Background The proportion of asymptomatic carriers and transmission risk factors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among household and non-household contacts remains unclear. In Singapore, extensive contact tracing by the Ministry of Health for every diagnosed COVID-19 case, and legally enforced quarantine and intensive health surveillance of close contacts provided a rare opportunity to determine asymptomatic attack rates and SARS-CoV-2 transmission risk factors among community close contacts of patients with COVID-19. Methods This retrospective cohort study involved all close contacts of confirmed COVID-19 cases in Singapore, identified between Jan 23 and April 3, 2020. Household contacts were defined as individuals who shared a residence with the index COVID-19 case. Non-household close contacts were defined as those who had contact for at least 30 min within 2 m of the index case. All patients with COVID-19 in Singapore received inpatient treatment, with access restricted to health-care staff. All close contacts were quarantined for 14 days with thrice-daily symptom monitoring via telephone. Symptomatic contacts underwent PCR testing for SARS-CoV-2. Secondary clinical attack rates were derived from the prevalence of PCR-confirmed SARS-CoV-2 among close contacts. Consenting contacts underwent serology testing and detailed exposure risk assessment. Bayesian modelling was used to estimate the prevalence of missed diagnoses and asymptomatic SARS-CoV-2-positive cases. Univariable and multivariable logistic regression models were used to determine SARS-CoV-2 transmission risk factors. Findings Between Jan 23 and April 3, 2020, 7770 close contacts (1863 household contacts, 2319 work contacts, and 3588 social contacts) linked to 1114 PCR-confirmed index cases were identified. Symptom-based PCR testing detected 188 COVID-19 cases, and 7582 close contacts completed quarantine without a positive SARS-CoV-2 PCR test. Among 7518 (96·8%) of the 7770 close contacts with complete data, the secondary clinical attack rate was 5·9% (95% CI 4·9–7·1) for 1779 household contacts, 1·3% (0·9–1·9) for 2231 work contacts, and 1·3% (1·0–1·7) for 3508 social contacts. Bayesian analysis of serology and symptom data obtained from 1150 close contacts (524 household contacts, 207 work contacts, and 419 social contacts) estimated that a symptom-based PCR-testing strategy missed 62% (95% credible interval 55–69) of COVID-19 diagnoses, and 36% (27–45) of individuals with SARS-CoV-2 infection were asymptomatic. Sharing a bedroom (multivariable odds ratio [OR] 5·38 [95% CI 1·82–15·84]; p=0·0023) and being spoken to by an index case for 30 min or longer (7·86 [3·86–16·02]; p<0·0001) were associated with SARS-CoV-2 transmission among household contacts. Among non-household contacts, exposure to more than one case (multivariable OR 3·92 [95% CI 2·07–7·40], p<0·0001), being spoken to by an index case for 30 min or longer (2·67 [1·21–5·88]; p=0·...
Background Rapid identification of COVID-19 cases, which is crucial to outbreak containment efforts, is challenging due to the lack of pathognomonic symptoms and in settings with limited capacity for specialized nucleic acid–based reverse transcription polymerase chain reaction (PCR) testing. Methods This retrospective case-control study involves subjects (7–98 years) presenting at the designated national outbreak screening center and tertiary care hospital in Singapore for SARS-CoV-2 testing from 26 January to 16 February 2020. COVID-19 status was confirmed by PCR testing of sputum, nasopharyngeal swabs, or throat swabs. Demographic, clinical, laboratory, and exposure-risk variables ascertainable at presentation were analyzed to develop an algorithm for estimating the risk of COVID-19. Model development used Akaike’s information criterion in a stepwise fashion to build logistic regression models, which were then translated into prediction scores. Performance was measured using receiver operating characteristic curves, adjusting for overconfidence using leave-one-out cross-validation. Results The study population included 788 subjects, of whom 54 (6.9%) were SARS-CoV-2 positive and 734 (93.1%) were SARS-CoV-2 negative. The median age was 34 years, and 407 (51.7%) were female. Using leave-one-out cross-validation, all the models incorporating clinical tests (models 1, 2, and 3) performed well with areas under the receiver operating characteristic curve (AUCs) of 0.91, 0.88, and 0.88, respectively. In comparison, model 4 had an AUC of 0.65. Conclusions Rapidly ascertainable clinical and laboratory data could identify individuals at high risk of COVID-19 and enable prioritization of PCR testing and containment efforts. Basic laboratory test results were crucial to prediction models.
