Tracking diarrhea viruses and mpox virus using the wastewater surveillance network in Hong Kong.

The wastewater surveillance network successfully established for COVID-19 showed great potential to monitor other infectious viruses, such as norovirus, rotavirus and mpox virus. In this study, we established and validated detection methods for these viruses in wastewater. We developed a supernatant-based method to detect RNA viruses from wastewater samples and applied it to the monthly diarrhea viruses (norovirus genogroup I & II, and rotavirus) surveillance in wastewater treatment plants (WWTPs) at a city-wide level for 16 months. Significant correlations were observed between the diarrhea viruses concentrations in wastewater and detection rates in faecal specimens by clinical surveillance. The highest norovirus concentration in wastewater was obtained in winter, consistent with the seasonal pattern of norovirus outbreak in Hong Kong. Additionally, we established a pellet-based method to monitor DNA viruses in wastewater and detected weak signals for mpox virus in wastewater from a WWTP serving approximately 16,700 people, when the first mpox patient in Hong Kong was admitted to the hospital within the catchment area. Genomic sequencing provided confirmatory evidence for the validity of the results. Our findings emphasized the efficacy of the wastewater surveillance network in WWTPs as a cost-effective tool to track the transmission trend of diarrhea viruses and to provide sensitive detection of novel emerging viruses such as mpox virus in low-prevalence areas. The developed methods and surveillance results provide confidence for establishing robust wastewater surveillance programs to control infectious diseases in the post-pandemic era.

Robust expansion of phylogeny for fast-growing genome sequence data.

Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ancestral sequences. It took about 21 seconds to insert 100 SARS-CoV-2 genomes into a 100k-taxa reference tree using 1.4 gigabytes. Benchmarking on four datasets, TIPars achieved the highest accuracy for phylogenies of moderately similar sequences. For highly similar and divergent scenarios, fully parsimony-based and likelihood-based phylogenetic placement methods performed the best respectively while TIPars was the second best. TIPars accomplished efficient and accurate expansion of phylogenies of both similar and divergent sequences, which would have broad biological applications beyond SARS-CoV-2. TIPars is accessible from https://tipars.hku.hk/ and source codes are available at https://github.com/id-bioinfo/TIPars.

Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study.

BACKGROUND: Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures. OBJECTIVE: This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses. METHODS: We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020. RESULTS: The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong. CONCLUSIONS: Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

Serological assays for differentiating natural COVID-19 infection from vaccine induced immunity.

BACKGROUND: Natural SARS-CoV-2 infection may elicit antibodies to a range of viral proteins including non-structural protein ORF8. RNA, adenovirus vectored and sub-unit vaccines expressing SARS-CoV-2 spike would be only expected to elicit S-antibodies and antibodies to distinct domains of nucleocapsid (N) protein may reliably differentiate infection from vaccine-elicited antibody. However, inactivated whole virus vaccines may potentially elicit antibody to wider range of viral proteins, including N protein. We hypothesized that antibody to ORF8 protein will discriminate natural infection from vaccination irrespective of vaccine type. METHODS: We optimized and validated the anti-ORF8 and anti-N C-terminal domain (NCTD) ELISA assays using sera from pre-pandemic, RT-PCR confirmed natural infection sera and BNT162b2 (BNT) or CoronaVac vaccinees. We then applied these optimized assays to a cohort of blood donor sera collected in April-July 2022 with known vaccination and self-reported infection status. RESULTS: We optimized cut-off values for the anti-ORF8 and anti-N-CTD IgG ELISA assays using receiver-operating-characteristic (ROC) curves. The sensitivity of the anti-ORF8 and anti-N-CTD ELISA for detecting past infection was 83.2% and 99.3%, respectively. Specificity of anti-ORF8 ELISA was 96.8 % vs. the pre-pandemic cohort or 93% considering the pre-pandemic and vaccine cohorts together. The anti-N-CTD ELISA specificity of 98.9% in the pre-pandemic cohort, 93% in BNT vaccinated and only 4 % in CoronaVac vaccinated cohorts. Anti-N-CTD antibody was longer-lived than anti-ORF8 antibody after natural infection. CONCLUSIONS: Anti-N-CTD antibody assays provide good discrimination between natural infection and vaccination in BNT162b2 vaccinated individuals. Anti-ORF8 antibody can help discriminate infection from vaccination in either type of vaccine and help estimate infection attack rates (IAR) in communities.

