School of Environmental Sciences, Bharathidasan University, Tiruchirappalli Centre for Research in Medical Entomology, Madurai

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1 Development Vector Surveillance System through Bio-spatial Technology for Better Public Health Services A case study M. Govindaraju 1, P. Suganthi 1, V.Thenmozhi 2 and B.K. Tyagi 2 1 Bio - Spatial Technology Research Unit, Department of Environmental Biotechnology School of Environmental Sciences, Bharathidasan University, Tiruchirappalli Centre for Research in Medical Entomology, Madurai Abstract: Our country facing serious issues in health sector due to population pressure, urbanization, environmental pollution and fast depletion of natural resources leads poor sanitation in urban environment. Breeding source and vector habitats are the main reason for re-emergence of VBD in the country. Monitoring and management of vectors through surveillance using GIS is more effective and useful to the public health services and to control vector borne diseases. The goal of present study is to map high risk areas in urban environment. In the study relevant parameters such as climatic factors, population, Land use/ land cover changes, environmental parameters, source of vector habitats, VBD occurrence, rate of infection and people perception where integrated and analyzed by Interpolation and overlay method at GIS platform. The study identifies sensitive areas in respect with environment and health aspects in the city. It is observed that GIS has its own potential for the development of vector control and disease surveillance in a systematic approach. Key words: Vector control, Public health, Risk assessment, Remote sensing and GIS. About the Author: Dr. M. Govindaraju Ph. D Dr. M. Govindaraju received his B.Sc., degree in Zoology from University of Madras, completed his M.S Ecology, M.Phil. degree at Pondicherry University, and awarded Ph.D., by Anna University, Chennai, India. He has eight years of research experience at Institute of Remote Sensing, Anna University and one plus eight years of teaching experiences as Assistant professor in the Department in Civil Engineering, Jayam College of Engineering and Technology, Dharmapuri and the Department of Environmental Biotechnology, Bharathidasan University till date respectively. His area of research interest includes development of Bio-Spatial Technology towards ecological restoration, climate change studies, Health GIS, EIA and Urban ecology. He has 25 research papers in international and national peer-reviewed journals and eleven papers as monographs in books. At present he is supervising eight Doctoral Researchers and one M.Phil, scholar. He is the Principal investigator of various major research projects funded by DST, ICMR, UGC, NRDMS and SERB for total cost of Rs. 87, 06,080. E mail ID: mgrasu@bdu.ac.in Phone : , Extn : 632 Fax : Mobile : Page 1 of 9

