Transmission of SARS-CoV-2 Delta Variant Among Vaccinated Healthcare Workers, Vietnam (preprint)

Background: Data on breakthrough SARS-CoV-2 Delta variant infections are limited.Methods: We studied breakthrough infections among healthcare workers of a major infectious diseases hospital in Vietnam. We collected demographics, vaccination history and results of PCR diagnosis alongside clinical data. We measured SARS-CoV-2 (neutralizing) antibodies at diagnosis, and at week 1, 2 and 3 after diagnosis. We sequenced the viruses using ARTIC protocol.Findings: Between 11th–25th June 2021 (week 7–8 after dose 2), 69 healthcare workers were tested positive for SARS-CoV-2. 62 participated in the clinical study. 49 were (pre)symptomatic with one requiring oxygen supplementation. All recovered uneventfully. 23 complete-genome sequences were obtained. They all belonged to the Delta variant, and were phylogenetically distinct from the contemporary Delta variant sequences obtained from community transmission cases, suggestive of ongoing transmission between the workers. Viral loads of breakthrough Delta variant infection cases were 251 times higher than those of cases infected with old strains detected between March-April 2020. Time from diagnosis to PCR negative was 8–33 days (median: 21). Neutralizing antibody levels after vaccination and at diagnosis of the cases were lower than those in the matched uninfected controls. There was no correlation between vaccine-induced neutralizing antibody levels and viral loads or the development of symptoms.Interpretation: Breakthrough Delta variant infections are associated with high viral loads, prolonged PCR positivity, and low levels of vaccine-induced neutralizing antibodies, explaining the transmission between the vaccinated people. Physical distancing measures remain critical to reduce SARS-CoV-2 Delta variant transmission.Funding: Wellcome (106680/B/14/Z and 204904/Z/16/Z).Declaration of Interest: None to declare.Ethical Approval: The study was approved by the Institutional Review Board of HTD and the Oxford Tropical Research Ethics Committee, University of Oxford, UK.

Immunogenicity of Oxford-AstraZeneca COVID-19 vaccine in Vietnamese healthcare workers (preprint)

We studied the immunogenicity of Oxford-AstraZeneca vaccine in Vietnamese healthcare workers. We collected blood samples before each dose, at 14 days after each dose, and month 1 and 3 after dose 1 from each participant alongside demographics data. We measured neutralizing antibodies using a surrogate virus neutralization assay. The 554 study participants (136 males and 418 females) were aged between 22-71 years (median: 36 years). 104 and 94 out of 144 selected participants were successfully followed up at 14 days after dose 2 and 3 months after dose 1, respectively. Neutralizing antibodies increased after each dose, with the sero-conversion rate reaching 98.1% (102/104) at 14 days after dose 2. At month 3 after dose 1, neutralizing antibody levels decreased, while 94.7% (89/94) of the study participants remained seropositive. Oxford-AstraZeneca COVID-19 vaccine is immunogenic in Vietnamese healthcare workers. The requirement for a third dose warrants further research.

Predicting COVID-19 incidence in French hospitals using human contact network analytics (preprint)

Coronavirus disease (COVID-19) was detected in Wuhan, China in 2019 and spread worldwide within few weeks. The COVID-19 epidemic started to gain traction in France in March 2020. Sub-national hospital admissions and deaths were then recorded daily and served as the main policy indicators. Concurrently, mobile phone positioning data have been curated to determine the frequency of users being colocalized within a given distance. Contrarily to individual tracking data, these can provide a proxy of human contact networks between subnational administrative units. Motivated by numerous studies correlating human mobility data and disease incidence, we developed predictive time series models of hospital incidence between July 2020 and April 2021. Adding human contact network analytics such as clustering coefficients, contact network strength, null links or curvature as regressors, we found that predictions can be improved substantially (more than 50%) both at the national and sub-national for up to two weeks. Our sub-national analysis also revealed the importance of spatial structure, as incidence in colocalized administrative units improved predictions. This original application of network analytics from co-localisation data to epidemic spread opens new perspectives for epidemics forecasting and public health.

Preventing laboratory-associated infections in the COVID-19 era: experience from a tertiary care infectious disease hospital in Southern Vietnam (preprint)

Objectives: Laboratory staff is at higher risk of coronavirus disease 2019 (COVID-19) infection owing to the handling of patient samples. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) focus risk assessment and risk management are essential for preventing laboratory acquired infections (LAIs). We present herein the steps taken to prevent LAIs related to SARS-CoV-2 testing from February 1, 2020 to September 17, 2020 in a tertiary care hospital in Vietnam. Results: A SARS-CoV-2-focused risk assessment was conducted for laboratory processes. Risk management strategies, including engineering, administrative and operations control procedures, were established. This includes the use of dedicated facility, instrument, and cold chain units for testing; SOPs; training (testing, decontamination and cleaning staff); the introduction of biosafety level 2+ laboratory practices; COVID-19 symptom reporting; enhanced cleaning protocols; and the assigning of additional staff for testing and safety system implementation. In total, 38,377 (daily mean and range: 166; 3 – 2,377) samples were received and tested. The turnaround time (median ± standard deviation (SD)) was 3.54 ± 2.97 days. Altogether, 32 staff members were involved with SARS-CoV-2 testing and biosafety management, and there were no reports of COVID-19 symptoms among them. 

