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Abstract 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.

Objective The study aimed to investigate the impact of COVID-19 on the cascade of HIV care for people living with HIV (PLHIV) in Ethiopia.Design A retrospective longitudinal study.Setting The study was conducted in North Showa Zone, Ethiopia, from pre-COVID-19 (January 2018–December 2019) and during COVID-19 (January 2020–December 2021).Participants We identified 61901 records from 3925 PLHIV, of which 23 848 were recorded during the pandemic.Main outcome measure We investigated indicators from four stages of the HIV care cascade, including HIV screening and diagnosis, HIV care, HIV treatment and HIV disease progression, according to a WHO framework. The indicator changes were assessed with incidence rate ratios (IRRs).Results For HIV screening and diagnosis, the monthly number of HIV tests experienced a 46% decline from 2520 to 1361 since the pandemic (IRR 0.553; 95% CI 0.546 to 0.561). For HIV care, the monthly number of consultations was reduced by 49.6% (from 1582 to 798) since the pandemic (IRR 0.591; 95% CI 0.581 to 0.601). Similarly, the monthly number of viral load tests was reduced by 42.8% (IRR 0.614; 95% CI 0.581 to 0.650). For HIV treatment, the number of antiretroviral therapy (ART) initiations was reduced by 27.8% and the number of ART adherence by 52.5% since the pandemic. For HIV disease progression, the monthly number of PLHIV achieving viral suppression was reduced by 61.6%, while HIV-related deaths doubled during the pandemic.Conclusion The study highlights pandemic-induced disruptions in the cascade of care for PLHIV. Targeted interventions are necessary to protect PLHIV in public health emergencies.

IntroductionDiabetes 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.MethodsWe 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.ResultsDuring 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.ConclusionOur 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.

Abstract 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.

Summary: 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.

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

BackgroundChina 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. ObjectiveWith 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. MethodsA 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. ResultsA 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

BackgroundThe association between gut microbiome and coronavirus disease 2019 (COVID-19) has attracted much attention, but its causality remains unclear and requires more direct evidence.MethodsIn 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.ResultsIn 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.ConclusionOur 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.

Abstract Background The World Health Organization (WHO) requires reduction in the prevalence of hepatitis B virus (HBV) surface antigen (HBsAg) in children to 0.1% by 2030, a key indicator for eliminating viral hepatitis as a major public health threat. Whether and how China can achieve this target remains unknown, although great achievements have been made. We aimed to predict the decline of HBsAg prevalence in China and identify key developments needed to achieve the target. Methods An age- and time-dependent dynamic compartmental model was constructed based on the natural history of HBV infection and the national history and current status of hepatitis B control. The model was run from 2006 to 2040 to predict the decline of HBsAg prevalence under three scenarios including maintaining current interventions (status quo), status quo + peripartum antiviral prophylaxis (PAP, recommended by WHO in 2020), and scaling up current interventions + PAP. Results Under the status quo, HBsAg prevalence would decrease steadily in all age groups, but the WHO’s target of 0.1% prevalence in children aged

Objectives: To evaluate the cost-effectiveness of a booster strategy in the United States. Methods: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy of the Pfizer-BioNTech BNT162b2 (administered 6 months after the second dose) among older adults from a healthcare system perspective. Results: Compared with 2 doses of BNT162b2 without a booster, the booster strategy in a 100,000 cohort of older adults would incur an additional cost of $3.4 million in vaccination cost but save $6.7 million in direct medical cost and gain 3.7 quality-adjusted life-years in 180 days. This corresponds to a benefit-cost ratio of 1.95 and a net monetary benefit of $3.4 million. Probabilistic sensitivity analysis indicates that a booster strategy has a high chance (67%) of being cost-effective. Notably, the cost-effectiveness of the booster strategy is highly sensitive to the population incidence of COVID-19, with a cost-effectiveness threshold of 8.1/100,000 person-day. If vaccine efficacies reduce by 10%, 30%, and 50%, this threshold will increase to 9.7/100,000, 13.9/100,000, and 21.9/100,000 person-day, respectively. Conclusion: Offering the BNT162b2 booster to older adults aged ≥65 years in the United States is likely to be cost-effective. Less efficacious vaccines and boosters may still be cost-effective in settings of high SARS-CoV-2 transmission.

