Background Data on breakthrough SARS-CoV-2 Delta variant infections in vaccinated individuals are limited. Methods We studied breakthrough infections among Oxford-AstraZeneca vaccinated healthcare workers in an infectious diseases hospital in Vietnam. We collected demographic and clinical data alongside serial PCR testing, measurement of SARS-CoV-2 antibodies, and viral whole-genome sequencing. Findings Between 11 th –25 th June 2021 (7-8 weeks after the second dose), 69 staff tested positive for SARS-CoV-2. 62 participated in the study. Most were asymptomatic or mildly symptomatic and all recovered. Twenty-two complete-genome sequences were obtained; all were Delta variant and were phylogenetically distinct from contemporary viruses obtained from the community or from hospital patients admitted prior to the outbreak. Viral loads inferred from Ct values were 251 times higher than in cases infected with the original strain in March/April 2020. Median time from diagnosis to negative PCR was 21 days (range 8–33). Neutralizing antibodies (expressed as percentage of inhibition) measured after the second vaccine dose, or at diagnosis, were lower in cases than in uninfected, fully vaccinated controls (median (IQR): 69.4 (50.7-89.1) vs. 91.3 (79.6-94.9), p=0.005 and 59.4 (32.5-73.1) vs. 91.1 (77.3-94.2), p=0.002). There was no correlation between vaccine-induced neutralizing antibody levels and peak viral loads or the development of symptoms. Interpretation Breakthrough Delta variant infections following Oxford-AstraZeneca vaccination may cause asymptomatic or mild disease, but are associated with high viral loads, prolonged PCR positivity and low levels of vaccine-induced neutralizing antibodies. Epidemiological and sequence data suggested ongoing transmission had occurred between fully vaccinated individuals. Funding Wellcome and NIH/NIAID
We studied the immunogenicity of the Oxford-AstraZeneca vaccine in health-care workers of a major infectious diseases hospital in Vietnam. We measured neutralizing antibodies before and 14 days after each dose, and at day 28 and month 3 after dose 1. A total of 554 workers (136 men and 418 women; age range, 22–71 years; median age, 36 years) participated with the study. Of the 144 participants selected for follow-up after dose 1, 104 and 94 gave blood for antibody measurement at weeks 6 and 8, and at month 3 after dose 1, respectively. The window time between the two doses was 6 weeks. At baseline, none had detectable neutralizing antibodies. After dose 1, the proportion of participants with detectable neutralizing antibodies increased from 27.3% (151 of 554) at day 14 to 78.0% (432 of 554) at day 28. Age correlated negatively with the development and the levels of neutralizing antibodies. However, at day 28, these differences were less profound, and women had a greater seroconversion rate and greater levels of neutralizing antibodies than men. After dose 2, these age and gender associations were not observable. In addition, the proportion of study participants with detectable neutralizing antibodies increased from 70.2% (73 of 104) before dose 2 (week 6, after dose 1) to 98.1% (102 of 104) 14 days later. At month 3, neutralizing antibodies decreased and 94.7% (89 of 94) of the study participants remained seropositive. The Oxford-AstraZeneca COVID-19 vaccine is immunogenic in Vietnamese health-care workers. These data are critical to informing the deployment of the COVID-19 vaccine in Vietnam and in Southeast Asia, where vaccination coverage remains inadequate.
For the treatment of patients with acute falciparum malaria, the combination of artemisinin as a single dose with a single dose of mefloquine was studied in 4 separate prospective trials, comprising 405 adults and 139 children with uncomplicated falciparum malaria in 2 in-patient and 2 rural out-patient studies in Viet Nam. Adults received oral artemisinin and children artemisinin suppositories. Randomized comparative treatment schedules were: artemisinin alone for 5 d, mefloquine-sulfadoxine-pyrimethamine (MSP), or quinine plus sulfadoxine-pyrimethamine (SP). Parasite clearance times (PCT) were rapid for artemisinin treated inpatients (90%: 14.8-20.4 h) but also for patients receiving MSP (PCT 90%: 18.0 h) and quinine (PCT 90%: 22.5 h). The recrudescence rate (RI) during a 28 d follow-up period among the patients given artemisinin plus mefloquine was 15% in the adult in-patients and zero in the adult and children out-patients. RI in the artemisinin 5 d treatment group was 33.3%; among those given artemisinin plus SP it was 47.3% in in-patients and in out-patients 46.1%. In the MSP treated out-patients RI was 1.5% in adults and zero in children. Artemisinin as a single dose (oral in adults and as a suppository in children) in combination with mefloquine was effective in rapidly lowering parasitaemia and in preventing recrudescence in hospital in-patients and in out-patients attending a rural health clinic. MSP alone as a single dose also rapidly reduced parasitaemia (but not as quickly as the artemisinin-mefloquine combination in out-patient children) and prevented recrudescence.
Background Interpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances in the use of Artificial Intelligence (AI) to automate many ultrasound imaging analysis tasks, no AI-enabled LUS solutions have been proven to be clinically useful in ICUs, and specifically in LMICs. Therefore, we developed an AI solution that assists LUS practitioners and assessed its usefulness in a low resource ICU. Methods This was a three-phase prospective study. In the first phase, the performance of four different clinical user groups in interpreting LUS clips was assessed. In the second phase, the performance of 57 non-expert clinicians with and without the aid of a bespoke AI tool for LUS interpretation was assessed in retrospective offline clips. In the third phase, we conducted a prospective study in the ICU where 14 clinicians were asked to carry out LUS examinations in 7 patients with and without our AI tool and we interviewed the clinicians regarding the usability of the AI tool. Results The average accuracy of beginners’ LUS interpretation was 68.7% [95% CI 66.8–70.7%] compared to 72.2% [95% CI 70.0–75.6%] in intermediate, and 73.4% [95% CI 62.2–87.8%] in advanced users. Experts had an average accuracy of 95.0% [95% CI 88.2–100.0%], which was significantly better than beginners, intermediate and advanced users (p < 0.001). When supported by our AI tool for interpreting retrospectively acquired clips, the non-expert clinicians improved their performance from an average of 68.9% [95% CI 65.6–73.9%] to 82.9% [95% CI 79.1–86.7%], (p < 0.001). In prospective real-time testing, non-expert clinicians improved their baseline performance from 68.1% [95% CI 57.9–78.2%] to 93.4% [95% CI 89.0–97.8%], (p < 0.001) when using our AI tool. The time-to-interpret clips improved from a median of 12.1 s (IQR 8.5–20.6) to 5.0 s (IQR 3.5–8.8), (p < 0.001) and clinicians’ median confidence level improved from 3 out of 4 to 4 out of 4 when using our AI tool. Conclusions AI-assisted LUS can help non-expert clinicians in an LMIC ICU improve their performance in interpreting LUS features more accurately, more quickly and more confidently.
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