Age-structured non-pharmaceutical interventions for optimal control of COVID-19 epidemic (preprint)

In an epidemic, individuals can widely differ in the way they spread the infection, for instance depending on their age or on the number of days they have been infected for. The latter allows to take into account the variation of infectiousness as a function of time since infection. In the absence of pharmaceutical interventions such as a vaccine or treatment, non-pharmaceutical interventions (e.g. social distancing) are of great importance to mitigate the pandemic. We propose a model with a double continuous structure by host age and time since infection. By applying optimal control theory to our age-structured model, we identify a solution minimizing deaths and costs associated with the implementation of the control strategy itself. This strategy depends on the age heterogeneity between individuals and consists in a relatively high isolation intensity over the older populations during a hundred days, followed by a steady decrease in a way that depends on the cost associated to a such control. The isolation of the younger population is weaker and occurs only if the cost associated with the control is relatively low. We show that the optimal control strategy strongly outperforms other strategies such as uniform constant control over the whole populations or over its younger fraction. These results bring new facts the debate about age-based control interventions and open promising avenues of research, for instance of age-based contact tracing.

The first 100 days of SARS-CoV-2 control in Vietnam (preprint)

Background: One hundred days after SARS-CoV-2 was first reported in Vietnam on January 23rd, 270 cases have been confirmed, with no deaths. We describe the control measures used and their relationship with imported and domestically-acquired case numbers. Methods: Data on the first 270 SARS-CoV-2 infected cases and the timing and nature of control measures were captured by Vietnam's National Steering Committee for COVID-19 response. Apple and Google mobility data provided population movement proxies. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of pre-symptomatic transmission events and time-varying reproduction numbers. Results: After the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, contact tracing, mandatory 14-day quarantine, school and university closures, and progressive flight restrictions. A national lockdown was implemented between April 1st and 22nd. Around 200,000 people were quarantined and 266,122 RT-PCR tests conducted. Population mobility decreased progressively before lockdown. 60% (163/270) of cases were imported; 43% (89/208) of resolved infections were asymptomatic. 21 developed severe disease, with no deaths. The serial interval was 3.24 days, and 27.5% (95% confidence interval, 15.7%-40.0%) of transmissions occurred pre-symptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% confidence interval, 0.37-2.36). No community transmission has been detected since April 15th. Conclusions: Vietnam has controlled SARS-CoV-2 spread through the early introduction of communication, contact-tracing, quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic cases and imported cases, and evidence for substantial pre-symptomatic transmission.

Social interventions can lower COVID-19 deaths in middle-income countries (preprint)

A novel pandemic coronavirus disease (COVID-19) was first detected in late 2019 in Wuhan (China)1,2. COVID-19 has caused 77 national governments worldwide to impose a lockdown in part or all their countries, as of April 4, 20203. The United States and the United Kingdom estimated the effectiveness of non-pharmaceutical interventions to reduce COVID-19 deaths, but there is less evidence to support choice of control measures in middle-income countries4. We used Colombia, an upper-middle income country, as a case-study to assess the effect of social interventions to suppress or mitigate the COVID-19 pandemic. Here we show that a combination of social distancing interventions, triggered by critical care admissions, can suppress and mitigate the peak of COVID-19, resulting in less critical care use, hospitalizations, and deaths. We found, through a mathematical simulation model, that a one-time social intervention may delay the number of critical care admissions and deaths related to the COVID-19 pandemic. However, a series of social interventions (social and work distance and school closures) over a period of a year can reduce the expected burden of COVID-19, however, these interventions imply long periods of lockdown. Colombia would prevent up to 97% of COVID-19 deaths using these triggered series of interventions during the first year. Our analyses could be used by decision-makers from other middle-income countries with similar demographics and contact patterns to Colombia to reduce COVID-19 critical care admissions and deaths in their jurisdictions.

Optimal COVID-19 epidemic control until vaccine deployment (preprint)

Since Dec 2019, the COVID-19 epidemic has spread over the globe creating one of the greatest pandemics ever witnessed. This epidemic wave will only begin to roll back once a critical proportion of the population is immunised, either by mounting natural immunity following infection, or by vaccination. The latter option can minimise the cost in terms of human lives but it requires to wait until a safe and efficient vaccine is developed, a period estimated to last at least 18 months. In this work, we use optimal control theory to explore the best strategy to implement while waiting for the vaccine. We seek a solution minimizing deaths and costs due to the implementation of the control strategy itself. We find that such a solution leads to an increasing level of control with a maximum reached near the 16th month of the epidemics and a steady decrease until vaccine deployment. The average containment level is approximately 50\% during the 25-months period for vaccine deployment. This strategy strongly outperforms others with constant or cycling allocations of the same amount of resources to control the outbreak. This work opens new perspectives to mitigate the effects of the ongoing COVID-19 pandemics, and be used as a proof-of-concept in using mathematical modelling techniques to enlighten decision making and public health management in the early times of an outbreak.