Development of Spatio-Temporal Land Use Regression Models for Fine Particulate Matter and Wood-Burning Tracers in Temuco, Chile.

Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) µg m-3 for PM2.5, 0.607 (0.538) µg m-3 for levoglucosan, and 0.635 (0.489) µg m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.

Temporal and Spatial Trends of Adverse Pregnancy and Birth Outcomes in a Sample of Births from a Public Hospital in Chile.

Understanding temporal and spatial trends in pregnancy and birth outcomes within an urban area is important for the monitoring of health indicators of a population. We conducted a retrospective cohort study of all births in the public hospital of Temuco, a medium-sized city in Southern Chile between 2009 and 2016 (n = 17,237). Information on adverse pregnancy and birth outcomes, as well as spatial and maternal characteristics (insurance type, employment, smoking, age, and overweight/obesity), was collected from medical charts. Home addresses were geocoded and assigned to neighborhood. We tested whether births and prevalence of adverse pregnancy outcomes changed over time, whether birth events were spatially clustered (Moran's I statistic), and whether neighborhood deprivation was correlated to outcomes (Spearman's rho). We observed decreases in eclampsia, hypertensive disorders of pregnancy, and small for gestational age, while gestational diabetes, preterm birth, and low birth weight increased over the study period (all p < 0.01 for trend), with little changes after adjusting for maternal characteristics. We observed neighborhood clusters for birth rate, preterm birth, and low birth weight. Neighborhood deprivation was negatively correlated with low birth weight and preterm birth, but not correlated with eclampsia, preeclampsia, hypertensive disorders of pregnancy, small for gestational age, gestational diabetes, nor stillbirth. Several encouraging downward trends and some increases in adverse pregnancy and birth outcomes, which, overall, were not explained by changes in maternal characteristics were observed. Identified clusters of higher adverse birth outcomes may be used to evaluate preventive health coverage in this setting.

Investigating the Risk Factors Associated with Injury Severity in Pedestrian Crashes in Santiago, Chile.

Pedestrians are vulnerable road users that are directly exposed to road traffic crashes with high odds of resulting in serious injuries and fatalities. Therefore, there is a critical need to identify the risk factors associated with injury severity in pedestrian crashes to promote safe and friendly walking environments for pedestrians. This study investigates the risk factors related to pedestrian, crash, and built environment characteristics that contribute to different injury severity levels in pedestrian crashes in Santiago, Chile from a spatial and statistical perspective. First, a GIS kernel density technique was used to identify spatial clusters with high concentrations of pedestrian crash fatalities and severe injuries. Subsequently, partial proportional odds models were developed using the crash dataset for the whole city and the identified spatial clusters to examine and compare the risk factors that significantly affect pedestrian crash injury severity. The model results reveal higher increases in the fatality probability within the spatial clusters for statistically significant contributing factors related to drunk driving, traffic signage disobedience, and imprudence of the pedestrian. The findings may be utilized in the development and implementation of effective public policies and preventive measures to help improve pedestrian safety in Santiago.

Quality of automatic geocoding tools: a study using addresses from hospital record files in Temuco, Chile.

Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.

Solving the bin location-allocation problem for household and recycle waste generated in the commune of Renca in Santiago, Chile.

In the commune of Renca in Santiago, Chile, the household waste is currently collected on the kerbside and then thrown in the rear of a compactor truck. This system becomes inefficient when not all citizens are always serviced, yielding high overall collection costs and negative impacts on the environment and the society. Recently, recyclable waste collection sites have been situated throughout the commune, which need to be examined with respect to population coverage and average travel distances to these sites. This study employs mixed-integer linear programming models and geographic information systems to solve the bin location-allocation problem for household and recyclable waste separately. The results are shown for different values of waste generation, bin capacities, and travel distances, in addition to considering the users' and municipality's preferences in the decision-making process. The proposed recyclable waste bin locations present a more efficient solution than the existing collection sites in the commune of Renca since more users are serviced within a shorter travel distance to dispose of their recyclable waste.

Quality of automatic geocoding tools: a study using addresses from hospital record files in Temuco, Chile / Calidad de las herramientas automáticas de geocodificación: un estudio usando direcciones de fichas de registro hospitalario en Temuco, Chile / A qualidade das ferramentas de geocodificação automática: um estudo utilizando endereços de prontuários hospitalares em Temuco, Chile

Abstract: Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.

Resumen: Los métodos automáticos de geocodificación se han convertido en algo popular durante los últimos años para facilitar el estudio de la asociación entre resultados de salud y lugar para vivir. No obstante, más bien pocos estudios han evaluado la calidad de la geocodificación, siendo realizados la mayoría de ellos en EE.UU. y Europa. El objetivo de este artículo es comparar la calidad de tres herramientas automáticas de geocodificación en línea frente a un método de referencia. La submuestra de 300 direcciones escritas a mano, procedentes del registro hospitalario, se geocodificaron usando Bing, Google Earth y Google Maps. Los porcentajes de coincidencia fueron mayores (> 80%) en el caso de Google Maps y Google Earth comparados con Bing. Sin embargo, la precisión de las direcciones fue mejor con Bing, en una proporción más grande (> 70%) de direcciones que tenían errores de posición por debajo de 20m. En general, el rendimiento no varió en cada método para diferentes niveles estatus socioeconómico. En general, los métodos mostraron un rendimiento aceptable, pero heterogéneo. Esto previene contra el uso de métodos automáticos sin evaluar la calidad en otras ciudades, particularmente en Chile y Latinoamérica.

Resumo: Os métodos de geocodificação automática se tornaram populares nos últimos anos para facilitar o estudo da associação entre desfechos de saúde e lugar de residência. Entretanto, poucos estudos avaliaram a qualidade da geocodificação, e a maioria dos estudos existentes foi realizada nos Estados Unidos e Europa. O estudo teve como objetivo comparar a qualidade de três ferramentas de geocodificação eletrônica automática em relação a um método de referência. Foi geocodificada uma subamostra de 300 endereços anotados à mão em prontuários hospitalares, usando Bing, Google Earth e Google Maps. As taxas de correspondência dos registros foram mais altas (> 80%) com Google Maps e Google Earth, comparado com Bing. Entretanto, a acurácia dos endereços foi melhor com Bing, com uma proporção maior (> 70%) de endereços com erros de localização menores que 20 metros. Em geral, o desempeno não variou para cada método de acordo com condição socioeconômica. Os métodos apresentaram desempenho geral aceitável, porém heterogêneo. Os resultados servem de alerta contra o uso de métodos automáticos sem avaliar a qualidade em outras cidades, particularmente no Chile e no resto da América Latina.

Differential impacts of ridesharing on alcohol-related crashes by socioeconomic municipalities: rate of technology adoption matters.

BACKGROUND: An emergent group of studies have examined the extent under which ridesharing may decrease alcohol-related crashes in countries such as United States, United Kingdom, Brazil, and Chile. Virtually all existent studies have assumed that ridesharing is equally distributed across socioeconomic groups, potentially masking differences across them. We contribute to this literature by studying how socioeconomic status at the municipal level impacts Uber's effect on alcohol-related crashes. METHODS: We use data provided by Chile's Road Safety Commission considering all alcohol-related crashes, and fatal and severe alcohol-related injuries that occurred between January 2013 and September 2013 (before Uber) and January and September 2014 (with Uber) in Santiago. We first apply spatial autocorrelation techniques to examine the level of spatial dependence between the location of alcohol-related crashes with and without Uber. We then apply random-effects meta-analysis to obtain risk ratios of alcohol-related crashes by considering socioeconomic municipality differences before and after the introduction of Uber. RESULTS: In both analyses, we find that the first 9 months of Uber in Santiago is associated with significant rate ratio decreases (RR = 0.71 [95% Confidence Interval (C.I.) 0.56, 0.89]) in high socioeconomic municipalities in all alcohol-related crashes and null (RR = 1.10 [95% C.I. 0.97, 1.23]) increases in low socioeconomic municipalities. No concomitant associations were observed in fatal alcohol-related crashes regardless of the socioeconomic municipality group. CONCLUSIONS: One interpretation for the decline in alcohol-related crashes in high socioeconomic municipalities is that Uber may be a substitute form of transport for those individuals who have access to credit cards, and thus, could afford to pay for this service at the time they have consumed alcohol. Slight increases of alcohol-related crashes in low socioeconomic municipalities should be studied further since this could be related to different phenomena such as increases in alcohol sales and consumption, less access to the provision of public transport services in these jurisdictions, or biases in police reports.

