Characterizing Gut Microbiota in Older Chinese Adults with Cognitive Impairment: A Cross-Sectional Study.

Background: Cognitive impairment is a clinical manifestation that occurs in the course of dementia like Alzheimer's disease. The association between cognitive impairment and gut microbiota is unclear. Objective: We aimed to identify gut microbiota characteristics and key gut microbiota biomarkers associated with cognitive impairment in a relatively large cohort of older adults in China. Methods: A total of 229 adults aged ≥60 years from Shenzhen, China were recruited into this cross-sectional study. Participants were divided into cognitive impairment (CI) and no cognitive impairment (NCI) groups according to the results of the Mini-Mental State Examination. Diversity analysis and network analysis were used to characterize the gut microbiota between the two groups. The linear discriminant analysis effect size method and machine learning approaches were sequentially performed to identify gut microbiota biomarkers. The relationship between biomarkers and lifestyle factors was explored using Transformation-based redundancy analysis (tb-RDA). Results: A total of 74 CI participants and 131 NCI participants were included in the analysis. The CI group demonstrated lower α-diversity compared to the NCI group (Shannon: 2.798 versus 3.152, p < 0.001). The density of the gut microbiota interaction network was lower in the CI group (0.074) compared to the NCI group (0.081). Megamonas, Blautia, Pseudomonas, Stenotrophomonas, and Veillonella were key biomarkers for CI. The tb-RDA revealed that increased fruit intake and exercise contribute to a higher abundance of Megamonas, Blautia, and Veillonella. Conclusions: We identified a significantly reduced abundance of certain beneficial gut microbiota in older Chinese adults with cognitive impairment.

Risk-prediction nomogram for congenital heart disease in offspring of Chinese pregnant women.

BACKGROUND: The identification and assessment of environmental risks are crucial for the primary prevention of congenital heart disease (CHD). We were aimed to establish a nomogram model for CHD in the offspring of pregnant women and validate it using a large CHD database in Northwest China. METHODS: A survey was conducted among 29,204 women with infants born between 2010 and 2013 in Shaanxi province, Northwest China. Participants were randomly assigned to the training set and to the validation set at a ratio of 7:3. The importance of predictive variables was assessed using random forest. A multivariate logistic regression model was used to construct the nomogram for the prediction of CHD. RESULTS: Multivariate analyses revealed that the gravidity, preterm birth history, family history of birth defects, infection, taking medicine, tobacco exposure, pesticide exposure and singleton/twin pregnancy were significant predictive risk factors for CHD in the offspring of pregnant women. The area under the receiver operating characteristic curve for the prediction model was 0.716 (95% CI: 0.671, 0.760) in the training set and 0.714 (95% CI: 0.630, 0.798) in the validation set, indicating moderate discrimination. The prediction model exhibited good calibration (Hosmer-Lemeshow χ2 = 1.529, P = 0.910). CONCLUSIONS: We developed and validated a predictive nomogram for CHD in offspring of Chinese pregnant women, facilitating the early prenatal assessment of the risk of CHD and aiding in health education.

Investigating the temporal trends of diabetes disease burden in China during 1990-2019 from a global perspective.

Introduction: Diabetes poses a global public health challenge and our understanding of its temporal evolution in China relative to the rest of the world is limited. Our study aims to comprehensively examine the temporal trend of diabetes DALYs in China from a global perspective. Methods: We analyzed data on diabetes incidence, prevalence, and mortality for individuals aged ≥20 years in China and globally from the Global Burden of Disease (GBD) 2019 study. We assessed trends in age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of diabetes in China and globally by estimating annual percentage changes (EAPCs). We employed decomposition analysis to reveal factors driving the trend of diabetes DALYs in China. Results: During 1990-2019, the number of diabetes patients increased by 160% from 35.14 million to 91.70 million in China. The ASIR of diabetes increased from 249 per 100,000 to 329 per 100,000 in China, which was lower than the global rate (419 per 100,000 in 2019). The EAPC of diabetes incidence was also lower in China compared to the global rate (1.02% vs. 1.57%). Consistently, the age-standardized prevalence rate of diabetes increased from 4788 per 100,000 to 8170 per 100,000 during 1990-2019 in China, which remained lower than the corresponding global rate (8827 per 100,000 in 2019). Further, the ASMR of diabetes increased from 9 per 100,000 to 15 per 100,000 during 1990-2019 in China, which was lower than the corresponding global rate (30 per 100,000 in 2019). However, EAPC of diabetes mortality in China was much higher than the global level (1.75% vs. 1.07%). Globally, the rising diabetes DALYs was predominantly attributed to population growth (55.2%) and epidemiologic changes (24.6%). In comparison, population growth (48.9%) also played an important role in the increasing diabetes DALYs in China, but aging (43.7%) was second major contributor. Conclusion: Our findings show that diabetes DALYs in China followed a global increasing trend during 1990-2019. Notably, aging has a very substantial contribution to the increase in diabetes DALYs in China in addition to population growth. .

