title: Benefits of natural habitat particularly woodland on children's cognition and mental health

abstract: Life in urban areas is associated with adverse human health effects, including risks of developing cognitive problems and mental health issues. Many epidemiological studies have established associations between urban nature, cognitive development and mental health, but why specifically we receive these health benefits remains unclear, especially in children. Here, we used longitudinal data in a cohort of 3,568 children aged 9 to 15 years at 31 schools across London to develop a model and examine the associations between natural habitat type, and childrens cognitive development and mental health. We show that, after adjusting for other environmental, demographic and socioeconomic variables, higher daily exposure rates to natural habitat and particularly woodland were associated with enhanced cognitive development and mental health from late childhood to early adolescence. Our results suggest that optimising ecosystem services linked to cognitive development and mental health benefits should prioritise the type of natural habitat for sustainable urban planning decisions.


title: National interest may require distributing COVID-19 vaccines to other countries

abstract: As the clinical trials for COVID-19 vaccine progress, understanding how to distribute the initially scarce doses is of paramount importance and a quantitative analysis of the trade-offs involved in domestic-only versus cooperative distribution is still missing. In this study we use a network Susceptible-Infected-Removed (SIR) model to show under which circumstances it is in a countrys self-interest to ensure other countries can also obtain a COVID-19 vaccine rather than focusing only on vaccination of their own residents. In particular, we focus our analysis on the USs decision and estimate the internal burden of COVID-19 disease under different scenarios about vaccine cooperation. We show that in scenarios in which the US has reached the threshold for domestic herd immunity, the US may find it optimal to donate doses to other countries with lower vaccination coverage, as this would allow for a sharp reduction in the inflow of infected individuals from abroad.

category: epidemiology


title: The feasibility of targeted test-trace-isolate for the control of B.1.1.7

abstract: The SARS-CoV-2 variant B.1.1.7 reportedly exhibits substantially higher transmission than the ancestral strain and may generate a major surge of cases before vaccines become widely available, while the P.1 and B.1.351 variants may be equally transmissible and also resist vaccines. All three variants can be sensitively detected by RT-PCR due to an otherwise rare del11288-11296 mutation in orf1ab; B.1.1.7 can also be detected using the common TaqPath kit. Testing, contact tracing, and isolation programs overwhelmed by SARS-CoV-2 could slow the spread of the new variants, which are still outnumbered by tracers in most countries. However, past failures and high rates of mistrust may lead health agencies to conclude that tracing is futile, dissuading them from redirecting existing tracers to focus on the new variants. Here we apply a branching-process model to estimate the effectiveness of implementing a variant-focused testing, contact tracing, and isolation strategy with realistic levels of performance. Our model indicates that bidirectional contact tracing can substantially slow the spread of SARS-CoV-2 variants even in regions where a large fraction of the population refuses to cooperate with contact tracers or to abide by quarantine and isolation requests.


title: The feasibility of targeted test-trace-isolate for the control of SARS-CoV-2 variants


title: Determining the optimal COVID-19 policy response using agent-based modelling linked to health and cost modelling: Case study for Victoria, Australia

abstract:
ImportanceDetermining the best policy on social restrictions and lockdowns for the COVID-19 pandemic is challenging.

ObjectiveTo determine the optimal policy response ranging from aggressive and moderate elimination, tight suppression (aiming for 1 to 5 cases per million per day) and loose suppression (5 to 25 cases per million per day).

DesignTwo simulation models in series: an agent-based model to estimate daily SARS-CoV-2 infection rates and time in four stages of social restrictions; a proportional multistate lifetable model to estimate long-run health impacts (health adjusted life years (HALYs) arising from SARS-CoV-2) and costs (health systems, and health system plus GDP).

The net monetary benefit (NMB) of each policy option at varying willingness to pay (WTP) per HALY was calculated: NMB = HALYs x WTP - cost. The optimal policy response was that with the highest NMB.

Setting and participantsThe State of Victoria, Australia, using simulation modeling of all residents.

Main Outcome and MeasuresSARS-CoV-2 infection rates, time under various stages of restrictions, HALYs, health expenditure and GDP losses.

ResultsAggressive elimination resulted in the highest percentage of days with the lowest level of restrictions (median 31.7%, 90% simulation interval 6.6% to 64.4%). However, days in hard lockdown were similar across all four strategies (medians 27.5% to 36.1%).

HALY losses (compared to a no-COVID-19 scenario) were similar for aggressive elimination (286, 219 to 389) and moderate elimination (314, 228 to 413), and nearly eight and 40-times higher for tight and loose suppression. The median GDP loss was least for moderate elimination ($US41.7 billion, $29.0 to $63.6 billion), but there was substantial overlap in simulation intervals between the four strategies.

From a health system perspective aggressive elimination was optimal in 64% of simulations above a willingness to pay of $15,000 per HALY, followed by moderate elimination in 35% of simulations.

Moderate elimination was optimal from a partial societal perspective in half the simulations followed by aggressive elimination in a quarter.

Shortening the pandemic duration to 6 months saw loose suppression become preferable under a partial societal perspective.

Conclusions and RelevanceElimination strategies were preferable over a 1-year pandemic duration.

FundingAnonymous philanthropic donation to the University of Melbourne.

Key pointsO_ST_ABSQuestionC_ST_ABSTo determine the optimal of four policy responses to COVID-19 in the State of Victoria, Australia (aggressive and moderate elimination, tight suppression (aiming for 1 to 5 cases per million per day) and loose suppression (5 to 25 cases per million per day), based on estimated future health loss and costs from both a health system and partial societal perspective.

FindingsFrom a health system perspective aggressive elimination was optimal in 64% of simulations above a willingness to pay of $15,000 per HALY, followed by moderate elimination in 35% of simulations. Moderate elimination was optimal from a partial societal perspective (i.e., including GDP losses) in half the simulations followed by aggressive elimination in a quarter.

MeaningWhilst there is considerable uncertainty in outcomes for all the four policy options, the two elimination options are usually optimal from both a health system and a partial societal (health expenditure plus GDP cost) perspective.


title: The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

abstract:
We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Among control measures implemented, only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier it could have reduced first wave deaths from 36,700 to 15,700 (95%CrI: 8,900-26,800). Improved clinical care reduced the infection fatality ratio from 1.25% (95%CrI: 1.18%-1.33%) to 0.77% (95%CrI: 0.71%-0.84%). The infection fatality ratio was higher in the elderly residing in care homes (35.9%, 95%CrI: 29.1%-43.4%) than those residing in the community (10.4%, 95%CrI: 9.1%-11.5%). England is still far from herd immunity, with regional cumulative infection incidence to 1st December 2020 between 4.8% (95%CrI: 4.4%-5.1%) and 15.4% (95%CrI: 14.9%-15.9%) of the population.

