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

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

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. HighlightsO_LIWe use novel human contact network analytics based on colocation data of mobile app users to follow the dynamics of disease incidence and interventions of COVID-19 in France. C_LIO_LITime series predictions of hospital incidence are greatly improved by adding these analytics as regressors. C_LIO_LISub-national analysis highlights both spatial correlations of incidence and network analytics to obtain high-precision predictions. C_LI

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

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

BackgroundOne 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 by the Government and their relationship with imported and domestically-acquired case numbers, with the aim of identifying the measures associated with successful SARS-CoV-2 control. MethodsClinical and demographic data on the first 270 SARS-CoV-2 infected cases and the timing and nature of Government control measures, including numbers of tests and quarantined individuals, were captured by Vietnams National Steering Committee for COVID-19 response. Apple and Google mobility data provided proxies for population movement. 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. FindingsAfter the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, case-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 remained asymptomatic for the duration of infection. 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. InterpretationVietnam has controlled SARS-CoV-2 spread through the early introduction of mass communication, meticulous contact-tracing with strict quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic and imported cases, and evidence for substantial pre-symptomatic transmission. FundingThe Vietnam Ministry of Health and Wellcome Trust, UK. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSVietnam was one of the first countries outside of China to detect imported and human-to-human transmitted SARS-CoV-2 within its borders. Yet, as of May 1st, a total of only 270 cases have been confirmed, no deaths have occurred, and no community transmission has been detected since April 15th despite intensive screening, tracing and testing. We did a PubMed database search to identify studies investigating COVID-19 response in Vietnam using the terms "Vietnam", "COVID-19", and "SARS-CoV-2". All relevant articles were evaluated. Studies describe cases of COVID-19 and their management, aspects of the government response from newspapers and online government sources, but there are no previous reports using national data to describe and investigate the national epidemic and the impact of control measures cases over time. Added value of this studyWe used data from the National Steering Committee for COVID-19 response to give a comprehensive account of the first 100 days of the SARS-CoV-2 epidemic in Vietnam, including case numbers and their symptomatology, the estimated reproductive number by week, and their relation to the multiple control measures instituted by the Vietnam Government over time. We show two distinctive features of Vietnams response. First, the Government took rapid actions to restrict international flights, closed schools and universities, and instituted meticulous case-contact tracing and quarantining from late January, well before these measures were advised by WHO. Second, they placed mass communication, education, and the identification, serial testing, and 14-day quarantine of all direct contacts of cases, regardless of symptom development, at the heart of the response. The value of strict contact-tracing and quarantine is supported by the high proportion of asymptomatic cases (43%) and imported cases (60%), and evidence for substantial pre-symptomatic transmission. Implications of all the available evidenceVietnam has had remarkable success in controlling the emergence of SARS-CoV-2. Our report provides a complete picture of the control of SARS-CoV-2 in Vietnam, with lessons for other Governments seeking to extend national SARS-CoV-2 control or prevent future epidemics. Our findings shows the importance of acting early, before the virus becomes established in the community, and before the case numbers overwhelm systems of case-contact tracing and mass quarantine. They also demonstrate the value of effective mass communication in rapidly educating the public in infection prevention measures and providing real-time information on the state of the epidemic.

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

Summary paragraphA 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

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 out-performs 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.