Landscape Epidemiology Modeling Using an Agent-Based Model and a Geographic Information System

Land

S. M. Niaz Arifin⁴  Rumana Reaz Arifin²  Dilkushi de Alwis Pitts³  M. Sohel Rahman⁵  Sara Nowreen⁶  Gregory R. Madey⁴  Frank H. Collins⁴  James Millington¹ 

[1] Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA; E-Mail;Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA; E-Mail:;Center for Research Computing, University of Notre Dame, Notre Dame, IN 46556, USA; E-Mail:;Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA; E-Mail:;Department of Computer Science and Engineering (CSE), Bangladesh University of Engineering and Technology (BUET), Dhaka 1205, Bangladesh; E-Mail:;Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh; E-Mail:

关键词: landscape epidemiology;    agent-based models;    simulation;    modeling;    spatial analysis;    hot spot analysis;    Kriging;   

DOI  :  10.3390/land4020378

来源: mdpi

【 摘 要 】

A landscape epidemiology modeling framework is presented which integrates the simulation outputs from an established spatial agent-based model (ABM) of malaria with a geographic information system (GIS). For a study area in Kenya, five landscape scenarios are constructed with varying coverage levels of two mosquito-control interventions. For each scenario, maps are presented to show the average distributions of three output indices obtained from the results of 750 simulation runs. Hot spot analysis is performed to detect statistically significant hot spots and cold spots. Additional spatial analysis is conducted using ordinary kriging with circular semivariograms for all scenarios. The integration of epidemiological simulation-based results with spatial analyses techniques within a single modeling framework can be a valuable tool for conducting a variety of disease control activities such as exploring new biological insights, monitoring epidemiological landscape changes, and guiding resource allocation for further investigation.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.