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Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Background: The control of Triatoma dimidiata, a major vector of Chagas disease, was believed to eliminate Trypanosoma cruzi transmission in Central America. This vector was known for its ability to repeatedly reinfest human dwellings even after initial insecticide spraying. Current vector control programs assume that community-based surveillance can maintain low levels of infestation over many years, despite a lack of evidence in the literature to corroborate this assumption. This study aims to evaluate long-term reinfestation risk in the Nicaraguan vector control program from 2010 to 2016. Methods: We collected data from a cohort of 395 houses in Pueblo Nuevo, Nicaragua. Primary data were collected through a field survey to assess post-intervention levels of T. dimidiata house infestation in 2016, two years after the large-scale insecticide spraying. We obtained secondary data from the records about past infestation levels and control activities between 2010 and 2015. Multilevel mixed-effects logistic regression analyses were used to identify factors associated with post-intervention house infestation. Results: The control program effectively reduced the infestation level from 2010 to 2014. Community-based surveillance was introduced in 2013; however, post-intervention infestation in 2016 had nearly reached pre-intervention levels in rural villages. Post-intervention house infestation was positively associated with poor wall construction, roofing tiles piled in the peri-domestic areas or the presence of dogs. Interestingly, the odds of post-intervention house infestation were one-fifth less when villagers sprayed their own houses regularly. Past infestation levels and the intensity of government-led insecticide spraying did not explain post-intervention house infestation. Conclusions: The vector control program failed to offer sustained reductions in T. dimidiata house infestation. This experience would suggest that community-based surveillance is an insufficient approach to suppressing T. dimidiata house infestation over many years. This study provides evidence to suggest that control policies for T. dimidiata should be reconsidered throughout Central America. [ABSTRACT FROM AUTHOR]

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the “stand age” variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical “mixed-severity” fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data. [ABSTRACT FROM AUTHOR]