Situation Report-12 SITUATION IN NUMBERS total and new cases in last 24 hours Globally 11953 confirmed (2128 new) China 11821 confirmed (2102 new) 1795 severe (268 new) 259 deaths (46 new) Outside of China 132 confirmed (26 new) 23 countries (4 new) WHO RISK ASSESSMENT China Very High Regional Level High Global Level High *The situation report includes information reported to WHO Geneva by 10 AM Additional instances of human-to-human transmission outside China were reported (see further information under Technical Focus).
ImportanceAssessing booster effectiveness of COVID-19 mRNA vaccine and inactivated SARS-CoV-2 vaccine over longer time intervals and in response to any further SARS-CoV-2 variants is crucial in determining optimal COVID-19 vaccination strategies.ObjectiveTo determine levels of protection against severe COVID-19 and confirmed SARS-CoV-2 infection by types and combinations of vaccine boosters in Singapore during the Omicron wave.Design, Setting, and ParticipantsThis cohort study included Singapore residents aged 30 years or more vaccinated with either at least 2 doses of mRNA COVID-19 vaccines (ie, Pfizer-BioNTech BNT162b2 or Moderna mRNA-1273) or inactivated SARS-CoV-2 vaccines (Sinovac CoronaVac or Sinopharm BBIBP-CorV) as of March 10, 2022. Individuals with a known SARS-CoV-2 infection prior to December 27, 2021, an infection on or before the date of their second vaccine dose, or with reinfection cases were excluded.ExposuresTwo or 3 doses of Pfizer-BioNTech BNT162b2, Moderna mRNA-1273, Sinovac CoronaVac, or Sinopharm BBIBP-CorV.Main Outcomes and MeasuresNotified infections from December 27, 2021, to March 10, 2022, adjusted for age, sex, race, housing status, and calendar days. Estimated booster effectiveness, defined as the relative incidence-rate reduction of severe disease (supplemental oxygen, intensive care, or death) or confirmed infection following 3-dose vaccination compared with 5 months after second mRNA dose, was determined using binomial regression.ResultsAmong 2 441 581 eligible individuals (1 279 047 [52.4%] women, 846 110 (34.7%) aged 60 years and older), there were 319 943 (13.1%) confirmed SARS-CoV-2 infections, of which 1513 (0.4%) were severe COVID-19 cases. mRNA booster effectiveness against confirmed infection 15 to 60 days after boosting was estimated to range from 31.7% to 41.3% for the 4 boosting combinations (homologous BNT162b2, homologous mRNA-1273, 2-dose BNT162b2/mRNA-1273 booster, and 2-dose mRNA-1273/BNT162b2 booster). Five months and more after boosting, estimated booster effectiveness against confirmed infection waned, ranging from –2.8% to 14.6%. Against severe COVID-19, estimated mRNA booster effectiveness was 87.4% (95% CI, 83.3%-90.5%) 15 to 60 days after boosting and 87.2% (95% CI, 84.2%-89.7%) 5 to 6 months after boosting, with no significant difference comparing vaccine combinations. Booster effectiveness against severe COVID-19 15 days to 330 days after 3-dose inactivated COVID-19 vaccination, regardless of combination, was estimated to be 69.6% (95% CI, 48.7%-81.9%).Conclusions and RelevanceBooster mRNA vaccine protection against severe COVID-19 was estimated to be durable over 6 months. Three-dose inactivated SARS-CoV-2 vaccination provided greater protection than 2-dose but weaker protection compared with 3-dose mRNA.
