In the United States, the rate of reported gonorrhea among men has increased steadily in recent years. Over 322,000 cases of gonorrhea were reported among men in 2017, an increase of 86% since 2013.1 Information on gender of sex partners for reported gonorrhea cases are not routinely reported to CDC,2 as many cases are not able to be investigated locally given the large burden of disease. Data from enhanced surveillance conducted in select jurisdictions suggest that a substantial proportion of gonorrhea cases occur among gay, bisexual, and other men who have sex with men (collectively referred to as MSM) and that the rates of reported gonorrhea among MSM are increasing.1,3
Interpreting trends in rates of reported cases of gonorrhea is difficult as infections, particularly extragenital infections, are often asymptomatic and increased screening coverage will result in increased case detection. To inform interpretation of gonorrhea case rates among MSM nationally, we estimated the number of tests needed to identify the estimated number of reported gonorrhea cases among MSM in a given year. We then compared estimated testing rates among MSM during 2016 to 2017.
We reviewed published and unpublished data from national and sentinel sources on gonococcal infection among men in the United States, including national gonorrhea (GC) case report data from the National Notifiable Disease Surveillance System,1 enhanced surveillance data from select jurisdictions participating in the STD Surveillance Network (SSuN, https://www.cdc.gov/std/ssun/default.htm), and published estimates of gonorrhea positivity in various clinical settings.4,5
To estimate the number of gonorrhea tests conducted among MSM, we assumed that all positive tests were reported as cases and that the following relationship exists between reported cases, testing, and test positivity:
To estimate the number of tests that would have had to occur among MSM to result in the estimated number of cases among MSM in a given year, we divided the number of estimated cases among MSM by estimated test positivity among MSM6:
As national estimates of the number of reported cases of gonorrhea that occurred among MSM ages 18 years and older are not available, we assumed the distribution of cases by sex and sex of sex partners in participating SSuN jurisdictions was representative of the distribution in all jurisdictions. We used the following equation to estimate the number of reported cases among MSM nationally for 2016 and 2017 (inputs reported in the Results and in supplemental material):
As national gonorrhea positivity among MSM is not available, we selected positivity estimates informed by published literature, including test positivity among MSM tested in STD clinics4 and rectal test results among men available from a national laboratory database.5 Although the laboratory database does not include information on sex of sex partners, we inferred that men with a rectal test were MSM since the CDC recommends rectal testing for those who have had receptive anal sex.7
Figure 1 visualizes the relationship between positivity and testing rates. We used the number estimated gonorrhea cases among MSM in 2017 and varied the positivity to estimate testing rates per 1,000 MSM using the following formula:
To identify possible changes in testing rates among MSM during 2016 to 2017, we calculated the estimated number of tests under both low positivity (3.5%) and high positivity (10%) for each year, as well as the estimated number of tests if positivity was changing or stable during 2016 to 2017. For this demonstration, the lower positivity of 3.5% was chosen because this positivity results in a testing rate of approximately 1,000 tests per 1,000 MSM (ie, at a 3.5% positivity every MSM would have 1 testing event each year to result in the observed case rate in 2016). The higher 10% positivity estimate approximates higher end findings on MSM positivity from published literature.4,5 If multiple anatomic sites test positive during a clinic visit, only one case is captured in the surveillance data. For this reason, multiple samples collected at the same time are considered one testing event.
Finally, to facilitate comparison in estimated test volume between years and account for any changes in the number of MSM in the population, we estimated the number of MSM nationally each year by applying published estimates of the proportion of men who are MSM (3.9%)8 to estimates of the number of men 18 years or older in the United States each year (121,620,398 in 2016 and 122,786,349 in 2017).9 We calculated the estimated testing rate as the number of gonorrhea tests among MSM per 1,000 MSM.
During 2016 to 2017, the number of gonorrhea cases among adult men increased 19.9% from 258,761 to 310,371 cases. In jurisdictions participating in SSuN, 63.2% (95% confidence interval, 60.8–65.5%) of male gonorrhea cases were estimated to be among MSM in 2016, similar to the estimated proportion in 2017 (62.1% [95% confidence interval, 59.8–64.3%]). Assuming a similar distribution nationally for each year, we estimated that 163,537 reported gonorrhea cases occurred among MSM in 2016 and increased by 17.9% to 192,740 cases in 2017 (Table S1, https://links.lww.com/OLQ/A384).
