Large-scale Outbreaks Research Articles

Challenges of COVID-19 prevention during protracted conflicts: differential adherence to preventive measures in "contact line" regions in eastern Ukraine.

Despite the epidemiological importance of social vulnerabilities in compliance with preventive measures, little is known about the disproportional nature of preventive behaviors in crisis-affected populations. We examined adherence to COVID-19 preventive behaviors, focusing on social distancing measures in the conflict-affected regions in eastern Ukraine. From a multisectoral needs assessment conducted in 2020 using a household interview of a stratified simple random sample, we included 1,617 rural and urban households located in the government-controlled area. We performed multivariable binary logistic regression analysis with latent class analysis (LCA) to identify unmeasured patterns of classification of preventive measures using data from a cross-sectional survey. The conflict-affected populations showed difficulty in complying with COVID-19 preventive measures due to losses of housing, partners, and access to food resources due to conflicts. Among the various preventive measures, wearing a face mask (88.1%) and washing hands more regularly (71.4%) were the most frequently reported. Compliance with social distancing was significantly lower in those who experienced the direct impacts of conflicts indicated by damaged accommodation or being widowed. Three different groups who showed distinctive patterns of employing COVID-19 preventive measures were identified via the LCA model, which were "highly complying group", "moderately complying group", and "face masks only group". The group membership was associated with a respondent's poverty status. The findings show the difficulty in compliance with COVID-19 preventive measures among conflict-affected populations indicating secondary impacts of the conflicts on preventive health behaviors. To mitigate the health impacts of conflicts, immediate attention is needed to address barriers to COVID-19 preventive measures among conflict-affected populations in Ukraine. This study suggests the need for public health strategies to improve preventive health behaviors in conflict-affected populations under pandemics or large-scale outbreaks.

Modelling the pulse population-wide nucleic acid screening in mitigating and stopping COVID-19 outbreaks in China

BackgroundDuring 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.MethodsWe develop a mathematical model with pulse population-wide nucleic acid screening, part of the zero-COVID 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.ResultsWithout 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.ConclusionsThe 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.

Quantifying the rebound of influenza epidemics after the adjustment of zero-COVID policy in China.

The coexistence 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 prepandemic 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.

Temperate phage influence virulence and biofilm-forming of Salmonella Typhimurium and enhance the ability to contaminate food product

Salmonella is a food-borne zoonotic pathogen that threatens food safety and public health security. Temperate phages can influence bacterial virulence and phenotype and play an important role in bacterial evolution. However, most studies on Salmonella temperate phages focus on prophage induced by bacteria, with few reports on Salmonella temperate phages isolated in the environment. Moreover, whether temperate phages drive bacterial virulence and biofilm formation in food and animal models remains unknown. In this study, Salmonella temperate phage vB_Sal_PHB48 was isolated from sewage. TEM and phylogenetic analysis indicated that phage PHB48 belongs to the Myoviridae family. Additionally, Salmonella Typhimurium integrating PHB48 was screened and designated as Sal013+. Whole genome sequencing revealed that the integration site was specific and we confirmed that the integration of PHB48 did not change the O-antigen and coding sequences of Sal013. Our in vitro and in vivo studies showed that the integration of PHB48 could significantly enhance the virulence and biofilm formation of S. Typhimurium. More importantly, the integration of PHB48 significantly improved the colonization and contamination ability of bacteria in food samples. In conclusion, we isolated Salmonella temperate phage directly from the environment and systematically clarified that PHB48 enhanced the virulence and biofilm-forming ability of Salmonella. In addition, we found that PHB48 increased the colonization and contamination ability of Salmonella in food samples. These results indicated that the highly pathogenic Salmonella induced by temperate phage was more harmful to food matrices and public health security. Our results could enhance the understanding of the evolutionary relationship between bacteriophages and bacteria, and raise public awareness of large-scale outbreaks resulting from Salmonella virulence enhancement in food industry.