Optimizing health resource allocation for improving timely HIV diagnosis in China.

INTRODUCTION: The Joint United Nations Programme on HIV/AIDS (UNAIDS) updated the 95-95-95 targets for the HIV endgame in 2030. To achieve the first target in a timely manner, we investigate the optimized strategy of resource allocation to maximize timely HIV diagnosis in 14 populations in China. METHODS: We developed a mathematical model by integrating epidemiological, demographical and behavioural data from 12 high-risk and two general populations to evaluate the impact of various resource allocation strategies of HIV testing on HIV incidence in China. We identified the optimized allocation strategy that maximizes the number of HIV diagnoses at an estimated total spending on HIV tests in China and calculated the per-capita cost of new HIV case detection. RESULTS: We estimated that 144,795 new HIV cases may occur annually in 14 populations in China, with a total annual spending of US$2.8 billion on HIV testing. The largest proportion of spending was allocated to general males (44.0%), followed by general females (42.6%) and pregnant women (5.1%). Despite this allocation strategy, only 45.5% (65,867/144,795, timely diagnosis rate) of annual new infections were diagnosed within a year of acquisition, with a cost of $42,852 required for each new HIV case detection. By optimizing the allocation of HIV testing resources within the same spending amount, we found that general females received the highest proportion of spending allocation (45.1%), followed by low-risk men who have sex with men (13.9%) and pregnant women (8.4%). In contrast, the proportion of spending allocation for the general males decreased to 0.2%. With this optimized strategy, we estimated that 120,755 (83.4%) of annual new infections would be diagnosed within a year of acquisition, with the cost required for one HIV case detection reduced to $23,364/case. Further spending increases could allow for significant increases in HIV testing among lower-risk populations. CONCLUSIONS: Optimizing resource allocation for HIV testing in high-risk populations would improve HIV timely diagnosis rate of new infections and reduce cost per HIV case detection.

Population impact and cost-effectiveness of artificial intelligence-based diabetic retinopathy screening in people living with diabetes in Australia: a cost effectiveness analysis.

