A sexually transmitted infection model with long-term partnerships in homogeneous and heterogenous populations
- PMID: 31193690
- PMCID: PMC6538957
- DOI: 10.1016/j.idm.2019.05.002
A sexually transmitted infection model with long-term partnerships in homogeneous and heterogenous populations
Erratum in
-
Erratum regarding missing Declaration of Competing Interest statements in previously published articles.Infect Dis Model. 2020 Dec 17;6:1259. doi: 10.1016/j.idm.2020.12.003. eCollection 2021. Infect Dis Model. 2020. PMID: 34938926 Free PMC article.
Abstract
Population models for sexually transmitted infections frequently use a transmission model that assumes an inherent partnership length of zero. However, in a population with long-term partnerships, the infection status of the partners, the length of the partnership, and the exclusivity of the partnership significantly affect the rate of infection. We develop an autonomous population model that can account for the possibilities of an infection from either a casual sexual partner or a longtime partner who was either infected at the start of the partnership or was newly infected. The impact of the long-term partnerships on the rate of infection is captured by calculating the expected values of the rate of infection from these extended contacts. We present a new method to evaluate partner acquisition rates for casual or long-term partnerships which produces in a more realistic number of lifetime sexual partners. Results include a SI model with different infectiousness levels for the transmission of HIV and HSV-2 with acute and chronic/latent infection stages for homogeneous (MSM) and heterogeneous (WSM-MSW) groups. The accompanying reproduction number and sensitivity studies highlight the impact of both casual and long-term partnerships on infection spread. We construct an autonomous set of equations that handle issues usually ignored by autonomous equations and handled only through simulations or in a non-autonomous form. The autonomous formulation of the model allows for simple numerical computations while incorporating a combination of random instantaneous contacts between individuals and prolonged contacts between specific individuals.
Figures






Similar articles
-
Staged HIV transmission and treatment in a dynamic model with long-term partnerships.J Math Biol. 2023 Apr 13;86(5):74. doi: 10.1007/s00285-023-01885-w. J Math Biol. 2023. PMID: 37052718 Free PMC article.
-
The core group revisited: the effect of partner mixing and migration on the spread of gonorrhea, Chlamydia, and HIV.Math Biosci. 1994 Mar;120(1):1-23. doi: 10.1016/0025-5564(94)90036-1. Math Biosci. 1994. PMID: 8155907
-
HIV transmissions by stage in dynamic sexual partnerships.J Theor Biol. 2012 Apr 7;298:147-53. doi: 10.1016/j.jtbi.2011.12.021. Epub 2012 Jan 12. J Theor Biol. 2012. PMID: 22261263 Free PMC article.
-
Pair formation models for sexually transmitted infections: A primer.Infect Dis Model. 2017 Jul 25;2(3):368-378. doi: 10.1016/j.idm.2017.07.002. eCollection 2017 Aug. Infect Dis Model. 2017. PMID: 29928748 Free PMC article. Review.
-
AIDS in rural Africa: a paradigm for HIV-1 prevention.Int J STD AIDS. 1996 Jul;7(4):236-43. doi: 10.1258/0956462961917906. Int J STD AIDS. 1996. PMID: 8876353 Review.
Cited by
-
Origin of HAV strains responsible for 2016-2017 outbreak among MSM: Viral phylodynamics in Lazio region.PLoS One. 2020 May 29;15(5):e0234010. doi: 10.1371/journal.pone.0234010. eCollection 2020. PLoS One. 2020. PMID: 32470049 Free PMC article.
-
Staged HIV transmission and treatment in a dynamic model with long-term partnerships.J Math Biol. 2023 Apr 13;86(5):74. doi: 10.1007/s00285-023-01885-w. J Math Biol. 2023. PMID: 37052718 Free PMC article.
References
-
- Admiraal R., Handcock M.S. Modeling concurrency and selective mixing in heterosexual partnership networks with applications to sexually transmitted diseases. Annals of Applied Statistics. 2016;10(4):2021–2046.
-
- Altmann M. The deterministic limit of infectious disease models with dynamics partners. Mathematical Biosciences. 1998;150:153–175. - PubMed
-
- Castillo-Chávez C., Feng Z., Huang W. On the computation R0 and its role on global stability. In: Castillo-Chavez C., Blower with S., van den Driessche P., Kirschner D., Yakubu A.-A., editors. Mathematical approaches for emerging and reemerging infectious diseases: An introduction. Springer; 2002.
-
- CDC FAST STATS http://www.cdc.gov/nchs/fastats/life-expectancy.htm
LinkOut - more resources
Full Text Sources