Clustering of vector control interventions has important consequences for their effectiveness: a modelling study.
Vector control interventions have resulted in considerable reductions in malaria morbidity and mortality. When universal coverage cannot be achieved for financial or logistical reasons, the spatial arrangement of vector control is potentially important for optimizing benefits. This study investigated the effect of spatial clustering of vector control interventions on reducing the population of biting mosquitoes. A discrete-space continuous-time mathematical model of mosquito population dynamics and dispersal was extended to incorporate vector control interventions of insecticide treated bednets (ITNs), Indoor residual Spraying (IRS), and larviciding. Simulations were run at varying levels of coverage and degree of spatial clustering. At medium to high coverage levels of each of the interventions or in combination was more effective to spatially spread these interventions than to cluster them. Suggesting that when financial resources are limited, unclustered distribution of these interventions is more effective. Although it is often stated that locally high coverage is needed to achieve a community effect of ITNs or IRS, our results suggest that if the coverage of ITNs or IRS are insufficient to achieve universal coverage, and there is no targeting of high risk areas, the overall effects on mosquito densities are much greater if they are distributed in an unclustered way, rather than clustered in specific localities. Also, given that interventions are often delivered preferentially to accessible areas, and are therefore clustered, our model results show this may be inefficient. This study provides evidence that the effectiveness of an intervention can be highly dependent on its spatial distribution. Vector control plans should consider the spatial arrangement of any intervention package to ensure effectiveness is maximized.
Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Ifakara Health Institute, Dar es Salaam, Tanzania.
Angelina Mageni
AM
Lutambi
Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
Nakul
N
Chitnis
Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Olivier J T
OJ
Briët
Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Thomas A
TA
Smith
Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
Melissa A
MA
Penny
D063147:Animal Distribution / Q000502:physiology; D000818:Animals; D016000:Cluster Analysis; D003198:Computer Simulation; D009033:Culicidae / Q000187:drug effects / Q000472:pathogenicity*; D007303:Insect Vectors / Q000187:drug effects / Q000472:pathogenicity*; D007306:Insecticides / Q000494:pharmacology; D008288:Malaria / Q000517:prevention & control*; D008954:Models, Biological; D009032:Mosquito Control / Q000379:methods* / Q000706:statistics & numerical data; D057147:Mosquito Nets; D011157:Population Dynamics
D007306:Insecticides