Symptoms associated with adverse dengue fever prognoses at the time of reporting in the 2015 dengue outbreak in Taiwan

Yeh, Chun Yin; Chen, Po‐Lin; Chuang, Kun Ta; Shu, Yu-Chen; Chien, Yu Wen; Perng, Guey Chuen; Ko, Wen Chien; Ko, Nai Ying

doi:10.1371/journal.pntd.0006091

Cited by 30 publications

(32 citation statements)

References 38 publications

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“…Many studies in Taiwan show that the elderly had a higher prevalence rate than those in younger dengue patients, which was in contrast to other Southeast Asian countries [ 52 , 53 , 54 ]. The length of time that people spend in green spaces may be an important factor that affects incidence of DF.…”

Section: Discussionmentioning

confidence: 88%

Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

Huang

Tam

Chern

et al. 2018

IJERPH

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With more than 58,000 cases reported by the country’s Centers for Disease Control, the dengue outbreaks from 2014 to 2015 seriously impacted the southern part of Taiwan. This study aims to assess the spatial autocorrelation of the dengue fever (DF) outbreak in southern Taiwan in 2014 and 2015, and to further understand the effects of green space (such as forests, farms, grass, and parks) allocation on DF. In this study, two different greenness indexes were used. The first green metric, the normalized difference vegetation index (NDVI), was provided by the long-term NASA MODIS satellite NDVI database, which quantifies and represents the overall vegetation greenness. The latest 2013 land use survey GIS database completed by the National Land Surveying and Mapping Center was obtained to access another green metric, green land use in Taiwan. We first used Spearman’s rho to find out the relationship between DF and green space, and then three spatial autocorrelation methods, including Global Moran’s I, high/low clustering, and Hot Spot were employed to assess the spatial autocorrelation of DF outbreak. In considering the impact of social and environmental factors in DF, we used generalized linear mixed models (GLMM) to further clarify the relationship between different types of green land use and dengue cases. Results of spatial autocorrelation analysis showed a high aggregation of dengue epidemic in southern Taiwan, and the metropolitan areas were the main hotspots. Results of correlation analysis and GLMM showed a positive correlation between parks and dengue fever, and the other five green space metrics and land types revealed a negative association with DF. Our findings may be an important asset for improving surveillance and control interventions for dengue.

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Section: Discussionmentioning

confidence: 88%

Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

Huang

Tam

Chern

et al. 2018

IJERPH

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“…Infeksi dengue memberikan beban eko o i terutama negara endemis n m di dengan sumber daya yang minim. [1][2][3] Dem am Berdarah Deng u e ( DB D) merupakan bentuk manifestasi infeksi dengue. DBD diperkirakan masih akan cenderung meningkat dan penyebarannya bertambah luas.…”

Section: Abstract / a B S T R A Kunclassified

Diagnosis Klinis Demam Berdarah Dengue di Tiga Kabupaten/Kota Sulawesi Tengah Tahun 2015-2016

Anastasia¹

2018

vektorp

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Abstract Dengue is a major public health problem in Indonesia including Central Sulawesi. In the past, Palu was the only city reported high dengue cases. Then, dengue outbreaks were also reported from several districts in Central Sulawesi. The Provincial Health Office suspected over-reporting of dengue infection. This reviewed article was aimed to identify whether the clinical diagnosis was the cause of over-reporting of dengue infection. Data of dengue cases from three districts/city in 2015-2016 were analyzed descriptively. The results showed that there was an over-reporting of dengue infection by 51.7%. The over-reporting occurred because the diagnosis of cases was not strictly followed the guideline for dengue infection classification by the Ministry of Health. Therefore, it is necessary for the health practitioners to understand fully the guideline of dengue infection classification used in Indonesia. Abstrak Dengue merupakan salah satu masalah kesehatan utama di Indonesia, termasuk di Sulawesi Tengah. Kota Palu merupakan daerah endemis Demam Berdarah Dengue (DBD) utama di Sulawesi Tengah. Namun, dalam beberapa tahun terakhir kejadian luar biasa DBD dilaporkan di beberapa kabupaten. Dinas Kesehatan Provinsi Sulawesi Tengah menduga adanya kemungkinan over-reporting kasus DBD yang menyebabkan meningkatnya laporan kasus DBD setiap tahunnya. Review ini bertujuan untuk mengidenfikasi kemungkinan adanya over-reporting kasus DBD di tiga kabupaten/kota di Sulwesi Tengah. Data kasus DBD tahun 2015-2016 dianalisis secara deskriptif untuk melihat adanya over-reporting. Hasil menujukkan bahwa terdapat kelebihan 51,7% kasus DBD yang disebabkan karena diagnosis tidak mengikuti kriteria diagnosis klinis sesuai panduan klasifikasi infeksi dengue yang dikeluarkan oleh Kementerian Kesehatan. Oleh karena itu sangat penting bagi klinisi untuk memahami kriteria diagnosis infeksi dengue yang digunakan di Indonesia.

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“…The risk factors associated with increased severity and fatal outcomes have been addressed in previous studies [ 15 , 16 , 17 , 18 , 19 ]. A study from Taiwan has shown that old age, respiratory distress, altered consciousness, and thrombocytopenia were significantly associated with the risk of mortality [ 15 ]. A study from Brazil reported that age >55 years, gastrointestinal bleeding, hematuria, and thrombocytopenia were independently associated with mortality [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Prognostic Factors in Adult Patients with Dengue: Developing Risk Scoring Models and Emphasizing Factors Associated with Death ≤7 Days after Illness Onset and ≤3 Days after Presentation

Lee

Huang

et al. 2018

JCM

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Dengue is a mosquito-borne viral disease that is a threat to global health. However, information relating to mortality ≤7 days after dengue onset and ≤3 days after presentation is limited. We retrospectively analyzed 1086 adults with dengue during a 12-year period. Three scoring models were established: model-1 (death ≤3 days after presentation), model-2 (death ≤7 days after illness onset), and model-3 (overall fatality). In total, 39 patients with fatal dengue were identified, of which 17 and 14 patients died ≤7 days after illness onset and ≤3 days after presentation, respectively. In model-1 (range: 0‒4 points), gastrointestinal bleeding ≤72 h after presentation, thrombocytopenia (<50 × 109 cells/L) at presentation, and acute kidney injury after hospitalization, using a cutoff level of 2 points, exhibited good discrimination (area under the receiver curve (AUC): 0.975) between survivors and non-survivors. In model-2, the significant predictors were gastrointestinal bleeding ≤72 h after presentation, and hemoconcentration and leukocytosis after hospitalization. Model-2 (range: 0–4 points) showed an AUC of 0.974, with a cutoff value of 2 points. The independent factors in model-2 were the predictors of overall mortality (model-3), which include thrombocytopenia (<50 × 109 cells/L) at presentation. Using a cutoff value of 2 points, model-3 (range: 0–7 points) revealed an excellent discrimination between survivors and non-survivors (AUC: 0.963).

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Symptoms associated with adverse dengue fever prognoses at the time of reporting in the 2015 dengue outbreak in Taiwan

Cited by 30 publications

References 38 publications

Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

Diagnosis Klinis Demam Berdarah Dengue di Tiga Kabupaten/Kota Sulawesi Tengah Tahun 2015-2016

Prognostic Factors in Adult Patients with Dengue: Developing Risk Scoring Models and Emphasizing Factors Associated with Death ≤7 Days after Illness Onset and ≤3 Days after Presentation

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