One-sentence summaryWe fit a mathematical model of SARS-CoV-2 transmission to surveillance data from England, to estimate transmissibility, severity, and the impact of interventions


title: Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March 20-November 11, 2020.

abstract: Mexico has experienced one of the highest COVID-19 death rates in the world. A delayed response towards implementation of social distancing interventions until late March 2020 and a phased reopening of the country in June 2020 has facilitated sustained disease transmission in the region. Here, we systematically generate and compare 30-day ahead forecasts using previously validated growth models based on mortality trends from the Institute for Health Metrics and Evaluation for Mexico and Mexico City in near real-time. Moreover, we estimate reproduction numbers for SARS-CoV-2 based on methods that rely on genomic data as well as case incidence data. Subsequently, functional data analysis techniques are utilized to analyze the shapes of COVID-19 growth rate curves at the state level to characterize the spatial-temporal transmission patterns. The early estimates of reproduction number for Mexico were estimated between R[~]1.1-from genomic and case incidence data. Moreover, the mean estimate of R has fluctuated [~]1.0 from late July till end of September 2020. The spatial analysis characterizes the state-level dynamics of COVID-19 into four groups with distinct epidemic trajectories. We found that the sequential mortality forecasts from the GLM and Richards model predict downward trends in the number of deaths for all thirteen forecasts periods for Mexico and Mexico City. The sub-epidemic and IHME models predict more realistic stable trajectory of COVID-19 mortality trends for the last three forecast periods (09/21-10/21 - 09/28-10/27) for Mexico and Mexico City. Our findings support the view that phenomenological models are useful tools for short-term epidemic forecasting albeit forecasts need to be interpreted with caution given the dynamic implementation and lifting of social distancing measures.


title: Monitoring the proportion infected by SARS-CoV-2 from age-stratified hospitalisation and serological data

abstract:
BackgroundRegional monitoring of the proportion infected by SARS-CoV-2 is important to guide local management of the epidemic, but is difficult in the absence of regular nationwide serosurveys.

MethodsWe developed a method to reconstruct in real-time the proportion infected by SARS-CoV-2 and the proportion of infections being detected from the joint analysis of age-stratified seroprevalence, hospitalisation and case data. We applied our approach to the 13 French metropolitan regions.

FindingsWe estimate that 5.7% [5.1%-6.4%] of adults in metropolitan France had been infected by SARS-CoV-2 by May 2020. This proportion remained stable until August and increased to 12.6% [11.2%-14.3%] by the end of November. With 23.8% [21.2%-26.8%] infected in the Paris region compared to 4.0% [3.5% - 4.6%] in Brittany, regional variations remained large (Coefficient of Variation CV: 0.53) although less so than in May (CV: 0.74). The proportion infected was twice higher (17.6% [13.4%-22.7%]) in 20-49 y.o. than in 50+ y.o (8.0% [5.7% - 11.5%]). Forty percent [33.7% - 45.4%] of infections in adults were detected in June-August compared to 55.7% [48.7% - 63.1%] in September-November. Our method correctly predicted seroprevalence in 11 regions in which only hospitalisation data were used.

InterpretationIn the absence of contemporary serosurvey, our real-time monitoring indicates that the proportion infected by SARS-CoV-2 may be above 20% in some French regions.

FundingEU RECOVER, ANR, Fondation pour la Recherche Medicale, Inserm.


title: Vaccination in a two-group epidemic model

abstract: Epidemic progression depends on the structure of the population. We study a two-group epidemic model with the difference between the groups determined by the rate of disease transmission. The basic reproduction number, the maximal and the total number of infected individuals are characterized by the proportion between the groups. We consider different vaccination strategies and determine the outcome of the vaccination campaign depending on the distribution of vaccinated individuals between the groups.


title: Seroprevalence of Chagas in urban and rural indigenous populations of the south of Gran Chaco

abstract:
Background & objectivesIn Latin America, Chagas disease is endemic, with high prevalence in rural indigenous communities and increasing prevalence in urban areas due to migration from rural areas with active vector transmission. The objective of the work was to assess differences in the prevalence of Chagas disease in urban and rural moqoit communities of the south of Gran Chaco, Santa Fe province, Argentina.

MethodsA seroprevalence study was conducted in six moqoit populations. Belonging to an urban community was considered as an exposure variable, whereas seropositivity for Chagas disease was considered as an outcome variable

ResultsThe results showed that 9.26% of the 702 volunteers evaluated and 3.50% of women of childbearing potential were seropositive. The prevalence of Chagas disease in urban communities was 6.41 times higher than in rural communities.

Interpretation & conclusionsThe seroprevalence found in the moqoit community is higher than that estimated for the general population of the same region, with greater impact in the urban area than in the rural area. The decline of vector transmission in the rural area could be related to the conservation of ancestral practices and the expansion of the agricultural model.


title: Lessons learnt from the use of compartmental models over the COVID-19 induced lockdown in France

abstract:
BackgroundCompartmental models help making public health decisions. They were used during the COVID-19 outbreak to estimate the reproduction numbers and predict the number of hospital beds required. This study examined the ability of closely related compartmental models to reflect equivalent epidemic dynamics.

MethodsThe study considered three independently designed compartmental models that described the COVID-19 outbreak in France. Model compartments and parameters were expressed in a common framework and models were calibrated using the same hospitalization data from two official public databases. The calibration procedure was repeated over three different periods to compare model abilities to: i) fit over the whole lockdown; ii) predict the course of the epidemic during the lockdown; and, iii) provide profiles to predict hospitalization prevalence after lockdown. The study considered national and regional coverages.

ResultsThe three models were all flexible enough to match real hospitalization data during the lockdown, but the numbers of cases in the other compartments differed. The three models failed to predict reliably the number of hospitalizations after the fitting periods at national as at regional scales. At the national scale, an improved calibration led to epidemic course profiles that reflected hospitalization dynamics and reproduction numbers that were coherent with official and literature estimates.

ConclusionThis study shows that prevalence data are needed to further refine the calibration and make a selection between still divergent models. This underlines strongly the need for repeated prevalence studies on representative population samples.


title: Individual prediction of trauma-focused psychotherapy response in youth with posttraumatic stress disorder using resting-state functional connectivity

abstract:
Randomized controlled trials have shown efficacy of trauma-focused psychotherapies in youth with posttraumatic stress disorder (PTSD). However, response varies considerably among individuals. Currently, no biomarkers are available to assist clinicians in identifying youth who are most likely to benefit from treatment. In this study, we investigated whether resting-state functional magnetic resonance imaging (rs-fMRI) could distinguish between responders and non-responders on the group- and individual patient level.

Pre-treatment rs-fMRI was recorded in 40 youth (ages 8-17 years) with (partial) PTSD before trauma-focused psychotherapy. Change in symptom severity from pre- to post-treatment was assessed using the Clinician-Administered PTSD scale for Children and Adolescents to divide participants into responders ([≥]30% symptom reduction) and non-responders. Functional networks were identified using meta-independent component analysis. Group-differences within- and between-network connectivity between responders and non-responders were tested using permutation testing. Individual predictions were made using multivariate, cross-validated support vector machine classification.

