This study, which demonstrates that the single-population Susceptible-Exposed-Infectious-Recovered (SEIR) model is also applicable to the assessment and prediction of vector-borne infectious disease outbreaks, provides a reliable model tool for the future prevention and control of vector-borne unknown (X) epidemics. One of the key contributions is the identification of a suitable interpretation of the model parameters. The EpiSIX prediction system, via application of a single SEIR model, was used to fit and analyse the 2025 Foshan City chikungunya fever epidemic data and the 2024-2025 dengue fever epidemics data from Guangdong Province. The results showed that the average serial interval of both fevers was approximately 11 days. The estimated basic reproduction number (R0) was around 6.0 for the chikungunya fever epidemic in Foshan City and approximately 4.0 and 3.0 for the 2024 and 2025 dengue fever epidemics in Guangdong Province, respectively. An additional prediction of the development trend of the ongoing 2025 dengue fever epidemic in Guangdong Province indicated that the final number of infections would range between 3400 and 6000 cases. Finally, a comparison between the uncontrolled developments of the omicron epidemic (with an average serial interval of 4 days) and the chikungunya fever epidemic (with an average serial interval of 11 days, 2.75 times that of omicron) under the same R0 value (5.60) showed that the omicron epidemic would last for 50 days, while the chikungunya fever epidemic would persist for 120 days. Theoretically, the pressure of the former on medical resources would be 2.5 times that of the latter. (c) 2026 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

The transmission and prevalence of Hand, Foot and Mouth Disease (HFMD) are affected by a variety of natural and socio-economic environmental factors. This study aims to quantitatively investigate the non-stationary and spatially varying associations between various environmental factors and HFMD risk. We collected HFMD surveillance cases and a series of relevant environmental data from 2013 to 2021 in Xi'an, Northwest China. By controlling the spatial and temporal mixture effects of HFMD, we constructed a Bayesian spatiotemporal mapping model and characterized the impacts of different driving factors into global linear, non-stationary and spatially varying effects. The results showed that the impact of meteorological conditions on HFMD risk varies in both type and magnitude above certain thresholds (temperature: 30 °C, precipitation: 70 mm, solar radiation: 13000 kJ/m2, pressure: 945 hPa, humidity: 69%). Air pollutants (PM2.5, PM10, NO2) showed an inverted U-shaped relationship with the risk of HFMD, while other air pollutants (O3, SO2) showed nonlinear fluctuations. Moreover, the driving effect of increasing temperature on HFMD was significant in the 3-year period, while the inhibitory effect of increasing precipitation appeared evident in the 5-year period. In addition, the proportion of urban/suburban/rural area had a strong influence on HFMD, indicating that the incidence of HFMD firstly increased and then decreased during the rapid urbanization process. The influence of population density on HFMD was not only limited by spatial location, but also varied between high and low intervals. Higher road density inhibited the risk of HFMD, but higher night light index promoted the occurrence of HFMD. Our findings further demonstrated that both ecological and socioeconomic environmental factors can pose multiple driving effects on increasing the spatiotemporal risk of HFMD, which is of great significance for effectively responding to the changes in HFMD epidemic outbreaks.

Background During 2021-2022, mainland China experienced multiple times of local COVID-19 outbreaks in several cities, including Yangzhou, Xi'an etc., and the Chinese government persistently adopted the zero-COVID policy in combating with the local outbreaks.Methods We develop a mathematical model with pulse population-wide nucleic acid screening, part of the zeroCOVID policy, to reveal its role in controlling the spread of COVID-19. We calibrate the model by fitting the COVID-19 epidemic data of the local outbreaks in Yangzhou and Xi'an, China. Sensitivity analysis is conducted to investigate the impact of population-wide nucleic acid screening on controlling the outbreak of COVID-19.Results Without the screening, the cumulative number of confirmed cases increases by 77.7% and 62.2% in Yangzhou and Xi'an, respectively. Meanwhile, the screening program helps to shorten the lockdown period for more than one month when we aim at controlling the cases into zero. Considering its role in mitigating the epidemics, we observe a paradox phenomenon of the screening rate in avoiding the runs on medical resource. That is, the screening will aggravate the runs on medical resource when the screening rate is small, while it helps to relieve the runs on medical resource if the screening rate is high enough. We also conclude that the screening has limited effects on mitigating the epidemics if the outbreak is in a high epidemic level or there has already been runs on medical resources. Alternatively, a smaller screening population per time with a higher screening frequency may be a better program to avoid the runs on medical resources.Conclusions The population-wide nucleic acid screening strategy plays an important role in quickly controlling and stopping the local outbreaks under the zero-COVID policy. However, it has limited impacts and even increase the potential risk of the runs on medical resource for containing the large scale outbreaks.

