ABSTRACT
Objectives: To estimate the protection against laboratory-confirmed SARS-CoV-2 infection, hospitalisations, and death after applying a homologous or heterologous third-dose (booster) in individuals who had previously received primary vaccination schemes with rAd26-rAd5, ChAdOx1 nCoV-19, BBIBP-CorV or a heterologous combination, during the period of Omicron BA.1 predominance. Design: Retrospective, test-negative, case-control study, with a matched analysis. Setting: Province of Buenos Aires, Argentina. Data were extracted from the National Surveillance System and VacunatePBA, a system developed in the province, between 12/1/21-4/1/21. Participants: 422,144 adults older than 50 who had received two doses of COVID-19 vaccines and were tested for SARS-CoV-2. Main outcome measures: Odds ratios of confirmed SARS-CoV-2 infection, hospitalisations and death after administering a booster, compared to a two-dose primary scheme. Results: Of 221,933 (52.5%) individuals with a positive test, 190,884 (45.2%) had received a two-dose scheme of SARS-CoV-2 vaccines and 231,260 (54.8%) a three-dose scheme. The matched analysis included 127,014 cases and 180,714 controls. The administration of a homologous booster after a primary scheme with vectored vaccines provided a large protection against hospitalisations and death (OR 0.30 [0.26-0.35] and OR 0.29 [0.25-0.33] respectively). However, this effect was lower and waned earlier compared to heterologous boosters (OR 0.59 [0.47-0.74] and OR 0.51 [0.41- 0.64] respectively). The inoculation of a heterologous booster after a primary course with ChAdOx1 nCoV-19, rAd26-rAd5, BBIBP-CorV, or heterologous schemes, provided some protection against infection (OR 0.70 [0.68-0.71]), which quickly decreased after 60 days (OR 1.01 [0.98-1.04]). Notwithstanding this, there was a clear protective effect against hospitalisations (OR 0.26 [0.22-0.31]) and deaths (OR 0.22 [0.18-0.25]) that persisted after 60 days (OR 0.43 [0.35-0.53] and 0.33 [0.26-0.41], respectively). Conclusions: This study shows that, during Omicron predominance, heterologous boosters provide an enhanced protection and longer effect duration against COVID-19-related hospitalisations and death in individuals older than 50 compared to homologous boosters.
Subject(s)
COVID-19 , DeathABSTRACT
Background: Although paediatric clinical presentations of COVID-19 are usually less severe than in adults, serious illness and death have occurred. Many countries started the vaccination rollout of children in 2021; still, information about effectiveness in the real-world setting is scarce. The aim of our study was to evaluate vaccine effectiveness (VE) against COVID-19-associated-hospitalisations in the 3-17-year population during the Omicron outbreak. Methods: We conducted a retrospective cohort study including individuals aged 3-17 registered in the online vaccination system of the Buenos Aires Province, Argentina. mRNA-1273 and BNT162b2 were administered to 12-17-year subjects; and BBIBP-CorV to 3-11-year subjects. Vaccinated group had received a two-dose scheme by 12/1/2021. Unvaccinated group did not receive any COVID-19 vaccine between 12/14/2021-3/9/2022, which was the entire monitoring period. Vaccine effectiveness (VE) against COVID-19-associated hospitalisations was calculated as (1-OR) x100. Findings: By 12/1/2021, 1,536,435 individuals aged 3-17 who had received zero or two doses of SARS-CoV-2 vaccines were included in this study. Of the latter, 1,440,389 were vaccinated and 96,046 not vaccinated. VE were 78.0% [68.7-84.2], 76.4%[62.9-84.5] and 80.0%[64.3-88.0] for the entire cohort, 3-11 subgroup and 12-17 subgroup, respectively. VE for the entire population was 82.7% during the period of Delta and Omicron overlapping circulation and decreased to 67.7% when Omicron was the only variant present. Interpretation: This report provides evidence of high vaccine protection against associated-hospitalisations in the paediatric population during the Omicron outbreak but suggests a decrease of protection when Omicron became predominant. Application of a booster dose in children aged 3-11 warrants further consideration.
Subject(s)
COVID-19 , DeathABSTRACT
BackgroundTherapies to interrupt progression of early COVID-19 remain elusive. Among them, convalescent plasma in hospitalized patients was unsuccessful, perhaps because antibody should be administered earlier. We advanced plasma infusions to the first 72 hours of symptoms to arrest COVID-19 progression. MethodsA randomized, double-blind, placebo-controlled trial of convalescent plasma with high IgG titers against SARS-CoV2 in elderly subjects within 72 hours of mild COVID-19 symptoms. The primary endpoint was severe respiratory disease defined as a respiratory rate [≥]30 and/or an O2 sat<93% in room air. The study was interrupted at 76% of its projected sample size, because cases in the region decreased considerably and steady enrollment of study subjects became virtually impossible. Results160 patients underwent randomization. In the intention-to-treat analysis (ITT), 13/80(16.2%) patients receiving plasma vs. 25/80(31.2%) receiving placebo experienced severe respiratory disease [RR(95%CI)= 0.52(0.29,0.94); p=0.026)] with an RRR=48%. A modified ITT analysis, excluding six subjects who experienced the primary endpoint before infusion, showed a larger effect size [RR(95%CI) = 0.40(0.20, 0.81), p=0.007]. High- and low-titer donor analyses, based on a median IgG titer=1:3,200, evidenced a dose-dependent response with an RRR=73.3% for recipients of high-titer plasma (p=0.016) and a number needed to treat (NNT)=4.4. All secondary endpoints exhibited trends towards protection. No solicited adverse events were observed. ConclusionsEarly administration of high-titer convalescent plasma against SARS-CoV2 to mildly ill infected seniors reduced COVID-19 progression. This safe, inexpensive, outpatient intervention facilitates access to treatment from industrialized to LMIC, can decompress demands on hospitals, and may contribute to save lives. Funded by The Bill & Melinda Gates Foundation and The Fundacion INFANT Pandemic Fund. Registered in the Direccion de Sangre y Medicina Transfusional del Ministerio de Salud (PAEPCC19), Plataforma PRIISA (1421), and clinicaltrials.gov (NCT04479163). All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organization for the submitted work; RL, GPM, DW and FPP are investigators in a phase 3 SARS CoV2 trial from Pfizer; no other relationships or activities that could appear to have influenced the submitted work.