2 Introduction Vector borne diseases like chikungunya and dengue are major problem in India. Poor environmental sanitation and high population density are the major factors causing these problems. Remote sensing is an advanced technology to apply and identify the vector habitats with maximum accuracy. GIS is a tool to integrate, analyze, predict and manipulation of data for specified purpose. It may also be able to predict the areas and periods of the high vector-borne disease transmission by using spatial and temporal changes of the environment. There is a wide scope for remote sensing and GIS in monitoring and evaluation of tropical diseases, which needs to be explored further towards research. But these technologies remains largely underutilized in less developed countries including India. Disease surveillance and its control activities require advanced technological applications with professional analysis to achieve the target in short term to cover maximum geographical area. Disease prevention, the ultimate objective of disease surveillance involves mapping the disease, host, vector, and parasite. Remote sensing data helps to identify and track environmental characteristics and changes are useful for the study of diseases. Satellite data through remote sensing may be integrated with other data and information using GIS to discern spatio-temporal landscape patterns. Role of Regional Environment in Vector Biology The distribution of vector-borne diseases is largely determined by the availability of suitable habitats. The environmental factors like climate, rainfall, soil, altitude and human population are very important parameter that responsive to spread of the diseases. The life of mosquitoes was influenced by variations in climatic conditions, and hence there is diversity in distribution and habitats of different vector species. Pemola and Jauhari (2006) have also reported that climate variability and breeding of mosquitoes are considered to be one of the important environmental contributors for disease transmission. In urban environment major factors for vector surveillance are garbage, sanitary waste, drainage, open water storage activities and landscape ecology etc. Type of ditch or drain, best suited for a particular situation, will depend upon topography, source of water and landscape ecology will be an important factor for VBD in city area. These factors are increased by increasing level of human population. The highest density of human population leads to increasing the vector abundance and increased the contact between humans where the diseases incidence and transmission highly occur. In forest environment soil and agricultural irrigation is an important factor for vector habitats. The soil drainage capacity determines internal hydro-mechanics. So the distribution pattern of soil plays a major role for mosquito breeding pools and can influence the development of the mosquito species. Mosquito species prefer to establish at various heights where optimum ecological requirements which favour their survival are met. Survey of India map showing 12 categories of altitude. Altitude up to 4500 m was considered in the study, as at an altitude above it mosquito survival is greatly reduced due to low temperature. Case Study - I Vector Surveillance System in Urban Environment About the Tiruchirappalli City Corporation The Study area, Tiruchirappalli city is the fourth largest city in Tamil Nadu, which is situated on the banks of the river Cauvery at 10.5 N, E in India. It spreads over an area of 5114 Sq. km with the population of the city is 1,021,717 of which 507,180 are males and 514,537 are females. Tiruchirappalli City Corporation consists of 60 wards and 4 zones, 15 wards to each zone namely, srirangam, ariyamangalam, ponmalai and K.Abishekapalayam (Fig.1). For the maintaining of better health resources, the population data, vector borne disease its prevalence, Land use/land Cover (2001), sanitation and other related factors were collected during the study period. From the population density analysis areas including Srirangam, Chattram bus terminus, KK Nagar etc., have been found to be on the higher side while outer regions of the city remains to be less populated. Page 2 of 9

3 Methodology Attribute Data Analysis The distribution of mosquitoes (Culex, Aedes, Anopheles Sp.,) in the wards of Tiruchirappalli were done and the data obtained from department of public health and preventive medicine during It has been mapped to find out the most vector prone habitats. The data has been presented in Fig.1. Fig.1Prevelance of Vector Distribution in Trichy City during Land use/land Cover (LU/LC) Map With help of visual interpretation key, change in satellite image was detection to process and identified the changes in LU/LC class based on coregister multi-dated satellite data during the year of may 2001 (Fig.2) and November 2012 (Fig. 4). The images were visually interpreted on system and classified base on the interpretation key prepared during ground truth verification and attribute to the corresponding LU/LC changes. The classified maps are shown in Fig. 3 & Fig. 5. Page 3 of 9

4 Page 4 of 9

5 Solid Waste dumpin site (Ariyamanagala 14 th Esri India User Conference 2013 Fig.2 Satellite imagery during May 2001 Fig.3 Land Use/Land Cover Map Page 5 of 9

6 Solid waste dumping site (Ariyamangalam) Fig. 4 Satellite imagery during November 2012 Fig.5 Land Use/Land Cover Map Observation From the attribute data analysis results, the presence of the vectors have been identified in the wards 1-4, 17, 21, 28, 37-39, 44, 48, 49, 51, 52. These wards include the areas adjacent to solid waste disposal sites, Ariyamangalam and Panchapur. Also wards in Srirangam and Chatram bus terminus are more prone for vector distribution. Hence the risk of occurrence of diseases like Malaria, Chikungunya and dengue in those wards are much higher than the rest. LU/LC results clearly indicate that there is a significant changes in settlement area. It may be due to increasing human populations which leads higher vector surveillance. Urban Legislative Body, all Municipal Corporations are to develop and implement Programme for water supply, sewage, drainage and solid waste management to keep the environment free from vector breeding. So, the diseases surveillance and control activities require advanced technological applications with professional analysis to achieve the target in short term to cover maximum geographical area. In urban high-risk areas can be identified using Remote sensing and GIS technology that would otherwise be difficult to control vector-borne diseases rapidly. Case Study - II Vector Surveillance System in Forest Environment Sitheri Hills Sitheri hills is one of the segments of Eastern Ghats of Tamil Nadu, within the geographical limit of E longitude and N latitude. The total area is about km 2 situated at Pappireddipatti Taluk, 28 Km distance from Harur town in Dharmapuri District. It is situated at an altitude of metres(3600 ft)the area comprises various vegetation types such as the evergreen, semi-evergreen, riparian, dry deciduous scrub and southern thorn scrub forests. The total area of Sitheri hills consists of 59 hamlets and all the hamlets are under the control of one Panchayat President. It has one Primary Health Centre which is located in Sitheri village and four Health Sub Centers, they are situated in Suriyakadai, Nochikuttai, Ammapalayam, and Kalasapadai. According to Health Department records the total population is 9045, Male 4656 and female 4389 with 1908 houses. Page 6 of 9

