Predicting dengue outbreaks in Brazil with manifold learning on climate data

2021 ◽  
pp. 116324
Author(s):  
Caio Souza ◽  
Pedro Maia ◽  
Lucas M. Stolerman ◽  
Vitor Rolla ◽  
Luiz Velho
Keyword(s):  
Manifold Learning ◽  
Climate Data ◽  
Dengue Outbreaks

scholarly journals Impacts of Climate Change on Dengue Haemorrhagic Fever Cases in Banjarbaru Municipal, South Kalimantan During the Year 2005-2010

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Tien Zubaidah
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Secondary Data ◽  
Hemorrhagic Fever ◽  
Health Department ◽  
Climate Data ◽  
Dengue Disease ◽  
Weather Patterns ◽  
Dengue Outbreaks ◽  
Almost All

<p>Environment is one of instrumental factor in the emerging and the spreading of dengue disease. The Climate change may causes affect to infectious disease pattern and the risk of transmission increasement. Disease of dengue hemorrhagic fever (DHF) has become endemic in the major cities in Indonesia. It has been suspected that dengue outbreaks that occur each year in almost all of Indonesia is closely related to weather patterns. The purpose of this study was to determine the influence of climate change (rainfall, humidity and air temperature) with dengue cases in the Banjarbaru municipal during the year 2005-2010. The design of the study is a over times studies of ecology. The research was conducted in April-May 2010 and located in the Banjarbaru municipal, South Kalimantan by using secondary data. Data on the number of dengue cases was derived from the Banjarbaru Health Office reports. Climate data used are rainfall data, temperature and humidity obtained from the Meteorology and Geophysics Board (BMKG) Station of Banjarbaru and Syamsudin Noor Station of Banjarmasin. The results showed that rainfall, humidity, air temperature and free number larva had influence toward insidence of DHF (27%). The conclusion of this study is that the increased rainfall and humidity affected the increased in dengue cases. Therefore, it requires a good cooperation between the health department and BMKG as the party in charge for climates data. </p>

Scientists struggle to access Africa's historical climate data

Nature ◽  
2019 ◽  
Vol 574 (7780) ◽  
pp. 605-606 ◽  
Author(s):  
Linda Nordling
Keyword(s):  
Climate Data ◽  
Historical Climate

Use of soil and climate data to assess the risk of agricultural drought for policy support in Europe

Agronomie ◽  
2001 ◽  
Vol 21 (1) ◽  
pp. 45-56 ◽  
Author(s):  
Pandi Zdruli ◽  
Robert J.A. Jones ◽  
Luca Montanarella
Keyword(s):  
Policy Support ◽  
Agricultural Drought ◽  
Climate Data

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.

EL NINO RELATED CLIMATE AND DENGUE FEVER CASES IN JEDDAH, SAUDI ARABIA

2019 ◽  
Vol 25 (1) ◽  
Author(s):  
MASROOR ALI KHAN ◽  
KHALID AL GHAMDI ◽  
JAZEM A. MEHYOUB ◽  
RAKHSHAN KHAN
Keyword(s):  
Relative Humidity ◽  
Dengue Fever ◽  
El Niño ◽  
Significant Relationship ◽  
El Nino ◽  
Climate Data ◽  
Light Traps ◽  
Mosquito Abundance ◽  
Dengue Transmission ◽  
The Relationship

The focus of this study is to find the relationship between El Nino and dengue fever cases in the study area.Mosquito density was recorded with the help of light traps and through aspirators collection. Climate data were obtained from National Meteorology and Environment centre. (Year wise El Nino and La Nina data are according to NOAA & Golden Gate Weather Services). Statistical methods were used to establish the correlation coefficient between different factors. A high significant relationship was observed between Relative Humidity and Dengue fever cases, but Aedes abundance had no significant relationship with either Relative humidity and Temperature. Our conclusion is that the El Nino does not affect the dengue transmission and Aedes mosquito abundance in this region, which is supported by earlier works.

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