Infectious Diseases of Poverty

RationaleSeveral studies have estimated basic production number of novel coronavirus pneumonia (NCP). However, the time-varying transmission dynamics of NCP during the outbreak remain unclear. ObjectivesWe aimed to estimate the basic and time-varying transmission dynamics of NCP across China, and compared them with SARS. MethodsData on NCP cases by February 7, 2020 were collected from epidemiological investigations or official websites. Data on severe acute respiratory syndrome (SARS) cases in Guangdong Province, Beijing and Hong Kong during 2002-2003 were also obtained. We estimated the doubling time, basic reproduction number (R0) and time-varying reproduction number (Rt) of NCP and SARS. Measurements and main resultsAs of February 7, 2020, 34,598 NCP cases were identified in China, and daily confirmed cases decreased after February 4. The doubling time of NCP nationwide was 2.4 days which was shorter than that of SARS in Guangdong (14.3 days), Hong Kong (5.7 days) and Beijing (12.4 days). The R0 of NCP cases nationwide and in Wuhan were 4.5 and 4.4 respectively, which were higher than R0 of SARS in Guangdong (R0=2.3), Hongkong (R0=2.3), and Beijing (R0=2.6). The Rt for NCP continuously decreased especially after January 16 nationwide and in Wuhan. The R0 for secondary NCP cases in Guangdong was 0.6, and the Rt values were less than 1 during the epidemic. ConclusionsNCP may have a higher transmissibility than SARS, and the efforts of containing the outbreak are effective. However, the efforts are needed to persist in for reducing time-varying reproduction number below one. At a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSSince December 29, 2019, pneumonia infection with 2019-nCoV, now named as Novel Coronavirus Pneumonia (NCP), occurred in Wuhan, Hubei Province, China. The disease has rapidly spread from Wuhan to other areas. As a novel virus, the time-varying transmission dynamics of NCP remain unclear, and it is also important to compare it with SARS. What This Study Adds to the FieldWe compared the transmission dynamics of NCP with SARS, and found that NCP has a higher transmissibility than SARS. Time-varying production number indicates that rigorous control measures taken by governments are effective across China, and persistent efforts are needed to be taken for reducing instantaneous reproduction number below one.

At present, the factors influencing Tuberculosis (TB) treatment effectiveness in HIV/TB co-infected patients need to be supported by more substantial real-world evidence. A retrospective study is conducted to fill the vacancy. 461 TB patients with HIV are defined as 742 samples according to each TB detection period. 7788 valid treatment records corresponding to 17 drug compositions for TB and 150 clinical indicators with more than 100 records are used to conduct data mining with consensus clustering, Fishers exact test, stratified analysis, and three modeling approaches, including logistic regression, support vector machine, and random forest. We find that A CD4+ T cell count of 42 cells per L may serve as a sensitive classification standard for the immune level to assist in evaluating or predicting the efficacy of TB (P=0.007); Rifabutin and levofloxacin alone or in combination may be more effective than other first- and second-line anti-TB agents in combination (P=0.037); Samples with low immune levels (CD4[less double equals]42) may be more resistant to first-line TB drugs (P=0.049); Age (P=0.015), bicarbonate radical (P=0.007), high-density lipoprotein cholesterol (P=0.026), pre-treatment CD8+ T cell count (P=0.015, age<60, male), neutrophil percentage (P=0.033, age<60), rifabutin (P=0.010, age<60), and cycloserine (P=0.027, age<60) may influence the TB treatment effectiveness; More evidence is needed to support the relationship between pre-treatment clinical indicators or drug regimens and TB treatment effectiveness (The best AUC is 0.560[~]0.763); The percentage of lymphocytes (P=0.028) can be used as an effective TB therapeutic target. These perspectives supplement knowledge in relevant clinical aspects.

The co-existence of coronavirus disease 2019 (COVID-19) and seasonal influenza epidemics has become a potential threat to human health, particularly in China in the oncoming season. However, with the relaxation of nonpharmaceutical interventions (NPIs) during the COVID-19 pandemic, the rebound extent of the influenza activities is still poorly understood. In this study, we constructed a susceptible-vaccinated-infectious-recovered-susceptible (SVIRS) model to simulate influenza transmission and calibrated it using influenza surveillance data from 2018 to 2022. We projected the influenza transmission over the next 3 years using the SVIRS model. We observed that, in epidemiological year 2021-2022, the reproduction numbers of influenza in southern and northern China were reduced by 64.0% and 34.5%, respectively, compared with those before the pandemic. The percentage of people susceptible to influenza virus increased by 138.6% and 57.3% in southern and northern China by October 1, 2022, respectively. After relaxing NPIs, the potential accumulation of susceptibility to influenza infection may lead to a large-scale influenza outbreak in the year 2022-2023, the scale of which may be affected by the intensity of the NPIs. And later relaxation of NPIs in the year 2023 would not lead to much larger rebound of influenza activities in the year 2023-2024. To control the influenza epidemic to the pre-pandemic level after relaxing NPIs, the influenza vaccination rates in southern and northern China should increase to 53.8% and 33.8%, respectively. Vaccination for influenza should be advocated to reduce the potential reemergence of the influenza epidemic in the next few years.

BackgroundChinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. There have been reports external icon of spread from an infected patient with no symptoms to a close contact, which means the incubation individuals may has the possibility of infectiousness. However, the traditional transmission model, Susceptible-Exposed-Infectious-Recovered (SEIR) model, assumes that the exposed individual is being infected but without infectiousness. Thus, the estimating infected populations based on SEIR model from the existing literatures seems too far more than the official reported data. MethodsHere, we inferred that the epidemic could be spread by exposed (incubation) individuals. Then, we provide a new Exposed-identified-Recovered (EIR) model, and simulated the epidemic spreading processes from free propagation phase to extremely control phase. Then, we estimate of the size of the epidemic and forecast the future development of the epidemics under strong prevention interventions. According to the spread characters of 2019-nCov, we construct a novel EIR compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported data from National Health Commission of the Peoples Republic of China, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the spreading trend of 2019-nCov under different prevention policy scenarios are estimated. The epidemic spreading trends under different quarantine rate and action starting date of prevention policy are simulated and compared. FindingsIn our baseline scenario, the government has taken strict prevention actions, and the estimate numbers fit the official numbers very well. Simulation results tells that, if the prevention measures are relaxed or the action starting date of prevention measures is later than Jan. 23, 2020, the peak of identified individuals would be greatly increased, and the elimination date also would be delayed. We estimate the reproductive number for 2019-nCoV was 2.7. And simulation of the baseline scenario tells that, the peak infected individuals will be 49093 at Feb.16, 2020 and the epidemic spreading will be eliminated at the end of March 2020. The simulation results also tell that the quarantine rate and the starting date of intervention action policy have great effect on the epidemic spreading. Specifically, if the quarantine rate is reduced from 100% to less than 63%, which is the threshold of the quarantine rate to control the epidemic spreading, the epidemic spreading would never be eliminated out. And, if the starting date of intervention is delayed for 1 day than the date Jan. 23, the peak infected population will increase about 6351 individuals. If the delayed period is 3 days or 7 days, the increasing number would be 21621 or 65929 individuals, thus the peak infected number would up to 70714 and 115022 individuals. InterpretationGiven that 2019-nCoV could be controlled under the strong prevention measures of what China has taken and it will take about three months. The confirmed infected individuals will still keep quick increasing for a generation period (27 days, equal to the sum of exposed period and identified period) after the start time point of control. The strong prevention measures should be insisted until the epidemics is wiped out. Other domestic places and overseas have confirmed infected individuals should take strong interventions immediately. Generally, earlier strong prevention measures could efficiently mitigate the outbreaks in other cities all over the world has confirmed individuals of epidemic of 2019-nCoV.

COVID-19 has become a global pandemic. However, the impact of the public health interventions in China needs to be evaluated. We established a SEIRD model to simulate the transmission trend of China. In addition, the reduction of the reproductive number was estimated under the current forty public health interventions policies. Furthermore, the infection curve, daily transmission replication curve, and the trend of cumulative confirmed cases were used to evaluate the effects of the public health interventions. Our results showed that the SEIRD curve model we established had a good fit and the basic reproductive number is 3.38 (95% CI, 3.25-3.48). The SEIRD curve show a small difference between the simulated number of cases and the actual number; the correlation index (H2) is 0.934, and the reproductive number (R) has been reduced from 3.38 to 0.5 under the current forty public health interventions policies of China. The actual growth curve of new cases, the virus infection curve, and the daily transmission replication curve were significantly going down under the current public health interventions. Our results suggest that the current public health interventions of China are effective and should be maintained until COVID-19 is no longer considered a global threat.

Inaccurate HIV risk perception is common among men who have sex with men (MSM). Accurate self-perceived risk and HIV testing are closely related and are essential in promoting HIV treatment cascade succeed. This cross-sectional study aims to 1) explore HIV risk perception and its associated sexual behaviors, 2) identify associated factors with HIV testing among Chinese MSM. Participants were recruited to an anonymous online survey in 2019 via an MSM social application. The questionnaire included sexual behaviors, HIV testing history, and the use of HIV prevention services. Logistic regression was used to explore the factors associated with higher risk perceptions and HIV testing in the past 12 months. Total 431 MSM were recruited, 73.3% had been tested for HIV in the past year and 47.80% of MSM self-reported in the high-risk group. MSM who perceived a higher risk (AOR=3.42, 95% CI:2.06-5.68), had multiple sexual partners (AOR=2.60, 95% CI:1.40-4.83), knew sex partners HIV status (AOR=7.96, 95% CI:4.33-14.65), and have STI diagnosis (AOR=2.76, 95% CI:1.10-6.95), were more likely to have been tested. Risk perception and sexual behavior were associated with HIV testing. Culturally adapted, theory-driven education programs are expected to utilize in improving MSMs risk perception accuracy and HIV testing.

