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Want to prevent pandemics? Stop spillovers
Decision-makers discussing landmark agreements on health and biodiversity must include four actions to reduce the risk of animals and people exchanging viruses.
Decision-makers discussing landmark agreements on health and biodiversity must include four actions to reduce the risk of animals and people exchanging viruses.
Journal Article
Warm Season and Emergency Department Visits to U.S. Children’s Hospitals
Extreme heat exposures are increasing with climate change. Health effects are well documented in adults, but the risks to children are not well characterized.
We estimated the association between warm season (May to September) temperatures and cause-specific emergency department (ED) visits among U.S. children and adolescents.
This multicenter time-series study leveraged administrative data on
ED visits by children and adolescents
of age to the EDs of 47 U.S. children's hospitals from May to September from 2016 to 2018. Daily maximum ambient temperature was estimated in the county of the hospital using a spatiotemporal model. We used distributed-lag nonlinear models with a quasi-Poisson distribution to estimate the association between daily maximum temperature and the relative risk (RR) of ED visits, adjusting for temporal trends. We then used a random-effects meta-analytic model to estimate the overall cumulative association.
Extreme heat was associated with an RR of all-cause ED visits of 1.17 (95% CI: 1.12, 1.21) relative to hospital-specific minimum morbidity temperature. Associations were more pronounced for ED visits due to heat-related illness including dehydration and electrolyte disorders (
1.83; 95% CI: 1.31, 2.57), bacterial enteritis (1.35; 95% CI: 1.02, 1.79), and otitis media and externa (1.30; 95% CI: 1.11, 1.52). Taken together, temperatures above the minimum morbidity temperature accounted for an estimated 11.8% [95% empirical 95% confidence interval (eCI): 9.9%, 13.3%] of warm season ED visits for any cause and 31.0% (95% eCI: 17.9%, 36.5%) of ED visits for heat-related illnesses.
During the warm season, days with higher temperatures were associated with higher rates of visits to children's hospital EDs. Higher ambient temperatures may contribute to a significant proportion of ED visits among U.S. children and adolescents. https://doi.org/10.1289/EHP8083.
Journal Article
Climate change and health in Kuwait: temperature and mortality projections under different climatic scenarios
It is uncertain what climate change could bring to populations and countries in the hot desert environment of the Arabian Peninsula. Not only because they are already hot, countries in this region also have unique demographic profiles, with migrant populations potentially more vulnerable and constituting a large share of the population. In Kuwait, two-thirds of the population are migrant workers and record-high temperatures are already common. We quantified the temperature-related mortality burdens in Kuwait in the mid- (2050–2059) and end-century (2090–2099) decades under moderate (SSP2-4.5) and extreme (SSP5-8.5) climate change scenarios. We fitted time series distributed lag non-linear models to estimate the baseline temperature–mortality relationship which was then applied to future daily mean temperatures from the latest available climate models to estimate decadal temperature-mortality burdens under the two scenarios. By mid-century, the average temperature in Kuwait is predicted to increase by 1.80 °C (SSP2-4.5) to 2.57 °C (SSP5-8.5), compared to a 2000–2009 baseline. By the end of the century, we could see an increase of up to 5.54 °C. In a moderate scenario, climate change would increase heat-related mortality by 5.1% (95% empirical confidence intervals: 0.8, 9.3) by end-century, whereas an extreme scenario increases heat-related mortality by 11.7% (2.7, 19.0). Heat-related mortality for non-Kuwaiti migrant workers could increase by 15.1% (4.6, 22.8). For every 100 deaths in Kuwait, 13.6 (−3.6, 25.8) could be attributed to heat driven by climate change by the end of the century. Climate change induced warming, even under more optimistic mitigation scenarios, may markedly increase heat-related mortality in Kuwait. Those who are already vulnerable, like migrant workers, could borne a larger impact from climate change.
Journal Article
The Untapped Potential of Precision Health to Improve Heat Resilience for Those Who Need It Most
Additionally, heat preparedness strategies often distribute scarce resources based on neighborhood-level social determinants of health, including wealth, health care access, and race.3 However, substantial variability in the social determinants of health relevant to heat risk-such as social isolation, living on the top floor of a residence, and access to air conditioning-leads to variation in heat exposure even within neighborhoods. Organisms-from mustard plants to humans-have genetically influenced responses to heat stress, and polymorphisms in several candidate genes may underlie variation in heat stroke risk.4 Variability in genes involved in drug metabolism (e.g., CYP2D6) might also explain why, for example, the use of beta blockers and selective serotonin reuptake inhibitors may increase the risk of hospitalization when temperatures rise 5 With more nuanced data input, heat alerts could be issued and resources deployed specifically based on the characteristics of individuals and specific populations most sensitive to heat at temperatures lower than would pose risks to the general population. [...]a targeted approach is already being used in 24 Italian cities6 REQUIRED STAKEHOLDERS AND COLLABORATORS To deliver a precision health-based heat response in the United States, health care providers and systems must serve as important allies of the public health agencies and atmospheric scientists charged with heat preparedness. Health care providers and systems likely have detailed information on heat risk and resilience factors for their patients, such as age, diagnoses, medications, occupation, and, increasingly, social determinants of health, including energy insecurity and access to air conditioning. [...]precision health has often been construed to value what can be learned from reductionist biology above qualitative and social science.
