Factors Leading Municipal Authorities to Implement Preventive Interventions for Lyme Disease.

Johann Jacob,Cécile Aenishaenslin,Denis Talbot,Sandie Briand,Maxime Tessier,Pierre Valois,Catherine Bouchard

doi:10.3390/ijerph16091547

Abstract

The aim of this study is to document climate change adaptation interventions targeting Lyme disease at the municipal level in the province of Quebec (Canada). This exploratory study relies on the theory of planned behavior and certain constructs from the health belief model to identify the factors leading municipal authorities to implement preventive interventions for Lyme disease (PILD). Data were obtained from an online survey sent, during the summer of 2018, to municipal officers in 820 municipalities in Quebec, in all health regions where the population is at risk of contracting Lyme disease (response rate = 36%). The questionnaire was used to measure the implementation of PILD, the intention to implement these interventions, attitudes, perceived social pressure, perceived control (levers and barriers) over interventions, perceived effectiveness of preventive measures, risk, and perceived vulnerability. Results of structural equation analyses showed that attitudes were significantly associated with municipal authorities’ intention to implement PILD, while the intention to implement PILD was a significant predictor of the implementation of PILD. Additional analyses showed that perceived barriers added a moderating effect in the intention-implementation relationship. The prediction of behaviors or practices that municipal authorities could implement to prevent Lyme disease will enable the evaluation over time of the evolution of Quebec municipalities’ adaptation to Lyme disease. Moreover, the examination of the associations of specific psychosocial factors revealed important implications for the design of effective behavior-change interventions, which would allow health officials doing awareness work to create personalized interventions better suited to municipal officers and their specific contexts.

Highlights

Beyond extreme weather events, such as heat waves, droughts, floods, and storm surges, climate change is linked to an increased prevalence of vector-borne diseases, such as Lyme disease [1,2,3].Ixodes scapularis ticks infected with Borrelia burgdorferi can transmit it to species, including humans, which can develop Lyme disease
To gain further insight into the underlying reasons for the implementation of preventive interventions for Lyme disease (PILD) among municipal officers, we examined the potential impact of two background factors from the health belief model: The perceived risk or vulnerability represented by the disease, the perceived impact of the disease on health [39,40]
We formulated the hypothesis that when municipal officers believe that their municipality has control over the implementation of PILD, they will tend to act in accordance with their intentions

Summary

Introduction

Beyond extreme weather events, such as heat waves, droughts, floods, and storm surges, climate change is linked to an increased prevalence of vector-borne diseases, such as Lyme disease [1,2,3].Ixodes scapularis ticks infected with Borrelia burgdorferi can transmit it to species, including humans, which can develop Lyme disease. To gain further insight into the underlying reasons for the implementation of PILD among municipal officers, we examined the potential impact of two background factors from the health belief model: The perceived risk or vulnerability represented by the disease (perceived by municipal officers), the perceived impact of the disease (severity) on health (again perceived by municipal officers) [39,40]. The respondents were asked the following question: “Do you believe it is possible to contract Lyme disease in your municipality?” For those who answered “Yes,” a second question assessed their perceived risk severity on a five-point scale ranging from “very low” (+1) to “very high” (+5). Responses to two questions were used as reflective indicators of perceived severity (correlation coefficient r = 0.81): (S-1) “If a person has Lyme disease, do you think the negative impact on his/her physical health would be .

Objectives

Methods

Results

Discussion

Conclusion