The DOI matches its Crossref record.
Concurrent partnerships and transmission dynamics in networks
Open accessAbstract
Network structure plays a critical role in channeling person-to-person transmission of infectious disease agents like HIV. Stochastic simulations are used here to examine the effect of two structural attributes: concurrent partnerships (degree) and mixing patterns (degree-based homophily bias). Four alternative partnership scenarios are compared: (1) sequential monogamy, and concurrent partnerships with (2) random (3) assortative and (4) disassortative mixing by degree. Concurrent partnerships are found to dramatically increase the speed and pervasiveness of epidemic spread, and the implications for HIV transmission are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Holme, P., & Saramäki, J. (2012) · Physics Reports · doi:10.1016/j.physrep.2012.03.001 · Cited by 2,736
“In a paper on measuring concurrency (the temporal overlap of partnerships) Morris and Kretschzmar [109] used the parameter values: N = 2000, ρ = 0.01/day, σ = 0.001/day and η = 0.1/day.”
MethodInfluentialIntroduction to stochastic actor-based models for network dynamics
Snijders, T. A. B., van de Bunt, G. G., & Steglich, C. E. G. (2010) · Social Networks · doi:10.1016/j.socnet.2009.02.004 · Cited by 2,103
Statistical physics of vaccination
Wang, Z., Bauch, C. T., Bhattacharyya, S., d'Onofrio, A., Manfredi, P., Perc, M., Perra, N., Salathé, M., & Zhao, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.10.006 · Cited by 872
A Survey of Statistical Network Models
Goldenberg, A., Zheng, A. X., Fienberg, S. E., & Airoldi, E. M. (2010) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000005 · Cited by 819
Chains of affection: the structure of adolescent romantic and sexual networks
Bearman, P. S., Moody, J., & Stovel, K. (2004) · American Journal of Sociology · doi:10.1086/386272 · Cited by 817
Metadata
- Authors
- Morris, M., & Kretzschmar, M.
- Venue
- Social Networks
- Publisher
- Elsevier BV
- Published
- 1995-07
- Volume
- 17
- Issue
- 3-4
- Pages
- 299-318
- ISSN
- 0378-8733 (ISSN-L)
- OpenAlex
- W2037513907
- Cited by
- 312
- References
- 0
- FWCI
- 5.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Concurrent partnerships and transmission dynamics in networks. https://app.cochat.ai/papers/10.1016/0378-8733(95)00268-s
- The paper
- Morris, M., & Kretzschmar, M. (1995). Concurrent partnerships and transmission dynamics in networks. Social Networks. https://doi.org/10.1016/0378-8733(95)00268-s
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.