Search

In the era of big data, ubiquitous Flickr geotagged photos have opened a considerable opportunity for discovering valuable geographic information. Point of interest (POI) and region of interest (ROI) are significant reference data that are widely used in geospatial applications. This study aims to develop an efficient method for POI/ROI discovery from Flickr. Attractive footprints in photos with a local maximum that is beneficial for distinguishing clusters are first exploited. Pattern discovery is combined with a novel algorithm, the spatial overlap (SO) algorithm, and the naming and merging method is conducted for attractive footprint clustering. POI and ROI, which are derived from the peak value and range of clusters, indicate the most popular location and range for appreciating attractions. The discovered ROIs have a particular spatial overlap available which means the satisfied region of ROIs can be shared for appreciating attractions. The developed method is demonstrated in two study areas in Taiwan: Tainan and Taipei, which are the oldest and densest cities, respectively. Results show that the discovered POI/ROIs nearly match the official data in Tainan, whereas more commercial POI/ROIs are discovered in Taipei by the algorithm than official data. Meanwhile, our method can address the clustering issue in a dense area. [ABSTRACT FROM AUTHOR]

While studies have examined the association between weather variables and acute diarrhea in a city, region, or country, less evidence is available on the temperature effect across countries. The objective of this study is to elucidate the nonlinear and lagged association between ambient temperature and acute diarrhea in Hong Kong, Taiwan, and Japan. We collected weekly surveillance statistics on acute diarrhea with the corresponding meteorological data from 12 regions of Hong Kong, Taiwan, and Japan during 2012–2016. Firstly, we fitted the region-specific counts of acute diarrhea in a distributed lag nonlinear model (DLNM) which accounts for the non-linearity and lagged effect of temperature. Secondly, we applied meta-analysis to pool estimates across 12 regions. A total of 5,992,082 acute diarrhea cases were identified. We found that (1) the pooled overall cumulative relationship between the relative risk (RR) of acute diarrhea and temperature was the greatest (RR = 1.216; 95% CI: 1.083, 1.364) at 11 °C; (2) a pooled predictor-specific summary association at lower temperatures (12 °C or 25th percentile) began immediately and vanished after four weeks. Predictions and error analysis for new onsets of acute diarrhea in 2017 were evaluated. An early warning system based on the information of temperature variation was suggested for acute diarrhea control management. [ABSTRACT FROM AUTHOR]

There are periodical norovirus-associated acute gastroenteritis outbreaks around the world. This study aimed to analyze the molecular and epidemiological features of norovirus infections in China during 2006-2016. We extracted epidemiological data from 132 norovirus outbreaks and the norovirus genotyping for 1291 sequences in China over the past ten years. A total of 132 norovirus outbreaks (8133 cases) were reported in China, where the east and south regions were most affected [47.7% (63/132)]. The highest number of outbreaks occurred in 2015. A seasonal pattern has been observed, with a peak from November to the following March. Most of the outbreaks occurred in middle and primary schools, accounting for 28.8% (38/132), and 28.0% (37/132) of outbreaks, respectively. The dominant age group was 10 to 19 years old, responsible for 75.7% (933/1232) of cases. Generally, the dominant genotypes was GII, for 81.9% (1058/1291) of sequences. G II.4 was the predominant genotype in China from 2004 to 2014. However, the GII.17 became more prevalent starting in 2014. Norovirus-associated acute gastroenteritis increased sharply in recent years caused by the emergence of GII.17, but epidemiological features have not changed during 2006-2016. Vigilant surveillance should be strengthened to promptly detect any variation., Competing Interests: The authors declare no conflict of interest.

Fine particulate matter (PM 2.5 ) is an air pollutant that is receiving intense regulatory attention in Taiwan. In previous studies, the effect of air pollution on bladder cancer has been explored. This study was conducted to elucidate the effect of atmospheric PM 2.5 and other local risk factors on bladder cancer mortality based on available 13-year mortality data. Geographically weighted regression (GWR) was applied to estimate and interpret the spatial variability of the relationships between bladder cancer mortality and ambient PM 2.5 concentrations, and other variables were covariates used to adjust for the effect of PM 2.5 . After applying a GWR model, the concentration of ambient PM 2.5 showed a positive correlation with bladder cancer mortality in males in northern Taiwan and females in most of the townships in Taiwan. This is the first time PM 2.5 has been identified as a risk factor for bladder cancer based on the statistical evidence provided by GWR analysis.

