Influence of urban and peri-urban habitat dynamics on dengue vector larval density and its epidemic implications: a geoinformatics based holistic analysis for dengue risk zonation | |
| Author | Sarfraz, Muhammad Shahzad |
| Call Number | AIT Diss. no.RS-12-06 |
| Subject(s) | Dengue--Geographic Information Systems Dengue--Epidemiology |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | In recent years, human society faced numerous challenges of vector-borne disease outbreaks as a repercussion of favourable local habitat for vector population. Increased frequency and intensity of such outbreaks are causing millions of individuals each year in tropical and subtropical areas. It is reemerging in areas that have been disease-free for relatively long periods of time. This expansion is creating new opportunities for viruses to propagate in new areas and is acting as a common cause of epidemics in what were Aedes(Ae.)free countries. According to estimates by the World Health Organization (WHO), there could be as many as 50 to 100 million dengue infections worldwide each year. In the absence of an effective drug or vaccine, the only strategic options to control dengue are case management to prevent death and control of vectors to reduce viral transmission. The appearance of numerous infectious diseases is strongly facilitated by environmental factors, such as climate or land-use change. Land-use change is a major constituent of global environmental change that can potentially affect human health in relation to mosquito-borne diseases by influencing the mosquito's habitat. The distribution and abundance of vectors concomitantly mediates human-mosquito interactions including biting rate. Besides this dengue fever (DF) and dengue hemorrhagic fever (DHF) are directly and indirectly partially associated with local climatic conditions determining the degree of appropriateness of local habitat for the two key players, the virus and vector. Land-cover type together with the availability of water, temperature, humidity and human population density are also playing important role in determining microclimate for the prevalence of dengue. Although climatic factors play an important role in the spread of vector-borne diseases, however in urban areas temperature, humidity and rainfall hardly vary, and therefore it is very difficult to find a relationship of said factors with dengue case incidences. In addition to the reported relationship between climatic dengue fever is potentially linked with urban features that are capable of mapping using remotely-sensed image to identify suitable dengue habitat. The present study was conducted to predict the suitable potential habitat for dengue-transmitting mosquitoes, integrating dengue indices and land-use. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson's correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic. Results of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively. Furthermore, the extent to which climatic conditions can influence dengue-transmitting mosquito growth was also investigated. Conventional methods including surveys for observing and studying breeding places is very complex and time-consuming. Reducing dependency on time consuming and laborious computation of climatic parameters and adopting usage of advanced remotely sensed freely available climatic data can help achieve timely awareness for vector borne diseases. On the basis of dengue indices approaches was adopted to ascertain the factors influencing dengue breeding habitats from 2007 to 2009. The most probable factors were temperature, humidity, rainfall, land-use patterns, population density and land-use/land-cover. All types of parameters were derived from freely available satellite images(land surface temperature from MODIS, rainfall from TRMM, humidity from AIRS, digital elevation model from SRTM, population density from (SEDAC). Parameters synchronization and predication algorithm were developed on the basis of data mining decision tree method. Results showed that the temperature between 30-40 °C with 70 to 80% relative humidity along10 to 70 mm rainfall provides higher B.I. This algorithm can be further improved by adding more sampling data to enhance its performance. On the basis of this algorithm prediction model was developed to map risk zones for dengue habitats and fuzzy logic methods were applied for predication. Additionally, the last objective of this study was to provide accurate land-use/land-cover information that forms the basis of further analysis of urban structures and refinement of the thematic map towards analyzing the land-use/land-cover types potentially responsible for public health issues. Detection of such features requires systems usually empowered with sensors of higher spatial resolution than those needed for just determining the presence of human settlements only. This is because the vector population is mostly associated with and determined by specific urban features, i.e. housing type and type of vegetation. Lack of real-time data for current urban features and recent unplanned build-up are major issues to be dealt with to reduce forthcoming risk of disease morbidity and mortality in urban and peri-urban areas. Although availability of high spatial resolution satellite imagery offers a novel opportunity to obtain urban information in detail, yet it is too expensive to be adopted in low-income countries. The target was to extract land-use types using object-based and spatial metric approach to explore the dengue incidence in relation to surrounding environment in near real-time using Google and ALOS (Advanced Land Observation Satellite) images. The resultant image showed a useful characterization of urban area with 77% accuracy with 0.68 Kappa. Geo-spatial analysis on public health data indicated that most of the dengue cases were found in densely populated areas surrounded by dense vegetation. People living in independent houses, having sparse vegetation in surrounding, were found to be less vulnerable. Proximity analyses indicated that most of the dengue cases were around institutions (40%), religious places (18%) and markets (15%).These findings showed that the micro-level datasets created using statistical methods and spatial tools are beneficial in predicting possible dengue habitat to facilitate early public health responses. These findings along with reported climatic and demographic factors have special significance in minimizing or curbing the potential risk of dengue outbreak. In conclusion, the use of integrative technologies and freely available tools and their use can be an economic way for disease management in developing countries. Furthermore, this study can be used to develop a monitoring mechanism for other type of diseases which are influenced by environmental and climatic factors. Thus, itis a potential and quick method to identify outbreak hotspots for early warning systems. |
| Year | 2012 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Tripathi, Nitin K.; |
| Examination Committee(s) | Hashim, Mazlan bin;Taravudh Tipdecho;Souris, Marc;Sakchai Chaiyamahapurk; |
| Scholarship Donor(s) | Higher Education Commission(HEC), Pakistan;Asian Institute of Technology Fellowship; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2012 |