BACKGROUND: Considering that many new HIV infections are transmitted by homosexual behaviors, gay, bisexual, and other men who have sex with men (GBMSM) are more likely to be infected with HIV than other groups due to the higher risk associated with unprotected anal intercourse. It is important to explore the changes in sexual behaviors and HIV-related knowledge among GBMSM in the last 10 years, which could provide evidence for improving public health interventions to reduce HIV infections.
OBJECTIVE: The study sought to explore the changes of 3 sexual behaviors and HIV knowledge among men who have sex with men from 2011 to 2021.
METHODS: Data were collected from national HIV sentinel surveillance among GBMSM in Hangzhou conducted between 2011 and 2021. Univariate and multivariate logistic regression were used to analyze the associated factors of sexual behaviors. The variation trend of variables was evaluated based on the linear trend test in the regression model.
RESULTS: A total of 5111 GBMSM with an average age of 32.00 years were incorporated in the analysis. From 2011 to 2021, the HIV-related knowledge score of GBMSM ranged from 6 to 7.5, and it increased significantly (P trend < .001). The rate of homosexual sex in the past 6 months remained at a high level (75.06%-82.75%). Homosexual behavior was associated with a higher HIV-related knowledge score (P = .004). Heterosexual sex was associated with an increase in the old age, married persons, and domicile outside the province (P < .05). Commercial sex was associated with an increase in drug users (P <.001).
CONCLUSIONS: In the past 10 years, HIV-related knowledge of GBMSM increased and the rate of unprotected sex was at a high level among GBMSM, especially in heterosexual behaviors. Moreover, the likelihood of having homosexual behaviors is raised with the increasing HIV-related knowledge. Conducting precise behavioral interventions for GBMSM are crucial for preventing HIV infection.

This research article presents a comprehensive analysis aimed at enhancing the stochastic modeling of COVID-19 dynamics by incorporating vaccination classes through a higher-order spectral scheme. The ongoing COVID-19 pandemic has underscored the critical need for accurate and adaptable modeling techniques to inform public health interventions. In this study, we introduce a novel approach that integrates various vaccination classes into a stochastic model to provide a more nuanced understanding of disease transmission dynamics. We employ a higher-order spectral scheme to capture complex interactions between different population groups, vaccination statuses, and disease parameters. Our analysis not only enhances the predictive accuracy of COVID-19 modeling but also facilitates the exploration of various vaccination strategies and their impact on disease control. The findings of this study hold significant implications for optimizing vaccination campaigns and guiding policy decisions in the ongoing battle against the COVID-19 pandemic.

This research aims to assess the effectiveness and cost-effectiveness of pre-pregnancy deafness screening policies.
Married couples from Shanghai, Beijing, and Suzhou in China were enrolled. We conducted high-throughput, pre-pregnancy genetic screenings for deafness in women and their partners. We compared the cost-effectiveness of deafness genetic screening with the status quo. The two-step screening (wife then partner) and following treatments and interventions were included in the decision tree model. We conducted a cost-effectiveness analysis based on the decrease in deaf newborns, healthy newborn births, and cost-utility analysis of pre-pregnancy deafness genetic screening separately. Cost, utility, and probability data used in the three models were collected from a survey combined with literature and expert consultants. A 5% discount rate and a series of one-way sensitivity analyses along with a Monte Carlo simulation were used to test the reliability of this research.
Between Jan 1, 2019, and Dec 31, 2021, we recruited 6,200 females and 540 male spouses from community health service centers in Shanghai, Beijing, and Suzhou. The incremental cost-effectiveness ratio (ICER) for reducing deaf newborn births was USD 32,656 per case and USD 1,203,926 per case for increasing one healthy newborn birth. This gap exists because of the overall decrease of newborn births. From the perspective of the whole society, deafness genetic screening is not cost-effective for reducing the overall quality-adjusted life years (QALY) in the population.
Pre-pregnancy genetic testing is effective in decreasing the occurrence of congenital deafness. It is a cost-saving measure when compared with the costs of future medical expenditure and income loss for the affected families. However, such screening and preventive avoidance of pregnancy will decrease the population size and QALY. Only post-screening ART with PGT was shown to increase the birth of healthy newborns. Focusing on key groups such as premature births or consanguineous couples may improve the societal effects of screening.