A Successful National and Multipartner Approach to Increase Immunization Coverage: The Democratic Republic of Congo Mashako Plan 2018-2020.

The immunization system in the Democratic Republic of the Congo faces many challenges, including persistent large-scale outbreaks of polio, measles, and yellow fever; a large number of unvaccinated children for all antigens; minimal and delayed funding; and poor use of immunization data at all levels. In response, the Expanded Programme on Immunization within the Ministry of Health (MOH) collaborated with global partners to develop a revitalization strategy for the routine immunization (RI) system called the Mashako Plan. The Mashako Plan aimed to increase full immunization coverage in children aged 12-23 months by 15 percentage points overall in 9 of 26 provinces within 18 months of implementation. In 2018, we conducted a diagnostic review and identified gaps in coordination, service delivery, vaccine availability, real-time monitoring, and evaluation as key areas for intervention to improve the RI system. Five interventions were then implemented in the 9 identified provinces. According to the 2020 vaccine coverage survey, full immunization coverage increased to 56.4%, and Penta3/DTP3 increased to 71.1% across the Mashako Plan provinces; the initial objective of the plan was reached and additional improvements in key service delivery indicators had been achieved. Increases in immunization sessions held per month, national stock of pentavalent vaccine, and supervision visits conducted demonstrate that simple, measurable changes at all levels can quickly improve immunization systems. Despite short-term improvements in all indicators tracked, challenges remain in vaccine availability, regular funding of immunization activities, systematic provision of immunization services, and ensuring long-term sustainability. Strong commitment of MOH staff combined with partner involvement enabled the improvement of the entire system. A simple set of interventions and indicators focused the energy of managers on discrete actions to improve outcomes. Further exploration of the results is necessary to determine the long-term impact and generate all-level engagement for sustainable success in all provinces.

Correlation between the IgG/IgA Antibody Response against PEDV Structural Protein and Virus Neutralization.

Porcine epidemic diarrhea (PED) is a highly contagious intestinal infectious disease caused by porcine epidemic diarrhea virus (PEDV). Large-scale outbreaks of PEDV have caused huge economic losses to the pig industry since 2010. Neutralizing antibodies play a pivotal role in protecting piglets from enteric infections. However, there has been no systematic report on the correlations between neutralizing antibody titers (NTs) and absorbance values of IgG or IgA to all PEDV individual structural proteins in clinical serum, fecal, and colostrum samples. In this study, the spike protein S1 domain (S1), membrane protein (M), envelope protein (E), and nucleocapsid protein (N) of the variant PEDV strain AH2012/12 were expressed and purified by using the human embryonic kidney (HEK) 293F expression system. A total of 92 clinical serum samples, 46 fecal samples, and 33 colostrum samples were collected, and the correlations between IgG or IgA absorbance values and NTs were analyzed. R2 values revealed that anti-S1 IgA absorbance values show the highest agreement with NTs in all serum, fecal, and colostrum samples, followed by the N protein. The correlations between anti-E or M IgA and NTs were very low. However, in the colostrum samples, both IgG and IgA to S1 showed high correlations with NTs. In addition, compared with E and M, the highest correlations of IgA absorbance values were with N and S1 in serum and fecal samples. Overall, this study revealed the highest correlation between NTs and IgA to PEDV S1 protein. Therefore, the diagnostic method with anti-S1 IgA can be used as a powerful tool for assessing the immune status of pigs. IMPORTANCE The humoral immune response plays an important role in virus neutralization. Against PEDV, both IgG and the mucosal immune component IgA play roles in virus neutralization. However, which plays a more prominent role and whether there are differences in different tissue samples are not clearly reported. Additionally, the relationship between IgG and IgA against individual structural proteins and viral neutralization remains unclear. In this study, we systematically determined the relationship between IgG and IgA against all PEDV structural proteins and viral neutralization in different clinical samples and found the highest correlation between neutralization activity and IgA to PEDV S1 protein. Our data have important guiding implications in the evaluation of immune protection.