HIV can be transmitted from a HIV infected mother to her child during pregnancy, delivery, or breastfeeding. According to NSDCC 2023, Kenya has estimated PMTCT coverage of 89.56% and PMTCT transmission rate of 8.6%. Even though there has been strides to address PMTCT, there is need to gear up approaches in addressing MTCT in order to significantly advance elimination. This research formulates a mathematical model to represent the dynamics of MTCT. Equilibrium points of the model are computed and the stability of HIV-free point is investigated. The numerical results show that a 50% decrease in maternal HIV transmission lowers infant infection rates by about 17.7%, whereas the same reduction in infant transmission decreases infections by nearly 39%, highlighting the greater sensitivity of infant transmission rates to direct interventions. While combination of strategies achieves the highest HIV minimization rates of up to 99.89% on infants, ART adherence alone significantly reduces transmission, particularly on infants (91.42%) while use of post-exposure prophylaxis (PEP) shows limited effectiveness when used alone(39.65%), suggesting that it should be complemented with other strategies for optimal impact. These findings emphasize the critical need for integrated interventions, where combining multiple prevention methods yields the best outcomes in reducing HIV infections on infants and moving closer to the elimination of pediatric HIV. These findings align with global recommendations from World Health Organization (WHO). This research can be used by the ministry of health to inform policy as well as recreated for other maternal infections. Author summaryHIV can be transmitted from a mother to her child during pregnancy, delivery, or breastfeeding. In Kenya, despite efforts to prevent mother-to-child transmission (PMTCT), HIV transmission rates remain a concern. In this study, we developed a mathematical model to understand how HIV spreads from mothers to infants and to evaluate the effectiveness of different prevention strategies. Our findings highlight that reducing HIV transmission in mothers lowers infant infection rates, but direct interventions for infants, such as early antiretroviral therapy (ART) and post-exposure prophylaxis (PEP), have an even greater impact. A combination of strategies--ensuring mothers adhere to ART, providing PEP for infants, and promoting safe breastfeeding practices--was found to reduce HIV infections in infants by up to 99.89%. These results support the need for integrated approaches to HIV prevention. Policymakers and healthcare providers can use this research to refine HIV prevention programs, ensuring better maternal and infant health outcomes. Our model can also be adapted for other maternal infections, contributing to broader public health efforts in disease prevention.

The 2022 mpox outbreak has spread rapidly across multiple countries in the non-endemic region, mainly among men who have sex with men (MSM), while China only has limited recorded importation and no local outbreak. We constructed probabilistic models to simulate the risk of mpox importation in mainland China, with the help of reported monkeypox cases during this multi-country outbreak and the international air-travel data. And we further evaluated the mpox outbreak potential given that undetected mpox infections were introduced into men who have sex with men, considering different transmissibility, population immunity and population activity. We found that the reduced international air-travel volume and stringent border entry policy decreased about 94% and 69% mpox importations respectively. Once a mpox case is introduced into active MSM population with almost no population immunity, the risk of triggering local transmission is estimated at 42%, and would rise to >95% with over six cases. Our study demonstrates the key role of the reduced international air-travel volume and stringent border entry policy during the COVID-19 pandemic on reducing mpox importations, and the subsequent risk of triggering local outbreaks among MSM.

