The present study deals with the role of Geographical Information Systems (GIS) in mapping the disease prevalence in areas and indicating the severity of a particular disease in certain areas. The primary and secondary data’s were collected from field and Municipal hospital respectively.
Spatial mapping of different diseases (i.e. vector borne and water borne diseases) and pollution sources like water distribution lines passing through parallel or cross to the drains/garbage sites.
The available number of health facilities such as PHC, HP and major hospitals were located in the GIS environment for further analysis. Based on the overlay and integrate analyses classified and zoned as mild, moderate and severe categories of flood epidemics.
Application of GIS in Post Flood Epidemics- A Case Study, Mumbai by Dr. Guru Balamurugan and Vikas N. Kurne
1. Application of GIS in Post Flood EpidemicsApplication of GIS in Post Flood Epidemics ––
A case study, MumbaiA case study, Mumbai
Guru Balamurugan* and VikasGuru Balamurugan* and Vikas
*Asst. Professor*Asst. Professor
JTCDM, TISSJTCDM, TISS
MumbaiMumbai
gurubala.jtcdm@gmail.comgurubala.jtcdm@gmail.com
2. IntroductionIntroduction
Purpose of the studyPurpose of the study
Floods can lead to property damage and loss of human life.Floods can lead to property damage and loss of human life.
Disruption of water purification and sewage disposal systems.Disruption of water purification and sewage disposal systems.
Floods have impact on public health due to water contamination,Floods have impact on public health due to water contamination, increase in vectorincrease in vector
population or direct injuries(Few and Ahern, 2005).population or direct injuries(Few and Ahern, 2005).
Physical health effects due to living in damp and dirty conditioPhysical health effects due to living in damp and dirty conditions.ns.
Potential outbreak of communicable diseases.Potential outbreak of communicable diseases.
Exposure to toxic substances, i.e., chemical and biological agenExposure to toxic substances, i.e., chemical and biological agents.ts.
Socioeconomic factors increases risk of health problems and becoSocioeconomic factors increases risk of health problems and become worst duringme worst during
floods like poverty, overcrowding, poor housing, low income statfloods like poverty, overcrowding, poor housing, low income status, education etcus, education etc
(Malilay, 2003).(Malilay, 2003).
After floods,After floods,
Increase in infectious diseasesIncrease in infectious diseases
Population displacement and change in density (overcrowding)Population displacement and change in density (overcrowding)
Disruption of basic public sanitation services, may occur.Disruption of basic public sanitation services, may occur.
3. ObjectivesObjectives
1)1) Mapping the Spatial variations in disease incidences.Mapping the Spatial variations in disease incidences.
2)2) Mapping of potential risk areas (low lying areas).Mapping of potential risk areas (low lying areas).
4. Study AreaStudy Area -- MumbaiMumbai
Mumbai area falls between Latitude N 18 30Mumbai area falls between Latitude N 18 30’’ to 19 20to 19 20’’ andand
Longitude E 72 45Longitude E 72 45’’ to 73 00to 73 00’’
AreaArea
437.71 Sq.km (approx.).437.71 Sq.km (approx.).
PhysiographyPhysiography
Terrain made of Deccan basalt. Soil is sandy in south and alluviTerrain made of Deccan basalt. Soil is sandy in south and alluvial andal and
loamy in suburbs (Apte, 2003)loamy in suburbs (Apte, 2003)
Topographic variationsTopographic variations –– 15 to 20m above MSL.15 to 20m above MSL.
Climate and rainfallClimate and rainfall
Tropical, moist (Sherbenin, 2007).Tropical, moist (Sherbenin, 2007).
Temperature max. 33Temperature max. 33˚˚C to 29C to 29˚˚C and min. 16C and min. 16˚˚C to 26C to 26˚˚C (Apte,2003)C (Apte,2003)
Monsoon between June and Sept. Average 2457Monsoon between June and Sept. Average 2457--2700 (IMD2700 (IMD--MumbaiMumbai
region). Nearly 70% rainfall during Jul.region). Nearly 70% rainfall during Jul. –– Aug.Aug.