Motivation for Critical Thinking in Nursing Students in Chile.

Nursing education includes a constant challenge regarding the competencies that nurses must possess to provide high-quality nursing care. One of these competencies is critical thinking (CT), and motivation for critical thinking (MCT) has been identified as an element necessary to develop CT. Expectancy and value are important components of the MCT. This study aimed to analyze sociodemographic and academic factors related to MCT in Chilean nursing students. This study is an analytical-correlational, cross-sectional study conducted with 478 nursing students in Chile. The data were collected using an online questionnaire. The Critical Thinking Motivation Scale was used to measure MCT. Pearson's square, Chi-square, means comparison test, and binomial logistic regression were used to analyze the data. The expectancy component of the MCT had the lowest scores on the scale. Age was associated with the cost subcomponent (p < .03), and high school was associated with the interest subcomponent (p < .01). Academic factors contributing to MCT were problem-based learning, professor motivation, and the inclusion of MCT in nursing disciplinary subjects. Strategies that improve CT and MCT should be implemented and evaluated periodically from the beginning of a nursing career. Faculty should be trained to motivate students to think critically.

Network design of a household waste collection system: A case study of the commune of Renca in Santiago, Chile.

This study proposes a design of a household waste collection system based on a two-stage procedure. First, the bin location-allocation problem is solved by selecting collection sites from a set of potential sites, and determining the type and number of bins at each selected collection site. Second, bin-to-bin waste collection routes are obtained for a fleet of homogeneous vehicles that are restricted by either work shift duration or vehicle capacity. Mixed integer linear programming (MILP) models are proposed for both stages, considering the particular characteristics of the problem. The models are applied to a real-world instance in the commune of Renca in Santiago, Chile. The results of first stage indicate an important preference for small bins since they have a lower unitary cost. Due to the large size of the real instance, a Large Neighborhood Search (LNS) heuristic is used in the second stage to find good feasible vehicle routing solutions in a reasonable period of time. The results for the routing phase suggest a larger number of routes in the morning work shift since these routes have shorter distances. The LNS heuristic presents a satisfactory behavior when compared to the MILP model with small instances. The proposed bin-to-bin household waste collection vehicle routing presents a more efficient solution than the existing door-to-door waste collection in the commune of Renca with respect to the total daily traveled distance and the average work shift duration. Finally, a sensitivity analysis is presented and discussed for both models.

Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile.

The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (i.e., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.

Children at risk: A comparison of child pedestrian traffic collisions in Santiago, Chile, and Seoul, South Korea.