This study aimed to assess the mortality risks for human infection with high (HPAI) and low (LPAI) pathogenicity avian influenza viruses. The HPAI case fatality rate (CFR) was far higher than the LPAI CFR [66.0% (293/444) vs. 68.75% (11/16) vs. 40.4% (265/656) vs. 0.0% (0/18) in the cases with H5N1, H5N6, H7N9, and H9N2 viruses, respectively; p < 0.001]. Similarly, the CFR of the index cases was greater than the secondary cases with H5N1 [100% (43/43) vs. 43.3% (42/97), p < 0.001]. Old age [22.5 vs. 17 years for H5N1, p = 0.018; 61 vs. 49 years for H7H9, p < 0.001], concurrent diseases [18.8% (15/80) vs. 8.33% (9/108) for H5N1, p = 0.046; 58.6% (156/266) vs. 34.8% (135/388) for H7H9, p < 0.001], delayed confirmation [13 vs. 6 days for H5N1, p < 0.001; 10 vs. 8 days for H7N9, p = 0.011] in the fatalities and survivors, were risk factors for deaths. With regard to the H5N1 clusters, exposure to poultry [67.4% (29/43) vs. 45.2% (19/42), p = 0.039] was the higher risk for the primary than the secondary deaths. In conclusion, old age, comorbidities, delayed confirmation, along with poultry exposure are the major risks contributing to fatal outcomes in human HPAI and LPAI infections.

Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model's demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations., Competing Interests: The authors declare no conflict of interest.

Global high-tech manufacturers are mainly located in newly industrialized countries, raising concerns about adverse health consequences from industrial pollution for people living nearby. We investigated the ecological association between respiratory mortality and the development of Taiwan's high-tech manufacturing, taking into account industrialization and socioeconomic development, for 19 cities and counties-6 in the science park group and 13 in the control group-from 1982 to 2007. We applied a linear mixed-effects model to analyze how science park development over time is associated with age-adjusted and sex-specific mortality rates for asthma and chronic obstructive pulmonary disease (COPD). Asthma and female COPD mortality rates decreased in both groups, but they decreased 9%-16% slower in the science park group. Male COPD mortality rates increased in both groups, but the rate increased 10% faster in the science park group. Science park development over time was a significant predictor of death from asthma (p ≤ 0.0001) and COPD (p = 0.0212). The long-term development of clustered high-tech manufacturing may negatively affect nearby populations, constraining health advantages that were anticipated, given overall progress in living standards, knowledge, and health services. National governments should incorporate the long-term health effects on local populations into environmental impact assessments.

Chronic obstructive pulmonary disease (COPD) mortality has been steadily increasing in Taiwan since 2009. In order to understand where the hotspot areas are and what the local risk factors are, we integrated an ecological and a case-control study. We used a two-stage approach to identify hotspots and explore the possible risk factors for developing COPD. The first stage used the annual township COPD mortality from 2000 to 2012 and applied the retrospective space-time scan statistic to calculate the local relative risks in each township. In the second stage, we conducted a case-control study, recruiting 200 patients from one local hospital within the one identified hotspot area located in southern Taiwan. Logistic regression was applied for analyzing the personal risk factors of COPD. The univariate analyses showed that higher percentages of aborigines, patients with tuberculosis (TB) history, and those with smoking history had COPD (p < 0.05). After controlling for demographic variables, aboriginal status (adjusted odds ratios (AORs): 3.01, 95% CI: 1.52-5.93) and smoking history (AORs: 2.64, 95% CI: 1.46-4.76) were still the two significant risk factors. This two-stage approach might be beneficial to examine and cross-validate the findings from an aggregate to an individual scale, and can be easily extended to other chronic diseases.

According to the official health statistics, Taiwan has the highest prevalence of end stage renal disease (ESRD) in the world. Each year, around 60,000 ESRD patients in Taiwan consume 6% of the national insurance budget for dialysis treatment. The prevalence of chronic kidney disease (CKD) has been climbing during 2008-2012. However, the spatial disparities and clustering of CKD at the public health level have rarely been discussed. The aims of this study are to explore the possible population level risk factors and identify any clusters of CKD, using the national health insurance database. The results show that the ESRD prevalence in females is higher than that in males. ESRD medical expenditure constitutes 87% of total CKD medical expenditure. Pre-CKD and pre-ESRD disease management might slow the progression from CKD to ESRD. After applying ordinary least-squares regression, the percentages of high education status and the elderly in the townships are positively correlated with CKD prevalence. Geographically weighted regression and Local Moran's I are used for identifying the clusters in southern Taiwan. The findings can be important evidence for earlier and targeted community interventions and reducing the health disparities of CKD.

A geostatistical method was developed to examine the correlation, or lack of it, between the levels of cadmium (Cd) detected in farm soils and those detected in the human specimens collected from residents around the contaminated areas in Changhua County where cadmium contamination of staple rice has been documented. We used the Taiwan EPA environment data in 2002 and human data which were generated by the National Health Research Institutes during 2003-2005. Kriging interpolation methods were used to determine soil Cd concentrations. A Zonal statistical function was performed to assess the individual exposure. Soil Cd levels and tissue Cd levels in residents were analyzed for contamination hotspots and other areas to determine correlation between the two variables. Three Cd contamination hotspots were identified, in which no correlation was found between soil Cd levels and tissue Cd levels in residents. Our results demonstrate how GIS spatial modeling technique can be used to estimate distribution of pollutants in an area using a limited number of data points. Results indicated no association between the soil contamination and the exposure of residents to Cd, suggesting that both the soils and the residents are receptors of Cd as a pollutant from as yet unidentified sources.