2026-10-08T23:23:31Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34022040 2026-09-29T12:07:19Z category_25033 category_27190 category_27205 category_29173 category_26878 item_type_3 month_year_09_2026

Predictions of Air Conditioner prevalence in low- and middle-income countries for the year 2023 Amber Vayani (25109643) Tim C. D. Lucas (10793607) Regional analysis and development Health equity Public health not elsewhere classified Machine learning not elsewhere classified Climate change impacts and adaptation not elsewhere classified Air conditioning Extreme heat Predictive Modelling Machine Learning <p dir="ltr">Rising temperatures globally has increased the exposure to extreme heat. However, access to air conditioning (AC) remains unequal leaving vulnerable populations without means of coping with the heat. Household survey data on AC is scarce in low- and middle-income countries (LMICs) limiting the ability to identify cooling gaps. This project combines household data from the Demographic and Health Surveys (DHS) program with high resolution climatic, socioeconomic and demographic covariates to generate a 5km resolution prediction of AC ownership across LMICs in Africa and Asia for the year 2023.</p> 2026-09-29T12:07:19Z Dataset Dataset 10.6084/m9.figshare.34022040.v1 https://figshare.com/articles/dataset/Predictions_of_Air_Conditioner_prevalence_in_low-_and_middle-income_countries_for_the_year_2023/34022040 CC BY 4.0