Cervical screening among Chinese females in the era of HPV vaccination: a population-based survey on screening uptake and regular screening following an 18-year organized screening program.

OBJECTIVE: China has a substantial disease burden of cervical cancer. To further understand preventive measures for reducing cervical cancer in China, this study aimed to correlate screening attendance and regular screening with human papillomavirus (HPV) vaccination among Chinese females. METHODS: This prospective questionnaire-based survey recruited Chinese females aged 25 or above in Hong Kong by random digit dialing telephone interviews in 2022. The survey studied women's practice of cervical screening and adherence to regular screening. Variables including HPV vaccination status and attendance of physical check-ups were involved in the questionnaire. Screening uptake and screening adherence were the main outcomes, which were measured as the proportion of women who reported having attended a cervical screening and screened regularly, respectively. RESULTS: Out of 906 valid respondents, the reported cervical screening uptake was over 70% among females aged 30 or above and particularly over 80% among women aged 35-59; however, the uptake was only 46% among those aged 25-29. Adherence to regular screening was 50%-60% across ages 25-59 years and dropped to approximately 40% for women older than 60 years. Both screening uptake and adherence were associated with HPV vaccination, with adjusted odds ratios of 2.37 and 2.23, respectively. A large proportion of regularly screened women may be overscreened for screening more frequently than recommended. CONCLUSION: Responded Chinese females showed good cervical screening uptake but were moderately adherent to regular screening. Policymakers should emphasize the importance of regular screening and the recommended screening frequency by HPV vaccination status for better healthcare resource use.

Avian Influenza A(H5N1) Neuraminidase Inhibition Antibodies in Healthy Adults after Exposure to Influenza A(H1N1)pdm09.

We detected high titers of cross-reactive neuraminidase inhibition antibodies to influenza A(H5N1) virus clade 2.3.4.4b in 96.8% (61/63) of serum samples from healthy adults in Hong Kong in 2020. In contrast, antibodies at low titers were detected in 42% (21/50) of serum samples collected in 2009. Influenza A(H1N1)pdm09 and A(H5N1) titers were correlated.

Optimal timing of nirmatrelvir/ritonavir treatment after COVID-19 symptom onset or diagnosis: target trial emulation.

Reports of symptomatic rebound and/or test re-positivity among COVID-19 patients following the standard five-day treatment course of nirmatrelvir/ritonavir have sparked debates regarding optimal treatment timing and dosage. It is unclear whether initiating nirmatrelvir/ritonavir immediately after symptom onset would improve clinical outcomes and/or lead to post-treatment viral burden rebound due to inadequate viral clearance during treatment. Here we show that, by emulating a randomized target trial using real-world electronic medical record data from all 87,070 adult users of nirmatrelvir/ritonavir in Hong Kong between 16th March 2022 and 15th January 2023, early initiation of nirmatrelvir/ritonavir treatment (0 to 1 days after symptom onset or diagnosis) significantly reduced the incidence of 28-day all-cause mortality and hospitalization compared to delayed initiation (2 or more days) (absolute risk reduction [ARR]: 1.50% (95% confidence interval 1.17-1.80%); relative risk [RR]: 0.77 (0.73, 0.82)), but may be associated with a significant elevated risk of viral burden rebound (ARR: -1.08% (-1.55%, -0.46%)), although the latter estimates were associated with high uncertainty due to limited sample sizes. As such, patients should continue to initiate nirmatrelvir/ritonavir early after symptom onset or diagnosis to better protect against the more serious outcomes of hospitalization and mortality.

COVID-19 Vaccination Willingness and Reasons for Vaccine Refusal.

