Research article Special Issues

A mathematical model for Zika virus disease: Intervention methods and control of affected pregnancies


  • Published: 24 June 2025
  • Zika virus is spread to human populations primarily by Aedes aegypti mosquitoes, and Zika virus disease has been linked to a number of developmental abnormalities and miscarriages, generally coinciding with infection during early pregnancy. In this paper, we propose a new mathematical model for the transmission of Zika and study a range of control strategies to reduce the incidence of affected pregnancies in an outbreak. While most infectious disease models primarily focus on measures of the spread of the disease, our model is formulated to estimate the number of affected pregnancies throughout the simulated outbreak. Thus the effectiveness of control measures and parameter sensitivity analysis is done with respect to this metric. In addition to traditional intervention strategies, we consider the introduction of Wolbachia-infected mosquitoes into the native population. Our results suggest a threshold parameter for Wolbachia as an effective control measure, and show the natural time scale needed for Wolbachia-infected mosquitoes to effectively replace the native population. Additionally, we consider the possibility of a Zika vaccine, both to avoid an outbreak through herd immunity and as a control measure administered during an active outbreak. With emerging data on persistence of Zika virus in semen, the proposed compartmental model also includes a component of post-infectious males, which introduces a longer time scale for sexual transmission than the primary route. While the overall role of sexual transmission of Zika in an outbreak scenario is small compared with the dominant human-vector route, this model predicts conditions under which subpopulations may make this secondary route more significant.

    Citation: Chad Westphal, Shelby Stanhope, William Cooper, Cihang Wang. A mathematical model for Zika virus disease: Intervention methods and control of affected pregnancies[J]. Mathematical Biosciences and Engineering, 2025, 22(8): 1956-1979. doi: 10.3934/mbe.2025071

    Related Papers:

  • Zika virus is spread to human populations primarily by Aedes aegypti mosquitoes, and Zika virus disease has been linked to a number of developmental abnormalities and miscarriages, generally coinciding with infection during early pregnancy. In this paper, we propose a new mathematical model for the transmission of Zika and study a range of control strategies to reduce the incidence of affected pregnancies in an outbreak. While most infectious disease models primarily focus on measures of the spread of the disease, our model is formulated to estimate the number of affected pregnancies throughout the simulated outbreak. Thus the effectiveness of control measures and parameter sensitivity analysis is done with respect to this metric. In addition to traditional intervention strategies, we consider the introduction of Wolbachia-infected mosquitoes into the native population. Our results suggest a threshold parameter for Wolbachia as an effective control measure, and show the natural time scale needed for Wolbachia-infected mosquitoes to effectively replace the native population. Additionally, we consider the possibility of a Zika vaccine, both to avoid an outbreak through herd immunity and as a control measure administered during an active outbreak. With emerging data on persistence of Zika virus in semen, the proposed compartmental model also includes a component of post-infectious males, which introduces a longer time scale for sexual transmission than the primary route. While the overall role of sexual transmission of Zika in an outbreak scenario is small compared with the dominant human-vector route, this model predicts conditions under which subpopulations may make this secondary route more significant.