When tree diversity does not work: The interacting effects of tree diversity, altitude and amount of spruce on European spruce bark beetle outbreaks

The frequency of large-scale insect outbreaks is expected to increase with climate change, and the European spruce bark beetle (Ips typographus) is a major forest pest in Europe that has caused more extensive and widespread outbreaks in recent years. It is therefore important to evaluate forest management strategies for controlling bark beetle populations. While tree species diversity is often promoted as a way to improve forest resistance to specialist insects, the relationship between tree species diversity and bark beetle outbreaks is not well understood, partly due to the complex interactions with other factors. The aim of this study was to assess the impact of tree species diversity on European spruce bark beetle outbreaks, while controlling for host availability across different altitudes. We analysed data from a systematic 1 × 1 km grid in Slovenia. For each grid cell, we extracted data on the sanitary felling of Norway spruce that followed bark beetle outbreaks from a national data base covering the period 1996–2017. Additionally, we extracted data on resource availability (i.e., the percentage of Norway spruce in the grid cell), non-host tree species diversity and average altitude. We analysed the effect of altitude, forest cover, percentage of spruce and non-host tree species diversity during outbreak and non-outbreak periods on the probability of sanitary felling and on the amount of sanitary felling, separately. The probability of sanitary felling was higher at low altitudes and increased with an increasing proportion of spruce in the growing stock in the grid cell, but it was not affected by non-host tree species diversity. In contrast, the amount of sanitary felling decreased with increasing non-host tree species diversity, particularly at low altitudes. However, the effect of non-host tree species diversity on the amount of sanitary felling diminished as the percentage of Norway spruce increased. Thus, non-host tree species diversity per se is not the main driver of outbreak risk but strengthens biotic resistance with lower host availability at low altitudes where abiotic conditions are the least favourable to Norway spruce.

SARS-CoV-2 surveillance in medical and industrial wastewater-a global perspective: a narrative review.

The novel coronavirus SARS-CoV-2 has spread at an unprecedented rate since late 2019, leading to the global COVID-19 pandemic. During the pandemic, being able to detect SARS-CoV-2 in human populations with high coverage quickly is a huge challenge. As SARS-CoV-2 is excreted in human excreta and thus exposed to the aqueous environment through sewers, the goal is to develop an ideal, non-invasive, cost-effective epidemiological method for detecting SARS-CoV-2. Wastewater surveillance has gained widespread interest and is increasingly being investigated as an effective early warning tool for monitoring the spread and evolution of the virus. This review emphasizes important findings on SARS-CoV-2 wastewater-based epidemiology (WBE) in different continents and techniques used to detect SARS-CoV-2 in wastewater during the period 2020-2022. The results show that WBE is a valuable population-level method for monitoring SARS-CoV-2 and is a valuable early warning alert. It can assist policymakers in formulating relevant policies to avoid the negative impacts of early or delayed action. Such strategy can also help avoid unnecessary wastage of medical resources, rationalize vaccine distribution, assistearly detection, and contain large-scale outbreaks.

Impacts of climate change on pine wilt disease outbreaks and associated carbon stock losses