Importance: Hong Kong was held as an exemplar for pandemic response until it recorded the world's highest daily COVID-19 mortality, which was likely due to vaccine refusal. To prevent this high mortality in future pandemics, information on underlying reasons for vaccine refusal is necessary. Objectives: To track the evolution of COVID-19 vaccination willingness and uptake from before vaccine rollout to mass vaccination, to examine factors associated with COVID-19 vaccine refusal and compare with data from Singapore, and to assess the population attributable fraction for vaccine refusal. Design, Setting, and Participants: This cohort study used data from randomly sampled participants from 14 waves of population-based studies in Hong Kong (February 2020 to May 2022) and 2 waves of population-based studies in Singapore (May 2020 to June 2021 and October 2021 to January 2022), and a population-wide registry of COVID-19 vaccination appointments. Data were analyzed from February 23, 2021, to May 30, 2022. Exposures: Trust in COVID-19 vaccine information sources (ie, health authorities, physicians, traditional media, and social media); COVID-19 vaccine confidence on effectiveness, safety, and importance; COVID-19 vaccine misconceptions on safety and high-risk groups; political views; and COVID-19 policies (ie, workplace vaccine mandates and vaccine pass). Main Outcomes and Measures: Primary outcomes were the weighted prevalence of COVID-19 vaccination willingness over the pandemic, adjusted incidence rate ratios, and population attributable fractions of COVID-19 vaccine refusal. A secondary outcome was change in daily COVID-19 vaccination appointments. Results: The study included 28 007 interviews from 20 waves of longitudinal data, with 1114 participants in the most recent wave (median [range] age, 54.2 years [20-92] years; 571 [51.3%] female). Four factors-mistrust in health authorities, low vaccine confidence, vaccine misconceptions, and political views-could jointly account for 82.2% (95% CI, 62.3%-100.0%) of vaccine refusal in adults aged 18 to 59 years and 69.3% (95% CI, 47.2%-91.4%) of vaccine refusal in adults aged 60 years and older. Workplace vaccine mandates were associated with 62.2% (95% CI, 9.9%-139.2%) increases in daily COVID-19 vaccination appointments, and the Hong Kong vaccine pass was associated with 124.8% (95% CI, 65.9%-204.6%) increases in daily COVID-19 vaccination appointments. Conclusions and Relevance: These findings suggest that trust in health authorities was fundamental to overcoming vaccine hesitancy. As such, engendering trust in health care professionals, experts, and public health agencies should be incorporated into pandemic preparedness and response.

Conversational AI and Vaccine Communication: Systematic Review of the Evidence.

BACKGROUND: Since the mid-2010s, use of conversational artificial intelligence (AI; chatbots) in health care has expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with health care providers during the COVID-19 pandemic. One emerging use for conversational AI is to capture evolving questions and communicate information about vaccines and vaccination. OBJECTIVE: The objective of this systematic review was to examine documented uses and evidence on the effectiveness of conversational AI for vaccine communication. METHODS: This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Web of Science, PsycINFO, MEDLINE, Scopus, CINAHL Complete, Cochrane Library, Embase, Epistemonikos, Global Health, Global Index Medicus, Academic Search Complete, and the University of London library database were searched for papers on the use of conversational AI for vaccine communication. The inclusion criteria were studies that included (1) documented instances of conversational AI being used for the purpose of vaccine communication and (2) evaluation data on the impact and effectiveness of the intervention. RESULTS: After duplicates were removed, the review identified 496 unique records, which were then screened by title and abstract, of which 38 were identified for full-text review. Seven fit the inclusion criteria and were assessed and summarized in the findings of this review. Overall, vaccine chatbots deployed to date have been relatively simple in their design and have mainly been used to provide factual information to users in response to their questions about vaccines. Additionally, chatbots have been used for vaccination scheduling, appointment reminders, debunking misinformation, and, in some cases, for vaccine counseling and persuasion. Available evidence suggests that chatbots can have a positive effect on vaccine attitudes; however, studies were typically exploratory in nature, and some lacked a control group or had very small sample sizes. CONCLUSIONS: The review found evidence of potential benefits from conversational AI for vaccine communication. Factors that may contribute to the effectiveness of vaccine chatbots include their ability to provide credible and personalized information in real time, the familiarity and accessibility of the chatbot platform, and the extent to which interactions with the chatbot feel "natural" to users. However, evaluations have focused on the short-term, direct effects of chatbots on their users. The potential longer-term and societal impacts of conversational AI have yet to be analyzed. In addition, existing studies do not adequately address how ethics apply in the field of conversational AI around vaccines. In a context where further digitalization of vaccine communication can be anticipated, additional high-quality research will be required across all these areas.

