scholarly journals Dengue Outbreaks in High-Income Area, Kaohsiung City, Taiwan, 2003–2009

2012 ◽  
Vol 18 (10) ◽  
pp. 1603-1611 ◽  
Author(s):  
Chia-Hsien Lin ◽  
Karin L. Schiøler ◽  
Martin R. Jepsen ◽  
Chi-Kung Ho ◽  
Shu-Hua Li ◽  
...  
Keyword(s):  
High Income ◽  
Dengue Outbreaks ◽  
Kaohsiung City

scholarly journals Relationship between the Incidence of Dengue Virus Transmission in Traditional Market and Climatic Conditions in Kaohsiung City

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chung-Hao Huang ◽  
Chun-Yu Lin ◽  
Chun-Yuh Yang ◽  
Ta-Chien Chan ◽  
Po-Huang Chiang ◽  
...  
Keyword(s):  
Relative Risk ◽  
Climatic Factors ◽  
Statistical Significance ◽  
Virus Transmission ◽  
Buffer Zone ◽  
Climatic Conditions ◽  
Traditional Market ◽  
Dengue Outbreaks ◽  
Southern Taiwan ◽  
Kaohsiung City

In 2014 and 2015, Southern Taiwan experienced two unprecedented outbreaks, with more than 10,000 laboratory-confirmed dengue cases in each outbreak. The present study was aimed to investigate the influence of meteorological and spatial factors on dengue outbreaks in Southern Taiwan and was conducted in Kaohsiung City, which is the most affected area in Taiwan. The distributed lag nonlinear model was used to investigate the role of climatic factors in the 2014 and 2015 dengue outbreaks. Spatial statistics in the Geographic Information System was applied to study the relationship between the dengue spreading pattern and locations of traditional markets (human motility) in the 2015 dengue outbreak. Meteorological analysis results suggested that the relative risk of dengue fever increased when the weekly average temperature was more than 15°C at lagged weeks 5 to 18. Elevated relative risk of dengue was observed when the weekly average rainfall was more than 150 mm at lagged weeks 12 to 20. The spatial analysis revealed that approximately 83% of dengue cases were located in the 1000 m buffer zone of traditional market, with statistical significance. These findings support the influence of climatic factors and human motility on dengue outbreaks. Furthermore, the study analysis may help authorities to identify hotspots and decide the timing for implementation of dengue control programs.

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

SATUAN TIMBULAN DAN KOMPOSISI SAMPAH DOMESTIK KABUPATEN TANAH DATAR

Jurnal Dampak ◽  
2014 ◽  
Vol 11 (1) ◽  
pp. 28 ◽  
Author(s):  
Yommi Dewilda ◽  
Yeggi Darnas
Keyword(s):  
Low Income ◽  
High Income ◽  
Income Data

Penelitian ini bertujuan untuk mendapatkan data timbulan dan komposisi sampah domestik di Kabupaten Tanah Datar serta dapat membandingkan perbedaan timbulan dan komposisi sampah yang dihasilkan berdasarkan tingkat pendapatan masyarakat (High income, Medium income dan Low income). Data timbulan dan komposisi sampah diperlukan dalam perencanaan dan pengembangan sistem pengelolaan sampah. Sampling timbulan dan jumlah sampling dilakukan berdasarkan SNI 19-3964-1994. Hasil penelitian timbulan sampah domestik dalam satuan berat 0,232 kg/o/h dan dalam satuan volume 3,646 l/o/h. Berdasarkan tingkat pendapatan dalam satuan berat High Income (HI) 0,308 kg/o/h, Medium Income (MI) 0,198 kg/o/h dan Low Income (LI) 0,190 kg/o/h dalam satuan volume HI 4,269 l/o/h, MI 3,835 l/o/h dan LI 2,835 l/o/h. Timbulan sampah yang dihasilkan penduduk dengan High Incame lebih besar dibandingkan dengan penduduk dengan pendapatan Medium Income dan Low Income. Komposisi sampah domestik untuk sampah basah 75,5%; sampah plastik 16,6%; sampah kertas 5,3%; sampah tekstil 0,8%; sampah kayu 0,3%; sampah kaca 0,7%; sampah logam ferrous 0,2%; sampah logam non ferrous 0,1%; dan sampah lain-lain 0,5%.Kata kunci: sampah domestik, komposisi sampah, timbulan Sampah

Vitamin A in Children Hospitalized for Measles in a High-Income Country

2020 ◽  
Author(s):  
Andrea Lo Vecchio ◽  
Maria Donata Cambriglia ◽  
Dario Bruzzese ◽  
Alfredo Guarino
Keyword(s):  
Vitamin A ◽  
High Income ◽  
Income Country ◽  
High Income Country

A Global Perspective on Occupational Health and Safety

2017 ◽  
Author(s):  
Jorma H. Rantanen
Keyword(s):  
Occupational Health ◽  
Occupational Injuries ◽  
Health And Safety ◽  
Psychosocial Problems ◽  
Occupational Health And Safety ◽  
High Income ◽  
Global Perspective ◽  
Occupational Hazards ◽  
Middle Income ◽  
Informal Workers

Occupational hazards as well as occupational injuries and diseases are frequent and serious problems not only in industrialized high-income countries, but also in low- and middle-income countries (LMICs). In high-income countries, the occurrence of occupational injuries and chemically-related disorders has decreased while psychosocial problems and issues for disabled, aging, and other vulnerable workers have increased. In the LMICs, “traditional” occupational hazards and related injuries and diseases are still a major concern. Globalization, while providing some benefits to workers, has presented many negative effects, such as transfer of hazardous technologies and substances to LMICs, widening of income gaps, and worsening of working conditions and worker income, especially for agricultural workers, those with little education, and informal workers. The chapter provides a global overview of work and workers as well occupational health and safety hazards and related challenges.

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