BranchPattern’s happēTM tool, or Health and Productivity Performance Estimator, provides quantitative estimates of the impacts on productivity and health resulting from various indoor environmental quality (IEQ) conditions, such as temperature, relative humidity, air quality, lighting quality, and sound quality. Based on decades of IEQ peer reviewed research, it provides both percentage impacts and dollar amounts using weighted average salary dollars. Originally developed over ten years ago, we periodically update existing modules based on new research and add new modules to address client and occupant needs. Individual modules range from assessing the productivity impacts of daylight access and glare to assessing the cognitive performance impacts due to CO2 levels to estimating the probability of Influenza A infection resulting from different space conditions.
We use happēTM as part of pre- and post-occupancy evaluations to assess the impacts that existing space conditions are having on occupants. We also use it during retrocomissioning and design to assess the relative impacts of different energy conservation measures (ECMs) or system types on productivity and health, and this is important for making life cycle cost analyses more comprehensive. We’ve found that quantifying productivity and health drives the decision-making process to be more inclusive of features impacting wellness, energy efficiency, and sustainability in general. It’s an important tool of our D.I.V.E. Project Framework®, used in conjunction with our other building performance modeling services, it increases our ability to maximize both the human experience and environmental stewardship, and to Improve Life through Better Built Environments®.
CO2 Levels & Cognitive Performance
Flu Infection Risk Estimator
BranchPattern’s Facility Infection Risk EstimatorTM module is intended to estimate the aerosol influenza particle removal efficiency resulting from several different removal mechanisms, and the associated probability of infection for adults and children, given a set of input conditions including space parameters, demographic factors, and time.
For more information, or to discuss your output results, feel free to connect with us.