OBJECTIVE: We examine and compare pedestrian-vehicle collisions and injury outcomes involving school-age children between 5 and 18 years of age in the capital cities of Santiago, Chile, and Seoul, South Korea. METHODS: We conduct descriptive analysis of the child pedestrian-vehicle collision (P-VC) data (904 collisions for Santiago and 3,505 for Seoul) reported by the police between 2010 and 2011. We also statistically analyze factors associated with child P-VCs, by both incident severity and age group, using 3 regression models: negative binomial, probit, and spatial lag models. RESULTS: Descriptive statistics suggest that child pedestrians in Seoul have a higher risk of being involved in traffic crashes than their counterparts in Santiago. However, in Seoul a greater proportion of children are unharmed as a result of these incidents, whereas more child pedestrians are killed in Santiago. Younger children in Seoul suffer more injuries from P-VCs than in Santiago. The majority of P-VCs in both cities tend to occur in the afternoon and evening, at intersections in Santiago and at midblock locations in Seoul. Our model results suggest that the resident population of children is positively associated with P-VCs in both cities, and school concentrations apparently increase P-VC risk among older children in Santiago. Bus stops are associated with higher P-VCs in Seoul, and subway stations relate to higher P-VCs among older children in Santiago. Zone-level land use mix was negatively related to child P-VCs in Seoul but not in Santiago. Arterial roads are associated with fewer P-VCs, especially for younger children in both cities. A share of collector roads is associated with increased P-VCs in Seoul but fewer P-VCs in Santiago. Hilliness is related to fewer P-VCs in both cities. Differences in these model results for Santiago and Seoul warrant additional analysis, as do the differences in results across model type (negative binomial versus spatial lag models). CONCLUSIONS: To reduce child P-VCs, this study suggests the need to assess subway station and bus stop area conditions in Santiago and Seoul, respectively; areas with high density of schools in Santiago; areas with greater concentrations of children in both cities; and collector roads in Seoul.

A spatial and temporal analysis of child pedestrian crashes in Santiago, Chile.

This paper presents a spatial and temporal analysis of child pedestrian crash data in Santiago, Chile during the period 2000-2008. First, this study identified seven critical areas with high child pedestrian crash risk employing kernel density estimation, and subsequently, statistically significant clusters of the main attributes associated to these crashes in each critical area were determined in a geographic information systems environment. Moran's I index test identified a positive spatial autocorrelation on crash contributing factors, time of day, straight road sections and intersections, and roads without traffic signs within the critical areas during the studied period, whereas a random spatial pattern was identified for crashes related to the age attribute. No statistical significance in the spatial relationship was obtained in child pedestrian crashes with respect to gender, weekday, and month of the year. The results from this research aid in determining the areas in which enhanced school-age child pedestrian safety is required by developing and implementing effective enforcement, educational, and engineering preventive measures.

A novel methodology for determining low-cost fine particulate matter street sweeping routes.

This paper addresses the problem of low-cost PM10 (particulate matter with aerodynamic diameter < 10 microm) street sweeping route. In order to do so, only a subset of the streets of the urban area to be swept is selected for sweeping, based on their PM10 emission factor values. Subsequently, a low-cost route that visits each street in the set is computed. Unlike related problems of waste collection where streets must be visited once (Chinese or Rural Postman Problem, respectively), in this case, the sweeping vehicle route must visit each selected street exactly as many times as its number of street sides, since the vehicle can sweep only one street side at a time. Additionally, the route must comply with traffic flow and turn constraints. A novel transformation of the original arc routing problem into a node routing problem is proposed in this paper. This is accomplished by building a graph that represents the area to sweep in such a way that the problem can be solved by applying any known solution to the Traveling Salesman Problem (TSP). As a way of illustration, the proposed method was applied to the northeast area of the Municipality of Santiago (Chile). Results show that the proposed methodology achieved up to 37% savings in kilometers traveled by the sweeping vehicle when compared to the solution obtained by solving the TSP problem with Geographic Information Systems (GIS)--aware tools.

Urban solid waste collection system using mathematical modelling and tools of geographic information systems.

A poorly designed urban solid waste collection system has an enormous impact on labour, operational and transport costs, and on society in general due to road contamination and negative effects on public health and the environment. This study proposes a methodology for designing an urban solid waste collection system. This methodology uses combinatorial optimisation and integer programing, and GIS tools to minimise collection time, and operational and transport costs while enhancing the current solid waste collection system. This methodology establishes feasible collection routes, determines an adequate vehicle fleet size and presents a comparative cost and sensitivity analysis of the results. The implementation of this methodology in a study case of a zone in Santiago yields significant cost savings in the total collection system.