Applying a novel approach to scoping review incorporating artificial intelligence: mapping the natural history of gonorrhoea

A Qualitative Concept Elicitation Study to Understand Patient-Reported Symptoms and Impacts of Neisseria gonorrhoeae Infections in the United States

BACKGROUND

Gonorrhea is the second most common bacterial sexually transmitted infection in the United States, with rising rates. Emerging antimicrobial resistance threatens public health, and vaccines are in development. This study documents patient-reported gonorrhea symptoms and health-related quality-of-life (HRQoL) impact in women who have sex with men (WSM), men who have sex with women (MSW), and men who have sex with men (MSM).

METHODS

Semistructured qualitative interviews were conducted (April 2021-March 2022) among US adults with recent (≤6 months) confirmed gonorrhea. Concept saturation was achieved, confirming adequate participant numbers to meet objectives. Elicited symptom and HRQoL impacts were used to develop a conceptual disease model. Common patient-reported outcome measure (PROM) items were compared with elicited concepts.

RESULTS

Thirty-two participants (15 WSM, 8 MSW, and 9 MSM) were included. Eight were asymptomatic, 6 had repeat infections, and 5 women and 4 men had complications (i.e., infertility or pelvic inflammatory disease, and urethritis, respectively).The most frequently reported symptoms were vaginal discharge (n = 11 of 12), dysuria (n = 10 of 12), and abdominal/vaginal pain (n = 9 of 12) for symptomatic WSM; dysuria (n = 5 of 6) and penile discharge (n = 4 of 6) for symptomatic MSW; and throat, testicular, or rectal pain (n = 4 of 6) for symptomatic MSM. All (symptomatic and asymptomatic) participants reported HRQoL impacts including negative emotional experiences (n = 31 of 32), and interference with sexual activity (n = 30 of 32), relationships (n = 24 of 32), and social life (n = 17 of 32). Concepts were poorly represented in existing PROMs.

CONCLUSIONS

Participants reported a diverse range of symptoms and HRQoL impacts, to help inform the value of new treatment and prevention options. More research is needed to quantify patient burden and develop PROMs.

Interruption time series analysis using autoregressive integrated moving average model: evaluating the impact of COVID-19 on the epidemic trend of gonorrhea in China

BACKGROUND

Interrupted time series (ITS) analysis is a growing method for assessing intervention impacts on diseases. However, it remains unstudied how the COVID-19 outbreak impacts gonorrhea. This study aimed to evaluate the effect of COVID-19 on gonorrhea and predict gonorrhea epidemics using the ITS-autoregressive integrated moving average (ARIMA) model.

METHODS

The number of gonorrhea cases reported in China from January 2005 to September 2022 was collected. Statistical descriptions were applied to indicate the overall epidemiological characteristics of the data, and then the ITS-ARIMA was established. Additionally, we compared the forecasting abilities of ITS-ARIMA with Bayesian structural time series (BSTS), and discussed the model selection process, transfer function, check model fitting, and interpretation of results.

RESULT

During 2005-2022, the total cases of gonorrhea were 2,165,048, with an annual average incidence rate of 8.99 per 100,000 people. The highest incidence rate was 14.2 per 100,000 people in 2005 and the lowest was 6.9 per 100,000 people in 2012. The optimal model was ARIMA (0,1, (1,3)) (0,1,1)12 (Akaike's information criterion = 3293.93). When predicting the gonorrhea incidence, the mean absolute percentage error under the ARIMA (16.45%) was smaller than that under the BSTS (22.48%). The study found a 62.4% reduction in gonorrhea during the first-level response, a 46.47% reduction during the second-level response, and an increase of 3.6% during the third-level response. The final model estimated a step change of - 2171 (95% confidence interval [CI] - 3698 to - 644) cases and an impulse change of - 1359 (95% CI - 2381 to - 338) cases. Using the ITS-ARIMA to evaluate the effect of COVID-19 on gonorrhea, the gonorrhea incidence showed a temporary decline before rebounding to pre-COVID-19 levels in China.

CONCLUSION

ITS analysis is a valuable tool for gauging intervention effectiveness, providing flexibility in modelling various impacts. The ITS-ARIMA model can adeptly explain potential trends, autocorrelation, and seasonality. Gonorrhea, marked by periodicity and seasonality, exhibited a downward trend under the influence of COVID-19 intervention. The ITS-ARIMA outperformed the BSTS, offering superior predictive capabilities for the gonorrhea incidence trend in China.