Background: We aimed to evaluate the cost-effectiveness of an artificial intelligence-(AI) based diabetic retinopathy (DR) screening system in the primary care setting for both non-Indigenous and Indigenous people living with diabetes in Australia. Methods: We performed a cost-effectiveness analysis between January 01, 2022 and August 01, 2023. A decision-analytic Markov model was constructed to simulate DR progression in a population of 1,197,818 non-Indigenous and 65,160 Indigenous Australians living with diabetes aged ≥20 years over 40 years. From a healthcare provider's perspective, we compared current practice to three primary care AI-based screening scenarios-(A) substitution of current manual grading, (B) scaling up to patient acceptance level, and (C) achieving universal screening. Study results were presented as incremental cost-effectiveness ratio (ICER), benefit-cost ratio (BCR), and net monetary benefits (NMB). A Willingness-to-pay (WTP) threshold of AU$50,000 per quality-adjusted life year (QALY) and a discount rate of 3.5% were adopted in this study. Findings: With the status quo, the non-Indigenous diabetic population was projected to develop 96,269 blindness cases, resulting in AU$13,039.6 m spending on DR screening and treatment during 2020-2060. In comparison, all three intervention scenarios were effective and cost-saving. In particular, if a universal screening program was to be implemented (Scenario C), it would prevent 38,347 blindness cases, gain 172,090 QALYs and save AU$595.8 m, leading to a BCR of 3.96 and NMB of AU$9,200 m. Similar findings were also reported in the Indigenous population. With the status quo, 3,396 Indigenous individuals would develop blindness, which would cost the health system AU$796.0 m during 2020-2060. All three intervention scenarios were cost-saving for the Indigenous population. Notably, universal AI-based DR screening (Scenario C) would prevent 1,211 blindness cases and gain 9,800 QALYs in the Indigenous population, leading to a saving of AU$19.2 m with a BCR of 1.62 and NMB of AU$509 m. Interpretation: Our findings suggest that implementing AI-based DR screening in primary care is highly effective and cost-saving in both Indigenous and non-Indigenous populations. Funding: This project received grant funding from the Australian Government: the National Critical Research Infrastructure Initiative, Medical Research Future Fund (MRFAI00035) and the NHMRC Investigator Grant (APP1175405). The contents of the published material are solely the responsibility of the Administering Institution, a participating institution or individual authors and do not reflect the views of the NHMRC. This work was supported by the Global STEM Professorship Scheme (P0046113), the Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075). The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian State Government. W.H. is supported by the Melbourne Research Scholarship established by the University of Melbourne. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Optimising HIV pre-exposure prophylaxis and testing strategies in men who have sex with men in Australia, Thailand, and China: a modelling study and cost-effectiveness analysis.

BACKGROUND: Men who have sex with men (MSM) in the Asia-Pacific region have a disproportionately high burden of HIV infection compared with the general population. Although pre-exposure prophylaxis (PrEP) for HIV is highly effective at preventing new HIV infections, the cost-effectiveness of PrEP for MSM in different countries in the Asia-Pacific region with varying PrEP coverage and HIV testing frequencies remains unstudied. We aimed to analyse the economic and health benefits of long-acting injectable cabotegravir (CAB-LA) compared with oral PrEP in high-income countries and low-income and middle-income countries within the Asia-Pacific region. METHODS: We developed a decision-analytic Markov model to evaluate the population impact and cost-effectiveness of PrEP scale-up among MSM in Australia, Thailand, and China. We assumed a static cohort of 100 000 MSM aged 18 years or older who were at risk of HIV infection, with a monthly cycle length over a 40-year time period. We evaluated hypothetical scenarios with universal PrEP coverage of 80% among 100 000 suitable MSM in each country. We modelled oral PrEP and CAB-LA for MSM with diverse HIV testing frequency strategies. We adopted the health-care system's perspective with a 3% annual discount rate. We calculated the incremental cost-effectiveness ratio (ICER), measured as additional cost per quality-adjusted life-year (QALY) gained, to compare different strategies with the status quo in each country. All costs were reported in 2021 US$. We also performed one-way, two-way, and probabilistic sensitivity analyses to assess the robustness of our findings. FINDINGS: Compared with the status quo in each country, expanding oral PrEP to 80% of suitable MSM would avert 8·1% of new HIV infections in Australia, 14·5% in Thailand, and 26·4% in China in a 40-year period. Expanding oral PrEP use with 6-monthly HIV testing for both PrEP and non-PrEP users was cost-saving for Australia. Similarly, expanding oral PrEP use remained the most cost-effective strategy in both Thailand and China, but optimal testing frequency varied, with annual testing in Thailand (ICER $4707 per QALY gained) and 3-monthly testing in China (ICER $16 926 per QALY gained) for both PrEP and non-PrEP users. We also found that replacing oral PrEP with CAB-LA for MSM could avert more new HIV infections (12·8% in Australia, 27·6% in Thailand, and 32·8% in China), but implementing CAB-LA was not cost-effective due to its high cost. The cost of CAB-LA would need to be reduced by 50-90% and be used as a complementary strategy to oral PrEP to be cost-effective in these countries. INTERPRETATION: Expanding oral PrEP use for MSM, with country-specific testing frequency, is cost-effective in Australia, Thailand, and China. Due to the high cost, CAB-LA is currently not affordable as a single-use strategy but might be offered as an additional option to oral PrEP. FUNDING: Ministry of Science and Technology of the People's Republic of China, the Australian National Health and Medical Research Council, National Key Research and Development Program of China, and National Natural Science Foundation of China.