5. DrainageDrainage
Three river, Mithi, Dahisar and Poisar. Mithi isThree river, Mithi, Dahisar and Poisar. Mithi is
largest and drains most of citylargest and drains most of city’’s effluents. Surfaces effluents. Surface
drains 2000km, underground drains 440 km anddrains 2000km, underground drains 440 km and
outfalls 186 discharge into rivers and Arabian sea.outfalls 186 discharge into rivers and Arabian sea.
PopulationPopulation
Around 1.19 cr (Census, 2001), now estimated 1.34Around 1.19 cr (Census, 2001), now estimated 1.34
cr (HDR, Mumbai, 2009), 54% residing in slums andcr (HDR, Mumbai, 2009), 54% residing in slums and
46% . Density46% . Density –– 27,209 people per Sq. km27,209 people per Sq. km
(Neelakantan, 2005).(Neelakantan, 2005).
8. Wards information and low lying areasWards information and low lying areas
Wards: H(E),K(E) and LWards: H(E),K(E) and L
H(E)H(E) –– AreaArea -- 18.53 sq.km; Population18.53 sq.km; Population -- 5,79123;5,79123;
7 Health posts and 1 Municipal hospital;7 Health posts and 1 Municipal hospital;
Low lying areas Vakola, Kalina, Shastri nagar, Bharat nagar,Low lying areas Vakola, Kalina, Shastri nagar, Bharat nagar,
New Agripada, Air India and Indian airlines colony.New Agripada, Air India and Indian airlines colony.
K(E)K(E) –– AreaArea –– 24.5 sq.km; Population 8,06,360;24.5 sq.km; Population 8,06,360;
11 Health posts;11 Health posts;
Low lying areas Sahar village, Chimat pada, Nav pada and SagLow lying areas Sahar village, Chimat pada, Nav pada and Sag
baug.baug.
LL –– AreaArea –– 15.9 sq.km; Population15.9 sq.km; Population-- 5,90,609;5,90,609;
12 Health posts and 1 Municipal hospital;12 Health posts and 1 Municipal hospital;
Low lying areas Kranti nagar, Jarimari, Lohia nagr, BuddhaLow lying areas Kranti nagar, Jarimari, Lohia nagr, Buddha
colony, Bamandaya pada, Sable nagar, Kapadia colony.colony, Bamandaya pada, Sable nagar, Kapadia colony.
10. GIS data generationGIS data generation
Primary dataPrimary data
Basic informationBasic information ::
Demographic informationDemographic information ::
Health informationHealth information
Secondary dataSecondary data
No. of patients taken treatment.No. of patients taken treatment.
Hospitalized or not.Hospitalized or not.
Laboratory findings.Laboratory findings.
Diagnosis.Diagnosis.
Disease wise categorizing of patients.Disease wise categorizing of patients.
No. of deaths, direct and due to illness.No. of deaths, direct and due to illness.
27. Water level with Jaundice and rashWater level with Jaundice and rash
28. Water level and dengue and malariaWater level and dengue and malaria
29. Union with all diseases and water levelUnion with all diseases and water level
30. ConclusionConclusion
Preventive measures to be taken after floodsPreventive measures to be taken after floods..
Clean up after flood, Increase frequency of garbageClean up after flood, Increase frequency of garbage
clearance.clearance.
Fogging and sanitization, Spraying of insecticide.Fogging and sanitization, Spraying of insecticide.
Protecting self from mould, injuries, electric shock.Protecting self from mould, injuries, electric shock.
Drinking water safety, Boil water at least for one minute.Drinking water safety, Boil water at least for one minute.
Food safety, avoid contaminated food.Food safety, avoid contaminated food.
Increase number of temporary clinics/ health services.Increase number of temporary clinics/ health services.
Create awareness among people regarding generalCreate awareness among people regarding general
precautions to be taken.precautions to be taken.