Updating STI Incidence Target Statistics for Model

[smjenness]

Just porting over a conversation from Slack to here for future reference.

From @laurammann:

I have been looking into current estimates of the incidence of gonorrhea and chlamydia among US MSM for calibration of our model. Previous models such as Sam’s 2017 model published in CID [1] used true GC and CT incidence of 4.2 and 6.6 per 100 PYAR, respectively, however these estimates are from cohorts from the pre-PrEP era [2]. Alternatively, CDC's SSuN data could be used. SSuN is a surveillance system that collects data from in 18 STD clinics in 9 jurisdictions [3]. SSuN is problematic though as it only collects data on MSM who present to STD clinics and opt for testing (is symptoms-driven). It also only provides positivity data; the 2018 data are in the attached Excel file.

From @smjenness:

One option might be to take the earlier Kojima estimates and multiply them by a factor equal to the ratio of case diagnoses currently versus around that period. For example, since NG/CT (diagnosed) cases have increased upwards of X-fold (need to find this specific number for MSM, by STI if possible from CDC surveillance reports) since 2010, we might assume that screening rates have been relatively stable and that the excess in diagnosed cases is attributable to increased (true) incidence. Therefore, we could estimate true incidence based on Kojima times X. Thoughts?

[smjenness]

Following conversation with @laurammann today, one approach may be to use both SSuN (which are stratified by MSM) and STD case surveillance data (which are not stratified by MSM) to triangulate the relative changes in true incidence over the past decade. SSuN may overestimate that change (because it is a selected population of STD clinic attendees) but case surveillance data may understand that change (because the relative increase is likely higher in MSM than in all males). @laurammann: you could either triangulate the two estimates, or take the ratio of change in MSM:change in all males from SSuN and then apply that ratio to the change in case surveillance for males. And then take that and multiply against Kojima!?

[laurammann]

So I have been looking at the available CDC surveillance data and unfortunately CDC does not present SSuN data for all males (for either GC or CT), nor does it present annual CT SSuN rate estimates (I found GC SSuN rate estimates for MSM, however). SSuN GC/CT positivity for recent years is reported, but it is not reported for older years (only GC/CT prevalence is reported).

I did find (1.) annual estimates of SSuN GC rates for MSM, and (2.) the annual number of GC and CT cases for all men in the US. Comparing 2010 and 2017/2018 estimates, gonorrhea has likely increased among MSM between the pre-PrEP era and the PrEP era by a factor of 2.27–3.83 (lower bound is among all men, upper bound is among MSM attending SSuN clinics). Chlamydia has likely increased among MSM between the pre-PrEP era and the PrEP era by at least a factor of 1.64 (lower bound only representing all men). Applying these estimates to the Kojima estimates, the updated true gonorrhea estimate may range from 9.538–16.068 per 100 PYAR and the updated true chlamydia estimate is likely at least 10.82 per 100 PYAR. The details of this estimation are in the attached document: GC and CT Estimation.docx

[laurammann]

Here are the final estimates.

Gonorrhea calculation: (3.05)*(4.2 per 100 PYAR)=12.81 per 100 PYAR

Chlamydia calculation: (3.83/2.27) (1.64) = 2.77 (upper bound) ⇒ (2.21)(6.6 per 100 PYAR)=14.59 per 100 PYAR

[smjenness]

Thanks @laurammann : could you write up a paragraph on this full calculation, bottom to top, that we can use in the paper. You can paste it in this issue here.

[laurammann]

See below, and let me know if you have any suggested revisions.

We estimated the incidence of gonorrhea and chlamydia to be 12.81 and 14.59 per 100 PYAR, respectively. These estimates were generated by updating pre-PrEP era estimates [1] using publically available CDC STI surveillance data [2,3,4]. During 2010–2018, the number of diagnosed gonorrheal and chlamydial infections among all US men increased by a factor of 2.27 and 1.64, respectively [2]. During 2010–2017, the number of diagnosed gonorrheal infections among MSM attending CDC’s STD Surveillance Network (SSuN) clinics increased by a factor of 3.83 [3,4]. Because the increase in STI incidence among all men is likely lower than among MSM only [3], and because SSuN represents only a select population that may have higher incidence of STIs [5], we assumed that all US men represented the lower bound of the increase in infections and SSuN MSM represented the upper bound of infection increase. Data on the annual chlamydia prevalence of SSuN MSM were not available, however we expect that the range of the true increase in chlamydia among MSM during this time is similar to that of gonorrhea. Therefore, we estimated the upper bound for the increase in chlamydia by multiplying the ratio of the gonorrhea bounds with the lower bound for chlamydia. We then averaged the factor bounds for each STI, and applied these averages to the pre-PrEP estimates to determine the updated incidences of each STI.

Referenced sources:

1. Kojima N, Davey DJ, Klausner JD. Pre-exposure prophylaxis for HIV infection and new sexually transmitted infections among men who have sex with men. AIDS. 2016 Sep 10;30(14):2251-2.
2. Centers for Disease Control and Prevention. NCHHSTP AtlasPlus. Updated 2019. https://www.cdc.gov/nchhstp/atlas/index.htm. Accessed on July 30, 2020.
3. Stenger MR, Pathela P, Anschuetz G, Bauer H, Simon J, Kohn R, Schumacher C, Torrone E. Increases in the rate of Neisseria gonorrhoeae among gay, bisexual and other men who have sex with men—findings from the Sexually Transmitted Disease Surveillance Network 2010–2015. Sexually transmitted diseases. 2017 Jul;44(7):393.
4. Centers for Disease Control and Prevention. Sexually Transmitted Disease Surveillance 2017. Atlanta: U.S. Department of Health and Human Services; 2018.
5. Celum CL, Bolan G, Krone M, Code K, Leone P, Spaulding C, Henry K, Clarke P, Smith M, HOOK III EW. Patients attending STD clinics in an evolving health care environment: demographics, insurance coverage, preferences for STD services, and STD morbidity. Sexually transmitted diseases. 1997 Nov 1;24(10):599-605.