Development Of Geographic Information System For Immunization Local Area Monitoring (LAM) In Palangka Raya City
Abstract
Lilyk Rakhmawaty, Hari Kusnanto, Anis Fuad
Background: Nowadays, the usage of Geographic Information System (GIS) has been shown improvement rapidly in various sectors, including health sector. GIS has features to present spatial and non-spatial information simultaneously. GIS also can be used to monitor the realization of immunization program. As the immunization program manager, Palangka Raya Health Office has not used the GIS yet in running the immunization program. Analysis was done through Local Area Monitoring (LAM) modestly. It is important to monitor the service coverage area and its effects so that it can detect quickly high risk areas for diseases which can be prevented by immunization (PD3I). Hopefully, GIS application for can help monitoring of immunization LAM program.
Objectives: It aimed to develop spatial-based information system for Immunization LAM in Palangka Raya which included need assessment, system design and its utilization.
Methods: It was a descriptive – qualitative with action research method. The subject included 3 managers, 3 program managers at the health office, and 2 immunization program executors at health centers. The data were collected through in-depth interview, observation, and literature review.
Results: Development of the GIS-based Immunization LAM resulted coverage area maps for all antigen, distribution of PD3I diseases and stratification of tetanus nenonatorum. The system also can provide information about program’s problem for anticipation immediately.
Conclusion: The spatial-based immunization LAM Information System was useful for program efficiency and effectively since it could minimize the working time and delivered the required information by manager. To maintain the information on immunization quality, the system supposed to be developed from individual analysis unit.
Keywords: Geographic Information System, Immunization LAM, Development
GIS on Weekend: Thematic Mapping
Today, people interest to GIS becomes greater since it can be applied to various sectors. It is also shown by the enthusiasm of participants in “GIS on Weekend” training held by the SIMKES, they come from various backgrounds, e.g. lecturers, graduate students, and staff of health office. In the third meeting on last Saturday (August 16, 2008), the topic was “thematic Mapping”, that was, participants were taught the way to make a thematic map. A thematic map displays spatial pattern of a theme or series of attributes and emphasizes spatial variation of one or a small number of geographic distributions. A thematic map can be made by converting Shapefiles (SHP) into a kml files which can be applied to Google Earth.
SHP is a vector format (format proprietary open specification) as the product of ESRI, a GIS software company (ArcInfo, ArcView, ArcIMS, dan ArcGIS). This format has 3 extension file, they are:
- Main file: *.shp
- Index file: *.shx
- DBase file: *.dbf
Data conversion from SHP files into kml files can be done in several ways. There are software which provide this conversion application, such as Arc GIS 9.2, Arc view GIS 3x (extension), DNR Garmin 5.3, Mapwindow 45CF with plug-ins Shape2earth 1.45.01, Shp2kml, etc. Among those softwares, Shp2kml is the easiest one and can be run indepedently without the main program. This application can be downloaded in http://www.zonums.com:80/files/Shp2kml.zip. After downloading the application, unzip the shp2kml.zip become shp2kml.exe.
Happy trying J
GIS on Weekend: Part 1
GIS on weekend is a set of training of Geographic Information System Implementation (GIS) for Health with 4 sessions. The first session has been held on Saturday, August 2, 2008. The topic was “GIS Implementation for Health” with the speakers of Anis Fuad, DEA (Overview of Health GIS), Sugeng Harianto (GIS Tools: Epimap, EpiInfo), and Adi Widagdo (Introduction to GPS). At last, a case study was lead by Anis Fuad to learn about GIS throughout the existed cases.
GIS was an information system with current data for showing the location in map. Along with the recent technology development, GIS also has been developed on the basis of computer and can be applied on other sectors including the health sector.
GIS can be used to answers the following questions:
- What did happen in a place?
- Where was something?
- What changes have happen during ….to…?
- How was the distribution pattern of something?
- How if…?
In public health sector, GIS based-spatial analysis is used for:
- Disease controlling (vector mapping, disease cases, distance identification, case clustering/cause of sickness)
- Health program planning
- Health program monitoring and evaluation
- A suporrting tool for health personnel allocation
The GIS integrate various data, e.g. satellite data, aerial photograph, digital maps, tabular information, etc., then forming new information in thematic map.
Before making a thematic map, we should prepare the spatial data to show location of an area. Gathering spatial data, we can use a GPS (global positioning system), that is a satellite based-navigation system which informing definite position of a location in the earth. The GPS receiver can detect the 24 orbited-satellite signals upon the earth. By using distance measuring function, we can determine position of a location in the world.
