Indoor PM₀.₁ and PM₂.₅ in Hanoi: Chemical characterization, source identification, and health risk assessment

This study attempted to provide comprehensive insights into the chemical composition, source identification, and health risk assessment of indoor particulate matter (PM) in urban areas of Vietnam. Three hundred and twenty daily samples of PM₀.₁ and PM₂.₅ were collected at three different types of dwellings in Hanoi in two seasons, namely summer and winter. The samples were analyzed for 10 trace elements (TEs), namely Cr, Mn, Co, Cu, Ni, Zn, As, Cd, Sn, and Pb. The daily average concentrations of indoor PM₀.₁ and PM₂.₅ in the city were in the ranges of 7.0–8.9 μg/m³ and 43.3–106 μg/m³, respectively. The average concentrations of TEs bound to indoor PM ranged from 66.2 ng/m³ to 216 ng/m³ for PM₀.₁ and 391 ng/m³ to 2360 ng/m³ for PM₂.₅. Principle component analysis and enrichment factor were applied to identify the possible sources of indoor PM. Results showed that indoor PM₂.₅ was mainly derived from outdoor sources, whereas indoor PM₀.₁ was derived from indoor and outdoor sources. Domestic coal burning, industrial and traffic emissions were observed as outdoor sources, whereas household dust and indoor combustion were found as indoor sources. 80% of PM₂.₅ was deposited in the head airways, whereas 75% of PM₀.₁ was deposited in alveolar region. Monte Carlo simulation indicated that the intake of TEs in PM₂.₅ can lead to high carcinogenic risk for people over 60 years old and unacceptable non-carcinogenic risks for all ages at the roadside house in winter

A model immunization programme to control Japanese encephalitis in Viet Nam.

In Viet Nam, an inactivated, mouse brain-derived vaccine for Japanese encephalitis (JE) has been given exclusively to ≤ 5 years old children in 3 paediatric doses since 1997. However, JE incidence remained high, especially among children aged 5-9 years. We conducted a model JE immunization programme to assess the feasibility and impact of JE vaccine administered to 1-9 year(s) children in 3 standard-dose regimen: paediatric doses for children aged <3 years and adult doses for those aged ≥ 3 years. Of the targeted children, 96.2% were immunized with ≥ 2 doses of the vaccine. Compared to the national immunization programme, JE incidence rate declined sharply in districts with the model programme (11.32 to 0.87 per 100,000 in pre-versus post-vaccination period). The rate of reduction was most significant in the 5-9 years age-group. We recommend a policy change to include 5-9 years old children in the catch-up immunization campaign and administer a 4th dose to those aged 5-9 years, who had received 3 doses of the vaccine during the first 2-3 years of life

A Model Immunization Programme to Control Japanese Encephalitis in Viet Nam

In Viet Nam, an inactivated, mouse brain-derived vaccine for Japanese encephalitis (JE) has been given exclusively to 645 years old children in 3 paediatric doses since 1997. However, JE incidence remained high, especially among children aged 5-9 years. We conducted a model JE immunization programme to assess the feasibility and impact of JE vaccine administered to 1-9 year(s) children in 3 standard-dose regimen: paediatric doses for children aged &lt;3 years and adult doses for those aged 653 years. Of the targeted children, 96.2% were immunized with 652 doses of the vaccine. Compared to the national immunization programme, JE incidence rate declined sharply in districts with the model programme (11.32 to 0.87 per 100,000 in pre- versus post-vaccination period). The rate of reduction was most significant in the 5-9 years age-group. We recommend a policy change to include 5-9 years old children in the catch-up immunization campaign and administer a 4th dose to those aged 5-9 years, who had received 3 doses of the vaccine during the first 2-3 years of life