A network centered on the bilateral superior temporal gyrus predicted treatment response for individual patients with 76.17% accuracy (pFWE = 0.018, 87.14% sensitivity, 65.20% specificity, area-under-receiver-operator-curve of 0.82). Functional connectivity between the frontoparietal and sensorimotor network was significantly stronger in non-responders (pFWE = 0.012) on the group-level. Within-network connectivity was not significantly different between groups.

This study provides proof-of-concept evidence for the feasibility to predict trauma-focused psychotherapy response in youth with PTSD at an individual-level. Future studies are required to test if larger cohorts could increase accuracy and to test further generalizability of the prediction models.

category: psychiatry and clinical psychology


title: Towards personalized rTMS in tinnitus: reliability of individualized stimulation protocols in behavioral and electrophysiological responses

abstract:
BackgroundRepetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation tool potentially modulating pathological brain activity. Its clinical effectiveness is hampered by varying results and characterized by inter-individual variability in treatment responses. RTMS individualization might constitute a useful strategy to overcome this variability. A precondition for this approach would be that repeatedly applied protocols result in reliable effects. The condition tinnitus provides the advantage of immediate behavioral consequences (tinnitus loudness changes) after interventions and thus offers an excellent model to exemplify TMS personalization.

ObjectiveThe aim was to investigate the test-retest reliability of short rTMS stimulations in modifying tinnitus loudness and oscillatory brain activity as well as to examine the feasibility of rTMS individualization in tinnitus.

MethodsThree short verum (1Hz, 10Hz, 20Hz; 200 pulses) and one sham (0.1Hz; 20 pulses) rTMS protocol were administered on two different days in 22 tinnitus patients. Before and after each protocol, oscillatory brain activity was recorded with electroencephalography (EEG) together with behavioral tinnitus loudness ratings. RTMS individualization was executed by dint of behavioral and electrophysiological responses. Stimulation responders were identified via consistent sham-superior increases in tinnitus loudness (behavioral responders) and alpha power increases or gamma power decreases (alpha responders/ gamma responders) in accordance to the prevalent neurophysiological models for tinnitus.

ResultsIt was feasible to identify individualized rTMS protocols featuring reliable tinnitus loudness changes (55% behavioral responder), alpha increases (91% alpha responder) and gamma decreases (100% gamma responder) respectively. Alpha responses primary occurred over parieto-occipital areas, whereas gamma responses mainly appeared over frontal regions. Contrary, test-retest correlation analyses per protocol on a group-level were not significant neither for behavioral nor for electrophysiological effects. No associations between behavioral and EEG responses were given.

ConclusionRTMS individualization via behavioral and electrophysiological data in tinnitus can be considered as a feasible approach to overcome low reliability on group-level. The present results open the discussion favoring personalization utilizing neurophysiological markers rather than behavioral responses. These insights are not only useful for the rTMS treatment of tinnitus but also for neuromodulation interventions in other pathologies as our results suggest that the individualization of stimulation protocols is feasible despite absent group-level reliability.


title: Heading for personalized rTMS in tinnitus: reliability of individualized stimulation protocols in behavioral and electrophysiological responses


title: Rates and predictors of uptake of formal and informal mental health support during the COVID-19 pandemic: an analysis of 26,740 adults in the UK in lockdown

abstract:
PurposeThe coronavirus disease 2019 (COVID-19) pandemic has put a great strain on peoples mental health. A growing number of studies have shown worsening mental health measures globally during the pandemic. However, there is a lack of empirical study on how people support their mental health during the COVID-19 pandemic. This study aimed to examine a number of formal and informal mental health supports. Further, it explored factors that might be associated with the use of different types mental health support.

MethodData from 26,740 adults in the UCL COVID -19 Social Study were analysed between 13th April, 2020 and 3rd July, 2020. Data were analysed using logistic and Poisson regression models.

ResultsAbout 45% of people reported talking to friends or family members to support their mental health, 43% engaging in self-care activities, 20% taking medication, 9% speaking to mental health professionals, 8% talking to a GP or other health professional, and another 8% using helpline or online services. Gender, education, living status, loneliness, pre-existing mental health conditions, general depression and anxiety, coping and personality were found to be associated with the use of mental health support.

ConclusionWhile the negative impacts caused by the COVID-19 pandemic are inevitable, people can play an active role in managing their mental health. Understanding the patterns and predictors of various kinds of mental health support during the pandemic is crucial for future service planning and delivery through recognising potential barriers to mental health care faced by certain groups.


title: Predictors of COVID-19 Vaccine Hesitancy: Socio-demographics, Co-Morbidity and Past Racial Discrimination

abstract:
ImportanceImmunization programs are only successful when there are high rates of acceptance and coverage. While delivering billions of COVID 19 doses globally addressing vaccine hesitancy will be one of the most significant public health communication efforts ever undertaken.

ObjectiveThe goal of this study is to explore predictors of COVID 19 vaccine hesitancy, including sociodemographic factors, comorbidity, risk perception, and experience of discrimination, in a sample of the U.S. population.

DesignWe used a cross sectional online survey study design. The survey was implemented between Dec 13 and 23, 2020.

SettingThe survey was limited to respondents over 18 years of age residing in the USA.

ParticipantsRespondents were individuals belonging to priority groups for vaccine distribution.

Main Outcome(s) and Measure(s)Respondents were asked how likely they would be to take a COVID 19 vaccine if offered at no cost within two months. Vaccine hesitancy was measured using a scale ranging from 1 (low hesitancy) to 6 (high hesitancy).

ResultsResponses were received from 2,650 respondents (response rate 84%) from all 50 states and Puerto Rico, American Samoa, and Guam. The majority were in the age category between 25 and 44 years (66%), male (53%), and working in the healthcare sector (61%). Most were White and non-Hispanic (66%) respondents followed by Black non-Hispanic (14%) and Hispanic (8%) respondents. Experience with racial discrimination was a predictor of vaccine hesitancy. Those reporting racial discrimination having 21% increased odds of being at a higher level of hesitancy compared to those who did not report such experience (OR=1.21, 95% C.I. 1.01-1.45).

Conclusions and RelevanceCommunication and logistical aspects during the COVID 19 vaccination campaign need to be sensitive to individuals past-experience of discrimination by identifying appropriate channels of communication and sites for vaccine distribution to reach those who may have sentiments of mistrust in the vaccination campaign.

category: public and global health


title: Based Analysis Framework for identifying COVID-19 Incidence and Fatality Determinants at National Level Case study: Africa

abstract:
BackgroundCOVID-19 pandemic is an extraordinary threat with significant implications in all aspects of human life, therefore, it represents the most immediate challenges for all countries all over the world.

ObjectivesThis study is intended to develop a GIS-based analysis model to explore, quantify and model the relationships between COVID-19 morbidity and mortality and their potential predictor variables.

MethodFor this purpose, a model was developed to estimate COVID-19 incidence and fatality rates in Africa up to 16th of August 2020 at the national level. The model involved Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) analysis through ArcGIS was applied.