Development and application of influenza virus wastewater surveillance in Hong Kong.

Wastewater surveillance is considered as a powerful tool in providing cost-effective, population-wide and near real-time surveillance results for controlling infectious diseases (i.e., SARS-CoV-2, influenza virus), complementary to clinical surveillance. To facilitate the utility of this emerging tool, we developed two preanalytical protocols (supernatant-based and pellet-based) for influenza A/B virus (IAV/IBV) wastewater surveillance and applied them to the established wastewater surveillance network for large-scale longitudinal monitoring in Hong Kong. We tested 724 wastewater samples from 24 stationary sites for weekly surveillance for 8 months and 458 wastewater samples from 11 wastewater treatment plants (WWTPs) for more frequent (three times per week) city-wide surveillance for 4 months when influenza season commenced. We found the city-wide IAV virus concentration in wastewater were associated with the detection rate and influenza-like illness plus rates (ILI+) of clinical respiratory specimens and increased significantly after the cancelling of mask mandate that was in place for COVID-19. IBV was at low detection rates and low virus concentration levels, consistent with the low detection rates observed by clinical surveillance. In addition, we conducted virus subtype identification in selected wastewater samples, and observed the H1pdm was the major circulation subtype. Moreover, the obtained virus signals were confirmed by Sanger sequencing of PCR products, suggesting the feasibility and applicability of established methods for rapid detection of influenza virus types and subtypes in wastewater surveillance. This study demonstrates the applicability of IAV/IBV wastewater surveillance to current wastewater infrastructures and it could be used as a rapid and cost-effective surveillance strategy to track virus transmission patterns in the community for timely public health actions in the future.

Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Effectiveness of chatbots on COVID vaccine confidence and acceptance in Thailand, Hong Kong, and Singapore.

Chatbots have become an increasingly popular tool in the field of health services and communications. Despite chatbots' significance amid the COVID-19 pandemic, few studies have performed a rigorous evaluation of the effectiveness of chatbots in improving vaccine confidence and acceptance. In Thailand, Hong Kong, and Singapore, from February 11th to June 30th, 2022, we conducted multisite randomised controlled trials (RCT) on 2,045 adult guardians of children and seniors who were unvaccinated or had delayed vaccinations. After a week of using COVID-19 vaccine chatbots, the differences in vaccine confidence and acceptance were compared between the intervention and control groups. Compared to non-users, fewer chatbot users reported decreased confidence in vaccine effectiveness in the Thailand child group [Intervention: 4.3 % vs. Control: 17%, P = 0.023]. However, more chatbot users reported decreased vaccine acceptance [26% vs. 12%, P = 0.028] in Hong Kong child group and decreased vaccine confidence in safety [29% vs. 10%, P = 0.041] in Singapore child group. There was no statistically significant change in vaccine confidence or acceptance in the Hong Kong senior group. Employing the RE-AIM framework, process evaluation indicated strong acceptance and implementation support for vaccine chatbots from stakeholders, with high levels of sustainability and scalability. This multisite, parallel RCT study on vaccine chatbots found mixed success in improving vaccine confidence and acceptance among unvaccinated Asian subpopulations. Further studies that link chatbot usage and real-world vaccine uptake are needed to augment evidence for employing vaccine chatbots to advance vaccine confidence and acceptance.

Imprinted Anti-Hemagglutinin and Anti-Neuraminidase Antibody Responses after Childhood Infections of A(H1N1) and A(H1N1)pdm09 Influenza Viruses.