After gathering spatial data from the GPS, so these data are processed by using GIS software such as Epimap, Quantum GIS, ArcView, etc. At last, it can produce a complete map with points of observed location.
GIS has several advantages for health sectors, particularly for spatial analysis which can support decision making corresponding to public health.
For the next session, the topic is Spatial Data for Mapping. The registration for the next training sessions is still opened. Just contact the SIMKES secretariat on (62)274 -549432.
Spatial Analysis of Post-Tsunami Malaria Cases at Johan Pahlawan Distrct, West Aceh
ABSTRACT
Abdullah, Hari Kusnanto, Anis Fuad
Background: Johan Pahlawan was one of districts in the area of West Aceh which experienced tsunami on Desember 26, 2006. After the disaster, it was predicted the increasing of various disease because of water, density, food emergency, and improper housing. The tsunami caused the increasing of sea water to the land as ± 3 kilometers, and the impact was water precipitations on the holes which have existed before the tsunami and also which created at the tsunami happened. Those places became new places for the anopheles mosquito grew. It was reported the increasing number of malaria incidents in the post-tsunami evacuation area, so that it needed geographical mapping of malaria cases.
Objectives: This study aimed to find out the malaria incidents post-tsunami disaster and the correlation of malaria incidents in tsunami experienced areas and non-tsunami experienced areas.
Methods: This was an analytical study with cross sectional approach. Sample for this study was all malaria incidents in Johan Pahlawan District, West Aceh during 2005 and 2006. The coordinate points of patients’ addresses were taken by using the Global Positioning Service (GPS).
Results: The results showed that correlations between malaria incidents and the use of land were as follows: the residential areas p = 0.965 in 2005 and p = 0.447 in 2006 (p > 0.05); the agriculture areas p = 0.00004 in 2005 and p = 0.0007 in 2006 (p < 0.05); the fishpond/pool areas p = 0.503 in 2005 and p = 0.953 in 2006 (p > 0.05), the rice field areas p = 0.0002 in 2005 and p = 0.001 (p < 0.05), the swamp areas p = 0.414 in 2005 and p = 0.929 in 2006 (p > 0.05) , and the wild jungle p = 0.074 in 2005 and p = 0.311 in 2006 (p > 0.05). The differences of malaria incidents in the tsunami experienced areas and non-tsunami experienced areas were t = -0.213, p = 0.833 in 2005 and t = 0.893, p = 0.383 in 2006 (p > 0.05).
Conclusion: The distribution patterns of malaria cases in Johan Pahlawan were correlated to the use of agriculture areas and rice field areas; meanwhile, they were not related to the use of pool areas, wild jungle, and residential areas. There were no differences between malaria prevalence in tsunami experienced areas and non-tsunami experienced areas.
Keywords: Malaria incidents, GIS, post-tsunami, the use of land.
Application of Geographic Information System into Spatial Model of Tuberculocis Cases at Depansar in the Year Of 2007
ABSTRACT
Ni Nyoman Kristina, Hari Kusnanto, Anis Fuad
Background: At Province of Bali, the contagious diseases which should be alerted are the new emerging diseases and re-emerging diseases. To cover this problem, the government has developed ten national priority programs and one of them is GERDUNAS (Gerakan Terpadu Nasional) Tuberculosis. Refer to this problem, the researcher would describe several aspects which influenced the prevalence of tuberculosis (TB), such as density, poverty, urban status, and the distance to healthcare facilities. This model suggested spatial model to determine the susceptible area of TB at Denpansar.
Objectives: This study was aimed to find out the benefits of spatial model in determining level of susceptible area to TB, to find out the relationship between density and TB cases, and also to find out the association of TB clustering in the poor area, urban clusters at Denpansar, and distance to the healthcare facilities with the benefit of spatial model in improving management of TB control at the high endemic area.
Method: This study was an observational research with cross sectional approach. Data analysis used software of Geoda and SatScan for the GIS process.
Results: There was correlation between TB cases and poverty (z = = 3,502, p = 0.0004). Meanwhile density (z = -1,529, p = 0.126) and urban status (z = -1.113, p = 0.909) were not related to TB cases. The chi-square analysis also showed that there was no correlation between TB cases and distance to the healthcare facilities (x2 = 0.21, p = 0.65). Analysis of spatial dependency with Moran’s test showed the value of 0.670 (p = 0.412).
