GIS-SAPIO

Automated Aedes Aegypti Web-based Analysis and Prevention Monitor

Georges D. A. Nze

, Lourdes M. Brasil

, Josiane S. A. Souza

and Marco A. B. Rodrigues

Engineering and Innovation Laboratory, University of Brasilia – UnB/FGA, Gama, Brazil

Biomedical Engineering Course, Federal University of Pernanbuco - UFPE, Recife, Brazil

Keywords: Dengue, Public health, GIS-SAPIO, Aedes aegypti, Web.

Abstract: This work proposes the creation of a fully automated and dynamic web platform to analyze and prevent the

Aedes aegypti mosquito's proliferation in Brazil. The Web Based Geographic Information System for

SAPIO (GIS-SAPIO) is part of a project denominated: System Acquisition and Image Processing Ovitraps

(SAPIO) for obtaining and processing ovitraps – traps where the mosquito’s eggs are deposited – and

algorithms are used for the automation of eggs counting. The data obtained from image processing is

processed thru an automated script and sent to SAPIO´s database, and finally displayed on a web platform.

This technique should help for monitoring and prevent Dengue overall Brazil dynamically.

1 INTRODUCTION

Aedes aegypti mosquito’s proliferation is increasing

all over Brazil. A large amount of cases having the

disease spread by the mosquito (known as dengue

fever) has been reported by the Brazilian Health

Ministry and to revert present scenario, efforts are

been made to prevent and control in old fashion, the

proliferation of dengue (Ministério da Saúde, 2010).

This old fashion prevention aims to report, door

to door, the implication of having containers that

could retain water for a long period of time, and

being a vector for the mosquito to lay its eggs in it.

Nonetheless, this prevention technique is useless

because not all citizens really understand the

problems that could imply in having stagnant water

containers at or near their houses, even being really

small quantities of water in any kind of recipient.

The Brazilian Health Ministry is doing a great

effort for the publication of online and printed

document that shows how citizens should protect

their surroundings from this mosquito on a daily

basis but the proliferation scenario is still maintained

since 2007 (Dengue, 2011).

In recent work, different Web-based application

proposals using relational database and analysis

(Sucaet, 2008) for monitoring the mosquito

population has been presented but do not treat the

current effect of dengue proliferation. Other Web-

based application for climate information resources

for Malaria control is proposed in (Emily, 2006) but

their main purpose is to reveal current precipitation,

temperature, relative humidity or general climate

conditions suitable for Malaria transmission and

nothing about the proliferation of the disease

dynamically with substantial data.

In (Dengue, 2011) is presented a public health

platform based on web application to follow the

proliferation of Dengue. Their proposal isn’t based

on real time data base acquisition but on stored data

from previous event collected in old fashion. Some

data as shown in Table 2 lack of data from previous

years and there is no explanation about it.

All these works demonstrate that it is a great deal

of using geographical and database processing

principles, and this work being part of the SAPIO

project propose another but simple and efficient free

Web-based application to monitor and analyze the

proliferation of dengue dynamically. The use of

Geographic Information System (GIS) is of great

interest because of collecting, storing, analyzing and

integrating it with different kind of database (Sucaet,

2008). This database is to be maintained by statistics

data collected by human health expert, thru GPS,

and automatic data processing. Doing so would be

easier to deployed general information of the virus

proliferation in a daily based technique for all kind

of users: government to general society.

366

D. A. Nze G., M. Brasil L., S. A. Souza J. and A. B. Rodrigues M..

GIS-SAPIO - Automated Aedes Aegypti Web-based Analysis and Prevention Monitor.

DOI: 10.5220/0003765803660369

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2012), pages 366-369

ISBN: 978-989-8425-88-1

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

2 METHODS

The methods herein explained are part of SAPIO´s

Public health research group. This project is divided

in two actions: (1) Putting ovitraps in region having

a dense concentration of dengue, and counting the

amount of eggs using System Acquisition and Image

Processing techniques (Mello, 2008) and (

Andrade,

2010); (2) Mapping the results on a website to show

the mosquito’s proliferation statistic as to prepare

the government and society in taking proper actions

in real time (Amvame, 2011).