7 Methodology Spatial Distribution Analysis Species abundance and surveillance of mosquito vectors in the study area was mapped by Inverse Distance Weighted (IDW) and Kriging Interpolation technique. The analysis was done for the data of indoor resting and dusk collection methods. For this analysis non-spatial entomological survey data were used and number of mosquitoes was identified. The result obtained from their study was used for the spatial distribution analysis by converting non-spatial data of mosquito abundance into spatial form. The maps are presented in Fig Observation From the study entomological results reveal predominant species is Cx.tritaeniorhynchus followed by An.subpictus. The distribution maps were prepared for total average of mosquito abundance in each year. During the first year ( ) mosquito abundance were found in Ammapalayam, Sitheri, Selur, Perperi villages, while second year ( ) Ammapalayam, Perperi, Pudur, Selur, Thekkalpatti are to be sensitive areas for vector abundance. It may be due to the water purity, environmental factors, vegetal cover, rainfall etc. In both the years vector abundance was very less in the Nochikudai HSC. Hence the cultivation is limited due to the better environmental status and peoples also having the awareness about the mosquito breeding sites. But the designed irrigation and water systems are poor, inadequate housing, poor waste disposal and water storage, deforestation and loss of biodiversity, all may be contributing factors to vectorborne diseases. For the both environment we need preventive, more confidence and effectiveness health measures methods. Fig.6 Spatial Distribution Analysis for Indoor Fig.7 Spatial Distribution Analysis for Indoor Resting Collection ( ) Resting Collection ( ) Page 7 of 9

8 Conclusion Fig.8 Spatial Distribution Analysis for Dusk Fig.9 Spatial Distribution Analysis for Dusk Collection ( ) Collection ( ) It reveals that GIS plays a major role to develop bio-spatial technology for the application of environment and health science studies. Also it provides an accurate scientific valuable data/solution for environment and health planers. Development of health information system using GIS is an excellent data integrated document for the purpose of disease emergence period. Further, It is an excellent interactive analytical tool enables the decision makers to solve public health problems. So this study concluded that GIS play a key role in the vectors distribution and identification of vector borne diseases in a cost effective way. Acknowledgement The authors are acknowledged to ICMR for their financial support through major research project during the period of for case study-ii present in the paper. Reference 1. Govindaraju M, (2008) Application of Remote Sensing and GIS to identify the Habitats of Vectors,Vector Borne Diseases: Epidemiology and control, Govindaraju M, Muthukumaran VR, Visvanathan P and Ganeshkumar RS (2009) Environmental Assessment for Health Management Through Spatial Technology A case Study from India, Health GIS Enabling Health Geospatially, Govindaraju M, Sunish IP,Tyagi BK, Rajina C, Suganthi P (2011) Development of Health Information System using Spatial Technologies for Sitheri Hills An integrated Approach, Health GIS Managing Health Geospatially, Pemola ND, Jauhari RK (2006) Climatic variables and malaria incidence in Dehradun, Uttaranchal, India. J Vector Borne Dis, 43: Page 8 of 9

9 5. R.M Bhati, R. C Warmai, R. S Yadavi, and V. P Warma (1989) Resting of Mosquitoes in outdoor Pit Shelters in Kheda district, Gujarat Indian Journal of Malariology Vol. 26, pp Reisen WK, Siddiqui TF, Aslamkhan M, Malik GM, (1981), Larval interspecific associations and physico-chemical relationships of the ground water breeding mosquitoes of Lahore. Pak J Sci Res; 3: Page 9 of 9

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