BackgroundMajor 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. ObjectiveWe 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. MethodsWe 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. ResultsOverall, 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. ConclusionsThe framework, if implemented, may provide an important tool for important decisions for early prevention and control of respiratory diseases for health stakeholders.

Summary: Background: This study projects the trend of disease burden and economic burden of diabetes in 33 Chinese provinces and nationally during 2020–2030 and investigates its spatial disparities. Methods: Time series prediction on the prevalence and disability-adjusted life-year (DALY) rates of diabetes was conducted using a Bayesian modelling approach in 2020–2030. The top-down method and the human capital method were used to predict the direct and indirect costs of diabetes for each Chinese province. Global and local spatial autocorrelation analyses were used to identify geographic clusters of low-or high-burden areas. Findings: Diabetes prevalence in Chinese adults aged 20–79 years was projected to increase from 8.2% to 9.7% during 2020–2030. During the same period, the total costs of diabetes would increase from $250.2 billion to $460.4 billion, corresponding to an annual growth rate of 6.32%. The total costs of diabetes as a percentage of GDP would increase from 1.58% to 1.69% in China during 2020–2030, suggesting a faster growth in the economic burden of diabetes than China's economic growth. Consistently, the per-capita economic burden of diabetes would increase from $231 to $414 in China during 2020–2030, with an annual growth rate of 6.02%. High disease and economic burden areas were aggregated in Northeast and/or North China. Interpretation: Our study projects a significant growth of disease and economic burden of diabetes in China during 2020–2030, with strong spatial aggregation in northern Chinese regions. The increase in the economic burden of diabetes will exceed that of GDP. Funding: National Natural Science Foundation of China, Outstanding Young Scholars Funding.

Abstract Background Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. Objective Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. Methods We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. Results Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75–100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65–100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0–44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0–17 and 75–100 age groups as of June 1, 2021, then the allocation of 80% to the 0–17 age group and 20% to the 75–100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. Conclusions The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections.

Objectives: The exact characteristics of a coronavirus disease 2019 (COVID-19) outbreak that trigger public health interventions are poorly defined. The aim of this study was to assess the critical timing and extent of public health interventions to contain COVID-19 outbreaks in Australia. Methods: A practical model was developed using existing epidemic data in Australia. The effective combinations of public health interventions and the critical number of daily cases for intervention commencement under various scenarios of changes in transmissibility of new variants and vaccination coverage were quantified. Results: In the past COVID-19 outbreaks in four Australian states, the number of reported cases on the day that interventions commenced strongly predicted the size and duration of the outbreaks. In the early phase of an outbreak, containing a wildtype-dominant epidemic to a low level (≤10 cases/day) would require effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches six. Containing an Alpha-dominant epidemic would require more stringent interventions that commence earlier. For the Delta variant, public health interventions alone would not contain the epidemic unless the vaccination coverage was ≥70%. Conclusions: This study highlights the importance of early and decisive action in the initial phase of an outbreak. Vaccination is essential for containing variants.

Abstract Background Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. Methods We used a simple suboptimal inoculation melanoma mouse model to obtain ‘pre-diagnostic samples’ of mice with macroscopic melanomas. High-throughput sequencing and bioinformatic analysis were employed to identify differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of melanoma cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. Moreover, 36 genes selected from the eDEGs via bioinformatics analysis were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was utilized to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. Results These RNAs identified from eDEGs of mice injected with a suboptimal number of cancer cells were strongly enriched in pathways related to immune response and regulation. The prediction models generated by 36 gene qPCR verification data showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). Conclusions Our proof-of-concept study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer.