2.1 Trapping Technique

Plastic buckets are filled of stained water with a

wood slide on the edge, Figure 1. This bucket and

slide (ovitrap) is currently used as a trap for the

mosquito. A smell from the wood slide is used to

attract the Aedes aegypti into the trap and lay the

larva on it: this is the ovitrap technique.

2.2 Counting Technique

A human health specialist collects the wood slides

and manually counts the eggs deposited by the

mosquito. The first part of this project, automates

using a special algorithm the eggs counting by

image processing techniques, and compares it with

the manual technique, Figure 1. All counting are

saved with respect to their localization.

2.3 Data Acquisition and Database

The resulting data collection obtained from the

Counting Technique, Table 1, goes thru SAPIO´s

XML script for correct translation of data into a free

relational database, Figure 1. The database is

dynamically maintained, using a 5 second refresh

time rate, as data comes from image processing.

Table 1: Example of Pernanbuco´s reported infection

cases from 2000 to 2004.

State 

UF

ReportedInfectionCases

Pernanbuco00 01 02 03 04

AFLITOS PE 10 28 43 0 0

AFOGADOS PE 8 8 39 0 0

AGUAFRIA PE 51 63 591 14 22

ALTODO

MANDU

PE 132 81 468 7 19

ALTOJOSE

BONIFIACIO

PE 5 2 181 1 3

2.4 Web-based Monitoring

After data acquisition, Table 2, a web-based is use to

show mapping and statistic information collected

from the first stage as shown in Figure 1. Google

Maps (Google, 2010) API are used to support

current implementation and phpMyAdmin

(PhpMyAdmin, 2010) is used for database

acquisition.

Figure 1: Diagram showing the methodology leading from

egg counting to web-based monitoring.

Table 2: Infection incidence related to Pernanbuco and

Brasília from 2009 to 2010.

StateorTerritory UF InfectionIncidence

Pernanbuco 2009 2010

IGARASSU PE ‐ noinfo.

GARANHUNS PE 2.1 2.3

ITAPISSUMA PE ‐ 0.8

FLORESTA PE ‐ 5.7

OLINDA PE 1.3 1.1

OURICURI PE ‐ 7.2

PETROLINA PE 0.8 0.9

RECIFE PE 1.6 1.9

DistritoFederal 2009 2010

BRASÍLIA DF 1.7 0.6



Satisfactory <1.0% 

Alert 1.0%‐3.9%

Epidemyrisk >3.9% 

Dataare stored

intoaDatabase

Eggsare counted

byimage

processing

Themosquitolay

theeggsintothe

ovitrap

Aedesaegypti

carryingdengue’s

virus

Awebserver retrievesthe

statisticsfromthedatabase

andputitonlinefor analysis

While(true)

xmlSAPIO =[DBname_root,'.xml'];

Listen Ovitrapsdata;

xmlwrite(xmlSAPIO,docNode);

Map XMLtoSQL=edit(xmlSAPIO);

SIG‐SAPIODBread =SQLread;

GIS-SAPIO - Automated Aedes Aegypti Web-based Analysis and Prevention Monitor

367

The prototype shown in Figure 2 demonstrates

how dengue monitoring would be displayed for web

users. A general map is presented for the user to

have direct statistic information from any state, and

in need of more detailed information from that state,

a link calls Google Maps to provide accurate

positioning of the dengue proliferation.

3 RESULTS

The results here by far obtained are very satisfactory

because of the difficulty in integrating Google APIs

with other open source applications. The present

work shows a great integration between the two

stages of the SAPIO project, and now can have a

simple but still great techniques and data acquisition

shown visually thru Web for monitoring the

proliferation of dengue, Figure 2.