    加载中


    [1] R. Lowe, C. Barcellos, P. Brasil, O. G. Cruz, N. A. Honório, H. Kuper, et al., The Zika virus epidemic in Brazil: from discovery to future implications, Int. J. Environ. Res. Public Health, 15 (2018), 96. https://doi.org/10.3390/ijerph15010096 doi: 10.3390/ijerph15010096
    [2] O. Pacheco, M. Beltrán, C. A. Nelson, D. Valencia, N. Tolosa, S. L. Farr, et al., Zika virus disease in Colombia—preliminary report, N. Engl. J. Med., 383 (2020), e44. https://doi.org/10.1056/NEJMoa1604037 doi: 10.1056/NEJMoa1604037
    [3] L. H. Chen, D. H. Hamer, Zika virus: Rapid spread in the western hemisphere, Ann. Intern. Med., 64 (2016), 613–615. https://doi.org/10.7326/M16-0150 doi: 10.7326/M16-0150
    [4] W. K. Oliveira, G. V. A. de França, E. H. Carmo, B. B. Duncan, R. S. Kuchenbecker, M. I. Schmidt, Infection-related microcephaly after the 2015 and 2016 Zika virus outbreaks in Brazil: a surveillance-based analysis, Lancet, 390 (2017), 861–870. https://doi.org/10.1016/S0140-6736(17)31368-5 doi: 10.1016/S0140-6736(17)31368-5
    [5] S. R. Ellington, O. Devine, J. Bertolli, A. M. Quiñones, C. K. Shapiro-Mendoza, J. Perez-Padilla, et al., Estimating the number of pregnant women infected with Zika virus and expected infants with microcephaly following the Zika virus outbreak in Puerto Rico, 2016, JAMA Pediatr., 170 (2016), 940–945. https://doi.org/10.1001/jamapediatrics.2016.2974 doi: 10.1001/jamapediatrics.2016.2974
    [6] M. L. Ospina, V. T. Tong, M. Gonzalez, D. Valencia, M. Mercado, S. M. Gilboa, et al., Zika virus disease and pregnancy outcomes in Colombia, N. Engl. J. Med., 383 (2020), 537–545. https://doi.org/10.1056/NEJMoa1911023 doi: 10.1056/NEJMoa1911023
    [7] D. F. Robbiani, P. C. Olsen, F. Costa, Q. Wang, T. Y. Oliveira, N. Nery Jr, et al., Risk of Zika microcephaly correlates with features of maternal antibodies, J. Exp. Med., 216 (2019), 2302–2315. https://doi.org/10.1084/jem.20191061 doi: 10.1084/jem.20191061
    [8] L. T. Keegan, J. Lessler, M. A. Johansson, Quantifying Zika: Advancing the epidemiology of Zika with quantitative models, J. Infect. Dis., 216 (2017), S884–S890. https://doi.org/10.1093/infdis/jix437 doi: 10.1093/infdis/jix437
    [9] V. C. Agumadu, K. Ramphul, Zika virus: A review of literature, Asian Pac. J. Trop. Biomed., 6 (2016), 989–994. https://doi.org/10.7759/cureus.3025 doi: 10.7759/cureus.3025
    [10] A. A. Momoh, A. Fügenschuh, Optimal control of intervention strategies and cost effectiveness analysis for a Zika virus model, Oper. Res. Health Care, 18 (2018), 99–111. https://doi.org/10.1016/j.orhc.2017.08.004 doi: 10.1016/j.orhc.2017.08.004
    [11] E. Bonyah, K. Okosun, Mathematical modeling of Zika virus, Asian Pac. J. Trop. Dis., 6 (2016), 673–679. https://doi.org/10.1016/S2222-1808(16)61108-8 doi: 10.1016/S2222-1808(16)61108-8
    [12] D. Gao, Y. Lou, D. He, T. C. Porco, Y. Kuang, G. Chowell, et al., Prevention and control of Zika as a mosquito-borne and sexually transmitted disease: A mathematical modeling analysis, Sci. Rep., 6 (2016), 28070. https://doi.org/10.1038/srep28070 doi: 10.1038/srep28070
    [13] D. F. Aranda, G. Gonzalez-Parra, T. Benincasa, Mathematical modeling and numerical simulations of Zika in Colombia considering mutation, Math. Comput. Simul., 163 (2019), 1–18. https://doi.org/10.1016/j.matcom.2019.02.009 doi: 10.1016/j.matcom.2019.02.009