Conclusion: TB cases correlated to poverty significantly, and have no correlation with density, urban status, and distance to the healthcare facilities. Spatial distribution pattern of TB did not follow any specific pattern. Clustering of TB tended to exist in poverty area and spread following the direction of road.
Keywords: Geographic Information System, Spatial Model, Smear (+) TB
Epidemiology Study of Dengue Hemorrhagic Fever Cases in South Palu Sub District, Palu by Using Spatial Approach of Geographic Information System
ABSTRACT
Oslan Daud, Hartono, Tri Baskoro Tunggul Satoto
Background: At the moment, Dengue Hemorrhagic Fever (DHF) is a public health problem which arise social and economic impacts. By the time, number of DHF cases tends to increase and the endemic area is wider. In 2004, number of DHF patients at Palu was 210 patients and 10 of them were died. The number of DHF patients increased to 627 patients (12 of them were died) in 2005 and 334 patients (5 of them were died) in 2006. In 2007, the number of DHF cases was enormous. Since January until April 2007, the number had reached number of 334 patients and 2 of them were died.
Objective: This study aimed to find out the epidemiology distribution of DHF cases at South Palu Sub district during the year of 2004 – 2006 in the basis of human, place and time characteristics; also to map its spatial distribution by using geographic information system (GIS) approach.
Methods: This was an analytical descriptive survey with cross sectional approach. This method was used to obtain the description of DHF spatial distribution in South Palu Sub District during 2004 – 2006. The coordinate points of patients’ addresses were taken by using Global Positioning System (GPS). The collected data were analyzed and presented on tables, graphics, and map.
Results: The epidemiology distribution results showed that most of DHF patients were men (52.48%); patients’ age were above 15 years old (46.60%); the highest endemic area was South Lolu village (15.41%), and the highest case numbers happened during May until September. There were 9 clusters of DHF cases in North Taturu and Tanamodindi villages. This study also reported that the DHF cases in South Palu Sub District related to density (p=0.004), air temperature (25.3ºC – 28.1ºC) and air humidity (71.3% - 79.7%). and Wiggler Free Rate (WFR) (p=0.462).
Conclusion: This study concluded that men had more activities than women; most of DHF patients were student aged; South Lolu village had high density and mobilization; and the increasing of DHF cases happened in rainy season during April – October. There were clustering of DHF cases in North Tatura and Tanamodindi village. Density and DHF had a significant relationship (p = 0.004). Air temperature and humidity supported the growth of DHF infector which caused the increasing of DHF patients year by year. Last, the WFR did not relate to DHF cases significantly.
Keywords: DHF cases, epidemiology characteristics, spatial distribution, GIS, South Palu.
Spatial Analysis of Malaria Cases During 2006 – 2007 in Lahewa Sub District, Nias District, Province of North Sumatera
ABSTRACT
Everoni Mendrofa, Sugeng Juwono, Dulbahri
Background : Nias District, Province of North Sumatera is one of malaria endemic areas which is influenced by the climate, heavy rainfall, mountainous topography, low socio economic status and education, most of the origin people work as farmers. Number of malaria cases in Lahewa Sub District were 1.432 clinical malaria cases (59,70%), 347 positive malaria cases (14,47%) in 2005, then they were 1.382 clinical malaria cases (44,13%) and 343 positive malaria cases (11,47%) in 2006. Therefore, it needed a geographical mapping for malaria cases in Lahewa Sub District.
Objective : This study aimed to map the spatial distribution of malaria cases and environment factors in Lahewa Sub District, Nias District in the year of 2007.
Method : This was a cross sectional study with analytical descriptive survey. Sample in this study were 84 patients with malaria symptoms, who lived in Lahewa, and had visited to the clinics during August 2007. Patients’ addresses were identified to determine coordinate points by using the Global Positioning System (GPS). The data were analyzed by using bivariate analysis with Chi Square test and spatial analysis with Sat Scan, Geode and Epi Info.
Results: This study resulted malaria cases associated with the use of mix garden (p = 0,0059) and humidity (p = 0,0309). However, malaria cases were not related to distance to health facilities (p = 0,084), the use of land as rice fields (p = 0,1405), the use of swamp area (p = 0,5442), the use of land as ponds (p = 0,6647), residential area (p = 0,0511), quantity of rainfall (p = 0,2379), and air temperatures ( p = 0,4513).
Conclusion: Malaria cases in Lahewa were not influenced by distance to health facilities and the use of land rice fields, ponds, residential area and swamp area, also the quantity of rainfall and air temperature. They were influenced significantly by the use of land as mix garden and humidity.