Summary: Background: Oral pre-exposure prophylaxis (PrEP) and antiretroviral therapy (ART) can effectively prevent HIV infections among men who have sex with men (MSM), but the emergence and transmission of HIV drug-resistance (HIVDR) may compromise their benefits. The costs and benefits of expanding PrEP and ART coverage in the presence of HIVDR in China remain unknown. Methods: We developed a comprehensive dynamic transmission model incorporating the transmitted (TDR) and acquired (ADR) HIV drug resistance. The model was calibrated by the HIV surveillance data from 2009 to 2019 among MSM in Jiangsu Province, China, and validated by the dynamic prevalence of ADR and TDR. We aimed to investigate the impact of eight intervention scenarios (no PrEP, 20%, 50% or 80% of PrEP, without (77% coverage) or with (90% coverage) expanded ART) on the HIV epidemic trend and cost-effectiveness of PrEP over the next 30 years. Findings: 20% or 50% PrEP + 90% ART would be cost-effective, with an incremental cost-effectiveness ratio (ICER) of 25,417 (95% confidence interval [CI]: 12,390–38,445) or 47,243 (23,756–70,729), and would yield 154,949 (89,662–220,237) or 179,456 (102,570–256,342) incremental quality-adjusted life-years (QALYs) over the next 30 years. No PrEP + 90% ART would yield 125,211 (73,448–176,974) incremental QALYs and be cost-saving. However, 20–80% PrEP + 77% ART and 80% PrEP + 90% ART with ICER of $77,862–$98,338 and $63,332, respectively, and were not cost-effective. A reduction of 64% in the annual cost of oral PrEP would make it highly cost-effective for 50% PrEP + 90% ART. Interpretation: 20% or 50% PrEP + 90% ART is cost-effective for HIV control in the presence of HIVDR. Expanded ART alone may be the optimal policy under the current limited budgets. Funding: National Natural Science Foundation of China, the National S&T Major Project Foundation of China.

The global pandemic of 2019 coronavirus disease (COVID-19) is a great assault to public health. Presymptomatic transmission cannot be controlled with measures designed for symptomatic persons, such as isolation. This study aimed to estimate the interval of the transmission generation (TG) and the presymptomatic period of COVID-19, and compare the fitting effects of TG and serial interval (SI) based on the SEIHR model incorporating the surveillance data of 3453 cases in 31 provinces. These data were allocated into three distributions and the value of AIC presented that the Weibull distribution fitted well. The mean of TG was 5.2 days (95% CI: 4.6–5.8). The mean of the presymptomatic period was 2.4 days (95% CI: 1.5–3.2). The dynamic model using TG as the generation time performed well. Eight provinces exhibited a basic reproduction number from 2.16 to 3.14. Measures should be taken to control presymptomatic transmission in the COVID-19 pandemic.

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.

Abstract Background In infectious disease transmission dynamics, the high heterogeneity in individual infectiousness indicates that few index cases generate large numbers of secondary cases, which is commonly known as superspreading events. The heterogeneity in transmission can be measured by describing the distribution of the number of secondary cases as a negative binomial (NB) distribution with dispersion parameter, k. However, such inference framework usually neglects the under-ascertainment of sporadic cases, which are those without known epidemiological link and considered as independent clusters of size one, and this may potentially bias the estimates. Methods In this study, we adopt a zero-truncated likelihood-based framework to estimate k. We evaluate the estimation performance by using stochastic simulations, and compare it with the baseline non-truncated version. We exemplify the analytical framework with three contact tracing datasets of COVID-19. Results We demonstrate that the estimation bias exists when the under-ascertainment of index cases with 0 secondary case occurs, and the zero-truncated inference overcomes this problem and yields a less biased estimator of k. We find that the k of COVID-19 is inferred at 0.32 (95%CI: 0.15, 0.64), which appears slightly smaller than many previous estimates. We provide the simulation codes applying the inference framework in this study. Conclusions The zero-truncated framework is recommended for less biased transmission heterogeneity estimates. These findings highlight the importance of individual-specific case management strategies to mitigate COVID-19 pandemic by lowering the transmission risks of potential super-spreaders with priority.

