Dataset Information

Spatial and temporal pattern of wildfires in California from 2000 to 2019.

ABSTRACT: The environmental pollution, property losses and casualties caused by wildfires in California are getting worse by the year. To minimize the interference of wildfires on economic and social development, and formulate targeted mitigation strategies, it is imperative to understand the scale and extent of previous wildfire occurrences. In this study, we first investigated the temporal distributions of past wildfires in California divided by size and causes and analyzed the changes observed in the past two decades against the last century. The trend of wildfires in different time scales (yearly and monthly), as well as the distribution of wildfires across different spatial scales (administrative units, climate divisions in California from 2000 to 2019) were also studied. Furthermore, to extract the significant variables on the risk of wildfire occurrence, multivariate analyses of environmental and human-related variables with wildfire densities were carried out. The results show that the wildfire density distribution of the burned area in California conforms to the characteristics of the Pareto distribution. Over the past two decades, the frequency of small (< 500 acres), human-caused wildfires has increased most rapidly, and they are widely distributed in central and western California. The wildfire season has lengthened and the peak months have been advanced from August to July. In terms of the variables related to the risk of wildfire occurrence, the temperature, vapor pressure deficit, grass cover, and the distance to roads are crucial. This study reveals the relationship between environmental and social background conditions and the spatial-temporal distribution of wildfires, which can provide a reference for wildfire management, the formulation of future targeted wildfire emergency plans, and the planning of future land use in California.

SUBMITTER: Li S

PROVIDER: S-EPMC8062671 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundResearch suggests that geographic location may affect ovarian cancer (OC) outcomes. Insurance status often remains an important predictor of outcomes. The Affordable Care Act was enacted in 2010 to expand access to affordable health insurance. Our objective was to examine spatiotemporal trends in OC treatment nonadherence and disease-specific mortality in California (USA) among women diagnosed with OC.MethodsNewly diagnosed epithelial OC cases between 1996 and 2017 were identified from the California Cancer Registry. Spatiotemporal trends in adherence to treatment guidelines were examined using generalized additive models and OC-specific mortality using Cox proportional hazards additive models. Prediction grids covering California were used to display the odds ratios (ORs) and hazard ratios of location using the median value for the study area as the referent value. Seven overlapping 5-year periods and 2 larger ones (pre- and post-2013) were assessed. Analyses were stratified according to stage (early vs advanced) and used P = .05 to determine statistical significance.ResultsStatistically significant spatial patterns in treatment nonadherence were observed for every time period examined (P < .001). Odds of treatment nonadherence associated with geographic location were highest among women with early-stage OC in southern Los Angeles County during 2014-2017 (OR max = 3.89, confidence interval = 1.04 to 7.61). For women with advanced-stage OC, residing in northern California was generally associated with lower odds ratios, whereas southern California was associated with higher odds ratios, with higher odds in the latter time period (OR range = 0.53-1.84 in 1996-2012 vs 0.49-2.37 in 2013-2017). Geographic location was not a statistically significant predictor of mortality.ConclusionsResidential location was statistically significantly associated with treatment received in California, with spatial patterns varying over time but not OC-specific mortality. Changes in insurance status over time were accompanied by shifts in population demographics and increased travel distances to receive care.

Project description:BackgroundCutaneous leishmaniasis (CL) is a vector-borne disease classified by the World Health Organization as one of the most neglected tropical diseases. Brazil has the highest incidence of CL in America and is one of the ten countries in the world with the highest number of cases. Understanding the spatiotemporal dynamics of CL is essential to provide guidelines for public health policies in Brazil. In the present study we used a spatial and temporal statistical approach to evaluate the dynamics of CL in Brazil.MethodsWe used data of cutaneous leishmaniasis cases provided by the Ministry of Health of Brazil from 2001 to 2017. We calculated incidence rates and used the Mann-Kendall trend test to evaluate the temporal trend of CL in each municipality. In addition, we used Kuldorff scan method to identify spatiotemporal clusters and emerging hotspots test to evaluate hotspot areas and their temporal trends.ResultsWe found a general decrease in the number of CL cases in Brazil (from 15.3 to 8.4 cases per 100 000 habitants), although 3.2% of municipalities still have an increasing tendency of CL incidence and 72.5% showed no tendency at all. The scan analysis identified a primary cluster in northern and central regions and 21 secondary clusters located mainly in south and southeast regions. The emerging hotspots analysis detected a high spatial and temporal variability of hotspots inside the main cluster area, diminishing hotspots in eastern Amazon and permanent, emerging, and new hotspots in the states of Amapá and parts of Pará, Roraima, Acre and Mato Grosso. The central coast the state of Bahia is one of the most critical areas due to the detection of a cluster of the highest rank in a secondary cluster, and because it is the only area identified as an intensifying hotspot.ConclusionsUsing a combination of statistical methods we were able to detect areas of higher incidence of CL and understand how it changed over time. We suggest that these areas, especially those identified as permanent, new, emerging and intensifying hotspots, should be targeted for future research, surveillance, and implementation of vector control measures.

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Spatial and temporal pattern of wildfires in California from 2000 to 2019.

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