Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on reverse transcriptase polymerase chain reaction (RT-PCR) are being used to rule out infection among high-risk persons, ...such as exposed inpatients and health care workers. It is critical to understand how the predictive value of the test varies with time from exposure and symptom onset to avoid being falsely reassured by negative test results.
To estimate the false-negative rate by day since infection.
Literature review and pooled analysis.
7 previously published studies providing data on RT-PCR performance by time since symptom onset or SARS-CoV-2 exposure using samples from the upper respiratory tract (
= 1330).
A mix of inpatients and outpatients with SARS-CoV-2 infection.
A Bayesian hierarchical model was fitted to estimate the false-negative rate by day since exposure and symptom onset.
Over the 4 days of infection before the typical time of symptom onset (day 5), the probability of a false-negative result in an infected person decreases from 100% (95% CI, 100% to 100%) on day 1 to 67% (CI, 27% to 94%) on day 4. On the day of symptom onset, the median false-negative rate was 38% (CI, 18% to 65%). This decreased to 20% (CI, 12% to 30%) on day 8 (3 days after symptom onset) then began to increase again, from 21% (CI, 13% to 31%) on day 9 to 66% (CI, 54% to 77%) on day 21.
Imprecise estimates due to heterogeneity in the design of studies on which results were based.
Care must be taken in interpreting RT-PCR tests for SARS-CoV-2 infection-particularly early in the course of infection-when using these results as a basis for removing precautions intended to prevent onward transmission. If clinical suspicion is high, infection should not be ruled out on the basis of RT-PCR alone, and the clinical and epidemiologic situation should be carefully considered.
National Institute of Allergy and Infectious Diseases, Johns Hopkins Health System, and U.S. Centers for Disease Control and Prevention.
COVID-19 could have even more dire consequences in refugees camps than in general populations. Bangladesh has confirmed COVID-19 cases and hosts almost 1 million Rohingya refugees from Myanmar, with ...600,000 concentrated in the Kutupalong-Balukhali Expansion Site (mean age, 21 years; standard deviation SD, 18 years; 52% female). Projections of the potential COVID-19 burden, epidemic speed, and healthcare needs in such settings are critical for preparedness planning.
To explore the potential impact of the introduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the Kutupalong-Balukhali Expansion Site, we used a stochastic Susceptible Exposed Infectious Recovered (SEIR) transmission model with parameters derived from emerging literature and age as the primary determinant of infection severity. We considered three scenarios with different assumptions about the transmission potential of SARS-CoV-2. From the simulated infections, we estimated hospitalizations, deaths, and healthcare needs expected, age-adjusted for the Kutupalong-Balukhali Expansion Site age distribution. Our findings suggest that a large-scale outbreak is likely after a single introduction of the virus into the camp, with 61%-92% of simulations leading to at least 1,000 people infected across scenarios. On average, in the first 30 days of the outbreak, we expect 18 (95% prediction interval PI, 2-65), 54 (95% PI, 3-223), and 370 (95% PI, 4-1,850) people infected in the low, moderate, and high transmission scenarios, respectively. These reach 421,500 (95% PI, 376,300-463,500), 546,800 (95% PI, 499,300-567,000), and 589,800 (95% PI, 578,800-595,600) people infected in 12 months, respectively. Hospitalization needs exceeded the existing hospitalization capacity of 340 beds after 55-136 days, between the low and high transmission scenarios. We estimate 2,040 (95% PI, 1,660-2,500), 2,650 (95% PI, 2,030-3,380), and 2,880 (95% PI, 2,090-3,830) deaths in the low, moderate, and high transmission scenarios, respectively. Due to limited data at the time of analyses, we assumed that age was the primary determinant of infection severity and hospitalization. We expect that comorbidities, limited hospitalization, and intensive care capacity may increase this risk; thus, we may be underestimating the potential burden.
Our findings suggest that a COVID-19 epidemic in a refugee settlement may have profound consequences, requiring large increases in healthcare capacity and infrastructure that may exceed what is currently feasible in these settings. Detailed and realistic planning for the worst case in Kutupalong-Balukhali and all refugee camps worldwide must begin now. Plans should consider novel and radical strategies to reduce infectious contacts and fill health worker gaps while recognizing that refugees may not have access to national health systems.