ResultSpatial Autocorrelation Analysis revealed that there was positive spatial autocorrelation in COVID-19 incidence (Moran index 0.16. P value <0.1), and fatality (Moran index 0.0.35, P value<0.01) rates within different African countries. At continental level, OLS revealed that COVID-19 incidence rate was found to be positively associated with overcrowding, health expenditure, HIV infections and air pollution and negatively associated with BCG vaccine ({beta}=2.97,1.45, 0.01, 3.29, -47.65 respectively, P< 0.05) At the same time, COVID-19 fatality was found to be positively related to asthma prevalence and tobacco use. Yet, certain level of inconsistency was noted in the case of COVID-19 fatality, which was negatively related to elder population, poverty, and cardiovascular mortality (P<0.05). This model showed convenient level of validity in modeling the relationship between COVID-19 incidence as well as fatality and their key predictors using GWR. In this respect, the model explained about 58% and 55% of the variance in COVID-19 incidence and fatality rates, respectively, as a function of considered predictors.

ConclusionApplication of the suggested model can assist in guiding intervention strategies, particularly in case of local and community level whenever the data on COVID-19 cases and predictors variables are available.


title: GIS-Based Analysis Framework for Identifying COVID-19 Incidence and Fatality Determinants at National Level Case study: Africa


title: Impact of the Coronavirus Disease (COVID-19) on the Mental Health and Physical Activity of Pharmacy Students at the University of Zambia: A Cross-Sectional Study

abstract:
BackgroundThe novel coronavirus disease (COVID-19) is a serious global health problem that has negatively impacted the mental health of students.

MethodsWe conducted an online descriptive cross-sectional study among 273 undergraduate pharmacy students at the University of Zambia. A partial proportional odds regression model was used to determine the predictors of anxiety. All statistical tests were set at 95% confidence level (p<0.05).

ResultsA response rate of 70% was obtained with the majority of the students being female 51.6%. Of the 273 respondents, 23.8% did not experience anxiety, 34.4% experienced mild anxiety, 24.9% experienced moderate anxiety while 16.9% experienced severe anxiety about COVID-19. It was also found that 61.2% of students reported that their attention to mental health increased during the COVID-19 pandemic whereas 44.3% reported an increased resting time with a significant reduction in relaxation 51.3% and physical activity 45.4% time. Factors that affected mental health included; reduced family care (OR: 2.27; 95% CI: 1.09-4.74), not changing attention to mental health (OR: 0.33; 95% CI: 0.18-0.62), being in the final year of study (OR: 0.33; 95% CI: 0.13-0.84), reduced time of resting (OR: 2.10; 95% CI: 1.26-3.50) and feeling helpless (OR: 0.42; 95% CI:0.23-0.75).

ConclusionCOVID-19 negatively impacted the mental health and physical activity of pharmacy students at the University of Zambia. This can have negative health and academic outcomes for students going forward. Higher learning institutions and key stakeholders should implement measures to aid students to recover from the impact of COVID-19 on their mental health and physical activity.


title: Aerosol tracer testing in the cabin of wide-bodied Boeing 767 and 777 aircraft to simulate exposure potential of infectious particulate such as SARS-CoV-2

abstract:
The COVID-19 pandemic has reintroduced questions regarding the potential risk of SARS-CoV-2 exposure amongst passengers on an aircraft. Quantifying risk with computational fluid dynamics models or contact tracing methods alone is challenging, as experimental results for inflight biological aerosols is lacking. Using fluorescent aerosol tracers and real time optical sensors, coupled with DNA-tagged tracers for aerosol deposition, we executed ground and inflight testing on Boeing 767 and 777 airframes.

Analysis here represents tracer particles released from a simulated infected passenger, in multiple rows and seats, to determine the exposure risk via penetration into breathing zones in that row and numerous rows ahead and behind the index case. We completed over 65 releases of 180,000,000 fluorescent particles from the source, with 40+ Instantaneous Biological Analyzer and Collector sensors placed in passenger breathing zones for real-time measurement of simulated virus particle penetration.

Results from both airframes showed a minimum reduction of 99.54% of 1 {micro}m aerosols from the index source to the breathing zone of a typical passenger seated directly next to the source. An average 99.97 to 99.98% reduction was measured for the breathing zones tested in the 767 and 777, respectively. Contamination of surfaces from aerosol sources was minimal, and DNA-tagged 3 {micro}m tracer aerosol collection techniques agreed with fluorescent methodologies.


title: Genomic and mobility data reveal mass population movement as a driver of SARS-CoV-2 dissemination and diversity in Bangladesh

abstract:
BackgroundNew data streams are being used to track the pandemic of SARS-CoV-2, including genomic data which provides insights into patterns of importation and spatial spread of the virus, as well as population mobility data obtained from mobile phones. Here, we analyse the emergence and outbreak trajectory of SARS-CoV-2 in Bangladesh using these new data streams, and identify mass population movements as a key early event driving the ongoing epidemic.

MethodsWe sequenced complete genomes of 67 SARS-CoV-2 samples (March-July 2020) and combined this dataset with 324 genomes from Bangladesh. For phylogenetic context, we also used 68,000 GISAID genomes collected globally. We paired this genomic data with population mobility information from Facebook and three mobile phone operators.

FindingsThe majority (85%) of the Bangladeshi sequenced isolates fall into either pangolin lineage B.1.36 (8%), B.1.1 (19%) or B.1.1.25 (58%). Bayesian time-scaled phylogenetic analysis predicted SARS-COV-2 first appeared in mid-February, through international introductions. The first case was reported on March 8th. This pattern of repeated international introduction changed at the end of March when three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity across Bangladesh is reflected in the mobility data which shows the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka and the rest of the country during the following months.

InterpretationIn Bangladesh, population mobility out of Dhaka as well as frequent travel from urban hotspots to rural areas resulted in rapid country-wide dissemination of SARS-CoV-2. The strains in Bangladesh reflect the local expansion of global lineages introduced early from international travellers to and from major international travel hubs. Importantly, the Bangladeshi context is consistent with epidemiologic and phylogenetic findings globally. Bangladesh is one of the few countries in the world with a rich history of conducting mass vaccination campaigns under complex circumstances. Combining genomics and these new data streams should allow population movements to be modelled and anticipated rendering Bangladesh extremely well prepared to immunize citizens rapidly. Based on our genomics data and the countrys successful immunization history, vaccines becoming available globally will be suitable for implementation in Bangladesh while ongoing genomic surveillance is conducted to monitor for new variants of the virus.

FundingGovernment of Bangladesh, Bill and Melinda Gates Foundation, Wellcome Trust.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThe emergence of SARS-CoV-2, leading to the COVID-19 pandemic, has motivated all countries in the world to obtain high resolution data on the virus. Globally over 300,000 strains have been sequenced and information made available in GISAID. Within the first 100 days of the emergence of SARS-CoV-2, genomic analysis from different countries led to the development of vaccines which have now reached market. Information on the prevailing genotypes of SARS-CoV-2 since introduction is needed in low and middle-income countries (LMICs), including Bangladesh, in order to determine the suitability of therapeutics and vaccines in the pipeline and help vaccine deployment.