    [14] C. L. Althaus, N. Low, How relevant is sexual transmission of Zika virus, PLOS Med., 13 (2016), 1–3. https://doi.org/10.1371/journal.pmed.1002157 doi: 10.1371/journal.pmed.1002157
    [15] A. Allard, B. M. Althouse, L. Hebert-Dufresne, S. V. Scarpino, The risk of sustained sexual transmission of Zika is underestimated, PLoS Pathog., 13 (2017), 1–12. https://doi.org/10.1371/journal.ppat.1006633 doi: 10.1371/journal.ppat.1006633
    [16] M. Sherley, C. W. Ong, Sexual transmission of Zika virus: a literature review, Sex Health, 15 (2018), 183–199. https://doi.org/10.1071/SH17046 doi: 10.1071/SH17046
    [17] C. R. Kim, M. Counotte, K. Bernstein, C. Deal, P. Mayaud, N. Low, et al., Investigating the sexual transmission of Zika virus, Lancet Global Health, 6 (2018), e24–e25. https://doi.org/10.1016/S2214-109X(17)30419-9 doi: 10.1016/S2214-109X(17)30419-9
    [18] T. Ferdousi, L. W. Cohnstaedt, D. S. McVey, C. M. Scoglio, Understanding the survival of Zika virus in a vector interconnected sexual contact network, Sci. Rep., 9 (2019), 7253. https://doi.org/10.1038/s41598-019-43651-3 doi: 10.1038/s41598-019-43651-3
    [19] B. S. von Essen, K. Kortsmit, L. Warner, D. V. D'Angelo, H. B. Shulman, W. H. Virella, et al., Preventing sexual transmission of Zika virus infection during pregnancy, Puerto Rico, USA, 2016, Emerg. Infect. Dis., 25 (2019), 2115–2119. https://doi.org/10.3201/eid2511.190915 doi: 10.3201/eid2511.190915
    [20] M. Rodriguez, A. Lord, C. C. Sanabia, A. Silverio, M. Chuang, S. M. Dolan, Understanding Zika virus as an STI: findings from a qualitative study of pregnant women in the Bronx, Sex. Transm. Infect., 96 (2020), 80–84. https://doi.org/10.1136/sextrans-2019-054093 doi: 10.1136/sextrans-2019-054093
    [21] C. G. Major, G. Paz-Bailey, S. L. Hills, D. M. Rodriguez, B. J. Biggerstaff, M. Johansson, Risk estimation of sexual transmission of Zika virus—United States, 2016–2017, J. Infect. Dis., 224 (2021), 1756–1764. https://doi.org/10.1093/infdis/jiab173 doi: 10.1093/infdis/jiab173
    [22] P. S. Mead, N. K. Duggal, S. A. Hook, M. Delorey, M. Fischer, D. Olzenak McGuire, et al., Zika virus shedding in semen of symptomatic infected men, N. Engl. J. Med., 378 (2018), 1377–1385. https://doi.org/10.1056/NEJMoa1711038 doi: 10.1056/NEJMoa1711038
    [23] F. A. Medina, G. Torres, J. Acevedo, S. Fonseca, L. Casiano, C. M. De León-Rodríguez, et al., Duration of the presence of infectious Zika virus in semen and serum, J. Infect. Dis., 219 (2019), 31–40. https://doi.org/10.1093/infdis/jiy462 doi: 10.1093/infdis/jiy462
    [24] M. Izquierdo-Suzán, S. Zárate, J. Torres-Flores, F. Correa-Morales, C. González-Acosta, E. E. Sevilla-Reyes, et al., Natural vertical transmission of Zika virus in larval Aedes aegypti populations, Morelos, Mexico, Emerg. Infect. Dis., 25 (2019), 1477–1484. https://doi.org/10.3201/eid2508.181533 doi: 10.3201/eid2508.181533
    [25] M. A. Ibrahim, A. Dénes, Threshold dynamics in a model for Zika virus disease with seasonality, Bull. Math. Biol., 83 (2021), 27. https://doi.org/10.1007/s11538-020-00844-6 doi: 10.1007/s11538-020-00844-6
    [26] A. Srivastav, J. Yang, X. F. Luo, M. Ghosh, Spread of Zika virus disease on complex network—a mathematical study, Math. Comput. Simul., 157 (2019), 15–38. https://doi.org/10.1016/j.matcom.2018.09.014 doi: 10.1016/j.matcom.2018.09.014