OBJECTIVE: To evaluate the impact of early implementation of public health and social measures (PHSMs) on contact rates over time and explore contact behavior of asymptomatic versus symptomatic cases.
METHODS: We used the largest contact tracing data in China thus far to estimate the mean contacts over time by age groups and contact settings. We used bootstrap with replacement to quantify the uncertainty of contact matrixes. The Pearson correlation was performed to demonstrate the number of contacts over time in relation to the evolution of restrictions. In addition, we analyzed the index cases with a high number of contacts and index cases that produced a high number of secondary cases.
RESULTS: Rapidly adapted PHSMs can reduce the mean contact rates in public places while increasing the mean contact rates within households. The mean contact rates were 11.81 (95% confidence interval, 11.61-12.01) for asymptomatic (at the time of investigation) cases and 6.70 (95% confidence interval, 6.54-6.87) for symptomatic cases. The percentage of asymptomatic cases (at the time of investigation) meeting >50 close contacts make up more than 65% of the overall cases. The percentage of asymptomatic cases producing >10 secondary cases account for more than 80% of the overall cases.
CONCLUSIONS: PHSMs may increase the contacts within the household, necessitating the need for pertinent prevention strategies at home. Asymptomatic cases can contribute significantly to Omicron transmission. By making asymptomatic people aware that they are already contagious, hence limiting their social contacts, it is possible to lower the transmission risk.

The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi-directional mutation rate. Many new variants even have an immune-evading property, which means that some individuals with antibodies against one variant can be reinfected by other variants. As a result, the realistic is still suffering from new waves of COVID-19 by its new variants. How to control the transmission or even eradicate the COVID-19 pandemic remains a critical issue for the whole world. This work presents an epidemiological framework for mimicking the multi-directional mutation process of SARS-CoV-2 and the epidemic spread of COVID-19 under realistic scenarios considering multiple variants. The proposed framework is used to evaluate single and combined public health interventions, which include non-pharmaceutical interventions, pharmaceutical interventions, and vaccine interventions under the existence of multi-directional mutations of SARS-CoV-2. The results suggest that several combined intervention strategies give optimal results and are feasible, requiring only moderate levels of individual interventions. Furthermore, the results indicate that even if the mutation rate of SARS-CoV-2 decreased 100 times, the pandemic would still not be eradicated without appropriate public health interventions.

Most countries have adopted public activity intervention policies to control the coronavirus disease 2019 (COVID-19) pandemic. Nevertheless, empirical evidence of the effectiveness of different interventions on the containment of the epidemic was inconsistent.
We retrieved time-series intervention policy data for 145 countries from the Oxford COVID-19 Government Response Tracker from December 31, 2019, to July 1, 2020, which included 8 containment and closure policies. We investigated the association of timeliness, stringency, and duration of intervention with cumulative infections per million population on July 1, 2020. We introduced a novel counterfactual estimator to estimate the effects of these interventions on COVID-19 time-varying reproduction number (Rt).
There is some evidence that earlier implementation, longer durations, and more strictness of intervention policies at the early but not middle stage were associated with reduced infections of COVID-19. The counterfactual model proved to have controlled for unobserved time-varying confounders and established a valid causal relationship between policy intervention and Rt reduction. The average intervention effect revealed that all interventions significantly decrease Rt after their implementation. Rt decreased by 30% (22%-41%) in 25 to 32 days after policy intervention. Among the 8 interventions, school closing, workplace closing, and public events cancellation demonstrated the strongest and most consistent evidence of associations.
Our study provides more reliable evidence of the quantitative effects of policy interventions on the COVID-19 epidemic and suggested that stricter public activity interventions should be implemented at the early stage of the epidemic for improved containment.

Sewage surveillance could help develop proactive response to the Coronavirus Disease 2019 (COVID-19) pandemic, but currently there are limited reports about examples in practical exercises. Here, we report a use case of intensified sewage surveillance to initiate public health action to thwart a looming Delta variant outbreak in Hong Kong. On 21 June 2021, albeit under basically contained COVID-19 situation in Hong Kong, routine sewage surveillance identified a high viral load of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a sewage sample from one site covering over 33,000 population, suggesting infected cases living in the respective sewershed. The use of a newly developed method based on allele-specific real-time quantitative polymerase chain reaction (AS RT-qPCR) served to alert the first documentation of the Delta variant in local community sewage three days before the case was confirmed to be a Delta variant carrier. Intensified sewage surveillance was triggered. Targeted upstream sampling at sub-sewershed areas pinpointed the source of positive viral signal across spatial scales from sewershed to building level, and assisted in determining the specific area for issuing a compulsory testing order for individuals on 23 June 2021. A person who lived in a building with the positive result of sewage testing was confirmed to be infected with COVID-19 on 24 June 2021. Viral genome sequences determined from the sewage sample were compared to those from the clinic specimens of the matched patient, and confirmed that the person was the source of the positive SARS-CoV-2 signal in the sewage sample. This study could help build confidences for public health agencies in using the sewage surveillance in their own communities.

