahn Hakes, 2003. "Risk ratings that do not measure probabilities," Journal of Risk Research, Taylor & Francis Journals, vol. 6(1), pages 23-43, January.
    3. Catherine E. Althaus, 2005. "A Disciplinary Perspective on the Epistemological Status of Risk," Risk Analysis, John Wiley & Sons, vol. 25(3), pages 567-588, June.
    4. Philipson, Tomas, 2000. "Economic epidemiology and infectious diseases," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 33, pages 1761-1799, Elsevier.
    5. Gabriel Picone & Robyn Kibler & Bénédicte H. Apouey, 2017. "Malaria Prevalence, Indoor Residual Spraying, and Insecticide Treated Net Usage in Sub-Saharan Africa," Journal of African Development, African Finance and Economic Association (AFEA), vol. 19(2), pages 19-32.
    6. Viscusi, W Kip, 1990. "Do Smokers Underestimate Risks?," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1253-1269, December.
    7. Ian Savage, 1993. "Demographic Influences on Risk Perceptions," Risk Analysis, John Wiley & Sons, vol. 13(4), pages 413-420, August.
    8. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    9. Paul Slovic, 1999. "Trust, Emotion, Sex, Politics, and Science: Surveying the Risk‐Assessment Battlefield," Risk Analysis, John Wiley & Sons, vol. 19(4), pages 689-701, August.
    10. Paul Slovic, 1999. "Are trivial risks the greatest risks of all?," Journal of Risk Research, Taylor & Francis Journals, vol. 2(4), pages 281-288, October.
    11. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    12. Lonzozou Kpanake & Bruno Chauvin & Etienne Mullet, 2008. "Societal Risk Perception Among African Villagers Without Access to the Media," Risk Analysis, John Wiley & Sons, vol. 28(1), pages 193-202, February.
    13. Petter Lundborg & Bj–rn Lindgren, 2004. "Do They Know What They are Doing? Risk Perceptions and Smoking Behaviour Among Swedish Teenagers," Journal of Risk and Uncertainty, Springer, vol. 28(3), pages 261-286, May.
    14. A. J. Culyer & J. P. Newhouse (ed.), 2000. "Handbook of Health Economics," Handbook of Health Economics, Elsevier, edition 1, volume 1, number 1.
    15. Jahn Karl Hakes & W. Kip Viscusi, 2004. "Dead Reckoning: Demographic Determinants of the Accuracy of Mortality Risk Perceptions," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 651-664, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Costa-Font, Joan & Vilaplana-Prieto, Cristina, 2022. "Risky restrictions? Mobility restriction effects on risk awareness and anxiety," Health Policy, Elsevier, vol. 126(11), pages 1090-1102.
    2. Raude, Jocelyn & MCColl, Kathleen & Flamand, Claude & Apostolidis, Themis, 2019. "Understanding health behaviour changes in response to outbreaks: Findings from a longitudinal study of a large epidemic of mosquito-borne disease," Social Science & Medicine, Elsevier, vol. 230(C), pages 184-193.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lundborg, Petter & Andersson, Henrik, 2008. "Gender, risk perceptions, and smoking behavior," Journal of Health Economics, Elsevier, vol. 27(5), pages 1299-1311, September.
    2. Katherine Carman & Peter Kooreman, 2014. "Probability perceptions and preventive health care," Journal of Risk and Uncertainty, Springer, vol. 49(1), pages 43-71, August.
    3. Henrik Andersson, 2011. "Perception of Own Death Risk: An Assessment of Road‐Traffic Mortality Risk," Risk Analysis, John Wiley & Sons, vol. 31(7), pages 1069-1082, July.
    4. Henrik Andersson & Petter Lundborg, 2007. "Perception of own death risk," Journal of Risk and Uncertainty, Springer, vol. 34(1), pages 67-84, February.
