Climatic factors
influencing dengue cases in Dhaka city: a model for dengue prediction

Md. Nazmul Karim, Saif Ullah Munshi*, Nazneen Anwar & Md. Shah Alam**

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WHO-Bangladesh, *Department of Virology, Bangabandhu Sheikh Mujib Medical
University & **The Bangladesh Meteorological Department, Dhaka, Bangladesh

Received November 2, 2010

 Linear regression is used to normalize the
data. Average monthly humidity, rainfall, minimum and maximum temperature were
used as independent variables and number of dengue cases reported monthly was
used as dependent variable. Accuracy of the model for predicting outbreak was
assessed through receiver operative characteristics (ROC) curve. The prediction
model had some limitations in predicting the monthly number of dengue cases, it
could forecast possible outbreak two months in advance with considerable



Department of Computer Science, Jamia Millia Islamia

New Delhi, India

 [email protected],
[email protected] and [email protected]

 Datasets that are available for dengue describe information about the
patients suffering with dengue disease and without dengue disease along with
their symptoms like: Fever Temperature, WBC, Platelets, Severe Headache,
Vomiting, Metallic Taste, Joint Pain, Appetite, Diarrhea, Hematocrit,
Hemoglobin, and how many days suffer in different city. Weka tool is used for
classification of data.

Mobile Application
for Dengue Fever Monitoring and Tracking via GPS: Case Study for Fiji

Emmenual Reddy1,3, Sarnil Kumar1,3, Nicholas Rollings2,3, and Rohitash


1 School of Computing, Information and Mathematical Statistics,

The University of the South Paci?c, Laucala Campus, Suva, Fiji.

2 Geography, Earth Science and Environment,

The University of the South Paci?c, Laucala Campus, Suva, Fiji.

3 Arti?cial Intelligence and Cybernetics Research Group, Software

Nausori, Fiji


Based on the
symptoms details given by the user the amount of disease spread in a particular
area is found. It helps authorities to helps the affected people.


Need for GIS based dengue surveillance with Google
internet real time

mapping for epidemic control in India

Palaniyandi M

Remote sensing and GIS laboratory, Vector Control
Research Centre, (ICMR),

Indira Nagar, Pondicherry-605006, India

[email protected]


Volume 5, No 1, 2014

Submitted on June 2014 published on August 2014 132



The information relevant to the geographical site specification of dengue vectors
breeding habitats, vector abundance, vector density, etc., could be recorded
using global positioning systems (GPS). This information could be mapped and
overlay on the the climatic layers of climate variables (Temperature, relative
humidity, saturation deficiency and Rainfall)under the geographical information
systems (GIS) software platform for spatial analysis(cluster analysis, nearest
neighbourhood analysis, fussy analysis, probability of maximum and minimum
likelihood analysis etc.,) for prediction of disease epidemics 7 days in


Dengue Fever
Prediction: A Data Mining Problem

Kamran Shaukat1*, Nayyer Masood2, Sundas Mehreen1 and Ulya Azmeen

1 IT Department, University of the Punjab, Jhelum Campus, Pakistan

2 Mohammad Ali Jinnah University, Islamabad Campus. Pakistan


Dengue fever is used in classification techniques to evaluate and compare
their performance. The dataset was collected from District Headquarter Hospital
(DHQ) Jhelum. For properly categorizing our dataset, different classification
techniques are used. These techniques are Naïve Bayesian, REP Tree, Random
tree, J48 and SMO. WEKA was used as Data mining tool for classification of

Nation-Wide, Web-Based,
Geographic Information System for the Integrated

Surveillance and Control of
Dengue Fever in Mexico

Juan Eugenio Hernández-Ávila,

Mario-Henry Rodríguez,

René Santos-Luna,

Veronica Sánchez-Castañeda,

Susana Román-Pérez

Published: August 6, 2013


Dengue-GIS provides the geographical detail
needed to plan, asses and evaluate the impact of control activities. The system
is beginning to be adopted as a knowledge base by vector control programs. It
is used to generate evidence on impact and cost-effectiveness of control
activities, promoting the use of information for decision making at all levels
of the vector control program. Dengue-GIS has also been used as a hypothesis
generator for the academic community.

Spatial point analysis based on
dengue surveys at household level in central Brazil

GersonLaurindo Barbosa, 1
, * Maria Rita Donalísio, 2 Celso Stephan, 2 Roberto Wagner Lourenço, 3 Valmir Roberto Andrade, 1 Marylene de BritoArduino, 1 and Virgilia Luna Castor de Lima 1


goal of this spatial point analysis was to identify potential high-risk
intra-urban areas of dengue, using data collected at household level from
surveysFirst survey screened 1,586 asymptomatic individuals older than 5 years
of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were
selected by multistage sampling (census tracts; blocks; households) using
available digital maps. Sera from participants were tested by dengue
virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to
detect the spatial varying risk over the region. Initially without any fixed
covariates, to depict the overall risk map, followed by a model including the
main covariates and the year, where the resulting maps show the risk associated
with living place, controlled for the individual risk factors. This method has
the advantage to generate smoothed risk factors maps, adjusted by
socio-demographic covariates.. Data from household surveys pointed out that low
prevalence areas

A study finds
that it is possible to forecast the outbreak of the disease

João B Siqueira-Junior,Ivan J Maciel,

Christovam Barcellos,

Wayner V Souza,

Marilia S Carvalho,

Nazareth E Nascimento,

Renato M Oliveira,

Otaliba Morais-Neto and

Celina MT MartelliEmail author

Public Health20088:361

 Siqueira-Junior et al; licensee BioMed Central Ltd. 2008

Received: 19 October 2007

Accepted: 20 October 2008

Published: 20 October 2008


have reached this conclusion after evaluating the relationship of climatic
factors to the spread of dengue in different climatic zones in India — Punjab,
Haryana, Rajasthan, Gujarat, and Kerala. They focussed on changes in a factor
called extrinsic incubation period (EIP) of the dengue virus, by taking into
account daily and monthly mean temperatures in these areas The EIP is the time
taken for incubation of the virus in the mosquito.Lower temperatures (17-18°C)
result in longer EIPs thereby leading to decreased virus transmission. With
increasing temperatures, feeding increases because of the enhanced metabolism
of the mosquito, leading to shorter EIPs. Even a five-day decrease in the
incubation period can hike the transmission rate by three times, and with an
increase in temperature from 17 to 30°C, dengue transmission increases
fourfold. A further increase in temperature beyond 35°C is detrimental to the
mosquito’s survival.








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