Cost-Effectiveness of the Second COVID-19 Booster Vaccination in the USA.

OBJECTIVE: To assess the cost effectiveness of the second COVID-19 booster vaccination with different age groups. METHODS: We developed a decision-analytic Susceptible-Exposed-Infected-Recovered (SEIR)-Markov model by five age groups (0-4 years, 5-11 years 12-17 years, 18-49 years, and 50+ years) and calibrated the model by actual mortality in each age group in the USA. We conducted five scenarios to evaluate the cost effectiveness of the second booster strategy and incremental benefits if the strategy would expand to 18-49 years and 12-17 years, from a health care system perspective. The analysis was reported according to the Consolidated Health Economic Evaluation Reporting Standards 2022 statement. RESULTS: Implementing the second booster strategy for those aged ≥ 50 years cost $823 million but reduced direct medical costs by $1166 million, corresponding to a benefit-cost ratio of 1.42. Moreover, the strategy also resulted in a gain of 2596 quality-adjusted life-years (QALYs) during the 180-day evaluation period, indicating it was dominant. Further, vaccinating individuals aged 18-49 years with the second booster would result in an additional gain of $1592 million and 8790 QALYs. Similarly, expanding the vaccination to individuals aged 12-17 years would result in an additional gain of $16 million and 403 QALYs. However, if social interaction between all age groups was severed, vaccination expansion to ages 18-49 and 12-17 years would no longer be dominant but cost effective with an incremental cost-effectiveness ratio (ICER) of $37,572 and $26,705/QALY gained, respectively. CONCLUSION: The second booster strategy was likely to be dominant in reducing the disease burden of the COVID-19 pandemic. Expanding the second booster strategy to ages 18-49 and 12-17 years would remain dominant due to their social contacts with the older age group.

A systematic review of cost-effectiveness analysis of different screening strategies for familial hypercholesterolemia.

AIMS: Diagnosis rate of familial hypercholesterolemia (FH) remained less than 10 % globally and the economic evaluation results of different FH screening strategies varied. This study aimed to systematically review the methodology and results of cost effectiveness analysis (CEA) of FH screening, which will provide evidence support for health-related decision-making. METHODS: The Medline/PubMed, Embase, Cochrane Library, Web of science, National Health Service Economic Evaluation Database (NHSEED) and CEA Registry databases were electronically searched to collect full economic evaluation from the establishment of the databases to June 30, 2022. The quality of included studies was evaluated by the Consolidated Health Economic Evaluation Reporting Standards statement 2022 (CHEERS 2022) checklist. RESULTS: Among 232 retrieved studies, 18 economic evaluations were included and all of them are from developed countries, with an average quality score of 0.73. The decision tree model and/or Markov model were constructed by thirteen articles (72 %). Twelve studies (67 %) adopted the healthcare perspective and the lifetime horizon to compare the costs and health outcome of different screening strategies. The results of eight studies indicated that cascade screening was a cost-effective strategy compared with no screening, which was more pronounced in younger adults. Universal screening in young adults aged 16 years or 18-40 years (n=3) and in children aged 1-2 years combined with reverse cascade screening (n=3) are both cost-effective. The probability of being cost-effective for cascade screening (n=6) and universal screening (n=1) of young aged 18-40 years were greater than 95 %. CONCLUSIONS: Our review demonstrated the economic advantages of cascade screening, universal screening of young adults, and universal screening of newborns combined with reverse cascade screening. Further health economic evaluation is needed in children and in low- and middle-income countries.

Blueprint to hepatitis B elimination in China: A modelling analysis of clinical strategies.