Pine wilt disease (PWD) is a significant threat to forests worldwide. Large-scale PWD outbreaks in China underline the need to understand the current and future distributions of PWD. We constructed a principal components analysis (PCA)-based environmental filter method in a three dimensional (3D) space to correct the sample bias caused by the strong autocorrelation of PWD outbreaks. The MaxEnt model was used to estimate the relationships between PWD occurrence and environmental characteristics and to predict potential PWD risk areas under four shared socioeconomic pathways (SSP) scenarios (SSP126, SSP245, SSP370, and SSP585) over the period 2020–2100. The model showed improved performance by correcting the sampling bias, with high accuracy (area under the curve values of 0.87 and 0.92 for model training and testing, respectively). Isothermality and annual precipitation contributed most strongly to the distribution of PWD. The potential PWD distribution will increase in the near future (2021–2040) and will expand northward in 2061–2100 under the SSP370 and SSP585 scenarios. This study also provides detailed maps of current and future carbon stock losses caused by PWD, which show the current maximum losses (∼24.9% of total forest carbon stocks) and an increase of ∼39,000 km2 in carbon stock losses in the northeast China for the period 2061–2100 under the SSP370 and SSP585 scenarios. Overall, our results show dramatic spatiotemporal shifts in the PWD distribution and forest carbon stock losses under climate change scenarios, and will provide a useful reference for implementing pest control techniques and forest management strategies.

Factors associated with medication interruption among outpatients with severe mental illness exposed to COVID-19.

Many patients with severe mental illness (SMI) relapsed and deteriorated during the COVID-19 pandemic, as they experienced medication interruption. This study aimed to investigate factors affecting medication interruption in patients with SMI during the COVID-19 pandemic. A total of 2,077 patients with SMI participated in an online survey on medication interruption during the COVID-19 outbreak. The questionnaire comprised six parts: basic demographic information, COVID-19 exposure, state of disease, medication compliance before COVID-19, medication interruption during COVID-19, and the specific impact and needs. A total of 2,017 valid questionnaires were collected. Nearly 50% of patients with SMI have been affected to varying degrees of life expectancy and treatment. Among them, 74 patients stopped taking medicines for more than 14 days without a prescription. Logistic regression analysis showed that cohabitant exposure [OR = 26.629; 95% CI (3.293-215.323), p = 0.002], medication partial compliance and non-compliance pre-COVID-19 [OR = 11.109; 95% CI (6.093-20.251), p < 0.001; OR = 20.115; 95% CI (10.490-38.571), p < 0.001], and disease status [OR = 0.326; 95% CI (0.188-0.564), p < 0.001] were related to medication interruption. More than 50% of the patients wanted help in taking medications, follow-up, and receiving more financial support and protective materials. We found that the daily lives of patients with SMI were much more susceptible to impact during the pandemic. Patients with a history of partial or non-medication compliance before COVID-19 and an unstable disease state are more easily affected by pandemics and epidemics and need extra attention should similar large-scale outbreaks occur in the future.

The COVID-19 Pandemic Sparked Off a Large-Scale Outbreak of Carbapenem-Resistant Acinetobacter baumannii from the Endemic Strains at an Italian Hospital.

Acinetobacter baumannii is a nosocomial pathogen that poses a serious threat due to the rise of incidence of multidrug-resistant (MDR) strains. During the COVID-19 pandemic, MDR A. baumannii clones have caused several outbreaks worldwide. Here, we describe a detailed investigation of an MDR A. baumannii outbreak that occurred at Policlinico San Matteo (Pavia, Italy). A total of 96 A. baumannii strains, isolated between January and July 2020 from 41 inpatients (both SARS-CoV-2 positive and negative) in different wards, were characterized by phenotypic and genomic analyses combining Illumina and Nanopore sequencing. Antibiotic susceptibility testing revealed that all isolates were resistant to carbapenems, and the sequence analysis attributed this to the carbapenemase gene blaOXA-23. Virulence factor screening unveiled that all strains carried determinants for biofilm formation, while plasmid analysis revealed the presence of two plasmids, one of which was ~100 kbp long and encoded a phage sequence. A core genome-based phylogeny was inferred to integrate outbreak strain genomes with background genomes from public databases and the local surveillance program. All strains belonged to the globally disseminated sequence type 2 (ST2) clone and were mainly divided into two clades. Isolates from the outbreak clustered with surveillance isolates from 2019, suggesting that the outbreak was caused by two strains that were already circulating in the hospital before the start of the pandemic. The intensive spread of A. baumannii in the hospital was enhanced by the extreme emergency situation of the first COVID-19 pandemic wave that resulted in reduced attention to infection prevention and control practices. IMPORTANCE The COVID-19 pandemic, especially during the first wave, posed a great challenge to the hospital management and generally promoted nosocomial pathogen dissemination. MDR A. baumannii can easily spread and persist for a long time on surfaces, causing outbreaks in health care settings. Infection prevention and control practices, epidemiological surveillance, and microbiological screening are fundamental in order to control such outbreaks. Here, we sequenced the genomes of 96 isolates from an outbreak of MDR A. baumannii strains using both short- and long-read technology in order to reconstruct the outbreak events in fine detail. The sequence data demonstrated that two endemic clones of MDR A. baumannii were the source of this large hospital outbreak during the first COVID-19 pandemic wave, confirming the effect of COVID-19 emergency disrupting the protection provided by the use of the standard prevention procedures.

Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach

Climate change-induced heat waves increase the global risk of forest fires, intensifying biomass burning and accelerating climate change in a vicious cycle. This presents a challenge to the response system in heavily forested South Korea, increasing the risk of more frequent and large-scale fire outbreaks. This study aims to optimize IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM)—a processed-based model integrating biophysical and human impacts—to South Korea for projecting the pattern and scale of future forest fires. The developments performed in this study include: (1) the optimization of probability algorithms in FLAM based on the national GIS data downscaled to 1 km2 with additional factors introduced for national specific modeling; (2) the improvement of soil moisture computation by adjusting the Fine Fuel Moisture Code (FFMC) to represent vegetation feedbacks by fitting soil moisture to daily remote sensing data; and (3) projection of future forest fire frequency and burned area. Our results show that optimization has considerably improved the modeling of seasonal patterns of forest fire frequency. Pearson’s correlation coefficient between monthly predictions and observations from national statistics over 2016–2022 was improved from 0.171 in the non-optimized to 0.893 in the optimized FLAM. These findings imply that FLAM’s main algorithms for interpreting biophysical and human impacts on forest fire at a global scale are only applicable to South Korea after the optimization of all modules, and climate change is the main driver of the recent increases in forest fires. Projections for forest fire were produced for four periods until 2100 based on the forest management plan, which included three management scenarios (current, ideal, and overprotection). Ideal management led to a reduction of 60–70% of both fire frequency and burned area compared to the overprotection scenario. This study should be followed by research for developing adaptation strategies corresponding to the projected risks of future forest fires.

Chikungunya Virus: Priority Pathogen or Passing Trend?

Chikungunya virus (CHIKV) is considered a priority pathogen and a major threat to global health. While CHIKV infections may be asymptomatic, symptomatic patients can develop chikungunya fever (CHIKF) characterized by severe arthralgia which often transitions into incapacitating arthritis that could last for years and lead to significant loss in health-related quality of life. Yet, Chikungunya fever (CHIKF) remains a neglected tropical disease due to its complex epidemiology and the misrepresentation of its incidence and disease burden worldwide. Transmitted to humans by infected Aedes mosquitoes, CHIKV has dramatically expanded its geographic distribution to over 100 countries, causing large-scale outbreaks around the world and putting more than half of the population of the world at risk of infection. More than 50 years have passed since the first CHIKV vaccine was reported to be in development. Despite this, there is no licensed vaccine or antiviral treatments against CHIKV to date. In this review, we highlight the clinical relevance of developing chikungunya vaccines by discussing the poor understanding of long-term disease burden in CHIKV endemic countries, the complexity of CHIKV epidemiological surveillance, and emphasising the impact of the global emergence of CHIKV infections. Additionally, our review focuses on the recent progress of chikungunya vaccines in development, providing insight into the most advanced vaccine candidates in the pipeline and the potential implications of their roll-out.