Immune imprinting is a driver known to shape the anti-hemagglutinin (HA) antibody landscape of individuals born within the same birth cohort. With the HA and neuraminidase (NA) proteins evolving at different rates under immune selection pressures, anti-HA and anti-NA antibody responses since childhood influenza virus infections have not been evaluated in parallel at the individual level. This is partly due to the limited knowledge of changes in NA antigenicity, as seasonal influenza vaccines have focused on generating neutralizing anti-HA antibodies against HA antigenic variants. Here, we systematically characterized the NA antigenic variants of seasonal A(H1N1) viruses from 1977 to 1991 and completed the antigenic profile of N1 NAs from 1977 to 2015. We identified that NA proteins of A/USSR/90/77, A/Singapore/06/86, and A/Texas/36/91 were antigenically distinct and mapped N386K as a key determinant of the NA antigenic change from A/USSR/90/77 to A/Singapore/06/86. With comprehensive panels of HA and NA antigenic variants of A(H1N1) and A(H1N1)pdm09 viruses, we determined hemagglutinin inhibition (HI) and neuraminidase inhibition (NI) antibodies from 130 subjects born between 1950 and 2015. Age-dependent imprinting was observed for both anti-HA and anti-NA antibodies, with the peak HI and NI titers predominantly detected from subjects at 4 to 12 years old during the year of initial virus isolation, except the age-independent anti-HA antibody response against A(H1N1)pdm09 viruses. More participants possessed antibodies that reacted to multiple antigenically distinct NA proteins than those with antibodies that reacted to multiple antigenically distinct HA proteins. Our results support the need to include NA proteins in seasonal influenza vaccine preparations. IMPORTANCE Seasonal influenza vaccines have aimed to generate neutralizing anti-HA antibodies for protection since licensure. More recently, anti-NA antibodies have been established as an additional correlate of protection. While HA and NA antigenic changes occurred discordantly, the anti-HA and anti-NA antibody profiles have rarely been analyzed in parallel at the individual level, due to the limited knowledge on NA antigenic changes. By characterizing NA antigenic changes of A(H1N1) viruses, we determined the anti-HA and anti-NA antibody landscape against antigenically distinct A(H1N1) and A(H1N1)pdm09 viruses using sera of 130 subjects born between 1950 and 2015. We observed age-dependent imprinting of both anti-HA and anti-NA antibodies against strains circulated during the first decade of life. A total of 67.7% (88/130) and 90% (117/130) of participants developed cross-reactive antibodies to multiple HA and NA antigens at titers ≥1:40. With slower NA antigenic changes and cross-reactive anti-NA antibody responses, including NA protein in influenza vaccine preparation may enhance vaccine efficacy.

Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong.

Hong Kong experienced a surge of Omicron BA.2 infections in early 2022, resulting in one of the highest per-capita death rates of COVID-19. The outbreak occurred in a dense population with low immunity towards natural SARS-CoV-2 infection, high vaccine hesitancy in vulnerable populations, comprehensive disease surveillance and the capacity for stringent public health and social measures (PHSMs). By analyzing genome sequences and epidemiological data, we reconstructed the epidemic trajectory of BA.2 wave and found that the initial BA.2 community transmission emerged from cross-infection within hotel quarantine. The rapid implementation of PHSMs suppressed early epidemic growth but the effective reproduction number (Re) increased again during the Spring festival in early February and remained around 1 until early April. Independent estimates of point prevalence and incidence using phylodynamics also showed extensive superspreading at this time, which likely contributed to the rapid expansion of the epidemic. Discordant inferences based on genomic and epidemiological data underscore the need for research to improve near real-time epidemic growth estimates by combining multiple disparate data sources to better inform outbreak response policy.

Maximizing the cost-effectiveness of cervical screening in the context of routine HPV vaccination by optimizing screening strategies with respect to vaccine uptake: a modeling analysis.