Background & Aims: Globally, one-third of individuals infected with HBV live in China. Eliminating HBV in China would therefore be paramount in achieving the World Health Organization's (WHO's) targets of viral hepatitis elimination as a worldwide public health threat. Methods: We constructed a dynamic HBV transmission model in China, structured by age and sex. We calibrated the model by HBsAg prevalence, acute HBV incidence, and nationally reported HBV-related cancer mortality. We investigated seven intervention scenarios (A-G) based on assumptions in diagnostic, linkage-to-care, and treatment coverages in achieving the WHO's HBV elimination goals. Results: With the status quo, HBsAg prevalence among children 1-4 years would reduce to 0.09% (95% CI 0.09-0.10%) by 2025; acute HBV incidence would drop to <2/100,000 person-years by 2024, achieving the elimination target of 90% incidence reduction. Nonetheless, China would not achieve a 65% reduction target in HBV-related mortality until 2059 with 9.98 (95% CI 9.27-10.70) million HBV-related deaths occurred by 2100. If China achieves 90% diagnostic and 80% treatment coverages (scenario E), HBV elimination would be achieved 8 years earlier, potentially saving 1.98 (95% CI 1.83-2.12) million lives. With more effective therapies for HBV control in preventing cirrhosis and hepatocellular carcinoma, elimination targets could be achieved in 2048 (scenario F) and 2038 (scenario G), additionally saving 3.59 (95% CI 3.37-3.82) and 5.19 (95% CI 4.83-5.55) million lives, respectively. Conclusions: Eliminating HBV will require interventional strategies to improve diagnostic, linkage-to-care, and treatment coverages. Developing novel therapies will be crucial in further reducing HBV-related mortality and removing HBV as a public health threat. Impact and Implications: This study explores the key developments and optimal intervention strategies needed to achieve WHO hepatitis B elimination targets by 2030 in China. It highlights that China can realise the HBV elimination targets in the incidence by 2025, and by upscaling diagnostic, linkage-to-care, and treatment coverages, up to 2 million lives could potentially be saved from HBV-related deaths.

A Multidimensional Assessment of Activities of Daily Living, Mental Status, Communication, and Social Abilities Among Older Adults in Shenzhen, China: Cross-Sectional Study.

BACKGROUND: China is facing a rapidly expanding aging population. Insights into the health status of older adults are of great significance for health resource allocation and health care provision to this population. OBJECTIVE: With the goal of providing a comprehensive understanding of the health status of older adults and to inform potential interventions, we investigated the level of disability and identified risk factors associated with disability among the older population (aged ≥60 years) living in China. METHODS: A total of 8467 older adults living in the Chinese city of Shenzhen were enrolled in this cross-sectional study. We used a multidimensional ability assessment survey, which assessed their activities of daily living (ADL; including eating, bathing, grooming, dressing, defecation control, urination control, using a toilet unaided, transfer, flat-ground walking, stair activity), mental status (including cognitive function, aggressive behavior, depression symptoms), sensory and communication (including consciousness level, vision, hearing, communication), and social participation (including living, working, time/space orientation, distinguish persons, social communication) abilities. The impact of demographic risk factors on ability levels was analyzed using ordinal logistic regression. The correlations between the four dimensions of ability mentioned above were analyzed using Spearman correlation analysis. RESULTS: A total of 7766 participants were effectively assessed. The participants' average age was 70.64 (SD 8.46) years comprising 56.53% females. The overall ability level was classified as mildly, moderately, and severely impaired for 27.57% (n=2141), 2.83% (n=220), and 4.28% (n=332) of the 7766 participants, respectively. With increasing age, the proportion of impaired participants increased from 17.62% (365/2071) in the age group 60-64 years to 91.3% (253/277) in the age group above 90 years (P<.001), corresponding to an approximate 10% rise for every 5-year age increment. The odds of having more severe overall ability impairment in females was 1.15 times that in males (odds ratio [OR] 1.15, 95% CI 1.04-1.28). Participants who were divorced or widowed had a higher risk of more severe overall ability impairment than those currently married (OR 1.98, 95% CI 1.68-2.33). Participants living with nonrelatives had an increased risk of more severe overall ability impairment than those living alone (OR 2.38, 95% CI 1.46-3.91). Higher education level was a protective factor of overall ability impairment (college degree or above: OR 0.32, 95% CI 0.24-0.42). The four dimensions of ability assessed were significantly correlated; a low score for ADL was significantly correlated with poorer mental status, sensory and communication, and social participation (all P<.001). CONCLUSIONS: The proportion of disability among Chinese older adults increases with age, being female, having lower education levels, being divorced or widowed, and living with nonrelatives. Impairment in ADL ability is significantly correlated with poor mental status, social participation, and sensory and communication abilities. A holistic approach to improving the health of the older population is recommended in China.