Keywords : GIS, spatial distribution, mapping, malaria cases.
Spatial Analysis of Tuberculosis in Sleman by Using Geographic Information System (GIS)
ABSTRACT
Wawan Kusugiharjo, Hari Kusnanto
Background : There are some problems in prevention of Tuberculosis cases in Sleman, especially in finding cases coverage of positive LUNG terbium BTA. This is caused by lack of support from the policy makers. This condition affects the organizers of the program and paramedics become unmotivated, so that the goals could not be reached. Nowadays, finding cases coverage has reached number of 50% and this condition probably derived the increasing of Lung TB infection risk in Sleman and it is predicted that a patient with positive Lung TB can infect other 10 persons in a year. From the explanation above, this study combined some variables that could affect Lung TB cases; they were density, poverty, and health service facilities. By using spatial factor analyzes, this study, hopefully, can be used as the consideration in policy making of Lung TB prevention at Sleman.
Objective: The study was aimed to find out the relationship between density, poorness and supporting facilities to health service of LUNG terbium BTA (+) case in District of Sleman.
Methods : A cross sectional survey was held in Sleman, Yogyakarta. The population was area population that involved area segments in all research units (the overall of Sleman areas) and all LUNG terbium BTA (+) cases during 2005 (387 cases). Independent variables were density, poverty, and facilities of health service. Meanwhile, dependent variable was LUNG terbium BTA (+) case.
Data analysis : Spatial analysis of SaTScan was used to find out LUNG terbium BTA (+) clusters, Excel Distcalc was used to measure distance between patient’s residence to the health service facilities, and spatially weighted regression analysis of GeoDa was used to find out the relationship among independent variables and dependent variables.
Results : Analysis of spatially weighted regression (spatial errors model) showed that density was related to LUNG terbium BTA(+) cases (t= -1,992 p = 0,049); LUNG terbium BTA(+) case was not related to poverty (t= -0,667 p = 0,506 ( p>0,05)); and LUNG Terbium BTA (+) was not based on current spatial distribution pattern (p= 0,622 (p>0,05)). From the Space-Time Permutation Model (Likelihood Ratio Test), it was obtained 8 clusters. First cluster happened on January 1, 2005 until January 31, 2005 with coordinate point of (- 7.767990 s, 110.391840 E) and radius of 2,18 km. Meanwhile, the Most Likely Cluster was cluster which happened on March 1,2005 until March 31, 2005 with coordinate point of (- 7.641750 sulfur, 110.382630 E) and radius of 2,11 km
Conclusion : LUNG terbium BTA (+) case did not associate with poverty, but it associated with density. There were significant clustering of LUNG terbium disease BTA(+) cases in Sleman. Cluster of LUNG terbium BTA(+) cases tended to follow high density pattern, not to follow poverty based on administration.
Keywords : LUNG terbium BTA(+) case, density, Poverty, facilities of health services, Geographic Information System.
The Geographic Information System Training for Midwives in Monitoring Antenatal Program at The Sleman Government Clinics
ABSTRACT
Senik Windyati, Hari Kusnanto, Kristiani
Background: In providing health services to the society, health centers have responsibilities to manage health problems in their working area. Maternal mortality is a major health problem in Indonesia; therefore, improvement of the quality of mother and child health service program is the main activity. Monitoring of the local region on mother and child health is a management tool for mother and child health program in a current working area of local government clinic. Success of its performance can be measured based on coverage level of mother and child health program in a particular area. The management of antenatal service data has been running well so far; however the data have not been well utilized for a follow-up program. An important element in health problem solving is the availability of data accurately, informatively and up-to-date in a working area. Geographic information system (GIS) is expected playing an important role in the process of mother and child health service program management.
Objective: The study was aimed to find out whether the training of GIS could improve the capacity of midwives to monitor antenatal program at the local government clinics.
Method: A quasi experiment was subjected to 32 midwives of the local government clinics centers who had a responsibility for mother and child health service program. Data were obtained from questionnaires and focus group discussion, and then they were analyzed by using repetitive observation t-test analysis.
Result: The result of t-test showed that the difference of average capacity of staff in monitoring antenatal service program before and after using GIS was 16.90%. There was a significant difference of midwives capability in monitoring antenatal service program at the health center before and after the treatment.
Conclusion: The training of GIS could improve the capability of midwives in monitoring antenatal service program at the Sleman government clinics.
Keywords: Geographic Information System, area monitoring, antenatal service