As it is really important to reach the entire

population for a daily prevention and alert, it should

be remembered that the access to the internet is still

a challenge in poor region of Brazil, and if not the

computers technologies and data speed rates used in

those areas are of poor performance. The idea is to

have the web-platform being accessible for those

having equipment working at transmission data rate

of at least 256 Kbps.

The Brazilian Ministry of Communication is

actually implementing the PNBL (National Plan of

High Speed Internet Connexion in Brazil) for

Internet access purpose overall Brazil for people

having small savings.

The web platform would permit users to surf

around the Brazilian map, top-left in Figure 2

showing the Pernanbuco State as an example, and

look at current or past statistic about dengue in their

region, top-right of Figure 2. This is important to

have as quickly as possible without having to

navigate thru many unnecessary links. Another

accurate information than the one displayed in the

top-right, would display their current localization.

The map shown at Figure 2 would bring the local

position of the treat were the disease is suppose to

occur or appeared, and the drop down box would

make available access to other cities in current or

other state.

Not seen in Figure 2 yet, would be multiple sort

of data displayed for better understanding of what is

going on in the area selected for analysis, and it all

would depend on what type of information is been

collected from the database. Figure 3 shows, as an

example, a static spatial data displaying 2008

Figure 2: SAPIO´s prototype Web Platform for Real Time Dengue Proliferation Analysis.

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Dengue Fever throughout Brazil, (Dengue, 2011).

This visualization technique will be implemented for

a real time analysis for SAPIO.

Figure 3: Dengue Fever incidence by State in Brazil, 2008.

All Data retrieve from the expert would be

uploaded thru a special link, in SAPIO´s web

platform, into the Database Server in real time with

their GPS coordinates.

As future work, the idea is to work with the

Brazilian National Climate Institute as to having a

more robust, detailed and statistical analysis scenario

were dengue is to be monitored before it causes

more damages throughout Brazil.

4 CONCLUSIONS

This work has shown the development of a web-

based application that can provide the monitoring

and analysis of dengue proliferation in real time. Its

database is filled with data coming from an

automated Aedes aegypti image processing egg

counting from ovitraps. This platform should be

used for monitoring and prevention of the disease as

an alert for all citizens. At this current stage, the

work herein proposed shows how important is it to

make all data collected from SAPIO been visualized

by anyone, and to fight and prevent dengue into a

web illustrated format.

ACKNOWLEDGEMENTS

This research is partially sponsored by FINEP-Brazil

and CNPq-Brazil.

REFERENCES

Amvame, G., Brasil, L., Rodrigues, M., 2011. Sistema

WEB para Monitoração e Análise de Proliferação do

Aedes aegypti. In Pan American Health Care

Exchanges. Rio de Janeiro, Brazil. PAHCE 2011.

Andrade, M., Brasil, L., 2010. Automatic Identification of

Aedes Aegypti Eggs Deposited in Ovitraps Slides

Using Image Processing Techniques. In Congresso

Brasileiro de Engenharia Biomédica. São João Del

Rei. CBEB 2010.

Mello, B., Santos, P., Rodrigues, M., 2008. Image

Segmentation of Ovitraps for Automatic Counting of

Aedes aegypti Eggs. In 30th Annual International

Conference Of The IEEE Engineering In Medicine

And Biology Society. Vancouver, Canada.

Dengue., 2011: Programa nacional de controle da Dengue.

In http://www.dengue.org.br/.

Ministério da Saúde. “Programa nacional de controle da

Dengue. Brazil”. http://portal.saude.gov.br/saude/area.

cfm?id_area=920. Brazil 2010.

Sucaet, Y., Van Hemert, J., 2008. Web-based relational

database for monitoring and analyzing mosquito

population dynamics. In J Med Entomol.

Emily, K., Pietro, Ceccato., Stephen, J., 2006. Web-based

climate information resources for malaria control in

Africa. In Malaria Journal 2006, 5:38.

Google Maps., 2010. In http://www.google.com.br/.

PhpMyAdmin., 2010. In http://www.phpmyadmin.net.

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