Shared-care models are highly effective and cost-effective for managing chronic hepatitis B in China: reinterpreting the primary care and specialty divide.

Background: We evaluate the impact and cost-effectiveness of shared primary-specialty chronic hepatitis B (CHB) care models in China. Methods: We constructed a decision-tree Markov model to simulate hepatitis B virus (HBV) disease progression in a cohort of 100,000 CHB individuals aged ≥18 years over their lifetime (aged 80). We evaluated the population impacts and cost-effectiveness in three scenarios: (1) status quo; (2) shared-care model with HBV testing and routine CHB follow-ups in primary care and antiviral treatment initiation in specialty care; and (3) shared-care model with HBV testing, treatment initiation and routine CHB follow-up in primary care and treatment for predetermined conditions in specialty care. We evaluated from a healthcare provider's perspective with 3% discounting rate and a willingness-to-pay (WTP) threshold of 1-time China's GDP. Findings: Compared with status quo, scenario 2 would result in an incremental cost of US$5.79-132.43m but a net gain of 328-16,993 quality-adjusted life years (QALYs) and prevention of 39-1935 HBV-related deaths over cohort's lifetime. Scenario 2 was not cost-effective with a WTP of 1-time GDP per capita, but became cost-effective when treatment initiation rate increased to 70%. In contrast, compared with status quo, secnario 3 would save US$144.59-192.93m in investment and achieve a net gain of 23,814-30,476 QALYs and prevention of 3074-3802 HBV-related deaths. Improving HBV antiviral treatment initiation among eligible CHB individuals substantially improved the cost-effectiveness of the shared-care models. Interpretation: Shared-care models with HBV testing, follow up and referring of predetermined conditions to specialty care at an appropriate time, especially antiviral treatment initiation in primary care, are highly effective and cost-effective in China. Funding: National Natural Science Foundation of China.

Genetic support of the causal association between gut microbiome and COVID-19: a bidirectional Mendelian randomization study.

Background: The association between gut microbiome and coronavirus disease 2019 (COVID-19) has attracted much attention, but its causality remains unclear and requires more direct evidence. Methods: In this study, we conducted the bidirectional Mendelian randomization (MR) analysis to assess the causal association between gut microbiome and COVID-19 based on the summary statistics data of genome-wide association studies (GWASs). Over 1.8 million individuals with three COVID-19 phenotypes (severity, hospitalization and infection) were included. And 196 bacterial taxa from phylum to genus were analyzed. The inverse-variance weighted (IVW) analysis was chosen as the primary method. Besides, false discovery rate (FDR) correction of p-value was used. To test the robustness of the causal relationships with p-FDR < 0.05, sensitivity analyses including the secondary MR analyses, horizontal pleiotropy test, outliers test, and "leave-one-out" analysis were conducted. Results: In the forward MR, we found that 3, 8, and 10 bacterial taxa had suggestive effects on COVID-19 severity, hospitalization and infection, respectively. The genus Alloprevotella [odds ratio (OR) = 1.67; 95% confidence interval (95% CI), 1.32-2.11; p = 1.69×10-5, p-FDR = 2.01×10-3] was causally associated with a higher COVID-19 severity risk. In the reverse MR, COVID-19 severity, hospitalization and infection had suggestive effects on the abundance of 4, 8 and 10 bacterial taxa, respectively. COVID-19 hospitalization causally increased the abundance of the phylum Bacteroidetes (OR = 1.13; 95% CI, 1.04-1.22; p = 3.02×10-3; p-FDR = 2.72×10-2). However, secondary MR analyses indicated that the result of COVID-19 hospitalization on the phylum Bacteroidetes required careful consideration. Conclusion: Our study revealed the causal association between gut microbiome and COVID-19 and highlighted the role of "gut-lung axis" in the progression of COVID-19.

Modelling the impact of treatment adherence on the transmission of HIV drug resistance.

