Background: In the United States, cases of human blastomycosis are largely described in defined geographic areas, with Mississippi reporting the highest prevalence of disease in the southeast region. The infection is uncommonly recognized in mountainous areas, and our previous report of blastomycosis in the southern Appalachian mountains of northeast Tennessee appeared to be an exception to the usual disease distribution. Methods: Our current retrospective study was undertaken to determine whether blastomycosis has persisted as an endemic fungal infection in our northeast Tennessee geographic area and whether epidemiologic features have changed over a 25-year time period. Results: Results show that clinical aspects of the disease have remained fairly constant with few exceptions; mass-type pulmonary lesions have become more common, and itraconazole has emerged as the therapy of choice. Most notably, however, are the observations that blastomycosis persists as a major endemic fungal infection in our mountain region, more than half of all cases occurring during the period from 1996 to 2005 were found in a core area centered on two counties, Washington and Unicoi; three of five counties surrounding the core counties experienced rate increases compared to our previous study. Conclusions: These findings suggest a further expansion of this endemic fungal disease beyond the core region.

En épidémiologie, une connaissance précise des populations à risque constitue un pré requis aucalcul d'indicateurs de l’état de santé d’une communauté (taux d'incidence). Néanmoins, les effectifsde population peuvent être indisponibles, ou peu fiables, ou insuffisamment détaillés pour un usageépidémiologique.L'objectif principal de ce travail est d'obtenir des taux d'incidence en l'absence de donnéesdémographiques, à une échelle spatiale infra-communale. Les objectifs secondaires sont d'estimerles populations humaines par l'intermédiaire de données satellitaires à très haute résolution spatiale(THRS), d'évaluer l'apport de ces données THRS par rapport aux données à haute résolution spatiale(Landsat) dans un même cadre urbain (Besançon), et de mettre au point une méthodologie simple etrobuste, pour garantir son exportabilité à d'autres zones.Nous proposons une approche en trois étapes, fondée sur la corrélation existant entre la densité depopulation et la morphologie urbaine. La première étape consiste à extraire des bâtiments à partirdes données télédétection THRS. Ces bâtiments sont utilisés dans la deuxième étape pour modéliserla population. A leur tour, ces populations servent de dénominateur, lors de la dernière étape, pourcalculer des taux d’incidence (cancers). Des données de référence sont utilisées à chaque étape pourévaluer les performances de notre méthodologie.Les résultats obtenus soulignent le potentiel de la télédétection pour mesurer l'état de santé d'unecommunauté (sous la forme de taux bruts d’incidence) à une échelle géographique fine. Ces tauxd'incidence estimés peuvent alors constituer des éléments de décision pour mieux adapter l'offre desoins aux besoin de santé, même en l'absence de données démographiques / In epidemiology, a precise knowledge of populations at risk is a prerequisite for calculating state ofhealth indicators of a community (incidence rates). The population data, however, may beunavailable, unreliable, or insufficiently detailed for epidemiological use.The main objective of this research is to estimate incidence rates, in cases of absence of demographicdata, at an infra-communal scale. The secondary objectives are to estimate the human populationthrough satellite data at very high spatial resolution (VHSR), to assess the contribution of this data(VHSR) compared with high spatial resolution data (Landsat) in a same urban framework (Besançon),and to develop a simple and robust methodology to ensure its exportability to other areas.We proposed a three-step approach based on the correlation between population density and urbanmorphology. The first step is to extract buildings from VHSR imagery data. These buildings are thenused in the second step to model the population data. Finally, this population data is used as thedenominator to calculate incidence rates (cancers). Reference data are used at each step to assessthe performance of our methodology.The results obtained highlight the potential of remote sensing to measure the state of health of acommunity (in the form of crude incidence rates) at a fine geographical scale. These estimatedincidence rates can be utilized as elements of decision to adapt better customized healthcare withrespect to the health needs of a given community, even in the absence of demographic data

近年來，隨著我國國民的壽命持續增長，人口老化愈加明顯。預期臺灣在2021年將進入人口零成長，2025年65歲以上人口比例也將超過20%（來源：國家發展委員會2014年人口推估）。人口老化帶來許多問題，如老年生活、醫療、以及長期照顧等需求，其中照顧需求與年齡正相關，預期需求將隨壽命延長而增加，需要及早規劃及因應，這也是今年通過長期照護法的原因。由於各國國情不同，對於長期照護的定義、補助及需求也不盡相同，有必要發展適用於臺灣特性的，推估長期照顧需求的所需之資源。重大傷病中的許多疾病與失能、甚至長期照護有關，由於全民健保實施至今已逾20年，重大傷病的認定標準及程序相對客觀、中立，受到民眾、學術、政府各界肯定。 有鑑於此，本文以全民健保資料庫的重大傷病資料庫為基礎，挑選八類引發長照的重大傷病，作為規劃長期照護保險的參考。本文以這些傷病的發生率、罹病後死亡率、罹病後存活率等，結合國發會所人口推估的結果，利用年輪組成法(Cohort Component Method)推估長期照顧的未來需求。研究發現：未來需求人口從2013年約10萬人，迅速增加至2060年的21萬人，增加速度相當快。而參考「長期照顧保險法」草案的給付內容，若聘請一名外籍看護每月20,000元計算，每人分擔將從2012年的$530元/月升至2060年的2,728元/月；若不調整保費且以隨收隨付計算，每人每月繳交400元長照保費，長照給付將從2012年每月13,353元降至2060年每月3,556元，由此可知壽命延長、人口老化將造成長照保險的財務問題。另外，本文考量的八項重大傷病較為保守，沒有加入老化、遺傳等因素的長照需求，預期將不足以因應實際需求，未來有必要引入商業保險來彌補社會保險的不足。 / In recent years, with the sustainable growth of the life expectancy in our country, population aging becomes more apparent. Taiwan’s population of ages 65 and over will exceed 20% within 10 years, before 2025. (Source: National Development Council - Population Projection on 2014). The population aging an prolonging life incurs a big demand for caring the elderly, such as the economic need after the retirement, medical cost, and long-term care. Among these needs, the demand of long term care was under-estimated and is only recognized recently. Thus, this study focuses on predicting the need of long-term care in Taiwan. Specifically, the definition and standard (as well as types and amounts of subsidy) for juding whether one needs long-terma care is not yet determined, although Taiwan’s government passed the long-term care law (Long-Term Care Insurance Law) earlier this year. We should adapt the notion of catastrophic illness (CI) and use certain CI categories, which are related to long-term care, to design the long-term care insurance. Catastrophic illness (CI) is one of the key features of Taiwan’s National Health Insurance (NHI), and the definition and process of evaluating if one is with the CI is quite complete. We choose eight categories of CI and use the NHI database to obtain their incidence rates, mortality rates, and survival probability. Together with the population projection from National Development Council in 2014 and the cohort component method to predict the long-term care demand in Taiwan. The syudy result shows that the population needing long-term care will rise from about 100 thousands in 2013 to about 210 thousands in 2060. Moreover, if the long-term care insurance is funded via pay-as-you-go, the individual premium required will rise 5 times from 2012 to 2060. This indicates that the long-term care might be too expensive and the commercial insurance can play an important role as a supplement.