Open AccessApplication of geographical information system-based analytical hierarchy process as a tool for dengue risk assessment
Author(s) -
Nazri Che Dom,
Abu Hassan Ahmad,
Zulkiflee Abd Latif,
Rozaina Ismail
Publication year - 2016
Publication title -
asian pacific journal of tropical disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 33
ISSN - 2222-1808
DOI - 10.1016/s2222-1808(16)61158-1
Subject(s) - analytic hierarchy process , dengue fever , consistency (knowledge bases) , geographic information system , environmental health , computer science , population , information system , process (computing) , geography , risk analysis (engineering) , environmental resource management , operations research , business , engineering , cartography , environmental science , medicine , electrical engineering , artificial intelligence , immunology , operating system
Objective: To highlight the use of analytical hierarchy process (AHP) in geographical\udinformation system that incorporates environmental indices to generate dengue risk zonation\udarea.\udMethods: The medical database considered for the study was referenced to the environmental\uddata layers. Factors related to the risk of dengue fever (DF) were selected throughout previous\udresearch and were arranged in a hierarchical structure. The relative weights of factors were\udcalculated, which were within acceptable range with the consistency ratio being less than 0.1.\udThe outcomes from AHP based DF risk zonation area produced useful information on different\udlevels of risks.\udResults: As a result, factor weights used in AHP were evaluated and found to be acceptable as\udthe consistency ratio of 0.05, which was < 0.1. The most influential factors were found to be\udhousing types, population density, land-use and elevation. Findings from this study provided\udvaluable insights that could potentially enhance public health initiatives. The geographical\udinformation system and spatial analytical method could be applied to augment surveillance\udstrategies of DF and other communicable diseases in an effort to promote actions of prevention\udand control. The disease surveillance data obtained could be integrated with environmental\uddatabase in a synergistic way, which will in turn provide additional input towards the\uddevelopment of epidemic forecasting models.\udConclusions: This attempt, if successful, will have significant implications that could\udstrengthen public health interventions and offers priorities in designing the most optimum and\udsustainable control program to combat dengue in Malaysia