INTRODUCTION: A lower adherence rate (percentage of individuals taking drugs as prescribed) to ART may increase the risk of emergence and transmission of HIV drug resistance, decrease treatment efficacy, and increase mortality rate. Exploring the impact of ART adherence on the transmission of drug resistance could provide insights in controlling the HIV epidemic. METHODS: We proposed a dynamic transmission model incorporating the CD4 cell count-dependent rates of diagnosis, treatment and adherence with transmitted drug resistance (TDR) and acquired drug resistance. This model was calibrated and validated by 2008-2018 HIV/AIDS surveillance data and prevalence of TDR among newly diagnosed treatment-naive individuals from Guangxi, China, respectively. We aimed to identify the impact of adherence on drug resistance and deaths during expanding ART. RESULTS: In the base case (ART at 90% adherence and 79% coverage), we projected the cumulative total new infections, new drug-resistant infections, and HIV-related deaths between 2022 and 2050 would be 420 539, 34 751 and 321 671. Increasing coverage to 95% would reduce the above total new infections (deaths) by 18.85% (15.75%). Reducing adherence to below 57.08% (40.84%) would offset these benefits of increasing coverage to 95% in reducing infections (deaths). Every 10% decrease in adherence would need 5.07% (3.62%) increase in coverage to avoid an increase in infections (deaths). Increasing coverage to 95% with 90% (80%) adherence would increase the above drug-resistant infections by 11.66% (32.98%). CONCLUSIONS: A decrease in adherence might offset the benefits of ART expansion and exacerbate the transmission of drug resistance. Ensuring treated patients' adherence might be as important as expanding ART to untreated individuals.

Cost-effectiveness of artificial intelligence-assisted liquid-based cytology testing for cervical cancer screening in China.

Background: The 2021 World Health Organization (WHO) guidelines for cervical cancer screening recommend human papillomavirus (HPV) DNA or mRNA testing. Artificial intelligence (AI)-assisted liquid-based cytology (LBC) systems also have the potential to facilitate rapid scale-up of cervical cancer screening. We aimed to evaluate the cost-effectiveness of AI-assisted LBC testing, compared with the manual LBC and HPV-DNA testing, for primary cervical cancer screening in China. Methods: We developed a Markov model for a cohort of 100,000 women aged 30 years over a lifetime to simulate the natural history of cervical cancer progression. We evaluated the incremental cost-effectiveness ratios (ICER) of 18 screening strategies (a combination of the three screening methods with six screening frequencies) from a healthcare provider's perspective. The willingness-to-pay threshold (US$30,828) was chosen as three times the Chinese per-capita gross domestic product in 2019. Univariate and probabilistic sensitivity analyses were performed to examine the robustness of the results. Findings: Compared with no screening, all 18 screening strategies were cost-effective, with an ICER of $622-24,482 per quality-adjusted life-year (QALY) gained. If HPV testing after scaling up to population level screening costs $10.80 or more, screening once every 5 years using AI-assisted LBC would be the most cost-effective strategy with an ICER of $8790/QALY gained compared with the lower-cost non-dominated strategy on the cost-effectiveness frontier. Its probability of being cost-effective was higher (55.4%) than other strategies. Sensitivity analyses showed that the most cost-effective strategy would become AI-assisted LBC testing once every 3 years if the sensitivity (74.1%) and specificity (95.6%) of this method were both reduced by ≥10%. The most cost-effective strategy would become HPV-DNA testing once every 5 years if the cost of AI-assisted LBC was more expensive than manual LBC or if the HPV-DNA test cost is slightly reduced (from $10.8 to <$9.4). Interpretation: AI-assisted LBC screening once every 5 years could be more cost-effective than manually-read LBC. Using AI-assisted LBC could have comparable cost-effectiveness to HPV DNA screening, but the relative pricing of HPV DNA testing is critical in this result. Funding: National Natural Science Foundation of China, National Key R&D Program of China.

Do Infrared Thermometers Hold Promise for an Effective Early Warning System for Emerging Respiratory Infectious Diseases?

