Arunba Srvastava1, B. N. Nagpal2
1Assistant Director, 2Senior Research Officer
Malaria Research Centre, 20, Madhuban, Delhi 110092
Remote sensing technologies combined with GIS can describe local and landscape-level features influencing disease and disease vector distirbution
GIS allows spatial data handling, manipulation, and analysis with a new dimension and unparalleled flexibility. These systems provide more accurate base maps and redefine several methods of data capturing within accepted levels of accuracy. Functionality on the Web for integrating data from various sources, including photographs, video, and sound data has given a new perception to spatial data management and global information sharing. In the current day scenario, GIS is finding application in diverse fields including health. In any disease control programme, there are several factors involved, namely estimation of disease burden, monitoring of disease trend, identification of risk factors, planning, allocation of resources, implementation etc. and a common thread involved in all these activities is ‘Geography’. Geographic Information System owing to its inherent ability to manage both spatial and non-spatial information provides an excellent framework for disease monitoring and control. Globally malaria clinical cases are reported as 300-500 million and 1.5-2.7 million deaths annually. The increasing trend of environmental change is dramatically changing malaria pattern at the local and as well as global scales. Malaria situation is worsening with large-scale epidemics and increasing mortality. There have been immense efforts to correlate malaria and the environment as the latter influences development of both parasite and the vector (https://www.who.ch/). Many parameters associated with environmental change can now be remotely sensed using remote sensing technologies and combined with geographic information system (GIS) can describe local and landscape-level features influencing disease and disease vector distribution. Here a brief review of the work a) Mapping of Vector distribution and b) development of GIS-based malaria surveillance system is presented. For other contributions one can refer to the enclosed list.
Fig 1: Distribution of An. sundaicus in India as predicted by GIS using altitude, soil, temperature and rainfall thematic maps. Light green colour on coastal areas and A & N island shows favourable for An. sundaicus distribution
a) Mapping of An. sundaicus, a malaria vector in India
There are six major vectors of malaria, they differ greatly in their biology, breeding habitats and distribution. Looking to the vast areas, the reports on vector distribution, which is an essential component of selective malaria control strategy are scanty and old. Manual surveys are very costly, cumbersome and time consuming. Therefore GIS was used to map distribution of coastal malaria vector An. sundaicus in India.
In India, An. sundaicus has been reported from eastern coast, two localities of western coast (Gujarat) and Andaman and Nicobar islands. The species is well known for its close association with coastal conditions. Its major breeding sites are swamps, creeks and pits containing stagnant brackish water. It is the sole malaria vector in Andamans and Nicobar islands.
Different vector species establish their population at different heights where ecology is suited for their survival. Impermeable soil allows water stagnation and creates grounds for mosquito breeding and thus favours malaria. Porous soil is devoid of stagnant water bodies, hence unfavourable for anopheline breeding. Longevity of vectors and the process of parasite development are sensitive to temperature. Vector species adapts to different temperature threshold depending on the area it occurs. Low temperature, when duration of parasite development in mosquitoes exceed 30 days i.e. beyond average life span of mosquitoes limits active malaria transmission. At higher temperatures the longevity of mosquitoes is exponentially reduced. The number of breeding sites is generally related to the amount of rainfall for most of the vector species but excessive rains cause flushing, thus killing immature stages. Considering the above close association of vector biology with ecological parameters, rainfall, soil, altitude and temperature were taken in the study. Survey of India topo sheets in the scale 1 : 6,000,000 were digitised to prepare thematic maps of these parameters.
Fig 2: Blow ups of areas favourable for An. sundaicus. Orissa showing Chilka lake, and Vishakha Pattanam in GIS favourable zone, from these places the species has been reported several times. Kerala in south of India show favourable areas for An. sundaicus, this is an unsurveyed area. Reported survey points shown by dots when overlaid on GIS predicted favourable areas shows perfect matching.
In Andaman and Nicobar Islands, the altitude ranges from sea level to 150 m, and the annual mean temperature is about 25 deg C. Since very high rainfall is not suitable for vector immature stages, areas having >= 1600 mm. rainfall were considered as unfavourable. Sandy soil is the characteristic of coastal area, therefore other categories of soil were taken as unfavorable. Altitude map was taken as the base map and other thematic layers were added. Suitable ecological conditions from the areas for reported distribution of vector existence were identified and similar areas were extracted from each thematic layer. In the overlaid maps intersection of regions favorable in different themes resulted in mapping of areas of occurrence of the vector species (Fig. 1).
For validity of the results, a blow up of the Orissa state was taken. It shows Chilka lake falling in GIS analysed favourable zone and An. sundaicus was reported from this lake. A little in south is Vishakha Pattanam of Andhra Pradesh state, it is also found in favourable GIS zone and the species has been recorded earlier from this area. Still down below on western coast Kerala state is situated and GIS studies revealed that a part of south Kerala is favourable for An. sundaicus but till date no survey has been conducted in this area. A comparison of GIS analysed map with reported distribution reveals a good spatial coherence. Since it is a coastal species, the comparison was restricted to coastal areas only (Fig. 2).
There are a few obvious advantages of this technique i) The technique is good for covering vast areas, ii) It can map distribution at macro and as well as micro level, iii) Through GIS vector distribution in inaccessible and unsurveyed areas can be mapped, iv) once the desired scale maps are ready the information can easily be updated and analysed quickly. The technique is fast, reliable and good to study vast geographic areas to identify regions for specific distribution of vectors for planning cost-effective control strategy to interrupt malaria transmission.
Fig 3: Maps showing Dindugul municipality. Dindigul, Tamil Nadu consisting of 44 wards, and some of the functionalities of GIS based malaria surveillance system.
b) GIS based malaria surveillance system
Health infrastructure is probably the most widely distributed network, the data is being generated at the local level, compiles and sent to national level successively through next higher administrative unit and by the time it reaches policy makers it loses its significance. Therefoe, an efficient information management system is highly required for surveillance of disease and control programme.
A GIS based surveillance system for Dindigul municipality, Dindigul, Tamil Nadu has been developed. The district initially composed of 44 wards (now 48), the map was digitised and streetwise information on 33 parameters of each ward has been attached. Information of any ward can be retrieved at the click of the mouse. Any desires area can be selected and zoomed in to reach from ward to street and street to house, and housewise information can be attached (Fig. 3). One can study malaria dynamics both in space and time and relate the increase in malaria incidence to specific breeding sites (Fig.4).
Nov 19th, 1999 was observed as ‘The World GIS Day’ and the same day, the GIS based Surveillance System was implemented in Dindigul municipality. Also a dynamic Web site was hosted on the same day at URL www.malaria-tn.org. Rights for updation of data are reserved for district health officers. The system has been developed using ARC/ Info NT and Arc/ View 3.1. Though one can have full GIS functionalities on the internet by installing Internet Map Server on the site, but initially a low cost GIS solution has been suggested. The data can be accessed and downloaded, the site also provides a link to the free download site of ESRI software. The user can download the software and play with the data at onsite computer. GIS Day was sponsored mainly by National Geographic Society, USA and Environmental Sciences Research Institute, USA, they have compiled success stories which includes MRC’S developed GIS based surveillance system. (One can visit the site .
The major advantages of this system are: i) Web hosting completely eliminates the traditional method of flow of information and the information is instantly available, ii) Once the basic structure is ready, it is easy to convert it to surveillance system; for any other disease viz. filaria, dengue, DHF, one needs to replace malaria data with the data of respective diseases, iii) Buffer zone creation capability of GIS can map the impact zone of any major breeding site, where control activity needs to be strengthened, iv)Net work analysis can identify catchment areas for some health facility and also appropriate sites for location of a new health facility.
Fig 4: Malaria dynamics both in space and time is depicted through GIS, wards where malaria has increased over any time unit can be spotted out malaria control activities can be strengthen in these areas.
A course module was developed and four health officers from Tamil Nadu, two from district and two from the State HQ were trained on GIS-based surveillance system. In consultation with District Malaria Officer and other health officers a revised schedule for surveillance to suit GIS based surveillance system was formulated which is now in action.
Expected applications of GIS in disease management:
The capabilities of GIS are tremendous which can be exploited in various ways; a few obvious applications are the following:
- Point pattern can attempt to display the distribution of disease cases as data location.
- Dynamic graph capability can highlight cases on maps allowing the eventual characterisation of region.
- Surveillance and monitoring which is a continuous systematic collection and analysis of series of quantitative measurements can greatly be facilitated by GIS.
- Overlying capacity can be used for identifying high risk areas and contaminated environmental factors.
- Temporal analysis techniques in built in GIS centre on procedures for timely detection of epidemics period.
- Pattern analysis could be used to describe epidemics diffusion.
- A sequence of contour maps characterising the spread of disease can describe spatio-temporal evolution.
- Contour maps having probability level can depict wave front of spread of disease and the line pattern analysis can describe the limited set of trajectories of the movement of foci across the region.
- The vector data aids in analysis of disease diffusion pattern and health care facility flow.
- The functionalities of GIS can help in developing Malaria Information System. At the micro level, in a village malaria cases can be pinpointed to a specific coordinate. Control measures can be easily determined by overlying topological map.
- Maps showing population density can be used to select sites for horizontal/vertical control programme.
- Population density map can also help in restructuring parasite control component by defining the catchment area of clinical facility. Also this information is useful for planning projected resource needs and the distribution/ requirement of satellite clinical facilities.
- Structural query language and geometric operationcapability of GIS involve computation of distance, area, volume and direction. This capability of GIS is specially useful for planning, logistics and operations of malaria control programme.
- In the context of forecasting and control by integration GIS with remote sensing technology it is possible to develop real-time information system depicting potential surges in disease transmission, enabling the initiation of rapid response strategies.
- A blend of GIS with artificial intelligence can be used for rule-based reasoning to automate interpretation of information.
The tremendous capabilities of GIS can be exploited in various ways. Integration of GIS with remote sensing technology can possibly develop real-time information system for depicting potential surges in disease transmission for implementation of rapid response strategies. Its buffer zone creation capabilities can help in studying the impact of some specific vector breeding site on the community within its impact zone. Network capabilities can be applied to a variety of planning, administrative and operational activities. A blend of GIS with artificial intelligence can be used to develop rule based reasoning system for automatic interpretation of interacting themes