Background:A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established a with age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios. Methods:All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios. Results:Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days. Conclusions:Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

Varicella is a highly prevalent infectious disease with a similar transmission pathway to coronavirus disease 2019 (COVID-19). In the context of the COVID-19 pandemic, anti-COVID-19 non-pharmaceutical interventions (NPIs) have been implemented to prevent the spread of the infection. This study aims to analyze varicella’s epidemiological characteristics and further investigate the effect of anti-COVID-19 NPIs on varicella in Xi’an, northwestern China. Based on the varicella surveillance data, search engine indices, meteorological factors from 2011 to 2021 in Xi’an, and different levels of emergency response to COVID-19 during the pandemic, we applied Bayesian Structural Time Series models and interrupted time series analysis to predict the counterfactual incidence of varicella and quantify the impact of varying NPIs intensities on varicella. From 2011 to 2021, varicella incidence increased, especially in 2019, with a high incidence of 111.69/100,000. However, there was a sharp decrease of 43.18% in 2020 compared with 2019, and the peak of varicella incidence in 2020 was lower than in previous years from the 21st to the 25th week. In 2021, the seasonality of varicella incidence gradually returned to a seasonal pattern in 2011-2019. The results suggest that anti-COVID-19 NPIs effectively reduce the incidence of varicella, and this reduction has spatiotemporal heterogeneity.

The number of measles cases reported worldwide has increased in recent years, and in 2015, there was a measles outbreak in Xi’an, China. However, the epidemiology of measles and the seroepidemiology of healthy people after 2015 have not been fully understood. We collected fingertip blood samples from healthy people around each suspected measles case in Xi’an in 2016-2018 and tested IgG using ELISA. Eighty measles cases were reported in Xi’an in 2016–2018, with an average annual incidence of 0.29 per 100,000 persons. Children aged ≤ 5 years and adults aged 25-29 accounted for a large proportion of measles cases. More than half of the cases in the 0-year group were under 8 months. A total of 5476 blood samples from healthy people were collected. Apart from 1-4 years and over 40, other age groups’ seroprevalence was 93%. Our findings suggest that the first vaccine shot should be administered at 6 months or earlier, the second at 12 months, and the third at 10 years, and couples prepared for [pregnancy](javascript:showjdsw(’showlj_1’,’lj_1’)) should be vaccinated with another dose. The findings may provide novel insights into measles elimination.

The prediction system EpiSIX was used to study the COVID-19 epidemic in mainland China between November 2022 and January 2023, based on reported data from December 9, 2022, to January 30, 2023, released by The Chinese Center for Disease Control and Prevention on February 1, 2023. Three kinds of reported data were used for model fitting: the daily numbers of positive nucleic acid tests and deaths, and the daily number of hospital beds taken by COVID-19 patients. It was estimated that the overall infection rate was 87.54% and the overall case fatality rate was 0.078%–0.116% (median 0.100%). Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023, induced by a slightly more infectious mutant strain, we predicted a possible large rebound between September and October 2023, with a peak demand of between 800,000 and 900,000 inpatient beds. If no such new outbreak was induced by other variants, then the current COVID-19 epidemic course in mainland China would remain under control until the end of 2023. However, it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future, especially for the period between September and October 2023.