Dengue virus, with all four serotypes in cocirculation, has created significant epidemiological and economic burdens in Singapore. Despite integrated vector control programs, the magnitude and frequency of dengue outbreaks has increased over the last few decades, which highlights the limits of existing strategies. In this context, vaccination has emerged as a promising approach to enhance population immunity and complement ongoing efforts. Qdenga (TAK-003), a commercially available dengue vaccine, has been recommended by the the World Health Organization Strategic Advisory Group of Experts (WHO-SAGE) for use in high-transmission settings. Although classified as a low transmission setting, Singapore faces a recurring public health burden from dengue, with high costs associated with both healthcare and sustained vector control. The age distribution of dengue in Singapore differs from high transmission settings, with more cases in young adults and hospitalizations concentrated among older individuals. These factors, combined with the complex efficacy profile of Qdenga, varying by baseline serostatus, infecting serotype, make it challenging to directly apply global vaccination recommendations to Singapore. Therefore, the population-level impact of introducing dengue vaccination remains uncertain, underscoring the need for context-specific evaluation. To estimate the potential public health impact of introducing routine dengue vaccination in Singapore, we develop an age-stratified, multi-serotype, compartmental transmission model informed by age-specific dengue seroprevalence and routine surveillance data. Our model predicts that vaccination can avert up to on average 9%, 12%, 7%, and 5% cases in DENV-1-4 dominant serotype scenarios respectively, over a 10-year routine vaccination program with 80% vaccine coverage. Moreover, dengue hospitalizations can be reduced by 12%-15% across all dominant serotype scenarios. Our results suggest that, in Singapore, targeting older age groups will be more beneficial than the 6-16-year window recommended by the WHO-SAGE for high-transmission settings. Vaccinating individuals aged 17-30 years achieves the greatest reduction in cases, whereas targeting those aged 51-70 years leads to the highest reduction in hospitalizations. Our model-based analysis provides useful insights to support policymakers and public health authorities in designing evidence-based, dengue vaccination strategies in Singapore. The findings also underscore the importance of tailoring dengue vaccination programs to local epidemiological conditions for effective disease control. Authors summarySingapore is experiencing more frequent dengue outbreaks, which impose a substantial burden through treatment costs and sustained vector control programs. Vaccination is a key public health measure that can help ease this burden by complementing existing control efforts. In clinical trials, Qdenga (TAK-003) demonstrated consistent protections against DENV-1 and DENV-2 among vaccine recipients irrespective of their baseline serostatus, but uncertainty remains for DENV-3 and DENV-4. Although WHO-SAGE recommended its use among children aged 6-16 years in high dengue transmission setting, uncertainty arises when extrapolating these recommendations to low transmission settings like Singapore. Moreover, unlike high transmission settings, Singapore currently shows a different age pattern of dengue burden, with higher incidence in young adults and more severe outcomes among older individuals, highlighting the need to contextualize these global recommendations using country-specific data and modelling approaches. To address this, we developed a detailed modelling framework that integrates local epidemiological characteristics and operational aspects of vaccine implementation and evaluated the potential impact of introducing a routine vaccination program in Singapore. We show that, with 80% coverage, vaccination can avert up to 12% of reported cases and 15% of hospitalizations over a 10-year period, with impact varying mainly by circulating serotype and target age group. Our findings suggest that in low-transmission settings like Singapore, vaccinating adults will achieve a greater public health impact than targeting children, as currently recommended for high-transmission settings by WHO-SAGE. These findings provide timely evidence to support national policy discussions on dengue vaccination in Singapore and other low-transmission settings, where adult disease burden is substantial.

Tick distribution in China has significantly expanded with urbanization and climate change. Chongqing faces a significant risk of severe fever with thrombocytopenia syndrome (SFTS), but targeted prevention efforts are challenging due to unclear exposure pathways. This study combined generalized linear model (GLM), Bayesian networks, and Bayesian multivariate GLM to assess environmental, agricultural, and socioeconomic drivers of tick exposure in southwestern China. Direct tick exposure risks primarily arose from proximity to shrublands, forests, and cattle farming. Pet ownership also increased risk, while proximity to croplands reduced exposure, likely due to the pesticide/herbicide use and tillage. Bayesian networks revealed that socioeconomic factors indirectly mediated risk. Higher education levels reduced cattle farming likelihood and increased income tier, lowering exposure by altering land-use proximity and agricultural activities. Key factors showing no significant association included demographics (age/gender), grassland proximity, and crop cultivation. Bayesian methods resolved collinearity and mediation effects in GLM, clarifying township-level tick exposure mechanisms in Southwest China and mapping driver networks. Findings demonstrate that tick exposure stems from complex interactions among environmental, agricultural, and socioeconomic factors. Prevention in mountainous southwest China should prioritize the shrubland/forest-cattle farming ecological interface. Future studies should integrate geospatial data for enhanced risk mapping.

The role of modelling in predicting the spread of an epidemic is important for health planning and policies. This study aimed to apply a compartmental model for predicting the variations of epidemiological parameters in Sri Lanka. We used a dynamic Susceptible-Exposed-Infected-Recovered-Vaccinated (SEIRV) model and simulated potential vaccine strategies under a range of epidemic conditions. The predictions were based on different vaccination coverages (5% to 90%), vaccination-rates (1%, 2%, 5%) and vaccine-efficacies (40%, 60%, 80%) under different R0 (2,4,6). We estimated the duration, exposed, and infected populations. When the R0 was increased, the days of reduction of susceptibility and the days to reach the peak of the infection were reduced gradually. At least 45% vaccine coverage is required for reducing the infected population to mitigate a disastrous situation in Sri Lanka. The results revealed that when R0 is increased in the SEIRV model along with the increase of vaccination efficacy and vaccination rate, the population to be vaccinated is reducing. Thus, the vaccination offers greater benefits to the local population by reducing the time to reach the peak, exposed and infected population through flattening the curves.

