Predicted heat strain (PHS)

PHS, Predicted Heat Strain, is an analytical model for estimating the body’s thermal response to heat exposure. It considers environment, activity, clothing, and duration to support preventive decisions.

In short

PHS estimates thermal overload under defined conditions and assumptions. Its results are not individual measurements nor an automatic permit to work for the calculated time.

Content
  1. What is predicted heat strain?
  2. Heat stress and the body’s response
  3. Required data
  4. Results and exposure times
  5. Limits and technical competence
  6. Practical example
  7. Incorporate measures and review
  8. Common mistakes
  9. Related concepts
  10. On the blog
  11. References

AZ Dictionary →

What is predicted heat strain?

The PHS model estimates the body’s response to specific thermal conditions. It helps analyze the predicted evolution of parameters related to heat accumulation and water loss. Its application is described in ISO 7933, the edition of which must be identified when documenting the study.

It differs from the WBGT index in its analytical approach. WBGT is used for screening, while PHS allows for a more detailed examination of a scenario within its parameters. Neither replaces job knowledge or the necessary preventive measures. Greater calculation complexity does not automatically guarantee a better conclusion.

Heat stress and the body’s response

Heat stress describes the heat load associated with the environment, activity, and clothing. Heat strain refers to the physiological response that this combination triggers. Distinguishing between these two concepts helps to understand why an environmental measurement is not equivalent to knowing a person’s internal temperature.

PHS calculates estimates using a model; it does not directly observe what happens to each worker. Individual differences and health conditions exist that require assessment by the appropriate professionals. A prediction should not be presented as a clinical measurement, nor should it be used to claim that a specific person will tolerate a given exposure without risk.

Required data

The analysis requires describing environmental conditions, metabolic activity, clothing characteristics, and duration. Representative data and correct units must be used. An input chosen for convenience can skew the result, especially if effort is underestimated or clothing is assumed to allow for greater heat loss than is actually used.

Each source—measurement, observation, equipment instructions, or applicable technical table—should be justified. If the task varies, it must be defined how that variation is represented and whether the tool can handle the scenario. A calculation based on unrealistic average values ​​can mask periods of intense exposure, even if the output is presented with numerous decimal places.

Results and exposure times

The INSST calculator, based on UNE-EN ISO 7933:2023, provides estimates and, where applicable, a time limit associated with reference values ​​for internal temperature or accumulated water loss. The interpretation must take into account the input conditions and the criterion that determines the most restrictive result.

This timeframe does not authorize work to continue until the last minute. It must be integrated into a plan that considers recovery, environmental changes, symptom monitoring, and model limitations. If a condition worsens or signs of impairment appear, immediate action is required, without waiting for the calculated timeframe to expire.

Limits and technical competence

Before applying PHS, the ranges and assumptions of the version and tool used must be verified. An equation should not be extrapolated from its field to solve for any combination of clothing, exposure, or activity. When an assumption is not met, another approach should be selected, or the assessment should be completed with expert assistance.

Health surveillance can provide individual and collective preventive measures within its intended purpose. Any physiological monitoring requires justification, competent interpretation, and respect for confidentiality. It is inappropriate to turn a sensor or computer estimate into an automated instruction that ignores symptoms reported by the individual.

Practical example

In a facility, a task is performed near a radiant source for varying periods. Initial screening identifies the need for improved control. To compare alternatives, a more detailed analysis of exposure is proposed, considering different distances, barriers, and work sequences, while maintaining consistent data on exertion and clothing.

PHS can help explore these options, but first, the model must be verified to accurately represent the scenario. The chosen alternative is validated in practice and integrated with recovery and symptom response. The example illustrates its usefulness in designing measures, rather than simply using the calculation to justify the duration of existing work.

Incorporate measures and review

Measures should reduce heat stress through design, insulation of heat sources, aids to reduce physical exertion, and organization. Acclimatization is part of the plan, along with accessible water, recovery, and monitoring. None of these measures should be interpreted in isolation as sufficient compensation for exposure that remains excessive.

After intervening, it’s advisable to review the model’s inputs and verify actual conditions. Version records, measurements, assumptions, and decisions must be maintained. If the process, protective clothing, or pace changes, the previous calculation may no longer accurately reflect the work. Updates should be linked to these changes and any incidents or difficulties observed.

Common mistakes

Common mistakes include introducing favorable values ​​without evidence, confusing prediction with personal measurement, and presenting a time limit as an absolute guarantee. It is also a mistake to compare results obtained with different versions or assumptions without explanation, or to select the most complex tool before defining which preventive question needs answering.

The usefulness of PHS depends on data quality and interpretation. It should support sound and verifiable decisions, ensuring a prepared response to heatstroke and other effects. Symptoms and changes in conditions take operational priority over a prediction developed for a scenario that no longer reflects reality.

Related concepts

On the blog

References

  1. National Institute for Occupational Safety and Health. Predicted heat strain calculator, according to UNE-EN ISO 7933:2023. 2025. Official source
  2. National Institute for Occupational Safety and Health. Thermal environment. Official source
  3. National Institute for Occupational Safety and Health. NTP 1189: Assessment of the risk of heat stress, WBGT index. 2023. Official source
  4. National Institute for Occupational Safety and Health. Heat Stress: Workplace Recommendations. 2026 update. Official source
  5. Official State Gazette. Law 31/1995, on Occupational Risk Prevention. Consolidated text. Official source

Editorial information

Publication date: October 10, 2026.

Editorial Manager: Sabentis Editorial Team.

Author: Pablo Rodríguez LinkedIn

Executive Vice President of the ORP International Foundation and Chief Financial Officer of Sabentis.

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