Variability in Media Content of Public Health Outbreak Coverage: A Crisis Communication Approach

ABSTRACT This study investigated the stage-specific nature of media coverage of a large-scale dengue outbreak in Bangladesh. We employed the three-stage model of crisis communication and the extended parallel process model as an integrated theoretical framework. A content analysis of two years (2019–2020) of media coverage (N = 615) showed that the number of dengue-related threat messages was significantly higher during the precrisis and crisis response stages than the postcrisis recovery stage. By delivering higher threat messages during the early phase, the media successfully alerted their audience about the forthcoming dengue crisis. During the crisis stage, when people are expected to engage with the crisis responses, efficacy messages are critical, along with threat messages. However, the number of efficacy messages was relatively low across the stages. Coverage of efficacy messages was not significantly different across the crisis stages. The findings also revealed significant relationships with the nature of media coverage and source types and story types. Findings have implications for public health crisis communication and management.

Establishment and Application of an Indirect ELISA for the Detection of Antibodies to Porcine Streptococcus suis Based on a Recombinant GMD Protein

S. suis is an important zoonotic pathogen from sick and recessive carrier pigs that poses a serious threat to animal husbandry production and public health. It usually causes horizontal transmission among pigs. The morbidity and mortality of this disease are very high. Human infection is caused through direct or indirect contact with sick pigs. The two large-scale outbreaks in China were due to the outbreak of S. suis on pig farms, which spread to human infection; thus, detecting S. suis in pig herds is crucial. At present, the commercial S. suis ELISA type 2 kits on the market can only detect single serotypes, high probabilities of interaction reactions, and biosafety risks when using inactivated S. suis as an antigen. Phosphate-3-glyceraldehyde dehydrogenase (GAPDH), muramidase-released protein (MRP), and dihydrolipoamide dehydrogenase (DLDH) are important S. suis type 2, S. suis type 7, and S. suis type 9 protective antigens. This study purified the GMD protein (B-cell-dominant epitopes of GAPDH, MRP, and DLDH antigens) and used a diverse combination of dominant epitopes of the multiple different antigens as coated antigens, improving the sensitivity and safety of the indirect ELISA experiments. An indirect ELISA method (GMD-ELISA) was developed for detecting S. suis antibodies. The antigen-antibody response was optimized using checkerboard titration. The results of testing using ELISA for Salmonella enterica (S. enterica), Escherichia coli (E. coli), Staphylococcus aureus (SA), and Streptococcus pyogenes (S. pyogenes) were all negative, indicating that this method had strong specificity. The results were still positive when the dilution ratio of S. suis-positive serum reached 1:6, 400, thus indicating that the method had high sensitivity. The results of the reproducibility assay for indirect ELISA showed that the intra-assay coefficient of variation and the inter-assay coefficient of variation were less than 10%, indicating that the method had good repeatability. We investigated the seroprevalence of S. suis in 167 serum samples collected in East China, and 33.5% of the samples were positive for antibodies against S. suis, indicating that the prevalence of S. suis is high in pig farms in Eastern China. The novel GMD-ELISA is a convenient, sensitive, and specific diagnostic method that provides technical support for rapid diagnosis and epidemiological investigation.

How susceptible is Sudetan larch to larch canker Lachnellula willkommii (R. Hartig) Dennis? Consequences for breeding and deployment

ABSTRACT Historical results from provenance trials tended to position Sudetan larch (Larix decidua Mill. sudetica) populations among the least susceptible to larch canker (Lachnellula willkommi (R.Hartig) Dennis), in sharp contrast to Alpine populations. However, a recent large-scale outbreak of larch canker in artificial French stands planted with Sudetan larch brings into question this conclusion but also, as a consequence, the value of Sudetan larch seed orchards to mass-propagate risk-limited forest reproductive material. Clonal material from the French breeding population and seed orchards was investigated for its susceptibility to larch canker. As a first step, a genetic structure analysis of this population (220 clones) was conducted: it revealed its genetic heterogeneity, with 53.1% of the clones classified as “pure” Sudetan, 3.1% as Alpine; 1.5% as Central European and 42.3% as introgressed. Following artificial inoculation, “pure” Sudetan clones appeared generally less susceptible to canker than Alpine clones; admixed clones behaved in a similar way to the pure Sudetan material. However, the broad clonal variability observed within each population prevents the sole use of genetic origin of clones to rogue the most susceptible ones within orchards. Artificial inoculation is, so far, the only reliable way to properly assess clonal behaviour towards canker and thus support genetic roguing of orchards.