Clonorchiasis is one of the major parasitic diseases in South Korea. Spatially explicit estimates of the infection risk are important for control and intervention. We did a systematic review of collected prevalence data on Clonorchis sinensis infection in South Korea. Data of potential influencing factors (e.g., environmental and social-economic factors) was obtained from open-access databases. Bivariate Bayesian geostatistical joint modeling approaches were applied to analyze disease data, within a logit regression in combination of potential influencing factors and spatial-temporal random effects. We identified surveys of C. sinensis infection done at 1362 unique locations, and presented the first spatial-temporal risk maps at high spatial resolution (5x5km) in South Korea. High infection risk areas shrunk significantly from 1970 to 2017. The overall risk decreased since the start of the national deworming program in 1969, and then slightly increased since the year 1995 when the program suspended, and maintained stable since 2005 when the Clonorchiasis Eradication Program begun. The population-weighted prevalence was estimated as 3.87% (95% BCI: 3.04-4.82%) in 2017, accounting to 1.92 (95% BCI: 1.51-2.40) million infected people. Although the prevalence over the country has been low, C. sinensis infection was still endemic in areas of eastern and southern regions, particularly the five major river basins. We also defined factors significantly correlated, such as, distance to the nearest open water bodies, annual precipitation, and land surface temperature at night. All findings above provide important information on spatial-targeting control and preventive strategies of C. sinensis infection in South Korea.

The current outbreak of novel coronavirus disease 2019 (COVID-19) is already causing a serious disease burden worldwide, this paper analyzed data of a delta variant Covid-19 outbreak in Hunan, China, and proposed an optimal dose-wise dynamical vaccinating process based on local contact pattern and vaccine coverage that minimize the accumulative cases in a certain future time interval. The optimized result requires an immediate vaccination to that none vaccinated at age group 30 to 39, which is coherent to the prevailing strategies. The dose-wise optimal vaccinating process can be directive for countries or regions where vaccines are not abundant. We recommend that vaccination should be further intensified to increase the coverage of booster shots, thus effectively reducing the spread of COVID-19.

BackgroundDespite advances in HIV treatment and prevention, men who have sex with men (MSM) remain disproportionately affected by HIV worldwide. This systematic review summarizes the results of mathematical modeling studies that evaluated whether interventions might eliminate HIV in MSM populations by geographical setting, type of intervention(s), elimination definition, and model characteristics. MethodsWe searched Embase and PubMed for modeling studies published between July 1, 2016 and January 7, 2025. Studies were included if they used a dynamic model to assess the impact of interventions on HIV transmission among MSM. Data were extracted on article information, study population, interventions, elimination definitions, model type, model structure, and calibration. The studies were critically appraised by evaluating the comprehensiveness of their models in addressing elimination. FindingsOf the 3,250 identified records, 89 studies were included. MSM populations in only five of the eight Joint United Nations Programme on HIV/AIDS (UNAIDS) regions were modeled, with over half of the models considering MSM in the USA. Complex agent-based models (ABMs) were as common as simpler compartmental models overall, with ABMs more frequently used in Western and Central Europe and North America (WCENA), while compartmental models predominated elsewhere. Thirty-nine of the 89 studies defined elimination as reductions or thresholds in HIV incidence or prevalence, a reproduction number below one, or the elimination of racial disparities. Elimination was achieved in 36 out of 50 modeled scenarios, but the authors of only six of these 36 scenarios thought the interventions required to achieve elimination were feasible. The six feasible elimination scenarios were reported in compartmental models for few countries in Western Europe and Asia. Models in which elimination was achieved most commonly used a combination of interventions that included pre-exposure prophylaxis (PrEP) and/or test-and-treat, except in Africa, where PrEP was not included. InterpretationModeling efforts to understand HIV elimination prospects among MSM outside WCENA should be intensified. To enhance study comparability and for models to contribute effectively to public health policy, the use of an elimination definition based on an incidence threshold would be the most valuable. Furthermore, by identifying gaps in current studies, we recommend novel research directions for modeling to inform a coordinated global response for HIV elimination among MSM.