Subject(s)
COVID-19ABSTRACT
BackgroundCongregate settings are at risk for coronavirus disease 2019 (COVID-19) outbreaks. Diagnostic testing can be used as a tool in these settings to identify outbreaks and to control transmission. MethodsWe used transmission modeling to estimate the minimum number of persons to test and the optimal frequency to detect small outbreaks of COVID-19 in a congregate facility. We also estimated the frequency of testing needed to interrupt transmission within a facility. ResultsThe number of people to test and frequency of testing needed depended on turnaround time, facility size, and test characteristics. Parameters are calculated for a variety of scenarios. In a facility of 100 people, 26 randomly selected individuals would need to be tested at least every 6 days to identify a true underlying prevalence of at least 5%, with test sensitivity of 85%, and greater than 95% outbreak detection sensitivity. Disease transmission could be interrupted with universal, facility-wide testing with rapid turnaround every three days. ConclusionsTesting a subset of individuals in congregate settings can improve early detection of small outbreaks of COVID-19. Frequent universal diagnostic testing can be used to interrupt transmission within a facility, but its efficacy is reliant on rapid turnaround of results for isolation of infected individuals.
Subject(s)
COVID-19ABSTRACT
One of the main problems in controlling COVID-19 epidemic spread is the delay in confirming cases. Having information on changes in the epidemic evolution or outbreaks rise before lab-confirmation is crucial in decision making for Public Health policies. We present an algorithm to estimate on-stream the number of COVID-19 cases using the data from telephone calls to a COVID-line. By modeling the calls as background (proportional to population) plus signal (proportional to infected), we fit the calls in Province of Buenos Aires (Argentina) with coefficient of determination R2 > 0.85. This result allows us to estimate the number of cases given the number of calls from a specific district, days before the lab results are available. We validate the algorithm with real data. We show how to use the algorithm to track on-stream the epidemic, and present the Early Outbreak Alarm to detect outbreaks in advance to lab results. One key point in the developed algorithm is a detailed track of the uncertainties in the estimations, since the alarm uses the significance of the observables as a main indicator to detect an anomaly. We present the details of the explicit example in Villa Azul (Quilmes) where this tool resulted crucial to control an outbreak on time. The presented tools have been designed in urgency with the available data at the time of the development, and therefore have their limitations which we describe and discuss. We consider possible improvements on the tools, many of which are currently under development.
Subject(s)
COVID-19ABSTRACT
One of the main problems in controlling COVID-19 epidemic spread is the delay in confirming cases. Having information on changes in the epidemic evolution or outbreaks rise before lab-confirmation is crucial in decision making for Public Health policies. We present an algorithm to estimate on-stream the number of COVID-19 cases using the data from telephone calls to a COVID-line. By modeling the calls as background (proportional to population) plus signal (proportional to infected), we fit the calls in Province of Buenos Aires (Argentina) with coefficient of determination $R^2 > 0.85$. This result allows us to estimate the number of cases given the number of calls from a specific district, days before the lab results are available. We validate the algorithm with real data. We show how to use the algorithm to track on-stream the epidemic, and present the Early Outbreak Alarm to detect outbreaks in advance to lab results. One key point in the developed algorithm is a detailed track of the uncertainties in the estimations, since the alarm uses the significance of the observables as a main indicator to detect an anomaly. We present the details of the explicit example in Villa Azul (Quilmes) where this tool resulted crucial to control an outbreak on time. The presented tools have been designed in urgency with the available data at the time of the development, and therefore have their limitations which we describe and discuss. We consider possible improvements on the tools, many of which are currently under development.
Subject(s)
COVID-19 , Abnormalities, Drug-InducedABSTRACT
Introduction: The aim of this study was to estimate the seroprevalence of the SARS-CoV-2 infection in health workers of the Sanitary Region VIII, at province of Buenos Aires during June 2020. Methods: a cross-sectional design was used. A probabilistic sampling by two-stage conglomerates was carried out. Data were collected from a self-administered questionnaire and a blood sample for antibody identification. The COVIDAR IgG and IgM test were used. RESULTS: 738 health workers were included; the overall response rate was 73.80%. 71.83% of that were women; age showed a normal distribution. Nurses and doctors accounted for more than half of the staff. 75.86% of people claimed to always use Personal Protective Equipment. 5.61% of people had close contact with a confirmed case of COVID-19. 4.60% of people had previously had a nasopharyngeal swab with a negative result. Five workers had positive IgG for SARS-CoV-2 (four women and one man) with negative IgM. The mean age of the cases was 35 years old; two of them were asymptomatic; neither of them had a swab sample taken. The overall seroprevalence was 0.75%, with no significant differences between strata. Discussion: the seroprevalence found was low; indicating a large proportion of workers was susceptible to infection. We stress the need to complement passive epidemiological surveillance strategies with serological monitoring in health workers.