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Japanese encephalitis (JE) is a mosquito-borne disease, known for its high mortality and disability rate among symptomatic cases. Many effective vaccines are available for JE, and the use of a recently developed and inexpensive vaccine, SA 14-14-2, has been increasing over the recent years particularly with Gavi support. Estimates of the local burden and the past impact of vaccination are therefore increasingly needed, but difficult due to the limitations of JE surveillance. In this study, we implemented a mathematical modelling method (catalytic model) combined with age-stratifed case data from our systematic review which can overcome some of these limitations. We estimate in 2015 JEV infections caused 100,308 JE cases (95% CI: 61,720–157,522) and 25,125 deaths (95% CI: 14,550–46,031) globally, and that between 2000 and 2015 307,774 JE cases (95% CI: 167,442–509,583) were averted due to vaccination globally. Our results highlight areas that could have the greatest benefit from starting vaccination or from scaling up existing programs and will be of use to support local and international policymakers in making vaccine allocation decisions.

Japanese Encephalitis (JE) is known for its high case fatality ratio (CFR) and long-term neurological sequelae. Over the years, efforts in JE treatment and control might change the JE fatality risk. However, previous estimates were from 10 years ago, using data from cases in the 10 years before this. Estimating JE disease severity is challenging because data come from countries with different JE surveillance systems, diagnostic methods, and study designs. Without precise and timely JE disease severity estimates, there is continued uncertainty about the JE disease burden and the effect of JE vaccination. We performed a systematic review to collate age-stratified JE fatality and morbidity data. We used a stepwise model selection with BIC as the selection criteria to identify JE CFR drivers. We used stacked regression, to predict country-specific JE CFR from 1961 to 2030. JE morbidity estimates were grouped from similar study designs to estimate the proportion of JE survivors with long-term neurological sequelae. We included 82 and 50 peer-reviewed journal articles published as of March 06 2021 for JE fatality and morbidity with 22 articles in both analyses. Results suggested overall JE CFR estimates of 26% (95% CI 22, 30) in 1961-1979, 20% (95% CI 17, 24) in 1980-1999, 14% (95% CI 11, 17) in 2000-2018, and 14% (95% CI 11, 17) in 2019-2030. Holding other variables constant, we found that JE fatality risk decreased over time (OR: 0.965; 95% CI: 0.947-0.983). Younger JE cases had a slightly higher JE fatality risk (OR: 1.012; 95% CI: 1.003-1.021). The odds of JE fatality in countries with JE vaccination is 0.802 (90% CI: 0.653-0.994; 95% CI: 0.62-1.033) times lower than the odds in countries without JE vaccination. Ten percentage increase in the percentage of rural population to the total population was associated with 15.35% (95% CI: 7.71, 22.57) decrease in JE fatality odds. Ten percentage increase in population growth rate is associated with 3.71% (90% CI: 0.23, 7.18; 95% CI: -0.4, 8.15) increase in JE fatality odds. Adjusting for the effect of year, rural population percent, age of JE cases, and population growth rate, we estimated that there was a higher odds of JE fatality in India compared to China. (OR: 5.46, 95% CI: 3.61-8.31). Using the prediction model we found that, in 2000-2018, Brunei, Pakistan, and Timor-Leste were predicted to have the highest JE CFR of 20%. Bangladesh, Guam, Pakistan, Philippines, and Vietnam had projected JE CFR over 20% for after 2018, whereas the projected JE CFRs were below 10% in China, Indonesia, Cambodia, Myanmar, Malaysia, and Thailand. For disability, we estimated that 36% (min-max 0-85) JE patients recovered fully at hospital discharge. One year after hospital discharge, 46% (min-max 0%-97%) JE survivors were estimated to live normally but 49% (min-max 3% - 86%)till had neurological sequelae. JE CFR estimates were lower than 20% after 2000. Our study provides an updated estimation of CFR and proportion of JE cases with long-term neurological sequelae that could help to refine cost-benefit assessment for JE control and elimination programs.

Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, serogroup A, rotavirus, rubella, , and yellow fever over the years 2000-2030 across 112 countries. Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

The role of the IFI6 gene has been described in several cancers, but its involvement in esophageal cancer (ESCA) remains unclear. This study aimed to identify novel prognostic indicators for ESCA-targeted therapy by investigating IFI6’s expression, epigenetic mechanisms, and signaling activities. We utilized public data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) to analyze IFI6’s expression, clinical characteristics, gene function, pathways, and correlation with different immune cells in ESCA. The TIMER2.0 database was employed to assess the pan-cancer expression of IFI6, while UALCAN was used to examine its expression across tumor stages and histology subtypes. Additionally, the KEGG database helped identify related pathways. Our findings revealed 95 genes positively correlated and 15 genes negatively correlated with IFI6 in ESCA. IFI6 was over-expressed in ESCA and other cancers, impacting patient survival and showing higher expression in tumor tissues than normal tissues. IFI6 was also correlated with CD4+ T cells and B cell receptors (BCRs), both essential in immune response. GO Biological Process (GO BP) enrichment analysis indicated that IFI6 was primarily associated with the Type I interferon signaling pathway and the defense response to viruses. Intriguingly, KEGG pathway analysis demonstrated that IFI6 and its positively correlated genes in ESCA were mostly linked to the Cytosolic DNA-sensing pathway, which plays a crucial role in innate immunity and viral defense, and the RIG-I-like receptor (RLR) signaling pathway, which detects viral infections and activates immune responses. Pathways related to various viral infections were also identified. It is important to note that our study relied on online databases. Given that ESCA consists of two distinct subgroups (ESCC and EAC), most databases combine them into a single category. Future research should focus on evaluating IFI6 expression and its impact on each subgroup to gain more specific insights. In conclusion, inhibiting IFI6 using targeted therapy could be an effective strategy for treating ESCA considering its potential as a biomarker and correlation with immune cell factors.