A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis

Background Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known. Methods We included 659 individuals aged ≥ 16 years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl–Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified the reduction in TBM risk after confirmatory tests were negative. We also fitted a simplified model and developed a scoring table for early screening. All models were compared and validated internally. Results Participants with HIV, miliary TB, long symptom duration, and high cerebrospinal fluid (CSF) lymphocyte count were more likely to have TBM. HIV and higher CSF protein were associated with higher mycobacillary burden. In the simplified model, HIV infection, clinical symptoms with long duration, and clinical or radiological evidence of extra-neural TB were associated with TBM At the cutpoints based on Youden’s Index, the sensitivity and specificity in diagnosing TBM for our full and simplified models were 86.0% and 79.0%, and 88.0% and 75.0% respectively. Conclusion Our diagnostic model shows reliable performance and can be developed as a decision assistant for clinicians to detect patients at high risk of TBM. Summary Diagnosis of tuberculous meningitis is hampered by the lack of gold standard. We developed a diagnostic model using latent class analysis, combining confirmatory test results and risk factors. Models were accurate, well-calibrated, and can support both clinical practice and research

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Data-driven approaches to linking hydrology, mineralogy, and biogeochemistry of groundwater arsenic contamination from grain to basin scale

Critical water resources, such as groundwater, are undergoing a period of intense and global environmental change, driven by climate change, anthropogenic impacts and exploitation, and perturbations to interactions of fundamental processes that are affected by hydrological, mineralogical and biogeochemical factors. Arsenic contamination is a significant threat to these water resources and the populations who depend on them, yet there are few studies directly linking water quality with changes in hydrology and geochemistry in sediments on varying scales. My research explores environmental variability in hydrology and redox processes that regulate soluble arsenic concentrations at the pore scale (µm to mm), and develops methods of upscaling these mechanistic studies to understand heterogeneity in groundwater arsenic levels and their impacts on public health at larger scales (a couple of meters to hundreds of kilometers). Specifically, my research examines the interaction of redox processes in the Earth’s subsurface that drive the release of arsenic into groundwater. Naturally-occurring, or geogenic, arsenic contamination is the main source of arsenic release into groundwater that affects human health, with possible anthropogenic exacerbation of this natural contamination. Throughout this dissertation, I have developed a suite of data-driven approaches to understand and quantify the highly variable factors that underlie the mechanisms of geogenic arsenic release into groundwater and its migration in the environment. In Chapter 1, I investigate the effects of hydrologic perturbations on formerly uncontaminated aquifers that release arsenic due to increased groundwater pumping in the Red River Delta, Vietnam. To compare the effect of hydrologic processes to measured groundwater arsenic concentrations, I used Monte Carlo simulations in an end-member mixing model and quantified fraction of different recharge sources into an aquifer based on stable water isotopes. I find that changing flow patterns due to groundwater abstraction have increased the extent of arsenic release into groundwater and also changed the location of where arsenic contamination originates. In Chapter 2, I characterize iron mineralogy associated with arsenic release through sampling of sediment cores across a lateral redox gradient in Vietnam with extensive spectroscopy measurements. Through hierarchical cluster analysis on this data set of X-ray absorption spectroscopy (XAS) measurements of borehole cuttings paired with dissolved groundwater measurements, I reveal signatures of iron mineral reduction that could cause or exacerbate arsenic release. This was upscaled to other deltaic aquifers in South and Southeast Asia based on groundwater data to identify aquifers at risk of arsenic release. I showed that the extent of older and previously pristine aquifers that have been contaminated may have been misclassified and thus underrepresented in deltaic aquifers throughout South and Southeast Asia, disrupting the assumption that older and deeper aquifers are oxidized and thus guarded against arsenic release. In Chapter 3, I use process-based reactive transport modeling of a laboratory-scale experiment to mechanistically explain the infiltration of contaminated water into uncontaminated aquifers and find that arsenic contamination cannot be explained by the commonly invoked mechanism of iron reducing bacteria only, but instead relies on sulfate reduction and complexation of aqueous arsenic in solution. The role of sulfate reduction in mobilizing arsenic in groundwater is in stark contrast to and undermines the previous use of sulfate reduction as strategy for arsenic remediation. Finally, in Chapter 4, I quantitatively examine the processes that release arsenic across different arsenic-impacted aquifers, based on the relationships between redox status of iron and arsenic mineralogy and groundwater concentrations. Synthesis of X-ray absorption spectra of the deltaic aquifers of Southeast Asia and the glacial aquifer system in the Northern United States shows that arsenic release occurs in similar geochemical environments in both systems, and is highly generalizable via statistical and unsupervised machine learning approaches. This dissertation demonstrates that common assumptions behind geogenic arsenic release must be tested: from which aquifers are low in arsenic to the commonly assumed mechanism of arsenic release by iron reducing bacteria. These findings also reveal that the extent of anthropogenic impact on geogenic arsenic contamination is detectable: from changes in recharge sources to changes in mineralogy that affect arsenic concentrations and human health. The next step is to use these data driven and machine learning approaches to quantify the vulnerability of affected aquifers, to mitigate the risk of those currently reliant on contaminated groundwater, to reduce the risks of future contamination and, ultimately, to protect human health

Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides: Model files

Model files for the reactive transport model in Nghiem et al. 2023. The folder contains a Readme.txt that describe the model files. The model files are part of the supplementary data to Nghiem et al. 2023, "Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides", Nature Water

Aquifer-scale Observations of Iron Redox Transformations in Arsenic-Impacted Environments to Predict Future Contamination: Data

Compilation of groundwater geochemistry data from compiled references and sediment classification from Nghiem et al. 2020 across South and Southeast Asia. The folder contains a Readme.txt file that describes the data and the data sources. This data was compiled as part of the Characterizing Global Variability in Groundwater Arsenic Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey. Supplementary data to Nghiem et al. 2020, “Aquifer-scale Observations of Iron Redox Transformations in Arsenic-Impacted Environments to Predict Future Contamination”, Environmental Science & Technology Letters, DOI: 10.1021/acs.estlett.0c0067

Determining demand for water, water supply and drainage balance to wastewater reuse for urbans in Vietnam

Wastewater reuse is very important in ensuring a stable water supply for the socio-economic development of cities in the future. That is even more meaningful for areas affected by climate change erratic, hot, arid, scarce and polluted due to different causes. Specifically, many regions and urban areas in Vietnam have not been proactive in water resources upstream; runoff through agricultural, industrial and urban areas contaminated by farming, industrial waste, wastewater and municipal solid waste. Based on published studies on the role and situation of wastewater reuse in urbans, as well as on legal documents Vietnam's current management related to wastewater drainage and reuse, the article presents how to calculate and determine the water demand in urban areas for calculating capacity of water supply plants; to set up the balance diagram of water supply and drainage for all types of urban areas (from special to grade V urbans) and the balance diagram of water supply and drainage in the works. The research results will be considered as a scientific basis for state management agencies as well as local authorities to appropriately and effectively use in formulating strategic orientations and objectives for urban water supply and drainage management in Vietnam urban areas

Outbreak investigation for COVID-19 in northern Vietnam

Two Vietnamese adults returned to their home province of Vinh Phuc in northern Vietnam on Jan 17, 2020, from Wuhan, China, where they had been living since Nov 15, 2019, for a business trip. They presented with mild respiratory symptoms to their local health facilities at 4 days and 8 days, respectively, after arrival in Vinh Phuc. Both individuals were initially placed into respiratory isolation in hospital. Case 1 tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative organism of coronavirus disease 2019 (COVID-19), on Jan 30, 2020, and remained in isolation until recovery. Case 2 was discharged from isolation in hospital after having one negative test result on Jan 28 (11 days after returning from Wuhan). Following discharge, the patient attended a family social function. 2 days later, she was readmitted after a second nasal swab for SARS-CoV-2 taken during her time in hospital was reported as positive