Added value of this studyWe sequenced SARS-CoV-2 genomes from strains that were prospectively collected during the height of the pandemic and combined these genomic data with mobility data to comprehensively describe i) how repeated international importations of SARS-CoV-2 were ultimately linked to nationwide spread, ii) 85% of strains belonged to the Pangolin lineages B.1.1, B.1.1.25 and B.1.36 and that similar mutation rates were observed as seen globally iii) the switch in genomic dynamics of SARS-CoV-2 coincided with mass migration out of cities to the rest of the country. We have assessed the contributions of population mobility on the maintenance and spread of clonal lineages of SARS-CoV-2. This is the first time these data types have been combined to look at the spread of this virus nationally.

Implications of all the available evidenceSARS-CoV-2 genomic diversity and mutation rate in Bangladesh is comparable to strains circulating globally. Notably, the data on the genomic changes of SARS-CoV-2 in Bangladesh is reassuring, suggesting that immunotherapeutic and vaccines being developed globally should also be suitable for this population. Since Bangladesh already has extensive experience of conducting mass vaccination campaigns, such as the rollout of the oral Cholera vaccine, experience of developing and using new data streams will enable efficient and targeted immunization of the population in 2021 with COVID-19 vaccine(s).


title: Maternal prenatal stress during the first trimester and infant birthweight in Soweto, South Africa

abstract:
BackgroundApproximately 14.2% of newborns are estimated to be born low birth weight (LBW) in South Africa. Past work has implicated maternal prenatal stress as a potent predictor of poor birth outcomes, including preterm birth, intrauterine growth restriction, and LBW. However, less is presently known about the impacts of prenatal stress during early gestation in low- and middle-income contexts, where public health burdens due to LBW are much higher.

ObjectiveWe assess the effects of psychosocial stress during the first trimester on birthweight in a large sample of women (n = 657) in Soweto, South Africa, a peri-urban township located in the Greater Johannesburg area.

MethodsData come from the Soweto First 1000 Days Cohort, a study of maternal and fetal predictors of infant birth outcomes. Multiple regression models were used to examine the impact of prenatal stress on infant birthweight.

ResultsThe prevalence of LBW was 16.6%. Adjusting for maternal age, gestational age, fetal gender, body mass index, and parity, maternal prenatal stress during the first trimester was a borderline predictor of lower birthweight in this sample ({beta} = 12.7, p = 0.071, 95% CI [-26.4, 1.10]). Women who reported greater levels of stress appeared to have non-significantly longer gestations, and the negative impact of maternal stress on birthweight only appeared after adjusting for this pattern.

ConclusionsThese results suggest that fetal growth restriction associated with first trimester maternal stress may contribute to lower birthweights in this sample. Our findings report modest relationships between maternal stress specific to early gestation as likely important to birth outcomes in this urban South African sample.


title: A Scoping Review of the Experience of Implementing Population Testing for SARS-CoV-2

abstract:
BackgroundThe SARS-CoV-2 pandemic has led to the swift introduction of population testing programmes in many countries across the world, using testing modalities such as drive-through, walk-through, mobile and home visiting programmes. Here, we provide an overview of the literature describing the experience of implementing population testing for SARS-CoV-2.

MethodsWe conducted a scoping review using Embase, Medline and the Cochrane Library in addition to a grey literature search. We identified indicators relevant to process, quality and resource outcomes related to each testing modality.

Results2,999 titles were identified from the academic literature and the grey literature search, of which 22 were relevant. Most studies were from the USA and the Republic of Korea. Drive-through testing centres were the most common testing modality evaluated and these provided a rapid method of testing whilst minimising resource use.

ConclusionsThe evidence base for population testing lacks high quality studies, however, the literature provides evaluations of the advantages and limitations of different testing modalities. There is a need for robust evidence in this area to ensure that testing is deployed in a safe and effective manner in response to the Covid-19 pandemic.


title: Cardiorespiratory Fitness and Neuromuscular Performance in Patients Recovered from COVID-19

abstract:
ObjectiveCOVID-19 affects cardiorespiratory and muscular systems, causing dysfunctions that may persist after recovery from the acute infection and treatment. The aim of this study was to evaluate cardiorespiratory fitness and neuromuscular performance in these patients.

MethodsPatients recovered from mild (n=31) and severe (n=17) COVID-19 were evaluated and compared to healthy subjects (n=15). All volunteers underwent a maximal cardiopulmonary exercise test with simultaneous acquisition of electromyography (EMG). Power output, oxygen uptake (VO2), pulse oxygen (O2Pulse), cardiovascular efficiency ({Delta}HR/{Delta}VO2), ventilation (VE), breathing reserve (BR) and ventilatory efficiency (VE/VCO2 slope) were analyzed. From EMG, power output for type Ia and IIa activation as well as total neuromuscular efficiency ({Delta}watts/{Delta}%RMS) were determined.

ResultsPatients with severe COVID-19 presented lower VO2, O2Pulse and VE than mild COVID-19 patients and healthy subjects (p < 0.05 for all comparisons). No differences in {Delta}HR/{Delta}VO2, BR or VE/VCO2 slope were observed among the groups (p > 0.05 for all comparisons). Type IIa and IIb fibers were activated at lower power output in severe than in mild COVID-19 patients and healthy subjects (p < 0.05). {Delta}watts/{Delta}%RMS was lower in severe than in mild COVID-19 patients and healthy subjects (p < 0.05).

ConclusionPatients recovered from severe COVID-19 present low cardiorespiratory fitness, activate glycolytic fibers at low power outputs, and show low neuromuscular efficiency; while patients recovered from mild COVID-19 do not present these sequels.

category: rehabilitation medicine and physical therapy


title: Variation in waiting times by diagnostic category: an observational study of 1951 referrals to a neurology outpatient clinic.

abstract:
ObjectiveTo investigate the frequency of diagnoses seen among new referrals to neurology outpatient services; to understand how these services are used through exploratory analysis of diagnostic tests and follow-up appointments; and to examine the waiting times between referral and appointment.

MethodsRoutine data from new NHS appointments at a single consultant-delivered clinic between Sept 2016 and January 2019 were collected. These clinical data were then linked to hospital administrative data. The combined data were assigned diagnostic categories based on working diagnoses to allow further analysis using descriptive statistics.

ResultsFive diagnostic categories accounted for 62% of all patients seen within the study period, the most common of which was headache disorders. Following a first appointment, 50% of all patients were offered at least one diagnostic test, and 35% were offered a follow-up appointment, with variation in both measures by diagnostic category. Waiting times from referral to appointment also varied by diagnostic category. 65% of patients with a seizure/epilepsy disorder were seen within the 18 week referral to treatment target, compared to 38% of patients with a movement disorder.

ConclusionsA small number of diagnostic categories account for a large proportion of new patients. This information could be used in policy decision making to describe a minimum subset of categories for diagnostic coding. We found significant differences in waiting times by diagnostic category, as well as tests ordered, and follow-up offered; further investigation could address causes of variation.

category: neurology


title: Proton magnetic resonance spectroscopy in frontotemporal lobar degeneration-related syndromes

abstract:
ObjectiveTo measure cortical metabolite deficits in vivo in syndromes associated with frontotemporal lobar degeneration, in relation to cognitive and behavioral change.