Descriptive network analysis and the influence of timescale on centrality and cohesion metrics from a system of between-herd dairy cow movements in Ontario, Canada

Previous research has demonstrated that static monthly networks of between-herd dairy cow movements in Ontario, Canada were highly fragmented, reducing potential for large-scale outbreaks. Extrapolating results from static networks can become problematic for diseases with an incubation period that exceeds the timescale of the network. The objectives of this research were to: 1) describe the networks of dairy cow movements in Ontario, and 2) describe the changes that occur among network analysis metrics when conducted at seven different timescales. Networks of dairy cow movements were created using Lactanet Canada milk recording data collected in Ontario between 2009 and 2018. Centrality and cohesion metrics were calculated after aggregating the data at seven timescales: weekly, monthly, semi-annual, annual, biennial, quinquennial, and decennial. There were 50,598 individual cows moved between Lactanet-enrolled farms, representing approximately 75% of provincially registered dairy herds. Most movements occurred over short distances (median = 39.18 km), with fewer long-range movements (maximum = 1150.80 km). The number of arcs increased marginally relative to the number of nodes with longer network timescales. Both mean out-degree, and mean clustering coefficients increased disproportionately with increasing timescale. Conversely, mean network density decreased with increasing timescale. The largest weak and strong components at the monthly timescale were small relative to the full network (267 and 4 nodes), whereas yearly networks had much higher values (2213 and 111 nodes). Higher relative connectivity in networks with longer timescales suggests pathogens with long incubation periods and animals with subclinical infection present increased potential for wide-spread disease transmission among dairy farms in Ontario. Careful consideration of disease-specific dynamics should be made when using static networks to model disease transmission among dairy cow populations.

Epidemiology and Outcomes of Hypernatraemia in Patients with COVID-19-A Territory-Wide Study in Hong Kong.

Dysnatraemias are commonly reported in COVID-19. However, the clinical epidemiology of hypernatraemia and its impact on clinical outcomes in relation to different variants of SARS-CoV-2, especially the prevailing Omicron variant, remain unclear. This was a territory-wide retrospective study to investigate the clinical epidemiology and outcomes of COVID-19 patients with hypernatraemia at presentation during the period from 1 January 2020 to 31 March 2022. The primary outcome was 30-day mortality. Key secondary outcomes included rates of hospitalization and ICU admission, and costs of hospitalization. In this study, 53,415 adult COVID-19 patients were included for analysis. Hypernatraemia was observed in 2688 (5.0%) patients at presentation, of which most cases (99.2%) occurred during the local "5th wave" dominated by the Omicron BA.2 variant. Risk factors for hypernatraemia at presentation included age, institutionalization, congestive heart failure, dementia, higher SARS-CoV-2 Ct value, white cell count, C-reactive protein and lower eGFR and albumin levels (p < 0.001 for all). Patients with hypernatraemia showed significantly higher 30-day mortality (32.0% vs. 5.7%, p < 0.001) and longer lengths of stay (12.9 ± 10.9 vs. 11.5 ± 12.1 days, p < 0.001) compared with those with normonatraemia. Multivariate analysis revealed hypernatraemia at presentation as an independent predictor for 30-day mortality (aHR 1.32, 95% CI 1.14-1.53, p < 0.001) and prolonged hospital stays (OR 1.55, 95% CI 1.17-2.05, p = 0.002). Hypernatraemia is common among COVID-19 patients, especially among institutionalized older adults with cognitive impairment and other comorbidities during large-scale outbreaks during the Omicron era. Hypernatraemia is associated with unfavourable outcomes and increased healthcare utilization.

