A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission

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• 作者：Lin Zhu (1)
  Whitney A Qualls (1)
  John M Marshall (2)
  Kris L Arheart (1)
  Donald L DeAngelis (3)
  John W McManus (4)
  Sekou F Traore (5)
  Seydou Doumbia (5)
  Yosef Schlein (6)
  G眉nter C M眉ller (6)
  John C Beier (1)
  
  1. Department of Public Health Sciences ; Miller School of Medicine ; University of Miami ; Miami ; Florida ; USA
  2. Department of Infectious Disease Epidemiology ; MRC Centre for Outbreak Analysis and Modelling ; Imperial College London ; London ; UK
  3. USGS/Biological Resources Division and Department of Biology ; University of Miami ; Coral Gables ; Florida ; USA
  4. Department of Marine Biology and Ecology ; University of Miami ; Miami ; Florida ; USA
  5. Malaria Research and Training Center ; Faculty of Medicine ; Pharmacy and Odonto-Stomatology ; University of Bamako ; BP 1805 ; Bamako ; Mali
  6. Department of Microbiology and Molecular Genetics ; IMRIC ; Kuvin Centre for the Study of Infectious and Tropical Diseases ; Faculty of Medicine ; Hebrew University ; Jerusalem ; Israel
  
• 关键词：Malaria ; Anopheles gambiae ; Sugar ; feeding ; Resting ; Behavior ; Individual ; based model ; Agent ; based model
• 刊名：Malaria Journal
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：14
• 期：1
• 全文大小：1,586 KB
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• 刊物主题：Parasitology; Infectious Diseases; Tropical Medicine;
• 出版者：BioMed Central
• ISSN：1475-2875

文摘

Background Agent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour. Methods A spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared. Results When the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P Conclusions Increases in densities of sugar sources or outdoor resting sites significantly increase the survival and human biting rates of An. gambiae mosquitoes. Survival of An. gambiae is more supported by random distribution of sugar sources than clustering of sugar sources around resting sites or houses. Density and spatial distribution of natural sugar sources and outdoor resting sites modulate vector populations and human biting rates, and thus malaria parasite transmission.