Abstract Background The long-term impact of sexual transmission on the hepatitis B virus (HBV) infection in China remains unclear. This study aims to estimate the independent influence of sexual transmission on HBV infection. Methods Based on the natural history of HBV infection and three national serosurvey data of hepatitis B in China, we developed an age- and sex-specific discrete model to describe the transmission dynamics of HBV. The initial conditions of the model were determined according to the age- and sex-specific national serosurvey data in 1992. Based on the national survey data of hepatitis B in 1992 and 2006, by using the Markov Chain Monte Carlo (MCMC) method, we estimated the age- and sex-specific seroclearance rates of hepatitis B surface antigen (HBsAg) and the horizontal transmission rates as well as their 95% confidence intervals (CI). Then we used the age- and sex-specific national serosurvey data of hepatitis B in 2014 to test the accuracy of our model-based estimation. Finally, we evaluated the independent impact of sexual transmission on HBV infection and discussed the long-term effect of promotion of condom use in China. Results We estimated that the annual rates of HBsAg seroclearance for males and females aged 1–59 years were respectively 1.04% (95% CI, 0.49–1.59%) and 1.92% (95% CI, 1.11–2.73%). Due to sexual transmission, in 2014, the total number of chronic HBV infections in people aged 0–100 years increased 292,581, of which males increased 189,200 and females increased 103,381. In 2006, the acute HBV infections due to sexual transmission accounted for 24.76% (male: 31.33%, female: 17.94%) and in 2014, which accounted for 34.59% (male: 42.93%, female: 25.73%). However, if the condom usage rate was increased by 10% annually starting in 2019, then compared with current practice, the total number of acute HBV infections from 2019 to 2035 would be reduced by 16.68% (male: 21.49%, female: 11.93%). The HBsAg prevalence in people aged 1–59 years in 2035 would be reduced to 2.01% (male: 2.40%, female: 1.58%). Conclusions Sexual transmission has become the predominant route of acute HBV infection in China, especially for men. The promotion of condom use plays a significant role in reducing the cases of acute HBV infection.

Abstract Objectives We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients. Methods We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality. Results The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8–5.5), 3.0 (1.0–7.0), 3.0 (1.0–8.0), and 6.5 (4.0–16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19. Conclusions Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.

Abstract Backgroud Diabetes mellitus is a common chronic disease and a severe public health issue. The incidence trends for type 1 diabetes (TIDM) and type 2 diabetes (T2DM) have rarely been studied on a global scale. We aimed to determine the temporal and geographical trends of diabetes globally. Methods Data on diabetes mellitus, including incidence, prevalence from 1990 to 2017 were obtained from the 2017 Global Burden of Disease study. We calculated the estimated annual percentage changes (EAPCs) in age-standardized incidence rate (ASIR) of diabetes mellitus according to sex, region, and disease type. Results The worldwide incident cases of diabetes mellitus has increased by 102.9% from 11,303,084 cases in 1990 to 22,935,630 cases in 2017 worldwide, while the ASIR increased from 234 /100,000 persons (95% UI, 219–249) to 285/100,000 persons (95% UI, 262–310) in this period [EAPC = 0.87, 95% confidence interval (CI):0.79–0.96]. The global ASIRs of T1DM and T2DM both demonstrated significant increase during 1990–2017, with EAPCs of 0.34 (95% CI,0.30–0.39) and 0.89 (95% CI,0.80–0.97), respectively. The ASIR trends also varied considerably by regions and countries. The increase in ASIR was greatest in high sociodemographic index regions (EAPC = 1.05, 95% CI:0.92–1.17) and lowest in low-SDI regions (EAPC = 0.79, 95% CI:0.71–0.88). Conclusions Both the number of incident cases and ASIR of diabetes mellitus increased significantly during 1990–2017 worldwide, but the temporal trends varied markedly across regions and countries.

Objectives: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. Methods: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January–15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. Results: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6–6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3–7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2–1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. Conclusions: Early epidemic characteristics are important indicators for the size of the entire epidemic.

Abstract Background The Guangxi Zhuang Autonomous Region bears a relatively high burden of HIV/AIDS infection. The number of accumulatively reported HIV/AIDS cases in Guangxi is the third highest among 31 provinces or Autonomous Region from 2004 to 2007, changed to the second highest between 2011 and 2013, then returned to the third highest again after 2014. We aim to estimate the new infections and evaluate the real-time HIV epidemic in Guangxi, China, in order to reveal the rule of HIV transmission. Methods Firstly, the number of annually reported HIV and AIDS cases, as well as the number of cases linked with CD4 data are extracted from the HIV/AIDS information system in China. Secondly, two CD4-staged models are formulated by linking the with-host information on CD4 level to between-host transmission and surveillance data. Thirdly, new HIV infections, diagnosis rates and undiagnosed infections over time are estimated by using Bayesian method and Maximum Likelihood Estimation method. Results The data reveal that the newly reported cases have been decreasing since 2011, while lots of cases are identified at late CD4 stage. The data fitted results indicate that both models can describe the trend of the epidemic well. The estimation results show that the new and undiagnosed infections began to decrease from the period2006 - 2008. However, the diagnosis probabilities/rates keep at a very low level, and there are still a large number of infections undiagnosed, most of which have a large probability to be identified at late CD4 stage. Conclusions Our findings suggest that HIV/AIDS epidemic in Guangxi has been controlled to a certain extent, while the diagnosis rate still needs to be improved. More attentions should be paid to identify infections at their early CD4 stages. Meanwhile, comprehensive intervention measures should be continually strengthened in avoid of the rebound of new infections.

