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In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with pre-existing health conditions. Accurately predicting indoor temperatures during these events is crucial for informing public health strategies and mitigating the adverse impacts of extreme heat. While current systems rely on outdoor temperature data, incorporating real-time indoor temperature estimations can significantly enhance decision-making and strengthen overall health system responses. Sensor-based technologies, such as ecobee smart thermostats installed in homes, enable effortless collection of indoor temperature and humidity data. This study evaluates the efficacy of deep learning models in predicting indoor temperatures during heat waves using smart thermostat data, to enhance public health responses. Utilizing ecobee smart thermostats, we analyzed indoor temperature trends and developed forecasting models. Our findings indicate the potential of integrating IoT and deep learning into health warning systems, enabling proactive interventions, and improving sustainable health care practices in extreme heat scenarios. This approach highlights the role of digital health innovations in creating the resilient and sustainable healthcare systems against climate-related health adversities.

Objectives: This study aimed to explore how the unprecedented stressors associated with the COVID-19 pandemic may have contributed to heightened levels of depression and anxiety among pregnant Indigenous persons, and identify protective individual-level factors., Design: The current study used a mixed-methods design including standardised questionnaires and open-ended response questions. Using hierarchical regression models, we examined the extent to which COVID-19-related factors of service disruption (ie, changes to prenatal care, changes to birth plans and social support) were associated with mental well-being. Further, through qualitative analyses of open-ended questions, we examined the coping strategies used by pregnant Indigenous persons in response to the pandemic., Setting: Participants responded to an online questionnaire consisting of standardised measures from 2020 to 2021., Participants: The study included 336 self-identifying Indigenous pregnant persons in Canada., Results: Descriptive results revealed elevated rates of clinically relevant depression (52.7%) and anxiety (62.5%) symptoms among this population. 76.8% of participants reported prenatal care service disruptions, including appointment cancellations. Thematic analyses identified coping themes of staying informed, social and/or cultural connections and activities, and internal mental well-being strategies. Disruptions to services and decreased quality of prenatal care negatively impacted mental well-being of Indigenous pregnant persons during the COVID-19 pandemic., Conclusions: Given the potential for mental well-being challenges to persist and long-term effects of perinatal distress, it is important to examine the quality of care that pregnant individuals receive. Service providers should advance policies and practices that promote relationship quality and health system engagement as key factors linked to well-being during the perinatal period for Indigenous persons., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)