Predicted increase in the area of tick establishment and the proportion of the human population living in municipalities with established tick population in Québec from 2008 to 2100.

Dashed lines show the percentage of the surface area of the province of Québec predicted to contain an established tick population by the lower, mean and upper predicted years (light, medium and dark grey, respectively). Solid lines show the percentage of the Québec human population living in areas predicted to have an established tick population by the lower, mean and upper predicted years (light, medium and dark grey lines, respectively).</p

Time lag between predicted tick establishment and detection of ticks by active surveillance.

Mean, range and standard deviation of the time lag in years between predicted tick establishment and observation of a ticks (three stages or tick presence) in a municipality according to lower, mean and upper predicted year of establishment.</p

Tick surveillance in Québec municipalities, 2010–2018, and predicted tick population establishment by 2018.

Active surveillance from 2010 to 2018: municipalities with detection of three stages are indicated by black stars; those with the presence of at least one tick by black triangles and those with no tick detection by white circles. Shaded areas of the map show municipalities with predicted tick population establishment by 2018 according to the lower, mean and upper predicted year (light, medium and dark grey zones, respectively).</p

Concordance between field data and predicted tick establishment by 2018.

Observed presence or absence of ticks during active surveillance (no detection, tick presence, three stages) in municipalities between 2010–2018 vs predicted tick establishment in 2018 (before or after 2018) according to lower, mean and upper model predicted year.</p

Prediction of tick population establishment in Québec from 2008 to 2100 by 5-year intervals.

Predicted year of tick population establishment for each Québec municipality based on the upper predicted year of the model of Leighton et al. (2012) [19].</p

Concordance between tick surveillance data and predicted year of establishment.

Observed presence or absence of ticks during active surveillance (no detection, tick presence, three stages) relative to model predictions (before or after the lower, mean and upper predicted year of establishment).</p

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Data_Sheet_1_Criteria for selecting sentinel unit locations in a surveillance system for vector-borne disease: A decision tool.pdf

ObjectivesWith vector-borne diseases emerging across the globe, precipitated by climate change and other anthropogenic changes, it is critical for public health authorities to have well-designed surveillance strategies in place. Sentinel surveillance has been proposed as a cost-effective approach to surveillance in this context. However, spatial design of sentinel surveillance system has important impacts on surveillance outcomes, and careful selection of sentinel unit locations is therefore an essential component of planning.MethodsA review of the available literature, based on the realist approach, was used to identify key decision issues for sentinel surveillance planning. Outcomes of the review were used to develop a decision tool, which was subsequently validated by experts in the field.ResultsThe resulting decision tool provides a list of criteria which can be used to select sentinel unit locations. We illustrate its application using the case example of designing a national sentinel surveillance system for Lyme disease in Canada.ConclusionsThe decision tool provides researchers and public health authorities with a systematic, evidence-based approach for planning the spatial design of sentinel surveillance systems, taking into account the aims of the surveillance system and disease and/or context-specific considerations.</p

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Lyme disease and other vector-borne diseases are on the rise because of climate change. In the province of Quebec, Canada, Lyme disease has become a public health problem deserving the attention of health authorities. Despite their recognized effectiveness at preventing tick-to-human transmission, rates of adoption of Lyme disease adaptive behaviours (LDAB) remain relatively low in the population. Using the Theory of Planned Behaviour (TPB), the aim of this study is to identify specific and actionable beliefs associated with the adoption of Lyme disease adaptive behaviours. Specifically, 2,011 people were surveyed to determine the decision-making process behind specific beliefs, which could be targeted for raising awareness. Statistically significant associations were found between the three determinants of the TPB (i.e., attitudes, perceived social pressure and perceived behavioral control) and the intention to adapt. In addition, the intention itself was significantly associated with adopting LDAB. Belief-based analyses indicated that 8 primary beliefs (4 behavioral beliefs, 2 normative beliefs, and 2 control beliefs) were associated with LDAB. Among these, control beliefs (barriers and facilitating factors) appeared to have the greatest impact on adaptation. These findings can be used to guide educational and awareness-raising campaigns to promote LDAB by changing or reinforcing these primary beliefs.</div

Appendices A - C from Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study

Appendix A: Model description; Appendix B: Input parameters; Appendix C: Sensitivity analysi