Several local outbreaks have occurred and been suppressed with the dynamic zero-COVID policy and widely promoted vaccination program implemented in China. The epidemic duration and final size vary significantly in different cities, which may be attributed to different implementation patterns and intensities of non-pharmaceutical interventions (NPIs). It's important to capture the underlying mechanism to explore more efficient implementation patterns of NPIs in order to prevent the future resurgence. In this study, outbreaks caused by Delta variant in Xi'an, Yangzhou and Guangzhou in 2021 are chosen as the examples. A novel model dividing the population into three groups is proposed to describe the heterogeneity of control interventions. The model is calibrated and key parameters related to NPIs are estimated by using multi-source epidemic data. The estimation results show a lower transmission probability but a higher initial reproduction number in Xi'an. Sensitivity analysis are conducted to investigate the impact of various control measures in different epidemic phases. The results identify the vital role of enhancing closed-off management, strengthening tracing and testing intensities, on shortening the epidemic durations and reducing the final size. Further, we find that sufficiently implemented closed-off management would prevent the city from lockdown. Strengthening the tracing other than the testing strategy in the initial stage is more effective on containing the epidemic in a shorter duration with less infections.

The World Health Organization (WHO) declared monkeypox as a public health emergency of international concern (PHEIC) on July 23, 2022, their highest level of alert. This raised concerns about the management of the global monkeypox outbreak, as well as the scientific analysis and accurate prediction of the future course of the epidemic. This study used EpiSIX (an analysis and prediction system for epidemics based on a general SEIR model) to analyze the monkeypox epidemic and to forecast the major tendencies based on data from the USA CDC (https://www.cdc.gov) and the WHO (https://www.who.int/health-topics/monkeypox). The global outbreak of monkeypox started in the UK on May 2, 2022, which marked the beginning of an epidemic wave. As of October 28, 2022, the cumulative number of reported cases worldwide was 77,115, with 36 deaths. EpiSIX simulations predict that the global monkeypox epidemic will enter a low epidemic status on March 1, 2023 with the cumulative number of confirmed cases ranging from 85,000 to 124,000, and the total number of deaths ranging from 60 to 87. Our analysis revealed that the basic reproduction number (R0) of monkeypox virus (MPXV) is near to 3.1 and the percentage of asymptomatic individuals is 13.1 %-14.5 %, both of which are similar to the data for SARS. The vaccination efficiency against susceptibility (VEs) of individuals who have had monkeypox is ∼ 79 %, and the vaccination efficiency against infectiousness (VEi) of individuals who have had monkeypox is ∼ 76 %-82 %. The mean incubation period for monkeypox is 8 days. In total, 94.7 % of infected individuals develop symptoms within 20 days and recover within 2 weeks after the confirmation of symptoms. Simulation results using EpiSIX showed that ring vaccination was remarkably effective against monkeypox. Our findings confirmed that a 20-day isolation for close contacts is necessary.

Introduction: Modeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and prediction of optimal early warning timing: the logistic differential equation (LDE) model and the more complex generalized logistic differential equation (GLDE) model. This study aimed to compare and analyze these two models. Methods: We collected data on (coronavirus disease 2019) COVID-19 and four other infectious diseases and classified the data into four categories: different transmission routes, different epidemic intensities, different time scales, and different regions, using R-2 to compare and analyze the goodness-of-fit of LDE and GLDE models. Results: Both models fitted the epidemic curves well, and all results were statistically significant. The R-2 test value of COVID-19 was 0.924 (p < 0.001) fitted by the GLDE model and 0.916 (p < 0.001) fitted by the LDE model. The R-2 test value varied between 0.793 and 0.966 fitted by the GLDE model and varied between 0.594 and 0.922 fitted by the LDE model for diseases with different transmission routes. The R-2 test values varied between 0.853 and 0.939 fitted by the GLDE model and varied from 0.687 to 0.769 fitted by the LDE model for diseases with different prevalence intensities. The R-2 test value varied between 0.706 and 0.917 fitted by the GLDE model and varied between 0.410 and 0.898 fitted by the LDE model for diseases with different time scales. The GLDE model also performed better with nation-level data with the R-2 test values between 0.897 and 0.970 vs. 0.731 and 0.953 that fitted by the LDE model. Both models could characterize the patterns of the epidemics well and calculate the acceleration weeks. Conclusion: The GLDE model provides more accurate goodness-of-fit to the data than the LDE model. The GLDE model is able to handle asymmetric data by introducing shape parameters that allow it to fit data with various distributions. The LDE model provides an earlier epidemic acceleration week than the GLDE model. We conclude that the GLDE model is more advantageous in asymmetric infectious disease data simulation.

Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis characterized by clinical features of high fever, hemorrhage, and renal damage. China has the largest number of HFRS cases worldwide, accounting for over 90% of the total reported cases. In this paper, we used surveyed HFRS data and satellite imagery to conduct geostatistical analysis for investigating the associations of rapid urbanization, water bodies, and other factors on the spatiotemporal dynamics of HFRS from year 2005 to 2018 in Xi'an City, Northwest China. The results revealed an evident epidemic aggregation in the incidence of HFRS within Xi'an City with a phenomenal fluctuation in periodic time series. Rapid urbanization was found to greatly affect the HFRS incidence in two different time phases. HFRS caused by urbanization influences farmers to a lesser extent than it does to non-farmers. The association of water bodies with the HFRS incidence rate was found to be higher within the radii of 696.15 m and 1575.39 m, which represented significant thresholds. The results also showed that geomatics approaches can be used for spatiotemporally investigating the HFRS dynamic characteristics and supporting effective allocations of resources to formulate strategies for preventing epidemics.

Growing evidence has shown that anti-COVID-19 nonpharmaceutical interventions (NPIs) can support prevention and control of various infectious diseases, including intestinal diseases. However, most studies focused on the short-term mitigating impact and neglected the dynamic impact over time. This study is aimed to investigate the dynamic impact of anti-COVID-19 NPIs on hand, foot, and mouth disease (HFMD) over time in Xi'an City, northwestern China. Based on the surveillance data of HFMD, meteorological and web search data, Bayesian Structural Time Series model and interrupted time series analysis were performed to quantitatively measure the impact of NPIs in sequent phases with different intensities and to predict the counterfactual number of HFMD cases. From 2013 to 2021, a total number of 172,898 HFMD cases were reported in Xi'an. In 2020, there appeared a significant decrease in HFMD incidence (-94.52%, 95% CI: -97.54% to -81.95%) in the first half of the year and the peak period shifted from June to October by a small margin of 6.74% compared to the previous years of 2013 to 2019. In 2021, the seasonality of HFMD incidence gradually returned to the bimodal temporal variation pattern with a significant average decline of 61.09%. In particular, the impact of NPIs on HFMD was more evident among young children (0-3 years), and the HFMD incidence reported in industrial areas had an unexpected increase of 51.71% in 2020 autumn and winter. Results suggested that both direct and indirect NPIs should be implemented as effective public health measures to reduce infectious disease and improve surveillance strategies, and HFMD incidence in Xi'an experienced a significant rebound to the previous seasonality after a prominent decline influenced by the anti-COVID-19 NPIs.

目的 分析2011-2020年西安市肺结核的发病情况和流行趋势,为制定防控策略和措施提供科学依据.方法 收集2011-2020年西安市肺结核登记资料,采用Joinpoint回归模型评价2011-2020年西安市肺结核发病特征的时间变化趋势.结果 2011-2020年西安市共报告肺结核患者45 458例,肺结核粗报告发病率年平均为49.49/10万,标化报告发病率年平均为46.97/10万,2011-2020年肺结核标化报告发病率整体呈上升趋势.男女标化报告发病率分别为60.05/10万和33.26/10万,男性报告发病率显著高于女性,差异有统计学意义(x2=509 206.81,P＜0.05),且二者在2011-2020年均呈上升趋势.新增肺结核患者中利福平耐药患者的比例呈逐年上升趋势,平均每年上升19.0％(P＜0.05).肺结核患者中初治患者的比例呈逐年上升趋势,平均每年上升0.6％(P＜0.05),其中利福平耐药患者中初治患者比例上升较快,平均每年上升15.1％(P＜0.05).结论 2011-2020年西安市肺结核报告发病率呈上升趋势,新增肺结核患者中利福平耐药患者的比例及初治患者的比例上升较快,提示要扩大耐药筛查范围,及早发现并治疗肺结核患者,减少耐药结核杆菌的持续传播.