BACKGROUND: Major respiratory infectious diseases, such as influenza, SARS-CoV, and SARS-CoV-2, have caused historic global pandemics with severe disease and economic burdens. Early warning and timely intervention are key to suppress such outbreaks. OBJECTIVE: We propose a theoretical framework for a community-based early warning (EWS) system that will proactively detect temperature abnormalities in the community based on a collective network of infrared thermometer-enabled smartphone devices. METHODS: We developed a framework for a community-based EWS and demonstrated its operation with a schematic flowchart. We emphasize the potential feasibility of the EWS and potential obstacles. RESULTS: Overall, the framework uses advanced artificial intelligence (AI) technology on cloud computing platforms to identify the probability of an outbreak in a timely manner. It hinges on the detection of geospatial temperature abnormalities in the community based on mass data collection, cloud-based computing and analysis, decision-making, and feedback. The EWS may be feasible for implementation considering its public acceptance, technical practicality, and value for money. However, it is important that the proposed framework work in parallel or in combination with other early warning mechanisms due to a relatively long initial model training process. CONCLUSIONS: The framework, if implemented, may provide an important tool for important decisions for early prevention and control of respiratory diseases for health stakeholders.

Instant Coffee Is Negatively Associated with Telomere Length: Finding from Observational and Mendelian Randomization Analyses of UK Biobank.

Telomere length, as a biomarker of accelerated aging, is closely related to many chronic diseases. We aimed to explore the association between coffee consumption and telomere length. Our study included 468,924 participants from the UK Biobank. Multivariate linear models (observational analyses) were conducted to evaluate the associations of coffee intake, instant coffee intake, and filtered coffee intake with telomere length. In addition, we evaluated the causality of these associations in Mendelian randomization (MR) analyses by four methods (inverse-variance weighted (IVW), MR pleiotropy residual sum and outlier (MR-PRESSO), MR-Egger, and weighted median). Observational analyses indicated that coffee intake and instant coffee intake were negatively correlated with telomere length, which was equal to 0.12 year of age-related decrease in telomere length for each additional cup of coffee intake (p < 0.001), and 0.38 year of age-related decrease in telomere length for each additional cup of instant coffee intake (p < 0.001), respectively. There was no significant correlation between filtered coffee and telomere length (p = 0.862). Mendelian randomization analyses supported the results of observational analyses. Coffee intake was found to have a causal effect on telomere length through weighted median analysis (p = 0.022), and instant coffee intake had a causal effect on telomere length through IVW analysis (p = 0.019) and MR-PRESSO analysis (p = 0.028). No causal relationship was found between filtered coffee intake and telomere length (p > 0.05). Coffee intake, particularly instant coffee, was found to have an important role in shortening telomere length.

A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US.

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.

The impact of attrition on the transmission of HIV and drug resistance.

BACKGROUND: Attrition due to loss to follow-up or termination of antiretroviral therapy (ART) among HIV-infected patients in care may increase the risk of emergence and transmission of drug resistance (TDR), diminish benefit of treatment, and increase morbidity and mortality. Understanding the impact of attrition on the epidemic is essential to provide interventions for improving retention in care. METHODS: We developed a comprehensive HIV transmission dynamics model by considering CD4 + cell count dependent diagnosis, treatment, and attrition involving TDR and acquired drug resistance. The model was calibrated by 11 groups HIV/AIDS surveillance data during 2008-2018 from Guangxi, China, and validated by the prevalence of TDR among diagnosed treatment-naive individuals. We aimed to investigate how attrition would affect the transmission of HIV and drug-resistance when expanding ART. RESULTS: In the base case with CD4 + cell count dependent per capita attrition rates 0.025∼0.15 and treatment rates 0.23∼0.42, we projected cumulative total new infections, new drug-resistant infections, and HIV-related deaths over 2022-2030 would be 145 391, 7637, and 51 965, respectively. Increasing treatment rates by 0.1∼0.2 can decrease the above total new infections (deaths) by 1.63∼2.93% (3.52∼6.16%). However, even 0.0114∼0.0220 (0.0352∼0.0695) increase in attrition rates would offset this benefit of decreasing infections (deaths). Increasing treatment rates (attrition rates) by 0.05∼0.1 would increase the above drug-resistant infections by 0.16∼0.30% (22.18∼41.15%). CONCLUSION: A minor increase in attrition can offset the benefit of treatment expansion and increase the transmission of HIV drug resistance. Reducing attrition rates for patients already in treatment may be as important as expanding treatment for untreated patients.