    [27] S. L. Li, J. P. Messina, O. G. Pybus, M. U. G. Kraemer, L. Gardner, A review of models applied to the geographic spread of Zika virus, Trans. R. Soc. Trop. Med. Hyg., 115 (2021), 956–964. https://doi.org/10.1093/trstmh/trab009 doi: 10.1093/trstmh/trab009
    [28] U. A. Danbaba, S. M. Garba, Modeling the transmission dynamics of Zika with sterile insect technique, Math. Methods Appl. Sci., 41 (2018), 8871–8896. https://doi.org/10.1002/mma.5336 doi: 10.1002/mma.5336
    [29] M. N. Rocha, M. M. Duarte, S. B. Mansur, B. D. M. e Silva, T. N. Pereira, T. é. R. Adelino, et al., Pluripotency of Wolbachia against arboviruses: the case of yellow fever, Gates Open Res., 3 (2019), 161. https://doi.org/10.12688/gatesopenres.12903.2 doi: 10.12688/gatesopenres.12903.2
    [30] C. Indriani, W. Tantowijoyo, E. Rancès, B. Andari, E. Prabowo, D. Yusdi, et al., Reduced dengue incidence following deployments of Wolbachia-infected Aedes aegypti in Yogyakarta, Indonesia: a quasi-experimental trial using controlled interrupted time series analysis, Gates Open Res., 4 (2020), 50. https://doi.org/10.12688/gatesopenres.13122.1 doi: 10.12688/gatesopenres.13122.1
    [31] S. B. Pinto, T. I. S. Riback, G. Sylvestre, G. Costa, J. Peixoto, F. B. S. Dias, et al., Effectiveness of Wolbachia-infected mosquito deployments in reducing the incidence of dengue and other Aedes-borne diseases in Niterói, Brazil: A quasi-experimental study, PLoS Negl. Trop. Dis., 15 (2021), e0009556. https://doi.org/10.1371/journal.pntd.0009556 doi: 10.1371/journal.pntd.0009556
    [32] L. Wang, H. Zhao, S. M. Oliva, H. Zhu, Modeling the transmission and control of Zika in Brazil, Sci. Rep., 7 (2017), 7721. https://doi.org/10.1038/s41598-017-07264-y doi: 10.1038/s41598-017-07264-y
    [33] L. Xue, X. Cao, H. Wan, Releasing Wolbachia-infected mosquitos to mitigate the transmission of Zika virus, journal of mathematical analysis and applications, J. Math. Anal. Appl., 496 (2021), 27. https://doi.org/10.1016/j.jmaa.2020.124804 doi: 10.1016/j.jmaa.2020.124804
    [34] Z. Qu, J. M. Hyman, Generating a hierarchy of reduced models for a system of differential equations modeling the spread of Wolbachia in mosquitoes, SIAM J. Appl. Math., 79 (2019), 1675–1699. https://doi.org/10.1137/19M1250054 doi: 10.1137/19M1250054
    [35] P. M. S. Castanha, E. T. A. Marques, A glimmer of hope: Recent updates and future challenges in Zika vaccine development, Viruses, 12 (2020), 1371. https://doi.org/10.3390/v12121371 doi: 10.3390/v12121371
    [36] S. E. Woodson, K. M. Morabito, Continuing development of vaccines and monoclonal antibodies against Zika virus, npj Vaccines, 9 (2024), 91. https://doi.org/10.1038/s41541-024-00889-x doi: 10.1038/s41541-024-00889-x
    [37] W. Valega-Mackenzie, K. Ríos-Soto, Can vaccination save a Zika virus epidemic, Bull. Math. Biol., 80 (2018), 598–625. https://doi.org/10.1007/s11538-018-0393-7 doi: 10.1007/s11538-018-0393-7
    [38] T. Y. Miyaoka, S. Lenhart, J. F. C. A. Meyer, Optimal control of vaccination in a vector-borne reaction-diffusion model applied to Zika virus, J. Math. Biol., 79 (2019), 1077–1104. https://doi.org/10.1007/s00285-019-01390-z doi: 10.1007/s00285-019-01390-z