The mass vaccination program has been actively promoted since the end of 2020. However, waning immunity, antibody-dependent enhancement (ADE), and increased transmissibility of variants make the herd immunity untenable and the implementation of dynamic zero-COVID policy challenging in China. To explore how long the vaccination program can prevent China at low resurgence risk, and how these factors affect the long-term trajectory of the COVID-19 epidemics, we developed a dynamic transmission model of COVID-19 incorporating vaccination and waning immunity, calibrated using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and two doses reach 77.92% on 31 August 2021. However, despite the mass vaccination, randomly introducing infected cases in the post-vaccination period causes large outbreaks quickly with waning immunity, particularly for SARS-CoV-2 variants with higher transmissibility. The results showed that with the current vaccination program and 50% of the population wearing masks, mainland China can be protected at low resurgence risk until 8 January 2023. However, ADE and higher transmissibility for variants would significantly shorten the low-risk period by over 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequent outbreaks decrease, indicating that subsequent outbreaks boosted immunity in the population level, further indicating that follow-up vaccination programs can help mitigate or avoid the possible outbreaks. The findings revealed that the integrated effects of multiple factors: waning immunity, ADE, relaxed interventions, and higher variant transmissibility, make controlling COVID-19 challenging. We should prepare for a long struggle with COVID-19, and not entirely rely on the COVID-19 vaccine.

目的 探讨陕西省手足口病疫情的时空演变规律,为优化手足口病的防控策略提供科学依据.方法 陕西省2013-2017年手足口病疫情个案数据来源于中国疾病预防控制信息系统,同期人口数据来源于陕西省统计年鉴,采用R 3.4.1、ArcGIS 10.2和SaTScan 9.2软件进行时空流行病学特征分析.结果 陕西省2013-2017年累计报告手足口病284 225例,年均发病率150.45/10万;历年4-7月病例数占总病例数的70.69％,高发病率区县主要分布在关中地区的中东部区域.重症病例、死亡病例分布与总病例的空间分布基本一致.时空扫描分析显示,全省2013-2017年手足口病存在4个高发热点区域;疫情的一类聚集区固定在以西安市为中心的全省中部和东南部区县(RR=2.25,95％CI:2.18～3.11,P＜0.001),但二类聚集区位置不固定.全省2013-2017.年手足口病的优势流行病原为其他肠道病毒.结论 陕西省手足口病疫情存在显著的时空聚集性特征,近年来病原以其他肠道病毒为主,呈现多病原交替流行;应针对不同时段和地区采取针对性的措施,以有效控制发病.

目的 分析手足口病病例可能的感染来源和影响发病的主要因素,为制定手足口病的针对性防控策略提供科学依据.方法 采用随机整群抽样方法,于2019-03/07在全市使用统一的调查问卷开展1:1现场病例对照调查和数据收集.采用广义估计模型和Logistic回归分析方法分析手足口病发病的危险因素及保护因素.结果 累计调查1936人,问卷回收率99.05％(1 936/2 080).统计分析显示儿童年龄、现住址类型、初步诊断、看护人文化、是否多次转诊、洗手与晾晒衣被、通风与消毒是手足口病发病的影响因素,其中,小年龄、首发症状为高热、初步诊断不明确、多次转诊、首发症状到初诊的间隔时间长、EV71感染是手足口病重症病例发生的危险因素.结论 西安市儿童手足口病发病有明显的危险因素,应采取针对性措施积极控制手足口病疫情.

目的 明确2019年不同水文期X市汉江水源水及其自来水中有机提取物的致突变性强度水平现状、变化趋势以及常规水处理工艺与管网输送对此趋势的影响.方法 应用XAD-2大孔树脂富集汉江流域X城市水源水、出厂水、末梢水中的有机物,经洗脱、浓缩、干燥制得非挥发性有机物(NOCs)干品,运用Ames试验检测并比较各水样中NOCs的致突变性.结果 在0.5～4.0L/皿的测试浓度范围内,枯水期出厂水、末梢水的NOCs对TA98(±S9)的致突变性检测结果为阳性(MR值＞2),在加S9后致突变性降低(MR值降低);其余水样的检测结果均为阴性.平水期出厂水、末梢水的NOCs仅对TA98(-S9)的检测结果为阳性,在加S9后致突变性降低;其余水样的检测结果均为阴性.丰水期时,除汉江出厂水外,其他水样对TA98(±S9)的检测结果均为阴性.但各水文期各水样NOCs对TA100(±S9)的检测结果均为阴性.出现阳性结果时的最低水样量为1.0 L/皿.结论 2019年X市的汉江供水水体(水源水及其自来水)中的有机提取物具有一定的致突变性.Ames试验呈阳性时的水质属于中度污染.致突变性强度依次为枯水期＞平水期＞丰水期.水源水经自来水厂消毒处理后,水中有机物致突变性增强,但经过管网后有所降低.水样中非挥发性有机致突变物的作用类型主要为移码突变型.