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% – 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% – 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens. Multi-strain pathogens, such as influenza, present challenges for interpretation of seroprevalence data as estimates may vary by strain. Here, the authors develop a method for estimating age-specific seroprevalence based on principal components analysis and apply it to influenza data from Vietnam.

The aim of this paper is to examine how a shock in the oil industry affects firms’ debt funding obligations using credit default swaps in different segments of the oil industry’s value chain. In particular, it focuses on two types of shocks suffered by upstream, integrated and downstream firms in the industry, namely (1) endogenous shocks resulting from oil-market shocks, and (2) exogenous shocks resulting from the recent financial crisis and the Covid-19 pandemic. Using a wide data set ranging from 2007 to 2020, this paper measures the dynamic relationships between the CDS spreads of oil-related firms, US dollar exchange rates, and crude oil prices at different sectors of the oil-industry value chain, namely, upstream, integrated and downstream. Overall results show that the upstream firms have suffered the largest impacts during the COVID-19 crisis, when experiencing shocks from USD rates or oil prices. Integrated firms have suffered the second-largest effects, however, and interestingly, no significant impacts from shocks are observed on CDS spreads for downstream firms.

Sand mining, among the many activities that have significant effects on the bed changes of rivers, has increased in many parts of the world in recent decades. Numerical modeling plays a vital role in simulation in the long term; however, computational time remains a challenge. In this paper, we propose a sand mining component integrated into the bedload continuity equation and combine it with high-performance computing using graphics processing units to boost the speed of the simulation. The developed numerical model is applied to the Mekong river segment, flowing through Tan Chau Town, An Giang Province, Vietnam. The 20 years from 1999 to 2019 is examined in this study, both with and without sand mining activities. The results show that the numerical model can simulate the bed change for the period from 1999 to 2019. By adding the sand mining component (2002–2006), the bed change in the river is modeled closely after the actual development. The Tan An sand mine in the area (2002–2006) caused the channel to deviate slightly from that of An Giang and created a slight erosion channel in 2006 (−23 m). From 2006 to 2014, although Tan An mine stopped operating, the riverbed recovered quite slowly with a small accretion rate (0.25 m/year). However, the Tan An sand mine eroded again from 2014–2019 due to a lack of sand. In 2014, in the Vinh Hoa communes, An Giang Province, the Vinh Hoa sand mine began to operate. The results of simulating with sand mining incidents proved that sand mining caused the erosion channel to move towards the sand mines, and the erosion speed was faster when there was no sand mining. Combined with high-performance computing, harnessing the power of accelerators such as graphics processing units (GPUs) can help run numerical simulations up to 23x times faster.

Seroepidemiological studies aim to understand population-level exposure and immunity to infectious diseases. Their results are normally presented as binary outcomes describing the presence or absence of pathogen-specific antibody, despite the fact that many assays measure continuous quantities. A population’s natural distribution of antibody titers to an endemic infectious disease may include information on multiple serological states – naiveté, recent infection, non-recent infection, childhood infection – depending on the disease in question and the acquisition and waning patterns of immunity. In this study, we investigate 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which we report antibody titers to the influenza virus HA1 protein using a continuous titer measurement from a protein microarray assay. We describe the distributions of antibody titers to subtypes 2009 H1N1 and H3N2. Using a model selection approach to fit mixture distributions, we show that 2009 H1N1 antibody titers fall into four titer subgroups and that H3N2 titers fall into three subgroups. For H1N1, our interpretation is that the two highest-titer subgroups correspond to recent and historical infection, which is consistent with 2009 pandemic attack rates. Similar interpretations are available for H3N2, but right-censoring of titers makes these interpretations difficult to validate.

Arbovirus infections are a serious concern in tropical countries due to their high levels of transmission and morbidity. With the outbreaks of chikungunya (CHIKV) in surrounding regions in recent years and the fact that the environment in Vietnam is suitable for the vectors of CHIKV, the possibility of transmission of CHIKV in Vietnam is of great interest. However, information about CHIKV activity in Vietnam remains limited. In order to address this question, we performed a systematic review of CHIKV in Vietnam and a CHIKV seroprevalence survey. The seroprevalence survey tested for CHIKV IgG in population serum samples from individuals of all ages in 2015 from four locations in Vietnam. The four locations were An Giang province (n = 137), Ho Chi Minh City (n = 136), Dak Lak province (n = 137), and Hue City (n = 136). The findings give us evidence of some CHIKV activity: 73/546 of overall samples were seropositive (13.4%). The age-adjusted seroprevalences were 12.30% (6.58-18.02), 13.42% (7.16-19.68), 7.97% (3.56-12.38), and 3.72% (1.75-5.69) in An Giang province, Ho Chi Minh City, Dak Lak province, and Hue City respectively. However, the age-stratified seroprevalence suggests that the last transmission ended around 30 years ago, consistent with results from the systematic review. We see no evidence for on-going transmission in three of the locations, though with some evidence of recent exposure in Dak Lak, most likely due to transmission in neighbouring countries. Before the 1980s, when transmission was occurring, we estimate on average 2-4% of the population were infected each year in HCMC and An Giang and Hue (though transmision ended earlier in Hue). We estimate lower transmission in Dak Lak, with around 1% of the population infected each year. In conclusion, we find evidence of past CHIKV transmission in central and southern Vietnam, but no evidence of recent sustained transmission. When transmission of CHIKV did occur, it appeared to be widespread and affect a geographically diverse population. The estimated susceptibility of the population to chikungunya is continually increasing, therefore the possibility of future CHIKV transmission in Vietnam remains.