Vaccination strategy is considered as the most cost-effective intervention measure for controlling diseases. It will strengthen the immunity and reduce the risks of infections. In this paper, a new delayed epidemic model with interim-immune and mixed vaccination strategy is studied. The diseasefree periodic solution is obtained by twice stroboscopic mapping and the corresponding dynamical behavior is analyzed. We determine a threshold parameter R1, the disease-free periodic solution is proved to be global attractive if R1 < 1. We also establish a threshold parameter R2 for the permanence of the model, i.e., if R2 > 1, the infectious disease will exist persistently. Then, we provide numerical simulations to illustrate our theoretical results intuitively. In particular, a practical application for newtype TB vaccine under mixed vaccination strategy is presented, based on the proposed theory and the data reported by NBSC. The mixed vaccination strategy can achieve the End TB goal formulated by WHO in limited time. Our study will help public health agency to design mixed control strategy which can reduce the burden of infectious diseases.

Background: Multiple SARS-CoV-2 variants are still rampant across the United States (US). We aimed to evaluate the impact of vaccination scale-up and potential reduction in the vaccination effectiveness on the COVID-19 epidemic and social restoration in the US.Methods: We extended a published compartmental model and calibrated the model to the latest US COVID-19 data. We estimated the vaccine effectiveness against the variant and evaluated the impact of a potential reduction in vaccine effectiveness on the epidemics. We explored the epidemic trends under different levels of social restoration.Results: We estimated the overall existing vaccine effectiveness against the variant as 88.5% (95% CI: 87.4–89.5%) with the vaccination coverage of 70% by the end of August, 2021. With this vaccine effectiveness and coverage, there would be 498,972 (109,998–885,947) cumulative infections and 15,443 (3,828–27,057) deaths nationwide over the next 12 months, of which 95.0% infections and 93.3% deaths were caused by the variant. Complete social restoration at 60, 65, 70% vaccination coverage would increase cumulative infections to 1.6 (0.2–2.9) million 0.7 (0.1–1.2) million, and 511,159 (110,578–911,740), respectively. At same time it would increase cumulative deaths to 39,040 (5,509–72,570), 19,562 (3,873–35,250), 15,739 (3,841–27,638), respectively. However, if the vaccine effectiveness were reduced to 75%, 50% or 25% due to new SARS-CoV-2 variants, there would be 667,075 (130,682–1,203,468), 1.7 (0.2–3.2) million, 19.0 (5.3–32.7) million new infections and 19,249 (4,281–34,217), 42,265 (5,081–79,448), 426,860 (117,229–736,490) cumulative deaths to occur over the next 12 months. Further, social restoration at a lower vaccination coverage would lead to even greater secondary outbreaks.Conclusion: Current COVID-19 vaccines remain effective against the SARS-CoV-2 variant, and 70% vaccination coverage would be sufficient to restore social activities to a pre-pandemic level. Further reduction in vaccine effectiveness against SARS-CoV-2 variants would result in a potential surge of the epidemic. Multiple measures, including public health interventions, vaccination scale-up and development of a new vaccine booster, should be integrated to counter the new challenges of new SARS-CoV-2 variants.