Since COVID-19 emerged in early December, 2019 in Wuhan and swept across China Mainland, a series of large-scale public health interventions, especially Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement, have been taken by the government to control the epidemic. Based on Baidu Migration data and the confirmed cases data, we identified two key factors affecting the later (e.g February 27, 2020) cumulative confirmed cases in non-Wuhan region (y). One is the sum travelers from Wuhan during January 20 to January 26 (x1), which had higher infected probability but lower transmission ability because the human-to-human transmission risk of COVID-19 was confirmed and announced on January 20. The other is the "seed cases" from Wuhan before January 19, which had higher transmission ability and could be represented with the confirmed cases before January 29 (x2) due to a mean 10-day delay between infection and detection. A simple yet effective regression model then was established as follow: y= 70.0916+0.0054xx1+2.3455xx2 (n = 44, R2 = 0.9330, P<10-7). Even the lock-down date only delay or in advance 3 days, the estimated confirmed cases by February 27 in non-Wuhan region will increase 35.21% or reduce 30.74% - 48.59%. Although the above interventions greatly reduced the human mobility, Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement do have a determining effect on the ongoing spread of COVID-19 across China Mainland. The strategy adopted by China has changed the fast-rising curve of newly diagnosed cases, the international community should learn from lessons of Wuhan and experience from China. Efforts of 29 Provinces and 44 prefecture-level cities against COVID-19 were also assessed preliminarily according to the interpretive model. Big data has played and will continue playing an important role in public health.

BackgroundRift Valley Fever (RVF) is a viral disease caused by the Rift Valley Fever virus and spread mainly by the Aedes and Culex mosquito species. The disease primarily infects domestic animals such as sheep, goats, and cattle, resulting in a spectrum of clinical outcomes including morbidity, massive storm abortions, and neonatal fatalities. RVF outbreaks are closely linked to above-average rainfall and flooding, which create an ideal environment for mosquitos to breed, multiply, and transmit the virus to animals. The outcomes of human RVF infection range from self-limiting febrile illness to potentially fatal hemorrhagic diatheses and miscarriage in pregnant women. Collectively, the economic losses due to the zoonotic RVF disease is immense. MethodsUsing the Weighted Gene Co-expression Network Analysis (WGCNA) package, RNA-Seq data generated from five healthy Bos taurus steer calves aged 4-6 months was obtained from the Gene Expression Omnibus (GEO) database (Accession number GSE71417). The data was utilized to construct a gene co-expression network. Enriched modules containing genes potentially involved in RVF infection progression were identified. Moreover, using the Multiple Expectation Maximizations for Motif Elicitation (MEME) suite, consensus regulatory motifs of enriched gene clusters were deciphered and the most abundant putative regulatory motif in each enriched module unveiled by comparative analysis with publicly available motifs using the TOMTOM motif comparison tool. The potential roles of the identified regulatory motifs were inferred by literature mining. ResultsThe constructed gene co-expression network revealed thirty-three (33) modules, nine of which were enriched for Gene Ontology terms linked to RVF pathogenesis. Functional enrichment in two (red and turquoise) of the nine modules was significant. ASH1-like histone lysine methyltransferase and Astrotactin were the hub genes for the red and turquoise modules respectively. ASH1-like histone lysine methyltransferase gene is involved in chromatin epigenetic modification while Astrotactin is a vertebrate-specific gene that plays an important role in neurodevelopment. Additionally, consensus regulatory motifs located on the 3' end of genes in each enriched module was identified. ConclusionsIn this study, we have developed a gene co-expression network that has aided in the unveiling of functionally related genes, intramodular hub genes, and immunity genes potentially involved in RVF pathogenesis. The discovery of functional genes with putative critical roles in the establishment of RVF infection establishment will contribute to the understanding of the molecular mechanism of RVF pathogenesis. Importantly, the putative regulatory motifs identified are plausible targets for RVF drug and vaccine development.

Backgroud and ObjectiveTo predict the epidemic of COVID-19 based on quarantined surveillance from real world in China by modified SEIR model different from the previous simply mathematical model. Design and MethodsWe forecasted the epidemic of COVID-19 based on current clinical and epidemiological data and built a modified SEIR model to consider both the infectivity during incubation period and the influence on the epidemic from strict quarantined measures. ResultsThe peak time of the curve for the infected newly diagnosed as COVID-19 should substantially present on Feb. 5, 2020 (in non-Hubei areas) and Feb. 19, 2020 (in Hubei). It is estimated that the peak of the curve of the cumulative confirmed cases will appear in non-Hubei areas on Mar. 3, 2020 and in Hubei province on Mar. 10, 2020, and the total number of the patients diagnosed as COVID-19 is 18,000 in non-Hubei areas and 78,000-96,000 in Hubei. The Chinese COVID-19 epidemic can be completetly controlled in May, 2020. ConclusionsCOVID-19 is only a local outbreak in Hubei Province, China. It can be probably avoided the pandemic of global SARS-CoV-2 cases rise with the great efforts by Chinese government and its people.

