Sex Differences in the Transmission, Prevention, and Disease Manifestations of Sexually Transmitted Diseases

Madkan, Vandana; Giancola, Angela A.; Karan, Kishalaya; Tyring, Stephen K.

doi:10.1001/archderm.142.3.365

Cited by 53 publications

(42 citation statements)

References 45 publications

(39 reference statements)

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“…This observed sex difference is not surprising given inherent immunologic and anatomical differences between males and females that are well known to result in differential susceptibility to most sexually transmitted infections. 42 Results of a study of genital warts among NHANES participants from 1999 to 2004 by Dinh et al indicate that "women were three times more likely to report having a history of genital warts than men," supporting our findings. 43 Moreover, seroprevalences of other genital HPVs have also been reported to be significantly higher in females compared to males.…”

Section: Discussionsupporting

confidence: 82%

Seroepidemiology of Human Papillomavirus Type 11 in the United States: Results From the Third National Health and Nutrition Examination Survey, 1991–1994

Hariri

Dunne²,

Sternberg³

et al. 2008

Sexually Transmitted Diseases

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Section: Discussionsupporting

confidence: 82%

Seroepidemiology of Human Papillomavirus Type 11 in the United States: Results From the Third National Health and Nutrition Examination Survey, 1991–1994

Hariri

Dunne²,

Sternberg³

et al. 2008

Sexually Transmitted Diseases

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“…Interestingly, sera from males infected with T. vaginalis were more reactive to anti-TvMIF antibodies than female-infected patient sera. This finding is particularly notable because women often have a more active immune system (55) and typically have greater risk for contraction and a heavier sexually transmitted infection burden due to their greater mucosal surface area (56). One hypothesis for this difference is that TvMIF is either produced or secreted by parasites to a greater extent in male patients due to potential involvement of TvMIF in parasite survival in the harsh environment of the penile urethra or prostate.…”

Section: Discussionmentioning

confidence: 99%

Trichomonas vaginalis homolog of macrophage migration inhibitory factor induces prostate cell growth, invasiveness, and inflammatory responses

Twu¹,

Dessì

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

153

138

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Significance Prostate cancer is the most common nonskin cancer in America and the fifth most common cancer worldwide. Inflammation is implicated in the initiation and progression of prostate cancer; however, sources of inflammation remain unidentified. Trichomonas vaginalis is a prevalent parasite that infects prostate epithelium and is associated with an increase in aggressive prostate cancer. Here, we demonstrate that a secreted T. vaginalis protein homologous to human macrophage migration inhibitory factor elicits antibodies in infected individuals, increases prostate cell proliferation and invasiveness, and induces cellular pathways linked to inflammation. This study demonstrates that a specific parasite-derived protein can mimic its human homolog to increase inflammation and cell proliferation, which, in turn, may result in the promotion and progression of prostate cancer.

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“…Typical examples include species differences in transmission of the foot and mouth pathogen (28) and polymorphism and recombinational hotspots in susceptibility to malaria (3). Sexual orientation, behavior, and partner choice impose heterogeneities in relation to sexually transmitted diseases (4,5) as do age (4,31) and sex (4,33) for a range of other diseases. Until now, it has been very difficult to parameterize models to take account of such heterogeneities, despite their implicit importance in the dissemination and control of disease, as for example in the recent outbreak of severe acute respiratory syndrome (29).…”

Section: Discussionmentioning

confidence: 99%

Estimation of multiple transmission rates for epidemics in heterogeneous populations

Cook

Otten

Marion

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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One of the principal challenges in epidemiological modeling is to parameterize models with realistic estimates for transmission rates in order to analyze strategies for control and to predict disease outcomes. Using a combination of replicated experiments, Bayesian statistical inference, and stochastic modeling, we introduce and illustrate a strategy to estimate transmission parameters for the spread of infection through a two-phase mosaic, comprising favorable and unfavorable hosts. We focus on epidemics with local dispersal and formulate a spatially explicit, stochastic set of transition probabilities using a percolation paradigm for a susceptibleinfected (S-I) epidemiological model. The S-I percolation model is further generalized to allow for multiple sources of infection including external inoculum and host-to-host infection. We fit the model using Bayesian inference and Markov chain Monte Carlo simulation to successive snapshots of damping-off disease spreading through replicated plant populations that differ in relative proportions of favorable and unfavorable hosts and with timevarying rates of transmission. Epidemiologically plausible parametric forms for these transmission rates are compared by using the deviance information criterion. Our results show that there are four transmission rates for a two-phase system, corresponding to each combination of infected donor and susceptible recipient. Knowing the number and magnitudes of the transmission rates allows the dominant pathways for transmission in a heterogeneous population to be identified. Finally, we show how failure to allow for multiple transmission rates can overestimate or underestimate the rate of spread of epidemics in heterogeneous environments, which could lead to marked failure or inefficiency of control strategies.Bayesian inference ͉ crop mixture ͉ susceptible-infected (S-I) epidemic ͉ spatially structured host populations ͉ Markov chain Monte Carlo O ne of the principal challenges in epidemiological modeling is to parameterize models with realistic estimates for transmission rates in order to analyze strategies for control and to predict disease outcomes. Although the durations of infectious and latent periods often can be estimated from observation of individuals challenged with inoculum, the probabilities and the associated rates for transmission of infection between infected and susceptible individuals are notoriously difficult to measure or estimate (1, 2). The problem is especially acute in spatially structured, heterogeneous host populations, in which hosts differ in susceptibility and infectivity. The magnitudes of the transmission rates typically change over space, according to the nature of the infected donor and the susceptible recipient, and also may change over time (2). In human diseases, infectivity and susceptibility may be affected by genetic, physiological, or social differences (3-5) as well as by immune and vaccination history. Examples also occur in animal epidemiology, with transmission of infection of a common path...

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Sex Differences in the Transmission, Prevention, and Disease Manifestations of Sexually Transmitted Diseases

Cited by 53 publications

References 45 publications

Seroepidemiology of Human Papillomavirus Type 11 in the United States: Results From the Third National Health and Nutrition Examination Survey, 1991–1994

Seroepidemiology of Human Papillomavirus Type 11 in the United States: Results From the Third National Health and Nutrition Examination Survey, 1991–1994

Trichomonas vaginalis homolog of macrophage migration inhibitory factor induces prostate cell growth, invasiveness, and inflammatory responses

Estimation of multiple transmission rates for epidemics in heterogeneous populations

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