MethodsSixty patients were recruited with a clinical syndrome associated with frontotemporal lobar degeneration (behavioral variant frontotemporal dementia n=11, progressive supranuclear palsy n=26, corticobasal syndrome n=11, primary progressive aphasias n=12), and 38 age- and sex-matched healthy controls. We measured nine metabolites in the right inferior frontal gyrus, superior temporal gyrus and right primary visual cortex using 3T semi-laser magnetic resonance spectroscopy. Metabolite concentrations were corrected for age, sex, and partial volume. We related corrected metabolite concentrations to cognitive and behavioral measures using canonical correlation analysis.

ResultsMetabolite concentrations varied significantly by brain region and diagnosis (region x metabolite x diagnosis interaction F(64)=1.73, p<0.001, corrected for age, sex, and atrophy within the voxel). N-acetyl aspartate and glutamate concentrations were reduced in the right prefrontal cortex in behavioral variant frontotemporal dementia and progressive supranuclear palsy, even after partial volume correction. The reduction of these metabolites was associated with executive dysfunction and behavioral impairment (canonical correlation analysis R=0.95, p<0.001).

ConclusionMagnetic resonance spectroscopy confirms behaviourally relevant metabolite deficits including glutamate, in syndromes associated with frontotemporal lobar degeneration. Magnetic resonance spectroscopy may be a useful index of neurodegeneration, and highlight candidates for pharmacological treatment.


title: Social and Leisure Activity Contribute to the Attenuation of Decline in Behavioral Variant Frontotemporal Degeneration

abstract: Behavioral variant frontotemporal degeneration (bvFTD) is clinically characterized by progressive decline in social and executive domains. Previous work suggests that early lifestyle factors such as education and occupational attainment may relate to structural integrity and moderate the rate of cognitive decline in bvFTD, but the role of other cognitively stimulating activities is understudied. We sought to investigate the effect of such activities on cortical thickness (CT) in bvFTD. bvFTD patients (n=31) completed a baseline MRI scan, and informants for the patients completed the Lifetime of Experiences Questionnaire (LEQ), which measures specific activities considered to be undertaken primarily within one particular life phase, such as education (young-life), occupation (mid-life), and social/leisure activity (late-life). At baseline, linear models assessed the effect of LEQ scores from each life phase on regional CT. A subset (n=19) of patients completed longitudinal MRI, and to evaluate the association of LEQ with longitudinal rates of CT decline, we derived individualized slopes of decline using linear mixed effects models and these were related to LEQ scores from each life phase. At baseline, a higher late-life LEQ score was associated with less atrophy in bilateral superior anterior temporal regions. Longitudinally, we observed that higher late-life LEQ scores were associated with an attenuated rate of CT loss in insular cortex. Late-life LEQ score was positively associated with both relatively preserved CT early in bvFTD and a slower rate of cortical loss in regions important for social functioning. These findings suggest that social and leisure activities may contribute to a form of resilience against pathologic effects of disease.


title: The impact of the coronavirus disease 2019 (COVID-19) pandemic on university students' dietary intake, physical activity, and sedentary behaviour

abstract:
University students are a vulnerable group for poor dietary intake, insufficient physical activity and sedentary behaviour. The purpose of this study was to examine the impact of COVID-19 on university students dietary intake, physical activity and sedentary behaviour. Participants were students (n=125) from the Universities of Saskatchewan and Regina. An online questionnaire was administered retrospectively (for pre-pandemic) and prospectively (during the pandemic) to examine students dietary intake, physical activity and sedentary behaviour. Overall, nutrient and caloric intakes were significantly reduced (p<0.05) during the pandemic, and alcohol intake increased (p=0.03). Before the pandemic, 16% and 54% of the participants were meeting the Canadian 24-Hour Movement Guidelines for Adults (18-64 years) of 150 minutes of moderate-vigorous physical activity and 8 hours or less of sedentary activity respectively. Only 10% met the guidelines for physical activity while 30% met the guidelines for sedentary behaviour during the pandemic. The minutes per week spent engaging in moderate to vigorous physical activity during the pandemic decreased by approximately 20% (p<0.001). The hours spent in sedentary activities increased by 3 hours per day (p<0.001). Our findings confirm that during the pandemic, students inadequate dietary intake, high alcohol consumption, low physical activity and high sedentary behaviour were significantly compounded.

NoveltyO_LIDuring COVID-19, the nutrient and caloric intakes of university students decreased, and alcohol intake increased significantly.
C_LIO_LIUniversity students physical activity levels decreased, and sedentary activity increased significantly during COVID-19.
C_LIO_LIDuring COVID-19 students did not engage in sufficient physical activity to offset the increased sedentary behaviour.
C_LI

category: nutrition


title: Early detection of prostate gland and breast cancer risk based on routine check-up data using survival analysis trees for left-truncated and right-censored data

abstract:
ObjectiveTo predict breast cancer (BC) and prostate gland cancer (PGC) risk among healthy individuals by analyzing routine laboratory measurements, vital signs and age.

Materials and MethodsWe analyzed electronic medical records of 20,317 healthy individuals who underwent routine checkups, encompassing more than 600 parameters per visit, and identified those who later developed cancer. We developed a novel ensemble method for risk prediction of multivariate time series data using a random forest model of survival trees for left truncated and right-censored data.

ResultsUsing cross-validation, our method predicted future PGC and BC 6 months before diagnosis, achieving an area under the ROC curve of 0.62{+/-}0.05 and 0.6{+/-}0.03 respectively, better than standard random forest, Cox-regression model and a single survival tree. Our method can complement existing screening tests such as clinical breast examination and mammography for BC, and help in detection of subjects that were missed by these tests.

DiscussionComputational analysis of results of routine checkups of healthy individuals can improve the detection of those at risk of cancer development.

ConclusionOur method may assist in early detection of breast and prostate gland cancer.

category: oncology


title: Hospital load and increased COVID-19 related mortality - a nationwide study in Israel

abstract: The spread of Coronavirus disease 19 (COVID-19) has led to many healthcare systems being overwhelmed by the rapid emergence of new cases within a short period of time. We explore the ramifications of hospital load due to COVID-19 morbidity on COVID-19 in-hospital patient mortality. We address this question with a nationwide study based on the records of all 22,636 COVID-19 patients hospitalized in Israel from mid-July 2020 to mid-January 2021. We show that even under moderately heavy patient load (>500 countrywide hospitalized severely-ill patients; the Israeli Ministry of Health defined 800 severely-ill patients as the maximum capacity allowing adequate treatment), in-hospital mortality rate of patients with COVID-19 significantly increased compared to periods of lower patient load (250-500 severely-ill patients): 14-day mortality rates were 22.1% (Standard Error 3.1%) higher (mid-September to mid-October) and 27.2% (Standard Error 3.3%) higher (mid-December to mid-January). We further show this higher mortality rate cannot be attributed to changes in the patient population during periods of heavier load.

category: health systems and quality improvement


title: Emergence and Evolution of Big Data Analytics in HIV Research: Bibliometric Analysis of Federally Sponsored Studies 2000-2019

abstract:
BackgroundThe rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance of Big Data Science. Recently, there have been increasing uptakes of Big Data techniques in basic, clinical, and public health fields of HIV/AIDS research. However, no studies have systematically elaborated on the evolving applications of Big Data in HIV/AIDS research. We sought to explore the emergence and evolution of Big Data Science in HIV/AIDS-related publications that were funded by the US federal agencies.