BACKGROUND: Regarding primary and secondary cervical cancer prevention, the World Health Organization proposed the cervical cancer elimination strategy that requires countries to achieve 90% uptake of human papillomavirus (HPV) vaccines and 70% screening uptake. The optimal cervical screening strategy is likely different for unvaccinated and vaccinated cohorts upon national HPV immunization. However, health authorities typically only provide a one-size-fits-all recommendation for the general population. We aimed to evaluate the cost-effectiveness for determining the optimal screening strategies for vaccinated and unvaccinated cohorts. METHODS: We considered the women population in Hong Kong which has a unique HPV infection and cervical cancer epidemiology compared to other regions in China and Asia. We used mathematical models which comprise a deterministic age-structured compartmental dynamic component and a stochastic individual-based cohort component to evaluate the cost-effectiveness of screening strategies for cervical screening. Following the recommendations in local guidelines in Hong Kong, we considered strategies that involved cytology, HPV testing, or co-testing as primary cervical screening. We also explored the impacts of adopting alternative de-intensified strategies for vaccinated cohorts. The 3-year cytology screening was used as the base comparator while no screening was also considered for vaccinated cohorts. Women's lifetime life years, quality-adjusted life years, and costs of screening and treatment were estimated from the societal perspective based on the year 2022 and were discounted by 3% annually. Incremental cost-effectiveness ratios (ICERs) were compared to a willingness to pay (WTP) threshold of one gross domestic product per capita (US $47,792). Probabilistic and one-way sensitivity analyses were conducted. RESULTS: Among unvaccinated cohorts, the strategy that adds reflex HPV to triage mild cytology abnormality generated more life years saved than cytology-only screening and could be a cost-effective alternative. Among vaccinated cohorts, when vaccine uptake was 85% (based on the uptake in 2022), all guideline-based strategies (including the cytology-only screening) had ICERs above the WTP threshold when compared with no screening if the vaccine-induced protection duration was 20 years or longer. Under the same conditions, HPV testing with genotyping triage had ICERs (compared with no screening) below the WTP threshold if the routine screening interval was lengthened to 10 and 15 years or screening was initiated at ages 30 and 35 years. CONCLUSIONS: HPV testing is a cost-effective alternative to cytology for vaccinated cohorts, and the associated optimal screening frequency depends on vaccine uptake. Health authorities should optimize screening recommendations by accounting for population vaccine uptake.

The Impacts of Computer-Aided Detection of Colorectal Polyps on Subsequent Colonoscopy Surveillance Intervals: Simulation Study.

BACKGROUND: Computer-aided detection (CADe) of colorectal polyps has been shown to increase adenoma detection rates, which would potentially shorten subsequent surveillance intervals. OBJECTIVE: The purpose of this study is to simulate the potential changes in subsequent colonoscopy surveillance intervals after the application of CADe in a large cohort of patients. METHODS: We simulated the projected increase in polyp and adenoma detection by universal CADe application in our patients who had undergone colonoscopy with complete endoscopic and histological findings between 2016 and 2020. The simulation was based on bootstrapping the published performance of CADe. The corresponding changes in surveillance intervals for each patient, as recommended by the US Multi-Society Task Force on Colorectal Cancer (USMSTF) or the European Society of Gastrointestinal Endoscopy (ESGE), were determined after the CADe was determined. RESULTS: A total of 3735 patients who had undergone colonoscopy were included. Based on the simulated CADe effect, the application of CADe would result in 19.1% (n=714) and 1.9% (n=71) of patients having shorter surveillance intervals, according to the USMSTF and ESGE guidelines, respectively. In particular, all (or 2.7% (n=101) of the total) patients who were originally scheduled to have 3-5 years of surveillance would have their surveillance intervals shortened to 3 years, following the USMSTF guidelines. The changes in this group of patients were largely attributed to an increase in the number of adenomas (n=75, 74%) rather than serrated lesions being detected. CONCLUSIONS: Widespread adoption of CADe would inevitably increase the demand for surveillance colonoscopies with the shortening of original surveillance intervals, particularly following the current USMSTF guideline.