Expedited Partner Therapy for Sexually Transmitted Diseases—Are We There Yet?

Kissinger, Patricia

doi:10.1097/olq.0000000000000207

Cited by 13 publications

(9 citation statements)

References 16 publications

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“…A sample of 616 people between ages

years old reside in Orleans Parish were asked about their number of concurrent partners ( Kissinger, 2014 ). This data (in agreement with other recent studies ( Colgate, Stanley, Hyman, Layne, & Qualls, 1989 )) show that the partner distribution often follows an inverse cubic power law,

, for

.…”

Section: Parameter Estimationmentioning

confidence: 99%

A risk-based model for predicting the impact of using condoms on the spread of sexually transmitted infections

Azizi

Rı́os-Soto

Mubayi

et al. 2017

Infectious Disease Modelling

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We create and analyze a mathematical model to estimate the impact of condom-use and sexual behavior on the prevalence and spread of Sexually Transmitted Infections (STIs). STIs remain a significant public health challenge globally with a high burden of some Sexually Transmitted Diseases (STDs) in both developed and undeveloped countries. Although condom-use is known to reduce the transmission of STIs, there are a few quantitated population-based studies on the protective role of condom-use in reducing the incidence of STIs. The number of concurrent partners is correlated with their risk of being infectious by a STI such as chlamydia, gonorrhea, or syphilis. We define a Susceptible-Infectious-Susceptible (SIS) model that distributes the population by the number of concurrent partners. The model captures the multi-level heterogeneous mixing through a combination of biased (preferential) and random mixing between individuals with different risks, and accounts for differences in condom-use in the low- and high-risk populations. We use sensitivity analysis to assess the relative impact of high-risk people using condom as a prophylactic to reduce their chance of being infectious, or infecting others. The model predicts the STI prevalence as a function of the number of partners that a person has, and quantifies how this distribution changes as a function of condom-use. Our results show that when the mixing is random, then increasing the condom-use in the high-risk population is more effective in reducing the prevalence than when many of the partners of high-risk people have high risk. The model quantified how the risk of being infected increases for people who have more partners, and and the need for high-risk people to consistently use condoms to reduce their risk of infection.

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“…A sample of 616 people between ages

, for

.…”

Section: Parameter Estimationmentioning

confidence: 99%

A risk-based model for predicting the impact of using condoms on the spread of sexually transmitted infections

Azizi

Rı́os-Soto

Mubayi

et al. 2017

Infectious Disease Modelling

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“…Methods that strengthen partner notification procedures have been found to contribute as much to chlamydia control as methods used to strengthen screening procedures, 34,35 as does EPT. [36][37][38] However, this would be only beneficial if CR cases are true reinfections rather than treatment failure or inadequacy. In addition, we will also evaluate screening coverage, which facilitate better understanding of the proportion and nature of individuals who are undergoing screening, their positivity rates, and the risk of CR.…”

Section: Discussionmentioning

confidence: 99%

Epidemiology and predictors of repeat positive chlamydia tests: The Brant County cohort, Ontario, Canada

Santos

Babayan

Hao

et al. 2019

Preprint

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Objectives: Repeat positive tests for chlamydia (CR) may help explain current high rates of chlamydia despite years of screening, partner notification and treatment to reduce sequelae. We wanted to determine the numbers of CRs over time as a proportion of all chlamydia cases, and define the differences in demographic, clinical, behavioural, and public health management indicators, between individuals who have experienced a CR and individuals who experienced a single infection in Brant County, Ontario. Methods: A retrospective cohort was developed using notifiable disease data extracted from the integrated public health system. Cases were laboratory confirmed chlamydia and gonorrhea infections in Brant County between January 1st, 2006 and December 31st, 2015. During the study period, 3,499 chlamydia cases and 475 gonorrhea cases were diagnosed. The total number of individuals with chlamydia in that period was 3,060, including 157 coinfections with gonorrhea. Differences between those with reinfection and those with single infection were evaluated using univariate and multivariate (Cox proportional hazards model) methods. Results: Four hundred and ninety-nine (16.30%) individuals experienced CR 28 days from initial infection; of which 328 (65.73%) occurred within 2 years and 211 (42.28%) within 1 year. The median time to CR was 276 days, consistent with existing Canadian literature. Independent risk factors for CR included being male, 25 years old or younger, and not receiving recommended treatment for initial and/or subsequent infection. Conclusions: These findings suggest that inadequate treatment play a significant role in CR, while accounting for young age and male gender, likely due to untreated sex partners.

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“…17,18 These EPT laws, which have been adopted in at least 35 states, are associated with an increase in such prescribing. [19][20][21] Nonepatient-specific prescriptions: Standing orders and protocol orders Standing medication orders, under which a prescriber authorizes the provision of medication to a person who meets predetermined criteria, are widely used in emergency medicine. 5 Although not typically used in the retail pharmacy context, 40 states have passed laws that permit naloxone to be dispensed via such nonepatient-specific (NPS) standing orders.…”

Section: Third-party Prescribingmentioning

confidence: 99%