The Contribution of Risk Perception and Social Norms to Reported Preventive Behaviour against Selected Vector-borne Diseases in Guyana

"Understanding the extent of the social determinants of preventive behaviour against vector-borne diseases (VBDs) is key to drawing effective health policies. When social norms are proven to influence individual behaviour, tailored interventions can be targeted to identified social groups, potentially multiplying the effects of policy interventions..."



Vector-borne diseases (VBDs) cause more than 700,000 deaths annually, with the morbidity and mortality burden disproportionately concentrated in low- and middle-income countries (LMICs). Risk perception has been seen as a significant determinant of preventive behaviour for VBDs. The perception of risk goes beyond individuals and constitutes a social and cultural construct reflecting values, symbols, history, and ideology, which reflect social norms. This study investigates the relationship between preventive behaviour, risk perception, and social norms for selected VBDs - namely, Zika virus (ZIKV) disease, malaria, dengue, and cutaneous leishmaniasis (CL) - in Guyana, South America.



As explained here, social norms have their origins within social groups - in particular: (i) those formed by individuals who actively participate in the enforcement of social norms (e.g., family members, friends, colleagues); and (ii) those formed by individuals who conform to similar others based on characteristics such as age, gender, or education, but who are not necessarily related to each other on the social sphere. The latter is called the reference group. Within this study, the social norm involves individuals comparing their risk perception to the group's commonly held norm, which in turn is assumed to influence the individual's reported behaviour.



Individuals can rely on non-exclusive active or passive behaviour measures to face risk. Passive behaviour refers to using measures the government provides free of charge as part of the national vector-control programme (indoor residual spraying (IRS), fogging, or bed nets). On the contrary, active behaviour involves preventive measures that individuals actively acquire. This study considered "active behaviour" to mean using preventive measures (screened windows, skin repellent, mosquito zapper rackets, beeper mosquito, mosquito coils, or bracelets) or sitting next to a fire at night. Active and passive preventive behaviours are conditioned on risk perception and jointly determined at the individual level.



The study's final analysis was performed on cross-sectional data collected from 497 individuals in four regions of Guyana in 2017. The researchers used a conditional mixed process estimator with multilevel coefficients, estimated through a Generalized Linear Model (GLM) framework, applying a simultaneous equation structure. CL, mostly unknown across regions, was not perceived as a risk. In contrast, individuals were more risk-averse against malaria, showing the highest heterogeneity across the four diseases (largest interquartile range (IQR)). Dengue and ZIKV were next in risk perception descending order. As expected, active measures were, on average, used by a significantly lower proportion of individuals compared to passive ones: ZIKV (26.2% vs 37.2%), dengue (24.1% vs 60.1%%), malaria (44.2% vs 82.2%%) and CL (4.3% vs 11.7%%).



The researchers find robust results on malaria: Risk perception was significantly influenced by the risk perception of the reference group across different definitions of the reference group (age and ethnic group; age and educational level), hinting at the existence of social norms. In addition, the results show that, when the reference group is based on age and education, increased malaria risk perception is associated with an increased (willingness to) uptake of both active and passive behaviours against the disease by 5.50% (95% confidence interval (CI) 2.67-8.33%) and 4.42% (95% CI 1.96-6.88%), respectively, per unitary increase in the risk perception scale. When the reference group is based on age and ethnic group, risk perception significantly increases the likelihood of passive behaviour by 4.48%. However, the association with passive behaviour disappeared when bed nets were withdrawn from the analysis. This finding highlights the perceived high effectiveness of bednets as a tool against malaria.

For dengue, the role of social norms in determining risk perception was weaker: The relationship between the reference group and the individual risk perception was dependent on the definition of the reference group. More specifically, the researchers only observed the presence of social norms when the reference group is based on age and ethnicity. Thus, when considering other definitions of the reference group, individual risk perception seems to be explained by factors other than the risk perception of the reference group. The role of risk perception in influencing dengue preventive behaviour also depends on the definition of passive behaviour: Risk perception is only a relevant factor in the uptake of passive behaviours such as fogging and IRS. In terms of the other VBDs, ZIKV and CL were excluded from the analysis, as both risk perception and behaviour were too low.



Notably, this study shows that, despite not engaging in active behaviours as a reaction to higher levels of (perceived) risk of infection, individuals are willing to accept or use passive measures to protect themselves. This finding should favour the government's provision of protective tools against both dengue and malaria. Furthermore, given the relevance of social norms in explaining malaria risk perception, interventions such as health communication and promotion activities tailored to groups based on key demographic and social characteristics (i.e., age, ethnicity, and education) could produce a replicative effect and reinforce malaria preventive behaviours. For example, information and awareness campaigns on the actual current and future infection, morbidity, and mortality risk should accommodate individual characteristics in order to reinforce the uptake of distributed protective measures against malaria.



The results of the study suggest a segmentation of the intended audience based on demographic characteristics such as age, ethnicity, and education. One common strategy in the customisation process is the personalisation of messages through contextualisation. By framing messages in contexts that resonate with the personal background of the recipients, it is possible to enhance their attention, interest, and motivation to actively and thoughtfully process information. For instance, incorporating the ethnic and educational context of each recipient should involve health communication tailoring ensuring cultural sensitivity, linguistic appropriateness, and literacy representation within the intended audience.



According to the researchers, the findings from this study could be extrapolated to similar settings, e.g. Suriname, with comparable disease epidemiology, common socio-economic conditions, and the movement of people between countries, with the associated sharing of knowledge and experiences. "All in all, evidence should be generated in Guyana and similar settings on the impact on preventive behaviour for VBDs of interventions aimed to correct risk perception tailored to groups at the intersection of certain socio-economic and demographic characteristics."