A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, ...including the incubation period for clinical disease (coronavirus disease 2019 COVID-19), which has important implications for surveillance and control activities.
To estimate the length of the incubation period of COVID-19 and describe its public health implications.
Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020.
News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China.
Persons with confirmed SARS-CoV-2 infection outside Hubei province, China.
Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization.
There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine.
Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases.
This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases.
U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.
AbstractObjectivesWithin health economic studies, it is often necessary to adjust costs obtained from different time periods for inflation. Nevertheless, many studies do not report the methods used ...for this in sufficient detail. In this article, we outline the principal methods used to adjust for inflation, with a focus on studies relating to healthcare interventions in low- and middle-income countries. We also discuss issues relating to converting local currencies to international dollars and US$ and adjusting cost data collected from other countries or previous studies. MethodsWe outlined the 3 main methods used to adjust for inflation for studies in these settings: exchanging the local currency to US$ or international dollars and then inflating using US inflation rates (method 1); inflating the local currency using local inflation rates and then exchanging to US$ or international dollars (method 2); splitting the costs into tradable and nontradable resources and using method 1 on the tradable resources and method 2 on the nontradable resources (method 3). ResultsIn a hypothetical example of adjusting a cost of US$100 incurred in Vietnam from 2006 to 2016 prices, the adjusted cost from the 3 methods were US$116.84, US$172.09, and US$161.04, respectively. ConclusionsThe different methods for adjusting for inflation can yield substantially different results. We make recommendations regarding the most appropriate method for various scenarios. Moving forward, it is vital that studies report the methodology they use to adjust for inflation more transparently.
Assessing the burden of COVID-19 on the basis of medically attended case numbers is suboptimal given its reliance on testing strategy, changing case definitions, and disease presentation. ...Population-based serosurveys measuring anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) antibodies provide one method for estimating infection rates and monitoring the progression of the epidemic. Here, we estimate weekly seroprevalence of anti-SARS-CoV-2 antibodies in the population of Geneva, Switzerland, during the epidemic.
The SEROCoV-POP study is a population-based study of former participants of the Bus Santé study and their household members. We planned a series of 12 consecutive weekly serosurveys among randomly selected participants from a previous population-representative survey, and their household members aged 5 years and older. We tested each participant for anti-SARS-CoV-2-IgG antibodies using a commercially available ELISA. We estimated seroprevalence using a Bayesian logistic regression model taking into account test performance and adjusting for the age and sex of Geneva's population. Here we present results from the first 5 weeks of the study.
Between April 6 and May 9, 2020, we enrolled 2766 participants from 1339 households, with a demographic distribution similar to that of the canton of Geneva. In the first week, we estimated a seroprevalence of 4·8% (95% CI 2·4–8·0, n=341). The estimate increased to 8·5% (5·9–11·4, n=469) in the second week, to 10·9% (7·9–14·4, n=577) in the third week, 6·6% (4·3–9·4, n=604) in the fourth week, and 10·8% (8·2–13·9, n=775) in the fifth week. Individuals aged 5–9 years (relative risk RR 0·32 95% CI 0·11–0·63) and those older than 65 years (RR 0·50 0·28–0·78) had a significantly lower risk of being seropositive than those aged 20–49 years. After accounting for the time to seroconversion, we estimated that for every reported confirmed case, there were 11·6 infections in the community.
These results suggest that most of the population of Geneva remained uninfected during this wave of the pandemic, despite the high prevalence of COVID-19 in the region (5000 reported clinical cases over <2·5 months in the population of half a million people). Assuming that the presence of IgG antibodies is associated with immunity, these results highlight that the epidemic is far from coming to an end by means of fewer susceptible people in the population. Further, a significantly lower seroprevalence was observed for children aged 5–9 years and adults older than 65 years, compared with those aged 10–64 years. These results will inform countries considering the easing of restrictions aimed at curbing transmission.