Figure 1 shows combinations of positivity and testing rates that would be consistent with the estimated number of MSM cases in 2017. For example, with 192,740 gonorrhea cases among MSM, a 5% positivity would imply a testing rate of approximately 800 tests per 1,000 MSM, and a 10% positivity would imply a testing rate of approximately 400 tests per 1,000 MSM.
Figure 2 shows how the number of tests in MSM might change during 2016 to 2017 under stable and changing positivity. Assuming no change in positivity, under a low positivity (3.5%), we estimated that 5.5 million tests would have needed to be performed among MSM in 2017, an increase of 830,000 tests from 2016; under a high positivity (10%), we estimated 1.9 million tests would have needed to be performed, an increase of 290,000 tests from 2016. If there were decreases in positivity, even more tests would be required under both low and high positivity. For example, if there was a 1 percentage point absolute decrease in positivity (eg, 10% to 9%), 220,000 more tests would be needed to detect the same number cases. Conversely, if positivity increased, fewer tests would be needed to detect the same number of cases.
Table S1, https://links.lww.com/OLQ/A384 presents the results of stable positivity from 2016 to 2017, and both a 20% increase and a 20% decrease in positivity in the low and high positivity scenarios. In most scenarios, the estimated testing rate among MSM increased (17% to 46%); the one exception was in the low positivity scenario with a 20% increase in positivity where the testing rate decreased by 2.7%. Further, Figure S1, https://links.lww.com/OLQ/A385 graphs the relationship between changing positivity and changes in the number of tests from 2016 to 2017.
We estimated that the number of reported gonorrhea cases that occurred among adult MSM nationally increased 18% during 2016 to 2017. Under a range of positivity assumptions, the number of tests among MSM increased in most scenarios.
There are a number of reasons testing may be increasing among MSM. First, incidence may be increasing, resulting in more men presenting with symptomatic infection. Second, screening MSM for asymptomatic infection may be increasing. Currently, CDC recommends that all MSM be screened for gonorrhea at all exposed anatomic sites annually, and more frequently if at high risk.7 And while not cleared by the FDA, there is increasing availability of extragenital testing using highly sensitivity nucleic acid amplification tests which has likely led to increased case detection among MSM.
At the national level, the Affordable Care Act increased insurance rates and decreased out of pocket costs for many preventive services, including some sexually transmitted infection testing.10 Both of these policies improved access to preventive care and may have led more MSM, both symptomatic and asymptomatic, to seek out testing and treatment for sexually transmitted infections, including gonorrhea.11 Insurance status has also been positively associated with the use of preexposure prophylaxis (PrEP).12 During 2012 to 2016, the number of PrEP users increased by 8.8-fold,13 and recommendations for at least biannual STD screening while on PrEP have likely lead to more frequent screening among MSM.
This analysis has several limitations. First, we focus on MSM and omit similar analyses for other subpopulations. Second, the proportion of gonorrhea cases attributable to MSM nationally may be lower than in jurisdictions participating in SSuN, which are biased toward urban areas on the East and West coasts that may have higher morbidity among MSM and have a higher proportion of the male population who are MSM than prevails nationally. If this is true, the national number of reported cases among MSM is an overestimate, and in turn, the number of MSM tested is also overestimated. However, the change in the number of estimated tests between years would be minimally affected. Next, national test positivity among all MSM is unknown. We assumed a range of estimates based on published literature; however, estimates of positivity can be affected by changes in the risk profile of population being tested/screened. For example, if MSM on PrEP are tested more frequently and have a higher likelihood of being infected with a STD due to changes in behavior (eg, decreased condom use), then an increase in test positivity would not necessarily indicate an increase in prevalent cases within the MSM population. Further, we cannot differentiate between changes in positivity resulting from an increase in incidence and changes resulting from new extragenital testing technologies and practices. Finally, given the uncertainty surrounding positivity, our estimates of changes in the number of tests have large ranges.
Under reasonable assumptions about baseline positivity and year to year changes in positivity (≤20% increases or decreases), we show that some increase in testing is likely occurring. While there are many reasons why testing might be increasing, it is unlikely that testing is increasing fast enough to account for the increases in diagnosed cases of gonorrhea among MSM if positivity is not also increasing. Therefore, observed increases in rates of reported gonorrhea among MSM are likely a result of both increased screening and increased incidence. We provide a framework to inform trends in case rates by analyzing the impact of changes in positivity and testing over time. Enhanced data on MSM testing behavior and trends could improve the accuracy of testing estimates and would allow researchers and public health to better interpret and respond to changes in reported rates of gonorrhea.
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