MethodsWe identified HIV/AIDS and Big Data related publications that were funded by seven federal agencies from 2000 to 2019 by integrating data from National Institutes of Health (NIH) ExPORTER, MEDLINE, and MeSH. Building on bibliometrics and Natural Language Processing (NLP) methods, we constructed co-occurrence networks using bibliographic metadata (e.g., countries, institutes, MeSH terms, and keywords) of the retrieved publications. We then detected clusters among the networks as well as the temporal dynamics of clusters, followed by expert evaluation and clinical implications.

ResultsWe harnessed nearly 600 thousand publications related to HIV/AIDS, of which 19,528 publications relating to Big Data were included in bibliometric analysis. Results showed that (1) the number of Big Data publications has been increasing since 2000, (2) US institutes have been in close collaborations with China, Canada, and Germany, (3) some institutes (e.g., University of California system, MD Anderson Cancer Center, and Harvard Medical School) are among the most productive institutes and started using Big Data in HIV/AIDS research early, (4) Big Data research was not active in public health disciplines until 2015, (5) research topics such as genomics, HIV comorbidities, population-based studies, Electronic Health Records (EHR), social media, precision medicine, and methodologies such as machine learning, Deep Learning, radiomics, and data mining emerge quickly in recent years.

ConclusionsWe identified a rapid growth in the cross-disciplinary research of HIV/AIDS and Big Data over the past two decades. Our findings demonstrated patterns and trends of prevailing research topics and Big Data applications in HIV/AIDS research and suggested a number of fast-evolving areas of Big Data Science in HIV/AIDS research including secondary analysis of EHR, machine learning, Deep Learning, predictive analysis, and NLP.

category: hiv aids


title: Emergence and Evolution of Big Data Science in HIV Research: Bibliometric Analysis of Federally Sponsored Studies 2000-2019


title: Modelling the impact of household size distribution on the transmission dynamics of COVID-19

abstract: Under the implementation of non-pharmaceutical interventions such as social distancing and lockdowns, household transmission has been shown to be significant for COVID-19, posing challenges for reducing incidence in settings where people are asked to self-isolate at home and to spend increasing amounts of time at home due to distancing measures. Accordingly, characteristics of households in a region have been shown to relate to transmission heterogeneity of the virus. We introduce a stochastic epidemiological model to examine the impact of the household size distribution in a region on the transmission dynamics. We choose parameters to reflect incidence in two health regions of the Greater Vancouver area in British Columbia and simulate the impact of distancing measures on transmission, with household size distribution the only different parameter between simulations for the two regions. Our result suggests that the dissimilarity in household size distribution alone can cause significant differences in incidence of the two regions, and the distributions drive distinct dynamics that match reported cases. Furthermore, our model suggests that offering individuals a place to isolate outside their household can speed the decline in cases, and does so more effectively where there are more larger households.

category: infectious diseases


title: Immunochromatographic SARS-CoV-2 IgG antibody assay: a cross-sectional study conducted at Wakayama Medical University in Japan

abstract: Asymptomatic patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be quickly identified and isolated to prevent the spread of the virus. The number of asymptomatic healthy people is completely unknown because they remain untested. Detection of specific SARS-CoV-2 antibodies has been widely accepted as a diagnostic test, and an immunochromatographic test, which is simpler and relatively cheaper than other methods, is becoming the gold standard for identifying healthy people who had been infected with SARS-CoV-2 in the past. In this study, 1,528 volunteers who worked at a particular hospital were subjected to an immunochromatographic IgG test for SARS-CoV-2 to determine the ratio of asymptomatic people. Only 12 volunteers (0.79%) were IgG+, with no significant background differences in the sex, age, profession, experiences of working at the emergency department or caring for coronavirus disease 2019 patients. If this IgG+ ratio was to be extrapolated to Wakayama citys population, 2,780 out of 3,54,063 people may be asymptomatic for SARS-CoV-2. The results imply that anyone may get infected with SARS-CoV-2 but remain asymptomatic.


title: An open-access database of infectious disease transmission trees to explore superspreader epidemiology

abstract:
Historically, emerging and re-emerging infectious diseases have caused large, deadly, and expensive multi-national outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes transmission between individuals as a network with nodes representing individuals and branches representing transmission from person to person. We compiled a database of 383 published, standardized transmission trees consisting of 16 directly-transmitted diseases ranging in size from 2 to 286 cases. For each tree and disease we calculated several key statistics, such as outbreak size, average number of secondary infections, the dispersion parameter, and the number of superspreaders. We demonstrated the potential utility of the database through short analyses addressing questions about superspreader epidemiology for a variety of diseases, including COVID-19. First, we compared the frequency and contribution of superspreaders to onward transmission across diseases. COVID-19 outbreaks had significantly fewer superspreaders than outbreaks of SARS and MERS and a dispersion parameter between that of SARS and MERS. Across diseases the presence of more superspreaders was associated with greater outbreak size. Second, we further examined how early spread impacts tree size. Generally, trees sparked by a superspreader had larger outbreak sizes than those trees not sparked by a superspreader, and this trend was significant for COVID-19 trees. Third, we investigated patterns in how superspreaders are infected. Across trees with more than one superspreader, we found support for the theory that superspreaders generate other superspreaders, even when controlling for number of secondary infections. In sum, our findings put the role of superspreading to COVID-19 transmission in perspective with that of SARS and MERS and suggest an avenue for further research on the generation of superspreaders. These data have been made openly available to encourage reuse and further scientific inquiry.

