Implicit versus explicit vector management strategies in models for vector-borne disease epidemiology

被引:0
作者
Jeffery Demers
Suzanne L. Robertson
Sharon Bewick
William F. Fagan
机构
[1] Center for Advanced Systems Understanding (CASUS),Department of Biology
[2] University of Maryland College Park,Department of Mathematics and Applied Mathematics
[3] Virginia Commonwealth University,Department of Biological Sciences
[4] Clemson University,undefined
来源
Journal of Mathematical Biology | 2022年 / 84卷
关键词
Vector-borne disease; Disease control; Mosquito control; Adulticide; Larvicide; Larval source reduction; 92; 93;
D O I
暂无
中图分类号
学科分类号
摘要
Throughout the vector-borne disease modeling literature, there exist two general frameworks for incorporating vector management strategies (e.g. area-wide adulticide spraying and larval source reduction campaigns) into vector population models, namely, the “implicit” and “explicit” control frameworks. The more simplistic “implicit” framework facilitates derivation of mathematically rigorous results on disease suppression and optimal control, but the biological connection of these results to real-world “explicit” control actions that could guide specific management actions is vague at best. Here, we formally define a biological and mathematical relationship between implicit and explicit control, and we provide mathematical expressions relating the strength of implicit control to management-relevant properties of explicit control for four common intervention strategies. These expressions allow the optimal control and basic reproduction number analyses typically utilized in implicit control modeling to be interpreted directly in terms of real-world actions and real-world monetary costs. Our methods reveal that only certain sub-classes of explicit control protocols are able to be represented as implicit controls, and that implicit control is a meaningful approximation of explicit control only when resonance-like synergistic effects between multiple explicit controls have negligible effects on population reduction. When non-negligible synergy exists, implicit control results, despite their mathematical tidiness, fail to provide accurate predictions regarding vector control and disease spread. Collectively, these elements build an effective bridge between analytically interesting and mathematically tractable implicit control and the challenging, action-oriented explicit control.
引用
收藏
相关论文
共 94 条
[1]  
Agusto F(2013)Optimal control of the spread of malaria superinfectivity J Biol Syst 21 1340002-320
[2]  
Lenhart S(2017)Optimal control and cost-effectiveness analysis of a three age-structured transmission dynamics of chikungunya virus Dis Continuous Dyn Syst Ser B 22 293-22
[3]  
Agusto FB(2017)Optimal control and cost-effective analysis of malaria/visceral leishmaniasis co-infection PLoS ONE 12 e0171102-267
[4]  
Agusto FB(2012)Application of optimal control to the epidemology of malaria Electr J Differ Equ 2012 1-1091
[5]  
Elmojtaba IM(2017)Mathematical model of Zika virus with veritcal transmission Infect Dis Model 2 244-436
[6]  
Agusto FB(2007)Approximation of the basic reproduction number Bull Math Biol 69 1067-561
[7]  
Marcus N(2006) for vector-borne diseases with a periodic vector population J Math Biol 56 421-130
[8]  
Oksun KO(2014)The epdemic threshold of vectir-borne diseases with seasonality: The case of cutaneous leishmaniasis in Chichaoua, Morocco Epidemio Infect 142 545-1133
[9]  
Agusto FB(2012)Modeling interventions during an dengue outbreak Med Vet Entoml 26 121-577
[10]  
Bewick S(2005)Ultra-low-volume space sprays in mosuito control: a critical review Bull Math Biol 67 1107-319