Literature DB >> 30063542

The Effect of Electrical Load Shedding on Pediatric Hospital Admissions in South Africa.

Christian Gehringer1,2, Heinz Rode2, Michael Schomaker3.   

Abstract

BACKGROUND: South Africa faced repeated episodes of temporary power shutdowns, or load shedding, in 2014/2015. The effect of load shedding on children's health is unknown.
METHODS: We determined periods of load shedding using Twitter, Facebook, and data from the City of Cape Town. We obtained the number of unscheduled hospital admissions between June 2014 and May 2015 from Red Cross Children's Hospital, Cape Town, and weather data from the South African Weather Service. We used quasi-Poisson regression models to explore the relationship between number of hospital admissions and load shedding, adjusted for season, weather, and past admissions. Based on assumptions about the causal process leading to hospital admissions, we estimated the average treatment effect, that is, the difference in expected number of admissions per day had there been load shedding each day or on any of the preceding 2 days compared with if there had not been any load shedding.
RESULTS: We found a 10% increase (95% confidence interval: 4%, 15%) in hospital admissions for days where load shedding was experienced on the same day, or no more than 2 days prior, compared with when there was no load shedding in the past 2 days. The increase was more pronounced during weekdays (12% [7%, 18%] vs. 1% [-9%, 11%]), and for specific diagnoses (e.g., respiratory system: 14% [2%, 26%]). The average treatment effect was estimated as 6.50 (5.12, 7.87) highlighting that about 6 additional admissions a day could be attributed to load shedding.
CONCLUSIONS: The association we measured is consistent with our hypothesis that failures of the power infrastructure increase risk to children's health. See video abstract at, http://links.lww.com/EDE/B409.

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Year:  2018        PMID: 30063542      PMCID: PMC6167164          DOI: 10.1097/EDE.0000000000000905

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


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