Performance of low-cost monitors to assess household air pollution.

Exposure to household air pollution is a leading cause of morbidity and mortality globally. However, due to the lack of validated low-cost monitors with long-lasting batteries in indoor environments, most epidemiologic studies use self-reported data or short-term household air pollution assessments as proxies of long-term exposure. We evaluated the performance of three low-cost monitors measuring fine particulate matter (PM2.5) and carbon monoxide (CO) in a wood-combustion experiment conducted in one household of Spain for 5 days (including the co-location of 2 units of HAPEX and 3 units of TZOA-R for PM2.5 and 3 units of EL-USB-CO for CO; a total of 40 unit-days). We used Spearman correlation (ρ) and Concordance Correlation Coefficient (CCC) to assess accuracy of low-cost monitors versus equivalent research-grade devices. We also conducted a field study in India for 1 week (including HAPEX in 3 households and EL-USB-CO in 4 households; a total of 49 unit-days). Correlation and agreement at 5-min were moderate-high for one unit of HAPEX (ρ = 0.73 / CCC = 0.59), for one unit of TZOA-R (ρ = 0.89 / CCC = 0.62) and for three units of EL-USB-CO (ρ = 0.82-0.89 / CCC = 0.66-0.91) in Spain, although the failure or malfunction rate among low-cost units was high in both settings (60% of unit-days in Spain and 43% in India). Low-cost monitors tested here are not yet ready to replace more established exposure assessment methods in long-term household air pollution epidemiologic studies. More field validation is needed to assess evolving sensors and monitors with application to health studies.

Characterizing Spatial Variability of Climate-Relevant Hazards and Vulnerabilities in the New England Region of the United States.

Weather and climate have substantial effects on human health. While much is known about how morbidity and mortality are affected by moderate-to-extreme heat, poor air quality, and heavy precipitation individually, less is known about the cumulative occurrence of these climatic hazards, and the extent to which they spatially overlap with community-scale vulnerabilities. Specifically, there is interest in determining whether individuals living in places with the highest exposure to multiple health hazardous climatic conditions are also more vulnerable to having negative health outcomes. Presented here is a spatial analysis of the distribution of health-relevant climatic hazards and social vulnerabilities across the New England region of the northeastern United States. We show that the frequency of excessive heat days, heavy precipitation days, and ozone (O3) and fine particulate matter (PM2.5) exceedances during the warm seasons (May-September) from 2009 to 2014 have distinct spatial distributions and are statistically significantly correlated across space with indicators of social vulnerability. We further quantify an integrated measure of the hazards and vulnerabilities to illustrate the spatial heterogeneity of overall risk, as well as to demonstrate how the choice of spatial scale influences the identification of high-risk areas. These methods are transferrable to other locations and contexts, which could be of utility not only to geographers and epidemiologists, but also to policymakers tasked with allocating public health resources to populations at greatest risk of weather- and climate-related health effects.

A comparison of head-unrestrained and head-restrained pursuit: influence of eye position and target velocity on latency.

Horizontal step-ramp target trajectories were used to study the initiation of head-unrestrained and head-restrained pursuit in the monkey. In a first series of experiments, initial target position (0 degrees, 5 degrees, or 30 degrees, contraversive to the direction of pursuit), fixation duration, target velocity (20 degrees, 40 degrees, 60 degrees and 80 degrees/s), and target direction were randomized in order to minimize predictive responses. Animals pursued the target either with their eyes alone (head-restrained: HR condition) or with a combination of eye and head movements (head-unrestrained: HU condition). Head motion onset consistently lagged pursuit onset (i.e., eye motion) by 50 ms or more in the HU condition, and was influenced by target velocity as well as by initial target position. Pursuit onset latencies did not vary systematically as a function of target velocity in either the HR or HU conditions. However, pursuit initiation latencies tended to be longer in the HU condition as compared to the HR condition when target motion started from the most contraversive position. A second series of experiments revealed that this difference in HR and HU pursuit onset latencies could be explained by the effects of initial eye-in-head position; more contraversive initial eye positions yielded shorter pursuit latencies in both conditions, and the monkeys generally moved their head towards the target in the HU condition, resulting in smaller eye-in-head eccentricities. Furthermore, we found that initial gaze and head positions had little or no effect on pursuit latencies. We conclude that the latency for pursuit initiation is similar irrespective of whether an animal is head-restrained or head-unrestrained, when initial eye position is held constant.