01 Set objectives

Agree with key stakeholders what question you are seeking to answer through a health impact assessment and why. For example, you may want to know the number of deaths and illnesses associated with air pollution in a specific location or the government may want to estimate the benefits of implementing a specific policy. At this Step, you should consider whether to first conduct a screening assessment to provide a basic understanding of who is potentially affected, the impact, if any, on health as well as the potential scale of any impacts before proceeding to a full health impact assessment. It may be useful to refer back to the Emission Inventory or Decision Support guidance to inform objectives or questions for analysis. 

02 Make a plan for health impact assessment

Based on the objectives set in Step 1, your jurisdiction's air quality and health staff should meet jointly to plan for a health impact assessment. Working collaboratively, you should develop a plan - following some of the guidance provided below - to gather appropriate baseline health data that is representative for your jurisdiction, to dedicate staff who will learn the appropriate tools and conduct the assessments, and to ensure you have the budgetary resources and buy-in from management to support the assessment process and utilize the results. 

03 Select HIA tools

A range of appropriate tools were listed under Step 5 of Stage 1. Based on your review of these tools, decide with your team on the most appropriate tool for your project. When choosing a tool, you should consider what data you have available and whether the outputs will answer the question you have identified in Step 1. Some decision support tools (e.g., GAINS or LEAP-IBC) include estimates of health effects and may be a good option if you are using them for other aspects of policy analysis. 

04 Prepare data - Air pollution

You will need information about the amount of air pollution that people are exposed to and, if analyzing the impacts of a policy change, the estimate of the change in air pollution that is expected to result from that policy change. The format of the data required will depend on the tool you are using. It is possible to use data for a range of spatial (i.e., geographic region) and temporal (i.e., time period) scales. However, the spatial and temporal scales should be the same across all data sets (e.g., air pollution, population, and health statistics). 

05 Prepare data - Population

You will need information about the population that is exposed to air pollution. The format of the data required will depend on the tool you are using and some tools have population information built in. It is possible to use data for a range of spatial (i.e., geographic region) and temporal (i.e., time period) scales. However, the spatial and temporal scales should be the same across all data sets (e.g., air pollution, population, and health statistics).

06 Prepare data - Health statistics

In order to determine the change in health impacts resulting from a change in air pollution, you will need data on baseline outcomes. Data on mortality may be easier to find than on morbidity (i.e., non-fatal health outcomes). The format of the data required will depend on the tool you are using and some tools have baseline health information built in. It is possible to use data for a range of spatial (i.e., geographic region) and temporal (i.e., time period) scales. However, the spatial and temporal scales should be the same across all data sets (e.g., air pollution, population, and health statistics). There are global datasets that can be used if local data is not available.

07 Select a concentration-response function (CRF)

A concentration-response (C-R) function is a mathematical formula that is used to calculate the health effects that occur as a result of a change in exposure to air pollution. Different C-R functions use different mathematical models (e.g., linear, logarithmic, etc.) and may produce very different results at different levels of exposure. There are publicly available C-R functions which are used for global analyses that can be used at this stage. Some tools have these functions already built in.

08 Run the Analysis - Analyze outcomes (including sensitivity)

After formatting the data to input in your preferred tool, you will run your analysis for your main question. You should also run a series of sensitivity analysis to understand how the results change when you adjust key variables or using different C-R functions. Based on the outcome of these analyses, you may choose to report a range of results rather than a single estimate. It is important to conduct rigorous QA/QC, which could include two analysts running the same analysis to ensure the results are replicable.

09 Implement a communication plan

It is important to carefully consider how you will communicate the results of your analysis and translate technical information into something that can be understood by policymakers and members of the public. First, consider the original question the analysis was conducted to answer and whether the results are useful for that purpose. You will also need to understand any uncertainties in the analysis or critical assumptions made and to be able to explain how changes in those factors could affect the results. If you are using global or remote sensing data, you will likely need to be able to explain how that is appropriate for understanding local conditions. The guidance on Public Engagement and Communication also provides helpful advice on how to approach this Step.