Expression profiles of lncRNAs and their possible regulatory role in monocrotaline-induced HSOS in rats.

Aims: Long non-coding RNAs (lncRNAs) contribute to the regulation of vital physiological processes and play a role in the pathogenesis of many diseases. Monocrotaline (MCT) can cause large-scale outbreaks of toxic liver disease in humans and animals in the form of hepatic sinusoidal obstruction syndrome (HSOS). Although many experiments have been carried out to explain the pathogenesis of Monocrotaline-induced hepatic sinusoidal obstruction syndrome and to develop treatments for it, no studies have examined the role of Long non-coding RNAs in this condition. This study aimed to investigate the Long non-coding RNAs-mRNA regulation network in Monocrotaline-induced hepatic sinusoidal obstruction syndrome in rats. Main methods: We established a model for MCT-induced hepatic sinusoidal obstruction syndrome, and then carried out microarray for liver tissues of SD rats in a model of early hepatic sinusoidal obstruction syndrome (12h Monocrotaline treatment vs. control group) to investigate the differentially expressed Long non-coding RNAs and mRNAs in early hepatotoxicity. This was followed by RT-PCR analysis of selected Long non-coding RNAs, which were markedly altered. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome analyses were also conducted. Key findings: 176 Long non-coding RNAs (63 downregulated and 113 upregulated) and 4,221 mRNAs (2,385 downregulated and 1836 upregulated) were differentially expressed in the Monocrotaline-treated group compared to the control group. The biological processes identified in GO enrichment analysis as playing a role in hepatotoxicity were positive regulation of guanosine triphosphate phosphohydrolase, liver development, and the oxidation-reduction process. Pathway analysis revealed that the metabolism pathways, gap junction, and ribosome biogenesis in eukaryotes were closely related to Monocrotaline-induced hepatotoxicity. According to these analyses, LOC102552718 might play an essential role in hepatotoxicity mechanisms by regulating the expression of inositol 1,4,5-trisphosphate receptor-1 (Itpr-1). Significance: This study provides a basis for further research on the molecular mechanisms underlying Monocrotaline-induced hepatotoxicity and its treatment, especially in the early stage, when successful treatment is critical before irreversible liver damage occurs.

Vaccination effects on post-infection outcomes in the Omicron BA.2 outbreak in Shanghai

ABSTRACT Omicron and its sublineages are currently predominant and have triggered epidemiological waves of SARS-CoV-2 around the world due to their high transmissibility and strong immune escape ability. Vaccines are key measures to control the COVID-19 burden. Omicron BA.2 caused a large-scale outbreak in Shanghai since March 2022 and resulted in over 0.6 million laboratory-confirmed infections. The vaccine coverage of primary immunization among residents aged 3 years and older in Shanghai exceeded 90%, and inactivated COVID-19 vaccines were mainly delivered. In the context of high vaccine coverage, we conducted a cohort study to assess vaccine effects on reducing the probability of developing symptoms or severity of disease in infections or nonsevere cases. A total of 48,243 eligible participants were included in this study, the majority of whom had asymptomatic infections (31.0%) and mild-to-moderate illness (67.9%). Domestically developed COVID-19 vaccines provide limited protection to prevent asymptomatic infection from developing into mild-to-moderate illness and durable protection to prevent nonsevere illness from progressing to severe illness caused by Omicron BA.2. Partial vaccination fails to provide effective protection in any situation. The level of vaccine effects on disease progression in the elderly over 80 years old was relatively lower compared with other age groups. Our study results added robust evidence for the vaccine performance against Omicron infection and could improve vaccine confidence.