    5. Lundborg, Petter, 2005. "Social capital and substance use among Swedish adolescents--an explorative study," Social Science & Medicine, Elsevier, vol. 61(6), pages 1151-1158, September.
    6. Anna Olofsson & Saman Rashid, 2011. "The White (Male) Effect and Risk Perception: Can Equality Make a Difference?," Risk Analysis, John Wiley & Sons, vol. 31(6), pages 1016-1032, June.
    7. Mary Riddel & David Hales, 2018. "Predicting Cancer‐Prevention Behavior: Disentangling the Effects of Risk Aversion and Risk Perceptions," Risk Analysis, John Wiley & Sons, vol. 38(10), pages 2161-2177, October.
    8. Lundborg, Petter, 2006. "Having the wrong friends? Peer effects in adolescent substance use," Journal of Health Economics, Elsevier, vol. 25(2), pages 214-233, March.
    9. Andersson, Henrik & Lundborg, Petter, 2006. "Perception of Own Death Risk: An Analysis of Road-Traffic and Overall Mortality Risks," Working Papers 2006:1, Swedish National Road & Transport Research Institute (VTI).
    10. Belot, Michèle & James, Jonathan & Spiteri, Jonathan, 2020. "Facilitating healthy dietary habits: An experiment with a low income population," European Economic Review, Elsevier, vol. 129(C).
    11. Petter Lundborg, 2007. "Smoking, information sources, and risk perceptions—New results on Swedish data," Journal of Risk and Uncertainty, Springer, vol. 34(3), pages 217-240, June.
    12. Frank Sloan & Alyssa Platt, 2011. "Information, risk perceptions, and smoking choices of youth," Journal of Risk and Uncertainty, Springer, vol. 42(2), pages 161-193, April.
    13. Frank Sloan & Lindsey Eldred & Tong Guo & Yanzhi Xu, 2013. "Are people overoptimistic about the effects of heavy drinking?," Journal of Risk and Uncertainty, Springer, vol. 47(1), pages 93-127, August.
    14. Yokoo, Hide-Fumi & Arimura, Toshi H. & Chattopadhyay, Mriduchhanda & Katayama, Hajime, 2023. "Subjective risk belief function in the field: Evidence from cooking fuel choices and health in India," Journal of Development Economics, Elsevier, vol. 161(C).
    15. Jesper Akesson & Sam Ashworth-Hayes & Robert Hahn & Robert Metcalfe & Itzhak Rasooly, 2022. "Fatalism, beliefs, and behaviors during the COVID-19 pandemic," Journal of Risk and Uncertainty, Springer, vol. 64(2), pages 147-190, April.
    16. Khwaja, Ahmed & Silverman, Dan & Sloan, Frank & Wang, Yang, 2009. "Are mature smokers misinformed?," Journal of Health Economics, Elsevier, vol. 28(2), pages 385-397, March.
    17. Stefan Pichler & Nicolas R. Ziebarth, 2015. "The Pros and Cons of Sick Pay Schemes: Testing for Contagious Presenteeism and Shirking Behavior," Discussion Papers of DIW Berlin 1509, DIW Berlin, German Institute for Economic Research.
    18. W. Kip Viscusi, 2016. "Risk Beliefs and Preferences for E-cigarettes," American Journal of Health Economics, University of Chicago Press, vol. 2(2), pages 213-240, Spring.
    19. Helen G. Levy & Edward C. Norton & Jeffrey A. Smith, 2018. "Tobacco Regulation and Cost-Benefit Analysis: How Should We Value Foregone Consumer Surplus?," American Journal of Health Economics, MIT Press, vol. 4(1), pages 1-25, Winter.
    20. Louie Rivers & Joseph Arvai & Paul Slovic, 2010. "Beyond a Simple Case of Black and White: Searching for the White Male Effect in the African‐American Community," Risk Analysis, John Wiley & Sons, vol. 30(1), pages 65-77, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:38:y:2018:i:3:p:377-389. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.