Background The impact of SARS-CoV-2 vaccination status and paediatric age on transmission of the Delta variant is key to preventing COVID-19 spread. In Singapore, quarantine of all close-contacts, and quarantine-entry and exit PCR testing, enabled evaluation of these factors. Methods This retrospective cohort study included all household close-contacts between March 1, 2021 and August 31, 2021. Logistic regression using generalized estimating equations was used to determine risk factors associated with SARS-CoV-2 acquisition and symptomatic disease. Findings Among 8470 Delta variant-exposed household close-contacts linked to 2583 indices, full-vaccination of the index with BNT162b2 or mRNA-1273 was associated with significant reduction in SARS-CoV-2 acquisition by contacts (adjusted odds ratio [aOR]:0.56, 95% robust confidence interval [RCI]:0.44–0.71 and aOR:0.51, 95%RCI:0.27–0.96 respectively). Compared to young adults (18–29y), children (0–11y) were significantly more likely to transmit (aOR:2.37 [95%RCI:1.57–3.60]) and acquire (aOR:1.43 [95%RCI:1.07–1.93]) infection, taking into account vaccination status. Longer duration from completion of vaccination among contacts was associated with decline in protection against acquisition (first-month aOR:0.42, 95%RCI:0.33–0.55; fifth-month aOR:0.84, 95%RCI:0.55–0.98; p<0.0001 for trend) and symptomatic disease (first-month aOR:0.30, 95%RCI:0.23–0.41; fifth-month aOR;0.62, 95%RCI:0.38–1.02; p<0.0001 for trend). Contacts immunized with mRNA-1273 had significant reduction in acquisition (aOR:0.73, 95%RCI:0.58–0.91) compared to BNT162b2. Conclusions Among household close-contacts, vaccination prevented onward SARS-CoV-2 transmission and there was increased risk of SARS-CoV-2 acquisition and transmission among children compared with young adults. Time after completion of vaccination and vaccine type affected SARS-CoV-2 acquisition.
Infrastructure is often thought of in big material terms: dams, buildings, roads, and so on. This study, instead, draws on literatures in anthropology and the social sciences to analyse infrastructures in relation to society and environment, and so cast current conceptions of infrastructure in a new light. Situating the analysis in context of President Biden’s recent infrastructure bill, the paper expands what is meant by and included in discussions of infrastructure. The study examines what it means for different kinds of material infrastructures to function (and for whom) or not, and also consider how the immaterial infrastructure of human relations are manifested in, for example, labour, as well as how infrastructures may create intended or unintended consequences in enabling or disabling social processes. Further, in this study, we examine concepts embedded in thinking about infrastructure such as often presumed distinctions between the technical and the social, nature and culture, the human and the non-human, and the urban and the rural, and how all of these are actually implicated in thinking about infrastructure. Our analysis, thus, draws from a growing body of work on infrastructure in anthropology and the social sciences, enriches it with ethnographic insights from our own field research, and so extends what it means to study ‘infrastructures’ in the 21st century.
As sustainability gains popularity in public discourse, scholars have noted its diverse uses, multiple meanings, and contradictory outcomes. This paper explores how the current proliferation of the concept of sustainability stems in part from its varied normative appeals, which in turn motivate, legitimate, and unsettle its diverse mobilizations. As the concept of sustainability calls for an extension of moral horizons beyond the immediate here and now, this redrawing of moral boundaries has simultaneously produced new externalities as well as enduring anxieties and responses within these moral bounds themselves. Drawing on ethnographic and historical materials, we argue that sustainability’s moral boundaries have become both an object of scholarly critique and their own productive site of anxiety and negotiation. Questions about sustainability’s moral horizons and externalities often surface in the concept’s public deployment itself. We suggest that these tensions can be made visible by attending to the intersections between sustainability and a broader range of moral concerns at work.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.