    [39] E. R. Krow-Lucal, B. J. Biggerstaff, J. E. Staples, Estimated incubation period for Zika virus disease, Emerg. Infect. Dis., 23 (2017), 841–845. https://doi.org/10.3201/eid2305.161715 doi: 10.3201/eid2305.161715
    [40] M. R. Duffy, T. H. Chen, W. T. Hancock, A. M. Powers, J. L. Kool, R. S. Lanciotti, et al., Zika virus outbreak on Yap Island, Federated States of Micronesia, N. Engl. J. Med., 360 (2009), 2536–2543. https://doi.org/10.1056/NEJMoa0805715 doi: 10.1056/NEJMoa0805715
    [41] M. M. Haby, M. Pinart, V. Elias, L. Reveiz, Prevalence of asymptomatic Zika virus infection: a systematic review, Bull. World Health Organ., 96 (2018), 402–413D. https://doi.org/10.2471/BLT.17.201541 doi: 10.2471/BLT.17.201541
    [42] National Administrative Department of Statistics (DANE) (Colombia), Colombia Population and Housing Census 2018, 2018. Available from: https://ghdx.healthdata.org/record/colombia-population-and-housing-census-2018.
    [43] L. M. Rueda, K. J. Patel, R. C. Axtell, R. E. Stinner, Temperature-dependent development and survival rates of Culex quinquefasciatus and Aedes aegypti (Diptera: Culicidae), J. Med. Entomol., 27 (1990), 892–898. https://doi.org/10.1093/jmedent/27.5.892 doi: 10.1093/jmedent/27.5.892
    [44] F. El Moustaid, L. R. Johnson, Modeling temperature effects on population density of the dengue mosquito Aedes aegypti, Insects, 10 (2019), 393. https://doi.org/10.3390/insects10110393 doi: 10.3390/insects10110393
    [45] H. L. C. Dutra, M. N. Rocha, F. B. S. Dias, S. B. Mansur, E. P. Caragata, L. A. Moreira, Wolbachia blocks currently circulating Zika virus isolates in Brazilian Aedes aegypti mosquitoes, Cell Host Microbe, 19 (2016), 771–774. https://doi.org/10.1016/j.chom.2016.04.021 doi: 10.1016/j.chom.2016.04.021
    [46] S. Towers, F. Brauer, C. Castillo-Chavez, A. Falconar, A. Mubayi, C. Romero-Vivas, Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission, Epidemics, 17 (2016), 50–55. https://doi.org/10.1016/j.epidem.2016.10.003 doi: 10.1016/j.epidem.2016.10.003
    [47] C. Poitras, Findings Shed New Light on Why Zika Causes Birth Defects in Some Pregnancies. Available from: https://ysph.yale.edu/news-article/findings-shed-new-light-on-why-zika-causes-birth-defects-in-some-pregnancies/.
    [48] O. Diekmann, J. A. Heesterbeek, M. G. Roberts, The construction of next-generation matrices for compartmental epidemic models, J. R. Soc. Interface, 7 (2010), 873–885. https://doi.org/10.1098/rsif.2009.0386 doi: 10.1098/rsif.2009.0386
    [49] O. Diekmann, J. A. P. Heesterbeek, Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis, and Interpretation, John Wiley & Sons, Ltd., New York, 2000.
    [50] A. Utarini, C. Indriani, R. A. Ahmad, W. Tantowijoyo, E. Arguni, M. R. Ansari, et al., Efficacy of Wolbachia-infected mosquito deployments for the control of Dengue, N. Engl. J. Med., 384 (2021), 2177–2186. https://doi.org/10.1056/NEJMoa2030243 doi: 10.1056/NEJMoa2030243
    [51] S. Marino, I. B. Hogue, C. J. Ray, D. E. Kirschner, A methodology for performing global uncertainty and sensitivity analysis in systems biology, J. Theor. Biol., 254 (2008), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 doi: 10.1016/j.jtbi.2008.04.011
  • Reader Comments
  • © 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(979) PDF downloads(65) Cited by(1)

Article outline

Figures and Tables

Figures(10)  /  Tables(3)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog