Ajit Rajiva

Small-scale local data resources may serve to provide a highly resolved estimate of health effects, which can be spatially heterogeneous in highly populated urban centers in developing countries. We aim to highlight the challenges and opportunities of health data registries in a developing world context. In western India, government-collected daily mortality registry data were obtained from five cities, along with daily hospital admissions data from three government hospitals in Ahmedabad. In Nepal, individual-level data on hospital admissions were collected from six major hospitals in Kathmandu Valley. Our process illustrates many challenges for researchers, governments, and record keepers inherent to data collection in developing countries: creating and maintaining a centralized record-keeping system; standardizing the data collected; obtaining data from some local agencies; assuring data completeness and availability of back-ups to the datasets; as well as translating, cleaning, and comparing data within and across localities. We suggest that these “small-data” resources may better serve the analysis of health outcomes than exposure-response functions extrapolated from data collected in other areas of the world.

Introduction: Increasing heat waves-particularly in urban areas where construction is most prevalent, highlight a need for heat exposure assessment of construction workers. This study aims to characterize the effects of heat on construction workers from a site in Gandhinagar. Materials and Methods: This study involved a mixed methods approach consisting of a cross sectional survey with anthropometric measurements (n = 219) and four focus groups with construction workers, as well as environmental measurements of heat stress exposure at a construction site. Survey data was collected in two seasons i.e., summer and winter months, and heat illness and symptoms were compared between the two time periods. Thematic coding of focus group data was used to identify vulnerability factors and coping mechanisms of the workers. Heat stress, recorded using a wet bulb globe temperature monitor, was compared to international safety standards. Results: The survey findings suggest that heat-related symptoms increased in summer; 59% of all reports in summer were positive for symptoms (from Mild to Severe) as compared to 41% in winter. Focus groups revealed four dominant themes: (1) Non-occupational stressors compound work stressors; (2) workers were particularly attuned to the impact of heat on their health; (3) workers were aware of heat-related preventive measures; and (4) few resources were currently available to protect workers from heat stress. Working conditions often exceed international heat stress safety thresholds. Female workers and new employees might be at increased risk of illness or injury. Conclusion: This study suggests significant health impacts on construction workers from heat stress exposure in the workplace, showed that heat stress levels were higher than those prescribed by international standards and highlights the need for revision of work practices, increased protective measures, and possible development of indigenous work safety standards for heat exposure.

Recurrent heat waves, already a concern in rapidly growing and urbanizing South Asia, will very likely worsen in a warming world. Coordinated adaptation efforts can reduce heat’s adverse health impacts, however. To address this concern in Ahmedabad (Gujarat, India), a coalition has been formed to develop an evidence-based heat preparedness plan and early warning system. This paper describes the group and initial steps in the plan’s development and implementation. Evidence accumulation included extensive literature review, analysis of local temperature and mortality data, surveys with heat-vulnerable populations, focus groups with health care professionals, and expert consultation. The findings and recommendations were encapsulated in policy briefs for key government agencies, health care professionals, outdoor workers, and slum communities, and synthesized in the heat preparedness plan. A 7-day probabilistic weather forecast was also developed and is used to trigger the plan in advance of dangerous heat waves. The pilot plan was implemented in 2013, and public outreach was done through training workshops, hoardings/billboards, pamphlets, and print advertisements. Evaluation activities and continuous improvement efforts are ongoing, along with plans to explore the program’s scalability to other Indian cities, as Ahmedabad is the first South Asian city to address heat-health threats comprehensively.

In the recent past, spells of extreme heat associated with appreciable mortality have been documented in developed countries, including North America and Europe. However, far fewer research reports are available from developing countries or specific cities in South Asia. In May 2010, Ahmedabad, India, faced a heat wave where the temperatures reached a high of 46.8°C with an apparent increase in mortality. The purpose of this study is to characterize the heat wave impact and assess the associated excess mortality. We conducted an analysis of all-cause mortality associated with a May 2010 heat wave in Ahmedabad, Gujarat, India, to determine whether extreme heat leads to excess mortality. Counts of all-cause deaths from May 1–31, 2010 were compared with the mean of counts from temporally matched periods in May 2009 and 2011 to calculate excess mortality. Other analyses included a 7-day moving average, mortality rate ratio analysis, and relationship between daily maximum temperature and daily all-cause death counts over the entire year of 2010, using month-wise correlations. The May 2010 heat wave was associated with significant excess all-cause mortality. 4,462 all-cause deaths occurred, comprising an excess of 1,344 all-cause deaths, an estimated 43.1% increase when compared to the reference period (3,118 deaths). In monthly pair-wise comparisons for 2010, we found high correlations between mortality and daily maximum temperature during the locally hottest “summer” months of April (r = 0.69, p<0.001), May (r = 0.77, p<0.001), and June (r = 0.39, p<0.05). During a period of more intense heat (May 19–25, 2010), mortality rate ratios were 1.76 [95% CI 1.67–1.83, p<0.001] and 2.12 [95% CI 2.03–2.21] applying reference periods (May 12–18, 2010) from various years. The May 2010 heat wave in Ahmedabad, Gujarat, India had a substantial effect on all-cause excess mortality, even in this city where hot temperatures prevail through much of April-June.