期刊
JOURNAL OF THEORETICAL BIOLOGY
卷 333, 期 -, 页码 126-134出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2013.05.017
关键词
Risk variability; Mathematical modelling; Epidemiology
资金
- ZonMW, The Netherlands [125020005]
Background. Interventions aimed at minimizing the spread of blood borne infections among Injecting Drug Users (IDU) are impeded by limitations in resources. To enhance their efficiency, it may be beneficial to target specific behavioural subpopulations, distinguished by syringe sharing tendencies. Methods. We used mathematical modelling to explore the effects of two types of intervention: removal of individuals from the injecting population and risk decrease at group-level (e.g. distribution of syringes). We computed the direct effects of intervention on the probability of obtaining and spreading infection as a function of baseline risk behaviour. Population level effects of (targeted) intervention were explored using a differential equations model, which incorporated two levels of risk. Results. Within most scenarios of risk distribution considered, HIV could be substantially reduced or eliminated by targeting high risk IDU only. Conversely, higher incidence reductions for HCV were reached in many scenarios when targeting low risk IDU. The potential for preventing infections by removal of uninfected IDU increases with baseline risk, but so does the probability that an IDU is already infected before being reached by intervention. Decreasing risk is likely to only delay rather than prevent infection for IDU borrowing many syringes, especially for a very infectious disease such as HCV. Conclusions. The efficiency of intervention on injecting drug users may be much enhanced by targeting specific risk subgroups. However, the optimal targeting policy depends strongly on the infection under consideration. Crown Copyright (c) 2013 Published by Elsevier Ltd. All rights reserved.
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