Forecasting Occupational Survivability of Rickshaw Pullers in a Changing Climate with Wearable Data

TL;DR

This study uses wearable sensors and climate models to predict heat-related health risks for rickshaw pullers in Dhaka, revealing increasing vulnerability due to climate change and providing a predictive framework for occupational survivability.

Contribution

It introduces a novel LGBN regression model combining real-time physiological data with climate projections to assess occupational heat stress risk.

Findings

Currently, 32% face high heat exposure risk.

Projected increase to 37% by 2026-2030.

Average heat exposure duration will nearly double.

Abstract

Cycle rickshaw pullers are highly vulnerable to extreme heat, yet little is known about how their physiological biomarkers respond under such conditions. This study collected real-time weather and physiological data using wearable sensors from 100 rickshaw pullers in Dhaka, Bangladesh. In addition, interviews with 12 pullers explored their knowledge, perceptions, and experiences related to climate change. We developed a Linear Gaussian Bayesian Network (LGBN) regression model to predict key physiological biomarkers based on activity, weather, and demographic features. The model achieved normalized mean absolute error values of 0.82, 0.47, 0.65, and 0.67 for skin temperature, relative cardiac cost, skin conductance response, and skin conductance level, respectively. Using projections from 18 CMIP6 climate models, we layered the LGBN on future climate forecasts to analyze survivability for current (2023-2025) and future years (2026-2100). Based on thresholds of WBGT above 31.1{\deg}C and skin temperature above 35{\deg}C, 32% of rickshaw pullers already face high heat exposure risk. By 2026-2030, this percentage may rise to 37% with average exposure lasting nearly 12 minutes, or about two-thirds of the trip duration. A thematic analysis of interviews complements these findings, showing that rickshaw pullers recognize their increasing climate vulnerability and express concern about its effects on health and occupational survivability.