The coronavirus disease outbreak of 2019 (COVID-19) has been spreading rapidly to all corners of the word, in a very complex manner. A key research focus is in predicting the development trend of COVID-19 scientifically through mathematical modelling. We conducted a systematic review of epidemic prediction models of COVID-19 and the public health intervention strategies by searching the Web of Science database. 55 studies of the COVID-19 epidemic model were reviewed systematically. It was found that the COVID-19 epidemic models were different in the model type, acquisition method, hypothesis and distribution of key input parameters. Most studies used the gamma distribution to describe the key time period of COVID-19 infection, and some studies used the lognormal distribution, the Erlang distribution, and the Weibull distribution. The setting ranges of the incubation period, serial interval, infectious period and generation time were 4.9-7 days, 4.41-8.4 days, 2.3-10 days and 4.4-7.5 days, respectively, and more than half of the incubation periods were set to 5.1 or 5.2 days. Most models assumed that the latent period was consistent with the incubation period. Some models assumed that asymptomatic infections were infectious or pre-symptomatic transmission was possible, which overestimated the value of R0. For the prediction differences under different public health strategies, the most significant effect was in travel restrictions. There were different studies on the impact of contact tracking and social isolation, but it was considered that improving the quarantine rate and reporting rate, and the use of protective face mask were essential for epidemic prevention and control. The input epidemiological parameters of the prediction models had significant differences in the prediction of the severity of the epidemic spread. Therefore, prevention and control institutions should be cautious when formulating public health strategies by based on the prediction results of mathematical models.

BACKGROUND: Human mobility was associated with epidemic changes of coronavirus disease 2019 (COVID-19) in the countries, where strict public health interventions reduced human mobility and COVID-19 epidemics. But its association with COVID-19 epidemics in the European Union (EU) is unclear.
METHODS: In this quasi-experimental interrupted time-series study, we modelled trends in human mobility and epidemics of COVID-19 in 27 EU states between January 15 and May 9, 2020. The associations of lockdown-date, and turning points of these trends were assessed.
RESULTS: There were 982,332 laboratory-confirmed COVID-19 cases in the EU states (median 7,896, interquartile 1,689 to 25,702 for individual states) during the study-period. COVID-19 and human mobility had 3 trend-segments, including an upward trend in COVID-19 daily incidence and a downward trend in most human mobilities in the middle segment. Compared with the states farther from Italy, the state-wide lockdown dates were more likely linked to turning points of human mobilities in the states closer to Italy, which were also more likely linked to second turning points of COVID-19 epidemics. Among the examined human mobilities, the second turning points in driving mobility and the first turning points in parks mobility were the best factors that connected lockdown dates and COVID-19 epidemics in the EU states closer to Italy.
CONCLUSIONS: We show state- and mobility-heterogeneity in the associations of public health interventions and human mobility with the changes of COVID-19 epidemics in the EU. These findings may help inform policymakers on the best timing and monitoring-parameters of state-level interventions in the EU.

Background: Few studies have reported the transmission characteristics of coronavirus disease (COVID-19) in low-density populations. This study has therefore analyzed the epidemiological characteristics and clinical outcomes of COVID-19 patients in Northwestern China, an area with low population density. Methods: From January 21 to March 11, 2020, data from patients diagnosed with novel coronavirus pneumonia (NCP) in areas of Northwestern China with lower population densities were retrospectively analyzed. Certain variables were categorized as numbers and percentages, with the ratio between resident patients (no history of going out during the epidemic) and imported patients representing the contagiousness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for COVID-19. Hospitalization time was also calculated. Results: A total of 617 COVID-19 patients were reported in Northwestern China, and the morbidity and mortality rates of 0.000005 and 0.011, respectively. Further analysis showed that the morbidity was inversely proportional to population density and distance from Wuhan City. This study enrolled 473 confirmed cases; among these patients, there were 248 residents and 225 imported cases with a ratio of 1:1. The youngest and oldest patients were 1 and 94 years of age, respectively, with a median age of 42 years. Fifteen (3.2%) patients were children or infants. Two patients were pregnant, and one patient gave birth to a healthy baby with negative results during her disease course. About 17.3% of patients (82 cases) were healthy carriers without any symptoms during their disease course. One male patient (0.2%) had recurrence of a positive test result 4 days after discharge. The median hospitalization time was 16.0 days, ranging from 2.0 to 43.0 days. Further analysis showed that age (P = 0.03) and severity status (P < 0.001) were significantly correlated with hospitalization time. Conclusions: The morbidity and mortality rates of COVID-19 patients in the regions with a low population density were lower than those of the national average in China. All populations were susceptible to infection by SARS-CoV-2. Asymptomatic patients with positive results should be taken seriously, and the hospitalization time of patients is associated with their age and severity status.