Shifting the focus to functioning: essential for achieving Sustainable Development Goal 3, inclusive Universal Health Coverage and supporting COVID-19 survivors

If Sustainable Developmental Goal 3 and Universal Health Coverage are to be achieved, functioning is a third health indicator which must be assessed and integrated into global health population-based metrics alongside mortality and morbidity. In this paper, we define functioning according to the International Classification of Functioning, Disability and Health (ICF) and present why functioning is important to measure, especially when considering the need for, and outcome of, rehabilitation and assistive technology. We discuss examples of tools that measure components of functioning through clinical assessment and self-report methodologies, and present the development of a comprehensive population level tool which aligns with the ICF and combines self-report and clinical measurement methods to measure functioning and the need for rehabilitation and AT. Throughout the paper a survivor of Coronavirus 2019 (COVID-19) is given as an example to illustrate functioning according to the ICF and how access to the interventions of rehabilitation and assistive technology might be of benefit to improve and optimise his/her functioning. We argue that the Global Health community must take action and ensure that the measurement of functioning is well established, accepted and integrated as the third health indicator following the COVID-19 pandemic.

Assessing a population's exposure to heat and humidity: an empirical approach

Background

It is widely accepted that assessing the impact of heat on populations is an important aspect of climate change research. However, this raises questions about how best to measure people's exposure to heat under everyday living conditions in more detail than is possible by relying on nearby sources of meteorological data.

Objective

This study aimed to investigate practical and viable approaches to measuring air temperature and humidity within a population, making comparisons with contemporaneous external data sources. This was done in a rural South African population during the subtropical summer season.

Results

Air temperature and humidity were measured indoors and outdoors at three locations over 10 days and the datalogger technology proved reliable and easy to use. There was little variation in measurements over distances of 10 km.

Conclusions

Small battery-powered automatic dataloggers proved to be a feasible option for collecting weather data among a rural South African population. These data were consistent with external sources but offered more local detail. Detailed local contemporary data may also allow post hoc modelling of previously unmeasured local weather data in conjunction with global gridded climate models.