Objectives The incidence of Neisseria gonorrhoeae and its antimicrobial resistance is increasing in many countries. Antibacterial mouthwash may reduce gonorrhoea transmission without using antibiotics. We modelled the effect that antiseptic mouthwash may have on the incidence of gonorrhoea.Design We developed a mathematical model of the transmission of gonorrhoea between each anatomical site (oropharynx, urethra and anorectum) in men who have sex with men (MSM). We constructed four scenarios: (1) mouthwash had no effect; (2) mouthwash increased the susceptibility of the oropharynx; (3) mouthwash reduced the transmissibility from the oropharynx; (4) the combined effect of mouthwash from scenarios 2 and 3.Setting We used data at three anatomical sites from 4873 MSM attending Melbourne Sexual Health Centre in 2018 and 2019 to calibrate our models and data from the USA, Netherlands and Thailand for sensitivity analyses.Participants Published available data on MSM with multisite infections of gonorrhoea.Primary and secondary outcome measures Incidence of gonorrhoea.Results The overall incidence of gonorrhoea was 44 (95% CI 37 to 50)/100 person-years (PY) in scenario 1. Under scenario 2 (20%–80% mouthwash coverage), the total incidence increased (47–60/100 PY) and at all three anatomical sites by between 7.4% (5.9%–60.8%) and 136.6% (108.1%–177.5%). Under scenario 3, with the same coverage, the total incidence decreased (20–39/100 PY) and at all anatomical sites by between 11.6% (10.2%–13.5%) and 99.8% (99.2%–100%). Under scenario 4, changes in the incidence depended on the efficacy of mouthwash on the susceptibility or transmissibility. The effect on the total incidence varied (22–55/100 PY), and at all anatomical sites, there were increases of nearly 130% and large declines of almost 100%.Conclusions The effect of mouthwash on gonorrhoea incidence is largely predictable depending on whether it increases susceptibility to or reduces the transmissibility of gonorrhoea.

Background: Gynecological cancers, including cervical cancer, ovarian cancer and endometrial cancer are leading causes of cancer-related death in women worldwide. Diet plays an important role in cancer development, which is widely accepted. However, the associations between dietary intakes and gynecological cancers remain unclear. Methods: A total of 12,437 women aged over 20 years from the National Health and Nutrition Examination Survey (NHANES), conducted from 2007–2016, were included in this study. The relationships between 30 dietary factors (4 macronutrients, 15 vitamins, 9 minerals, caffeine and alcohol) and gynecological cancers were assessed. Results: We observed negative correlations of intakes of phosphorus (odds ratio (OR), 95% confidence interval (CI); 0.998 (0.996, 0.999), p = 0.002) with cervical cancer, and intakes of vitamin B12 (0.812 (0.714, 0.925), p = 0.002), phosphorus (0.997 (0.996, 0.999), p < 0.001) and alcohol (0.971 (0.950, 0.992), p = 0.009) with endometrial cancer. The data showed positive associations of intake of caffeine (1.002 (1.001, 1.003), p = 0.003) with cervical cancer, and intake of copper (2.754 (1.313, 5.778), p = 0.009) with endometrial cancer. In addition, we found potential negative correlations between intake of vitamin B1 (p = 0.025) and cervical cancer; zinc (p = 0.048) and ovarian cancer; and potassium (p = 0.032) and endometrial cancer. Potential positive associations were found between intake of calcium and cervical cancer (p = 0.026) and endometrial cancer (p = 0.034), and between sodium (p = 0.042) and endometrial cancer. Intakes of protein, total sugars, total fat, cholesterol, vitamin A, alpha-carotene, beta-carotene, beta-cryptoxanthin, lycopene, vitamin B2, niacin, vitamin B6, food folate, vitamin C, vitamin D, vitamin E, vitamin K, magnesium, iron and selenium showed no relationship with gynecological cancers (p > 0.05). Conclusions: Specific dietary factors were associated with gynecological cancers. More epidemiological studies are needed to validate our results.

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently.Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19.Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method.Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0–17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0–17 and 18–44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC.Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

Hubei province in China has completed cycle of quarantine-resumption in 23rd Janauary and 8th April 2020, providing a unique opportunity as for now to assess its intervention impact and the pattern of SARS-COV-2 transmission during the quarantine period. In this study, we evaluate the impact of the metropolitan-wide quarantine on the trend and transmission route of the COVID-19 epidemic in Hubei, China. The intervention reduces more than 70% of new infections in both households and the public space, as well as the deaths caused by COVID-19 pneumonia. Household transmission is the dominant route of disease spread regardless of quarantine. This will provide important evidence and scientific insights to other worldwide countries that are currently under quarantine.

It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1–6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275–3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = −0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.

The ongoing global pandemic of COVID-19 poses unprecedented public health risks for governments and societies around the world, which have been exacerbated by the emergence of SARS-CoV-2 variants. Pharmaceutical interventions with high antiviral efficacy are expected to delay and contain the COVID-19 pandemic. Molnupiravir, as an oral antiviral prodrug, is active against SARS-CoV-2 and is now (23 February 2022) one of the seven widely-used coronavirus treatments. To estimate its antiviral efficacy of Molnupiravir, we built a granular mathematical within-host model. We find that the antiviral efficacy of Molnupiravir to stop the growth of the virus is 0.56 (95% CI: 0.49, 0.64), which could inhibit 56% of the replication of infected cells per day. There has been good progress in developing high-efficacy antiviral drugs that rapidly reduce viral load and may also reduce the infectiousness of treated cases if administered as early as possible.