BackgroundDengue fever is a major neglected tropical disease with a rapidly rising global burden, and localized outbreaks are increasingly reported in southern subtropical China. Fujian Province, a coastal subtropical region with favorable ecological conditions for Aedes albopictus breeding and frequent cross-border exchanges with dengue-endemic areas, has had continuous local dengue cases for over a decade, raising concerns about the establishment of a stable natural endemic focus. Sustained local dengue transmission is defined by four core criteria, but no systematic assessment of these criteria has been conducted for Fujian using long-term multi-dimensional surveillance data. We aimed to evaluate whether a natural endemic focus for sustained local dengue transmission has been established in Fujian Province from 2014 to 2024 using four core evidence dimensions. MethodsWe extracted data on imported and locally acquired dengue cases in Fujian from 2014 to 2024 from Chinas National Notifiable Disease Reporting System (NNDRS). Serological surveillance for dengue IgG antibodies and virological surveillance for dengue virus in Aedes albopictus were conducted at seven sentinel sites. The study period was stratified into three phases based on the impact of COVID-19 non-pharmacological interventions: pre-pandemic (2014-2019), pandemic(2020-2022), and post-pandemic(2023-2024). Descriptive epidemiological analysis and data visualization were performed using R software (version 4.4.1), with t-tests for continuous variables and {chi}{superscript 2} tests for categorical variables. ResultsA total of 3,606 dengue cases were reported in Fujian during the study period, including 1,229 imported and 2,377 locally acquired cases. Key findings were as follows: (1) Temporal distribution: Local dengue transmission was completely interrupted during the 2020-2022 COVID-19 pandemic (0 local cases, only 26 imported cases), and resumed at a low level in 2023-2024 (160 local cases). (2) Serology: The overall population dengue IgG antibody positivity rate was 4.2% (66/15,736), with no statistically significant difference between pre-epidemic (3.8%, 30/7,835) and post-epidemic seasons (4.5%, 36/7,901; P=0.48), and no year with a positivity rate exceeding 10%. (3) Vector surveillance: Only one dengue virus-positive sample was detected among 385,000 Aedes albopictus mosquitoes collected during routine surveillance (Taijiang District, Fuzhou, October 2017), with no viral nucleic acid detected in all other samples. (4) Age distribution: The mean age of locally acquired cases (46.1{+/-}19.8 years) was significantly higher than that of imported cases (35.8{+/-}11.2 years, P<0.001), and local cases were concentrated in the middle-aged group (40-60 years) with no child-dominant pattern observed. ConclusionsFujian Province has not established a stable natural endemic focus for sustained local dengue transmission, and imported cases are the primary driver of local outbreaks in the region. Strengthened surveillance and early management of imported cases, integrated vector control targeting Aedes albopictus, and targeted public health education are critical and essential strategies to prevent the establishment of a dengue natural endemic focus in Fujian and other subtropical coastal regions with similar epidemiological characteristics. Author SummaryDengue fever is a rapidly spreading neglected tropical disease worldwide, and southern China faces persistent threats of local transmission due to favorable ecological conditions for mosquito breeding and frequent cross-border travel. Fujian Province, a subtropical coastal region in southeastern China, has reported annual local dengue cases for over a decade, raising public health concerns about the potential establishment of a stable natural endemic focus--where the virus circulates sustainably without relying on imported cases. To address this critical question, we conducted a comprehensive 11-year assessment (2014-2024) of dengue transmission in Fujian using four key evidence dimensions defined for identifying dengue endemic foci: the continuity of local cases independent of imported sources, population antibody levels, dengue virus detection in local mosquitoes (Aedes albopictus), and the age distribution of infected patients. We also leveraged the COVID-19 pandemic(2020-2022) as a unique natural experiment, during which strict travel restrictions drastically reduced imported dengue cases, to test whether local transmission could persist on its own. Our findings showed that local dengue transmission in Fujian completely stopped during the COVID-19 pandemic and only resumed when cross-border travel and imported cases recovered, confirming local transmission is entirely dependent on imported virus sources. Additionally, the local population had a very low dengue antibody positivity rate (4.2%), dengue virus was detected in only one mosquito sample over 11 years of surveillance, and local cases were concentrated in middle-aged adults (not children--the typical group affected in endemic areas). Together, these results confirm that Fujian Province has not established a stable natural endemic focus for dengue fever. While no endemic focus exists yet, Fujian remains at high risk of imported-driven local outbreaks due to its climate and cross-border exchanges. Our study highlights three critical strategies to prevent the future establishment of a dengue endemic focus in Fujian and other similar subtropical coastal regions: strengthening surveillance and early response for imported dengue cases, implementing targeted mosquito control measures during peak transmission seasons, and conducting public health education to raise awareness of dengue prevention. These evidence-based interventions are key to blocking the formation of sustained local dengue transmission and protecting regional population health.