Journal Article
Extreme heat and work injuries in Kuwait’s hot summers
BackgroundHot, desert Gulf countries are host to millions of migrant workers doing outdoor jobs such as construction and hospitality. The Gulf countries apply a summertime ban on midday work to protect workers from extreme heat, although without clear evidence of effectiveness. We assessed the risk of occupational injuries associated with extreme hot temperatures during the summertime ban on midday work in Kuwait.MethodsWe collected daily occupational injuries in the summer months that are reported to the Ministry of Health’s Occupational Health Department for 5 years from 2015 to 2019. We fitted generalised additive models with a quasi-Poisson distribution in a time series design. A 7-day moving average of daily temperature was modelled with penalised splines adjusted for relative humidity, time trend and day of the week.ResultsDuring the summertime ban, the daily average temperature was 39.4°C (±1.8°C). There were 7.2, 7.6 and 9.4 reported injuries per day in the summer months of June, July and August, respectively. Compared with the 10th percentile of summer temperatures in Kuwait (37.0°C), the average day with a temperature of 39.4°C increased the relative risk of injury to 1.44 (95% CI 1.34 to 1.53). Similarly, temperatures of 40°C and 41°C were associated with relative risks of 1.48 (95% CI 1.39 to 1.59) and 1.44 (95% CI 1.27 to 1.63), respectively. At the 90th percentile (42°C), the risks levelled off (relative risk 1.21; 95% CI 0.93 to 1.57).ConclusionWe found substantial increases in the risk of occupational injury from extremely hot temperatures despite the ban on midday work policy in Kuwait. ‘Calendar-based’ regulations may be inadequate to provide occupational heat protections, especially for migrant workers.
Journal Article
A national assessment of underground natural gas storage: identifying wells with designs likely vulnerable to a single-point-of-failure
The leak of processed natural gas (PNG) from October 2015 to February 2016 from the Aliso Canyon storage facility, near Los Angeles, California, was the largest single accidental release of greenhouse gases in US history. The Interagency Task Force on Natural Gas Storage Safety and California regulators recently recommended operators phase out single-point-of-failure (SPF) well designs. Here, we develop a national dataset of UGS well activity in the continental US to assess regulatory data availability and uncertainty, and to assess the prevalence of certain well design deficiencies including single-point-of-failure designs. We identified 14 138 active UGS wells associated with 317 active UGS facilities in 29 states using regulatory and company data. State-level wellbore datasets contained numerous reporting inconsistencies that limited data concatenation. We identified 2715 active UGS wells across 160 facilities that, like the failed well at Aliso Canyon, predated the storage facility, and therefore were not originally designed for gas storage. The majority (88%) of these repurposed wells are located in OH, MI, PA, NY, and WV. Repurposed wells have a median age of 74 years, and the 2694 repurposed wells constructed prior to 1979 are particularly likely to exhibit design-related deficiencies. An estimated 210 active repurposed wells were constructed before 1917-before cement zonal isolation methods were utilized. These wells are located in OH, PA, NY, and WV and represent the highest priority related to potential design deficiencies that could lead to containment loss. This national baseline assessment identifies regulatory data uncertainties, highlights a potentially widespread vulnerability of the natural gas supply chain, and can aid in prioritization and oversight for high-risk wells and facilities.
Journal Article
Improved Bounds for Matching in Random-Order Streams
We study the problem of computing an approximate maximum cardinality matching in the semi-streaming model when edges arrive in a random order. In the semi-streaming model, the edges of the input graph G=(V,E) are given as a stream e1,…,em, and the algorithm is allowed to make a single pass over this stream while using O(npolylog(n)) space (m=|E| and n=|V|). If the order of edges is adversarial, a simple single-pass greedy algorithm yields a 1/2-approximation in O(n) space; achieving a better approximation in adversarial streams remains an elusive open question. A line of recent work shows that one can improve upon the 1/2-approximation if the edges of the stream arrive in a random order. The state of the art for this model is two-fold: Assadi et al. [SODA 2019] show how to compute a 23(∼.66)-approximate matching, but the space requirement is O(n1.5polylog(n)). Very recently, Farhadi et al. [SODA 2020] presented an algorithm with the desired space usage of O(npolylog(n)), but a worse approximation ratio of 611(∼.545), or 35(=.6) in bipartite graphs. In this paper, we present an algorithm that computes a 23(∼.66)-approximate matching using only O(nlog(n)) space, improving upon both results above. We also note that for adversarial streams, a lower bound of Kapralov [SODA 2013] shows that any algorithm that achieves a 1-1e(∼.63)-approximation requires (n1+Ω(1/loglog(n))) space; recent follow-up work by the same author improved this lower bound to 1+ln(2)∼.59 [SODA 2021]. As a consequence, both our result and the earlier result of Farhadi et al. prove that the problem of computing a maximum matching is strictly easier in random-order streams than in adversarial ones.
Journal Article
Climate, air quality, and health benefits of a carbon fee-and-rebate bill in Massachusetts, USA
State and regional climate policies in the United States are becoming more prevalent. Quantifying these policies' health co-benefits provides a local and near-term rationale for actions that also mitigate global climate change and its accompanying harms. Here, we assess the health benefits of a carbon fee-and-rebate policy directed at fuel use in transport, residential and commercial buildings and industry in Massachusetts. We find that the air pollution reductions from this policy would save 340 lives (95% CI: 82-590), 64% of which would occur in Massachusetts, and reduce carbon emissions by 33 million metric tons, with 2017 as an implementation year, through 2040. When monetized, the benefits to health may be larger than the benefits from climate mitigation, but are sensitive to valuation methods, discount rates, and the leakage rate of natural gas, among other factors. These benefits derive largely from lower transportation emissions, including volatile organic compounds from gasoline combustion. Reductions in oil and coal use have relatively large benefits, despite their limited use in Massachusetts. This study finds substantial health benefits of a proposed statewide carbon policy in Massachusetts that carries near-term and direct benefit to residents of the commonwealth and demonstrates the importance of co-benefits modeling.
Journal Article