Characterization of Streptococcus pneumoniae isolates obtained from the middle ear fluid of US children, 2011-2021.

Introduction: Pneumococcal conjugate vaccines (PCVs), including higher valency vaccines such as PCV20, have the potential to reduce pediatric otitis media. We assessed serotype distribution, potential PCV coverage, and antimicrobial susceptibility of Streptococcus pneumoniae isolates cultured from middle ear fluid (MEF) of US children age ≤5 years. Methods: S. pneumoniae isolates identified from US hospitals participating in the SENTRY Antimicrobial Surveillance program from 2011 to 2021 were included. Serotypes were determined by in silico analysis based on Pneumococcal Capsular Typing methodology. The percentage of isolates belonging to serotypes included in PCV13 (serotypes 1, 3, 4, 5, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, 23F), PCV15 (PCV13 plus 22F, 33F), and PCV20 (PCV13 plus, 8, 10A, 11A, 12F, 15B, 22F and 33F) was calculated. Antimicrobial susceptibility testing was performed by broth microdilution and interpreted using CLSI criteria. Nonsusceptibility was defined as isolates that were intermediate or resistant to a selected antimicrobial. Results: Among the 199 S. pneumoniae isolates that were identified, 56.8% were from children age <2 years. Six serotypes accounted for around 60% of isolates: 35B (16.6%), 15B (14.6%), 15A (7.5%), 19A (7.5%), 19F (7.5%), and 3 (7.0%). Serotypes included in PCV13, PCV15, and PCV20 accounted for 23.1%, 30.2%, and 54.8% of isolates, respectively. Overall, 45.2% of isolates were penicillin non-susceptible, and 13.6% were MDR, of which 48% were serotype 19A. Seven serotypes (19A, 15A, 15B, 15C, 23A, 33F, and 35B) accounted for the majority of non-susceptible isolates. Discussion: PCVs, particularly PCV20, may prevent a substantial fraction of S. pneumoniae otitis media (OM), including OM due to non-susceptible serotypes. The addition of serotypes 15A, 23A, and 35B would improve coverage against susceptible and non-susceptible pneumococcal OM.

Correction: Estimating the Size of Key Populations in Kampala, Uganda: 3-Source Capture-Recapture Study.

[This corrects the article DOI: 10.2196/12118.].

Capture-Recapture Among Men Who Have Sex With Men and Among Female Sex Workers in 11 Towns in Uganda.

BACKGROUND: Key populations at higher risk for HIV infection, including people who inject drugs, men who have sex with men (MSM), and female sex workers (FSWs), are disproportionately affected by the HIV/AIDS epidemic. Empirical estimates of their population sizes are necessary for HIV program planning and monitoring. Such estimates, however, are lacking for most of Uganda's urban centers. OBJECTIVE: The aim of this study was to estimate the number of FSWs and MSM in select locations in Uganda. METHODS: We utilized conventional 2-source capture-recapture (CRC) to estimate the population of FSWs in Mbale, Jinja, Wakiso, Mbarara, Gulu, Kabarole, Busia, Tororo, Masaka, and Kabale and the population of MSM in Mbale, Jinja, Wakiso, Mbarara, Gulu, Kabarole, and Mukono from June to August 2017. Hand mirrors and key chains were distributed to FSWs and MSM, respectively, by peers during capture 1. A week later, different FSWs and MSM distributors went to the same towns to collect data for the second capture. Population size estimates and 95% CIs were calculated using the CRC Simple Interactive Statistical Analysis. RESULTS: We estimated the population of FSWs and MSM using 2 different recapture definitions: those who could present the object or identify the object from a set of photos. The most credible (closer to global estimates of MSM; 3%-5%) estimates came from those who presented the objects only. The FSW population in Mbale was estimated to be 693 (95% CI 474-912). For Jinja, Mukono, Busia, and Tororo, we estimated the number of FSWs to be 802 (95% CI 534-1069), 322 (95% CI 300-343), 961 (95% CI 592-1330), and 2872 (95% CI 0-6005), respectively. For Masaka, Mbarara, Kabale, and Wakiso, we estimated the FSWs population to be 512 (95% CI 384-639), 1904 (95% CI 1058-2749), 377 (95% CI 247-506), and 828 (95% CI 502-1152), respectively. For Kabarole and Gulu, we estimated the FSWs population to be 397 (95% CI 325-469) and 1425 (95% CI 893-1958), respectively. MSM estimates were 381 (95% CI 299-462) for Mbale, 1100 (95% CI 351-1849) for Jinja, 368 (95% CI 281-455) for Wakiso, 322 (95% CI 253-390) for Mbarara, 180 (95% CI 170-189) for Gulu, 335 (95% CI 258-412) for Kabarole, and 264 (95% CI 228-301) for Mukono. CONCLUSIONS: The CRC activity was one of the first to be carried out in Uganda to obtain small town-level population sizes for FSWs and MSM. We found that it is feasible to use FSW and MSM peers for this activity, but proper training and standardized data collection tools are essential to minimize bias.

Estimating the Size of Key Populations in Kampala, Uganda: 3-Source Capture-Recapture Study.

BACKGROUND: Key populations, including people who inject drugs (PWID), men who have sex with men (MSM), and female sex workers (FSW), are disproportionately affected by the HIV epidemic. Understanding the magnitude of, and informing the public health response to, the HIV epidemic among these populations requires accurate size estimates. However, low social visibility poses challenges to these efforts. OBJECTIVE: The objective of this study was to derive population size estimates of PWID, MSM, and FSW in Kampala using capture-recapture. METHODS: Between June and October 2017, unique objects were distributed to the PWID, MSM, and FSW populations in Kampala. PWID, MSM, and FSW were each sampled during 3 independent captures; unique objects were offered in captures 1 and 2. PWID, MSM, and FSW sampled during captures 2 and 3 were asked if they had received either or both of the distributed objects. All captures were completed 1 week apart. The numbers of PWID, MSM, and FSW receiving one or both objects were determined. Population size estimates were derived using the Lincoln-Petersen method for 2-source capture-recapture (PWID) and Bayesian nonparametric latent-class model for 3-source capture-recapture (MSM and FSW). RESULTS: We sampled 467 PWID in capture 1 and 450 in capture 2; a total of 54 PWID were captured in both. We sampled 542, 574, and 598 MSM in captures 1, 2, and 3, respectively. There were 70 recaptures between captures 1 and 2, 103 recaptures between captures 2 and 3, and 155 recaptures between captures 1 and 3. There were 57 MSM captured in all 3 captures. We sampled 962, 965, and 1417 FSW in captures 1, 2, and 3, respectively. There were 316 recaptures between captures 1 and 2, 214 recaptures between captures 2 and 3, and 235 recaptures between captures 1 and 3. There were 109 FSW captured in all 3 rounds. The estimated number of PWID was 3892 (3090-5126), the estimated number of MSM was 14,019 (95% credible interval (CI) 4995-40,949), and the estimated number of FSW was 8848 (95% CI 6337-17,470). CONCLUSIONS: Our population size estimates for PWID, MSM, and FSW in Kampala provide critical population denominator data to inform HIV prevention and treatment programs. The 3-source capture-recapture is a feasible method to advance key population size estimation.