BackgroundWhile the COVID-19 pandemic seemed far from the end, the booster vaccine project was proposed to further reduce the transmission risk and infections. However, handful studies have focused on questions that with limited vaccine capacity ether boosting high-risk workers first or prioritizing susceptible normal individuals is optimal, and vaccinating how many people can lead us to the goal of herd immunity. In this study we aimed to explore the conclusions of such two problems with consideration of non-pharmacological interventions including mandatory quarantine for international entrants, keeping social distance and wearing masks. MethodsBy implementing the corresponding proportion of individuals who remain infectious after four lengths of quarantine strategies to the novel population-stratified model, we quantified the impact of such measures on optimizing vaccine prioritization between high-risk workers and normal populations. Furthermore, by setting the hypothetical COVID-19 transmission severity (reproduction number, R0) to the level of the most contagious COVID-19 variant (B.1.617.2, delta variant, R0 = 5.0), we separately estimated the threshold vaccine coverage of five countries (China, United States, India, South Africa and Brazil) to reach herd immunity, with and without the consideration of interventions including wearings masks and keeping social distance. At last, the sensitive analysis of essential parameter settings was performed to examine the robustness of conclusions. ResultsFor Chinese scenarios considered with moderate hypothetical transmission rate (R0 = 1.15-1.8), prioritizing high-risk workers the booster dose reached lower cumulative infections and deaths if at least 7-days of quarantine for international travelers is maintained, and the required screening time to remain such vaccinating strategy as optimal increased from 7-days to 21-days with the transmission severity. Although simply maintaining at least 7-days quarantine can lead to over 69.12% reduction in total infections, the improvement of longer quarantine strategies was becoming minimum and the least one was 2.28% between the 21 and the 28-days of quarantine. Besides, without the vaccination program, the impact of such measures on transmission control dropped significantly when R0 exceeded 1.5 and reached its minimal level when R0 equal to 2.5. On the other hand, when we combat the delta variant, the threshold vaccine coverage of total population to reach herd immunity lay within 74%-89% (corresponding to the vaccine efficiency from 70% to 50%), and such range decreased to 71%-84% if interventions including wearing mask and keeping social distance were implemented. Furthermore, Results of other countries with 85% vaccine efficiency were estimated at 79%, 91%, 94% and 96% for South Africa, Brazil, India and United States respectively. ConclusionsNon-pharmacological interventions can substantially affect booster vaccination prioritization and the threshold condition to reach herd immunity. To combat the delta variant, restrictions need to be integrated with mass vaccination so that can reduce the transmission to the minimum level, and the 21-days might be the suggested maximum quarantine duration according to the cost-effectiveness. Besides, by implementing interventions, the requirement to reach herd immunity can be lower in all countries. Lastly, the following surveillance after vaccination can help ensure the real-time proportion of vaccinated individuals with sufficient protection.

BackgroundThe rapid expansion of the current COVID-19 outbreak has caused a global pandemic but how quarantine-based measures can prevent or suppress an outbreak without other more intrusive interventions has not yet been determined. Hong Kong had a massive influx of travellers from mainland China, where the outbreak began, during the early expansion period coinciding with the Lunar New Year festival; however, the spread of the virus has been relatively limited even without imposing severe control measures, such as a full city lockdown. Understanding how quarantine measures in Hong Kong were effective in limiting community spread can provide us with valuable insights into how to suppress an outbreak. However, challenges exist in evaluating the effects of quarantine on COVID-19 transmission dynamics in Hong Kong due to the fact that the effects of border control have to be also taken into account. MethodsWe have developed a two-layered susceptible-exposed-infectious-quarantined-recovered (SEIQR) meta-population model which can estimate the effects of quarantine on virus transmissibility after stratifying infections into imported and subsequent community infections, in a region closely connected to the outbreaks source. We fitted the model to both imported and local confirmed case data with symptom onset from 18 January to 29 February 2020 in Hong Kong, together with daily transportation data and the transmission dynamics of COVID-19 from Wuhan and mainland China. After model fitting, epidemiological parameters and the timing of the start of quarantine for infected cases were estimated. ResultsThe model estimated that the reproduction number of COVID-19 in Hong Kong was 0.76 (95% CI, 0.66 to 0.86), achieved through quarantining infected cases -0.57 days (95% CI, -4.21 - 3.88) relative to symptom onset, with an estimated incubation time of 5.43 days (95% CI, 1.30 - 9.47). However, if delaying the quarantine start by more than 1.43 days, the reproduction number would be greater than one, making community spread more likely. The model also determined the timing of the start of quarantine necessary in order to suppress an outbreak in the presence of population immunity. ConclusionThe results suggest that the early quarantine for infected cases before symptom onset is a key factor to prevent COVID-19 outbreak.