Spatial epidemiological diffusion patterns and hotspot mapping : a case of Mueang Phayao, Thailand | |
| Author | Goud C, Raasi Kumar |
| Call Number | AIT Thesis no.RS-17-10 |
| Subject(s) | Mapping--Thailand--Phayao Spatial systems--Thailand--Phayao |
| Note | A thesis report submitted in partial fulfillment of the requirements for the degree of Masters of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. RS-17-10 |
| Abstract | Extensive utilization of RS and GIS in health sector had given an open door for healthcare specialists to distinguish the risk zones for various diseases through which the administrations can be rendered all the more successfully, yet this work is still under gigantic pressure particularly in creating countries and countries with vast populace, because of the constraints in information accessibility. When considering the low mortality rate ailment with high morbidity rate are further dismissed. For quite a long time healthcare specialists reacted to outbreak of diseases by expanding healthcare services offices. Different looks into have demonstrated that expanding healthcare services offices alone can't assist in ad lobbing administration to individuals, additionally administration to the most required for identifying risk zones to a little scale can acquire an intense change allotment of administrations by healthcare segment. So rendering administrations all the more adequately is vital. Hemorrhagic conjunctivitis, pyreaxia of unknown origin, dengue hemorrhagic fever, dengue fever and hand foot mouth disease are the endemic ailments found in Thailand as well as considered as risky all through the world. This review focuses on distinguishing spatial patterns, and hotspots for the years 2006 -2014 considered Mueang Phayao district as study area, capital of Phayao territory disease, statistics and GIS information is obtained and arranged for examination. Disease incidence rate is computed for every village and empirical Bayes smoothing is utilized to kill anomalies from data and kernel density is utilized to create choropleth maps utilizing disease morbidity rate. Local SAA and global are utilized to decide spatial patterns and hotspots separately. Techniques utilized for this procedure are LISA and global Moran's I separately. Risk modeling is done considering elements, for example, land-use, distance from water bodies, rainfall, population and dem factors utilizing Analytical Hierarchical Process (AHP). The risk maps can be confirmed by overlaying malady hotspots and checking their reality. The models can be utilized by public health officers to distinguish risk territories for every infection and render their administrations all the more adequately and taking preventive measures. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-17-10 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Tripathi, Nitin Kumar |
| Examination Committee(s) | Miyazaki, Hiroyuki;Chatterjee, Joyee S. |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |