Vector-borne diseases are sensitive to climate and weather, which affect vector survival, life cycles and activity, and the development of disease-causing microbes in the vectors. Climate change is anticipated to drive geographic range expansions of many vector-borne diseases towards the poles and to higher altitudes. People will be exposed to vector-borne diseases for the first time, so public health needs to know how to respond and adapt to these new health threats. Canada’s cold climate has protected people from most vectorborne diseases, but that is changing rapidly. The use of vector and disease transmission models coupled with outputs from climate models can better support in the task of projecting future risk.

A first step to adaptation is understanding which geographic regions are going to be affected and when future risks are likely to appear. This is achieved by developing comprehensive knowledge of disease risk occurrence, for example, in the form of risk maps, under current and projected future climate. Mathematical models (of vector species life cycles, and vector-borne disease transmission) allow us to assess climatic limits for a vector or disease, and how risk might increase as temperature warms and rainfall increases/ decreases from current levels. These models synthesize information on how climate affects disease risk, while accounting for other factors (environmental or socioeconomic) that also limit disease occurrence. For this, data on current climate are essential. Once we understand how climate determines and influences where, when and how disease risk occurs, we can then predict future occurrence with climate change, by using outputs from global and/or regional climate models. Outputs from ensembles of climate models are used which employ a range of scenarios for greenhouse gas emissions. Therefore, projections account for variations in model performance at different locations and future time periods, and uncertainty as to how societies will respond to the challenge of the climate crisis by mitigating greenhouse gas emissions.

Firstly, projections of the expansion of the range of the blacklegged tick vector of Lyme disease with climate change have been proven to be highly accurate and have given early warning of the emergence of Lyme disease in Canada. In addition, this allowed attribution of Lyme disease emergence in Canada to climate change. This early warning also enabled public health programmes to step up their surveillance efforts while also raising awareness of Lyme disease ,as well as preventative measures, within the public and medical community. Similar projections have raised awareness that another tick vector of infectious diseases, the lone star tick, may also emerge in southern Canada in the near future. Projections of the occurrence of the Asian tiger mosquito (and the diseases it can transmit, like Chikungunya) alerted us that this mosquito may spread into Canada and may already be present in the warmest locations. This has been confirmed by surveillance, again providing early warning of possible future disease risks.

Predicting future disease risks requires knowledge of the occurrence and biology of infectious diseases, while confidence in predictions depends on validation by surveillance. None of this is possible without data on current climate, and state-of-the-art climate models that provide us with the capacity to project future climate, particularly at the regional scales. Nevertheless, with adequate knowledge, accurate and useful predictions can be made.

Climate-informed projections for the occurrence of Lyme disease in Canada have allowed the government to attribute disease risk to climate change – and to get ahead of the epidemic curve to prepare public health responses.