Swiss Federal Office of Public Health, Swiss School of Public Health (Corona Immunitas research program), Fondation de Bienfaisance du Groupe Pictet, Fondation Ancrage, Fondation Privée des Hôpitaux Universitaires de Genève, and Center for Emerging Viral Diseases.
Summary The obesity epidemic is spreading to low-income and middle-income countries as a result of new dietary habits and sedentary ways of life, fuelling chronic diseases and premature mortality. In ...this report we present an assessment of public health strategies designed to tackle behavioural risk factors for chronic diseases that are closely linked with obesity, including aspects of diet and physical inactivity, in Brazil, China, India, Mexico, Russia, and South Africa. England was included for comparative purposes. Several population-based prevention policies can be expected to generate substantial health gains while entirely or largely paying for themselves through future reductions of health-care expenditures. These strategies include health information and communication strategies that improve population awareness about the benefits of healthy eating and physical activity; fiscal measures that increase the price of unhealthy food content or reduce the cost of healthy foods rich in fibre; and regulatory measures that improve nutritional information or restrict the marketing of unhealthy foods to children. A package of measures for the prevention of chronic diseases would deliver substantial health gains, with a very favourable cost-effectiveness profile.
SeqSero, launched in 2015, is a software tool for
serotype determination from whole-genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United ...States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here, we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include (i) additional sequence markers for identification of
species and subspecies and certain serotypes, (ii) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies, and (iii) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common U.S. serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification.
Serotyping is the basis of public health surveillance of
It remains a first-line subtyping method even as surveillance continues to be transformed by whole-genome sequencing. SeqSero allows the integration of
serotyping into a whole-genome-sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large-scale surveillance of
by whole-genome sequencing.
Objective The purpose of this study was to describe the unequal distribution in the performance of cesarean section delivery (CS) in the world and the resource-use implications of such inequity. ...Study Design We obtained data on the number of CSs performed in 137 countries in 2008. The consensus is that countries should achieve a 10% rate of CS; therefore, for countries that are below that rate, we calculated the cost to achieve a 10% rate. For countries with a CS rate of >15%, we calculated the savings that could be made by the achievement of a 15% rate. Results Fifty-four countries had CS rates of <10%, whereas 69 countries showed rates of >15%. The cost of the global saving by a reduction of CS rates to 15% was estimated to be $2.32 billion (US dollars); the cost to attain a 10% CS rate was $432 million (US dollars). Conclusion CSs that are potentially medically unjustified appear to command a disproportionate share of global economic resources.
The Himalayas and the Tibetan Plateau region (HTP), despite being a remote and sparsely populated area, is regularly exposed to polluted air masses with significant amounts of aerosols including ...black carbon. These dark, light-absorbing particles are known to exert a great melting potential on mountain cryospheric reservoirs through albedo reduction and radiative forcing. This study combines ground-based and satellite remote sensing data to identify a severe aerosol pollution episode observed simultaneously in central Tibet and on the southern side of the Himalayas during 13-19 March 2009 (pre-monsoon). Trajectory calculations based on the high-resolution numerical weather prediction model COSMO are used to locate the source regions and study the mechanisms of pollution transport in the complex topography of the HTP. We detail how polluted air masses from an atmospheric brown cloud (ABC) over South Asia reach the Tibetan Plateau within a few days. Lifting and advection of polluted air masses over the great mountain range is enabled by a combination of synoptic-scale and local meteorological processes. During the days prior to the event, winds over the Indo-Gangetic Plain (IGP) are generally weak at lower levels, allowing for accumulation of pollutants and thus the formation of ABCs. The subsequent passing of synoptic-scale troughs leads to southwesterly flow in the middle troposphere over northern and central India, carrying the polluted air masses across the Himalayas. As the IGP is known to be a hotspot of ABCs, the cross-Himalayan transport of polluted air masses may have serious implications for the cryosphere in the HTP and impact climate on regional to global scales. Since the current study focuses on one particularly strong pollution episode, quantifying the frequency and magnitude of similar events in a climatological study is required to assess the total impact.
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