Yuming Guo and colleagues discuss the research by Teslya et al that highlights the importance of personal preventative measures in avoiding a second wave of the COVID-19 epidemic.

Summary: Background: The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19. Lifting of this quarantine is imminent. We modelled the effects of two key health interventions on the epidemic when the quarantine is lifted. Methods: We constructed a compartmental dynamic model to forecast the trend of the COVID-19 epidemic at different quarantine lifting dates and investigated the impact of different rates of public contact and facial mask usage on the epidemic. Results: We projected a declining trend of the COVID-19 epidemic if the current quarantine strategy continues, and Wuhan would record the last new confirmed cases in late April 2020. At the end of the epidemic, 65,733 (45,722-99,015) individuals would be infected by the virus, among which 16,166 (11,238-24,603, 24.6%) were through public contacts, 45,996 (31,892-69,565, 69.7%) through household contact, and 3,571 (2,521-5,879, 5.5%) through hospital contacts (including 778 (553-1,154) non-COVID-19 patients and 2,786 (1,969-4,791) medical staff). A total of 2,821 (1,634-6,361) would die of COVID-19 related pneumonia in Wuhan. Early quarantine lifting on 21st March is viable only if Wuhan residents sustain a high facial mask usage of ≥85% and a pre-quarantine level public contact rate. Delaying city resumption to mid/late April would relax the requirement of facial mask usage to ≥75% at the same contact rate. Conclusions: The prevention of a second epidemic is viable after the metropolitan-wide quarantine is lifted but requires a sustaining high facial mask usage and a low public contact rate.

Abstract Background Poor adherence to either antiretroviral treatment (ART) or pre-exposure prophylaxis (PrEP) can promote drug resistance, though this risk is thought to be considerably higher for ART. In the population of men who have sex with men (MSM) in San Francisco, PrEP coverage reached 9.6% in 2014 and has continued to rise. Given the risk of drug resistance and high cost of second-line drugs, the costs and benefits of initiating ART earlier while expanding PrEP coverage remain unclear. Methods We develop an infection–age-structured mathematical model and fit this model to the annual incidence of AIDS cases and deaths directly, and to resistance and demographic data indirectly. We investigate the impact of six various intervention scenarios (low, medium, or high PrEP coverage, with or without earlier ART) over the next 20 years. Results Low (medium, high) PrEP coverage with earlier ART could prevent 22% (42%, 57%) of a projected 44,508 total new infections and 8% (26%, 41%) of a projected 18,426 new drug-resistant infections, and result in a gain of 43,649 (74,048, 103,270) QALYs over 20 years compared to the status quo, at a cost of $4745 ($78,811, $115,320) per QALY gained, respectively. Conclusions High PrEP coverage with earlier ART is expected to provide the greatest benefit but also entail the highest costs among the strategies considered. This strategy is cost-effective for the San Francisco MSM population, even considering the acquisition and transmission of ART-mediated drug resistance. However, without a substantial increase to San Francisco’s annual HIV budget, the most advisable strategy may be initiating ART earlier, while maintaining current strategies of PrEP enrollment.

An epidemiological model is proposed and studied to understand the transmission dynamics and prevalence of HCV infection in China. Theoretical analysis indicates that the basic reproduction number R0 provides a threshold value determining whether the disease dies out or not. Two Lyapunov functions are constructed to prove the global asymptotic stability of the disease-free and the endemic equilibria, respectively. Based on data reported by the National Health and Family Planning Commission of China, the basic reproduction number is estimated as approximately R0=1.9897, which is much less than that for the model when a treatment strategy is not considered. An ever-increasing HCV infection is predicted in the near future. Numerical simulations, performed to investigate the potential effect of antiviral treatment, show that increasing the treatment cure rate and enlarging the treatment rate for patients at the chronic stage remain effective in reducing the number of new infections and the equilibrium prevalence. The finding suggests that treatment measures are significantly beneficial for disease control in terms of reducing new infections and, in particular, more attention should be paid to treatment for patients at the chronic stage.