Since the end of 2020, the mass vaccination has been actively promoted and seemed to be effective to bring the COVID-19 pandemic under control. However, the fact of immunity waning and the possible existence of antibody-dependent enhancement (ADE) make the situation uncertain. We developed a dynamic model of COVID-19 incorporating vaccination and immunity waning, which was calibrated by using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. We explored how long the current vaccination program can prevent China in a low risk of resurgence, and how ADE affects the long-term trajectory of COVID-19 epidemics. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and with two-doses reach 77.92% on August 31, 2021. However, even with the mass vaccination, randomly introducing infected cases in the post-vaccination period can result in large outbreaks quickly in the presence of immunity waning, particularly for SARS-CoV-2 variants with higher transmission ability. The results showed that with the current vaccination program and a proportion of 50% population wearing masks, mainland China can be protected in a low risk of resurgence till 2023/01/18. However, ADE effect and higher transmission ability for variants would significantly shorten the protective period for more than 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequential outbreaks are decreasing, meaning that subsequential outbreaks boosted the immunity in the population level, which further indicating that catching-up vaccination program can help to mitigate the possible outbreaks, even avoid the outbreaks. The findings reveal that integrated effects of multiple factors, including immunity waning, ADE, relaxed interventions, and higher transmission ability of variants, make the control of COVID-19 much more difficult. We should get ready for a long struggle with COVID-19, and should not totally rely on COVID-19 vaccine.

Hand, foot, and mouth disease (HFMD) is a common infectious disease in the Asia-Pacific region that primarily affects children younger than 5 years. Previous studies have confirmed that the seasonal transmission of this disease is strongly related to meteorological factors, but the results are not consistent. In addition, the associations between weather conditions and HFMD in northwestern China have not been investigated. Therefore, we aimed to examine this issue in Xi'an, the largest city of northwestern China that has been suffering from serious HFMD epidemics. In the current study, data for HFMD and six meteorological factors were collected from 2009 to 2018. Using cross-correlation analysis, the Granger causality test, and the distributed lag nonlinear model, we estimated the quantitative relationships and exposure-lag-response effects between weekly meteorological factors and HFMD incidence among children. We found that the seasonal distribution of HFMD in Xi'an has two peaks each year and is significantly impacted by the weekly temperature, precipitation, and evaporation over an 8-week period. Higher values of temperature and evaporation had positive associations with disease transmission, whereas the association between precipitation and HFMD showed an inverted-U shape. The maximum relative risks (RRs) of HFMD for the weekly mean temperature (approximately 31.1 degrees C), weekly cumulative evaporation (57.9 mm), and weekly cumulative precipitation (30.0 mm) were 1.56 (95% CI: 1.35-1.81), 1.40 (95% CI: 1.05-1.88), and 1.16 (95% CI: 1.11-1.70), respectively. The identified risk determinants and lag effects could provide important information for early interventions to reduce the local disease burden.

目的 分析西安市手足口病聚集性疫情的流行病学和病原学特征,为防控工作提供科学依据.方法 采用描述性流行病学方法对西安市2014-2019年手足口病聚集性疫情数据进行分析,通过RT-PCR方法进行病原鉴定.采用SPSS 20.0软件进行Mann-Whitney U检验、χ2检验.结果 西安市2014-2019年累计报告手足口病聚集性疫情4246起,涉及病例11280例.聚集性疫情每年主要发生在4～7月(58.10％).雁塔区、长安区和未央区的疫情数位居全市前3位.疫情发生场所以托幼机构为主(87.52％).疫情的肠道病毒阳性检出率为56.99％(1671/2932),其中以Cox A16(23.53％,690/2932)为主.疫情发生报告间隔与疫情持续时间、发病人数呈正相关(r分别为0.727、0.502,P<0.05).结论 西安市手足口病聚集性疫情主要发生在托幼机构,春夏季高发.