Author SummaryPublic health investigations often aim to identify who infected whom, or the transmission tree, during outbreaks of infectious diseases. These investigations tend to be resource intensive but valuable as they contain epidemiological information, including the average number of infections caused by each individual and the variation in this number. To date, there remains no standardized format nor comprehensive database of infectious disease transmission trees. To fill this gap, we standardized and compiled more than 350 published transmission trees for 16 directly-transmitted diseases into a database that is publicly available. In this paper, we give an overview of the database construction process, as well as a demonstration of the types of questions that the database can be used to answer related to superspreader epidemiology. For example, we show that COVID-19 outbreaks have fewer superspreaders than outbreaks of SARS and MERS. We also find support for the theory that superspreaders generate other superspreaders. In the future, this database can be used to answer other outstanding questions in the field of epidemiology.


title: Impact of COVID-19 on the indigenous population of Brazil: A geo-epidemiological study

abstract: This study aimed to analyze the geographical distribution of COVID-19 and to identify highrisk areas for the occurrence of cases and deaths from the disease in the indigenous population of Brazil. This is an ecological study whose units of analysis were the Special Indigenous Sanitary Districts. Cases and deaths by COVID-19 notified by the Special Secretariat for Indigenous Health between March and October 2020 were included. To verify the spatial association, the Getis-Ord General G and Getis-Ord Gi * techniques were used. High spatial risk clusters have been identified by the scan statistics technique. 32,041 cases of COVID-19 and 471 deaths were reported. The incidence and mortality rates were between 758.14 and 18530.56 cases and 5.96 and 265.37 deaths per 100 thousand inhabitants, respectively. The non-randomness of cases (z-score = 5.40; p <0.001) and deaths (z-score = 3.83; p <0.001) was confirmed. Hotspots were evidenced for both events with confidence levels of 90, 95 and 99% concentrated in the North and Midwest regions of the country. Eight high-risk spatial clusters for cases with a relative risk (RR) between 1.08 and 4.11 (p <0.05) and two risk clusters for deaths with RR between 3.08 and 3.97 (p <0.05) were identified. The results indicate critical areas in the indigenous territories of Brazil and contribute to better targeting the control actions of COVID-19 in this population.


title: Diffusion basis spectrum imaging in post-hemorrhagic hydrocephalus of prematurity

abstract:
ObjectiveThe debilitating neurological deficits of neonatal post-hemorrhagic hydrocephalus (PHH) have been linked to periventricular white matter injury. To improve understanding of the deleterious mechanisms underlying PHH-related brain injury, this study applied diffusion basis spectrum imaging (DBSI) for the first time in neonates, modeling white matter fibers to assess axonal and myelin integrity, fiber density, and extra-fiber pathologies including cellularity, edema, and inflammation. The objectives of the study were to characterize DBSI measures in key periventricular white matter tracts of PHH infants, associate those diffusion measures with ventricular size, and utilize postmortem white matter histology to compare with the MRI findings.

MethodA prospective cohort of very preterm infants (n=95) underwent MRI at term equivalent age, of which 68 were controls (VPT group), 15 had high-grade intraventricular hemorrhage without hydrocephalus (IVH group), and 12 had PHH (PHH group). DBSI metrics extracted from manually segmented corpus callosum (CC), corticospinal tracts (CST), and optic radiations (OPRA) included fiber level axial diffusivity (FAD), fiber radial diffusivity (FRD), fiber fractional anisotropy (FFA), fiber fraction (FF), restricted fractions (RF), and non-restricted fractions (NRF). All measures were contrasted across groups and correlated with frontal occipital horn ratio (FOHR), a measure of ventricular size. Postmortem immunohistochemistry was performed on the CC of 10 preterm infants (five VPT, three IVH, and two PHH) and two full-term infants who died from non-neurologic causes assessing white matter intra- and extra-fiber pathologies, as well as the integrity of the adjoining ventricular and subventricular zones.

ResultsExcept for FF in the CC, there were no differences in all measures between IVH and VPT infants. In the unmyelinated CC, PHH had the lowest FF, FAD, and FFA and the highest RF. In the CC, FOHR related negatively with FAD, FFA, and FF and positively with RF. In the myelinated CST, PHH had the lowest FAD, FFA, and FF and the highest FRD and RF. FOHR related negatively to FAD and FFA and positively with NRF and FRD. In the OPRA, PHH was associated with the lowest FF and the highest RF, NRF, and FAD. FOHR related positively with FAD and NRF and negatively with FF. On postmortem tissues, PHH was associated with the highest white matter cellularity counts, variable amounts of cytoplasmic vacuolation, and the lowest synaptophysin marker intensity. The adjoining ventricular and subventricular zones in PHH had poor cytoarchitecture on H&E staining and relatively increased expression of GFAP and IBA1.

ConclusionsThis initial utilization of DBSI to investigate neonatal brain development and injury demonstrated that PHH was associated with diffuse periventricular white matter injury, with tract-specific microstructural patterns and severity of axonal injury, myelin injury, white matter fiber loss, hypercellularity, and inflammation. While axonal injury was present in the CST and unmyelinated CC, myelin injury occurred only in the CST. The OPRA predominantly showed inflammation with myelin preservation. White matter cellular infiltration occurred in all tracts. Postmortem immunohistochemistry confirmed the imaging findings of decreased axonal fiber density, sparser fiber architecture, and increased cellular infiltration. Larger ventricular size was associated with greater white matter disruption. Building upon these results, DBSI provides an innovative approach for investigating the complex neuropathological effects of PHH on periventricular white matter microstructure.

category: pediatrics


title: The National COVID Cohort Collaborative: Clinical Characterization and Early Severity Prediction

abstract: Withdrawal StatementThe authors have withdrawn this version of the manuscript to correct errors in Figure 1, Table 1, and Supplementary Table 1. Therefore, the authors do not wish this version of the work to be cited, please see version 2. If you have any questions, please contact the corresponding author.

category: health informatics


title: Modeling the COVID-19 transmission in Italy: The roles of asymptomatic cases, social distancing, and lockdowns

abstract: The SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is very high so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding on the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow.


title: Modeling the COVID-19 transmission in Italy: The roles of asymptomatic cases, social distancing, and lockdowns in the first and the second waves


title: Analysis of 200,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of developing a mood disorder resulting in psychiatric referral

abstract:
BackgroundDepression is moderately heritable but there is no common genetic variant which has a major effect on susceptibility. A previous analysis of 50,000 subjects failed to implicate any genes or sets of genes associated with risk of affective disorder requiring specialist treatment. A large exome-sequenced dataset is now available.

MethodsData from 200,632 exome-sequenced UK Biobank participants was analysed. Subjects were treated as cases if they had reported having seen a psychiatrist for "nerves, anxiety, tension or depression". Gene-wise weighted burden analysis was performed to see if there were any genes or sets of genes for which there was an excess of rare, functional variants in cases.

ResultsThere were 22,886 cases and 176,486 controls. There were 22,642 informative genes but no gene or gene set produced a statistically significant result after correction for multiple testing. None of the genes or gene sets with the lowest p values appeared to be a biologically plausible candidate.

LimitationsThe phenotype is based on self-report and the cases are likely to somewhat heterogeneous. Likewise, it is expected that some of the subjects classed as controls will in fact have suffered from depression or some other psychiatric diagnosis.

ConclusionsThe results conform exactly with the expectation under the null hypothesis. It seems unlikely that the use of common, poorly defined phenotypes will produce useful advances in understanding genetic contributions to affective disorder and it might be preferable to focus instead on obtaining large exome-sequenced samples of conditions such as bipolar 1 disorder and severe, recurrent depression.


title: Magnitude, change over time, demographic characteristics and geographic distribution of excess deaths among nursing home residents during the first wave of COVID-19 in France: a nationwide cohort study

abstract:
ImportanceNursing home (NH) residents are particularly vulnerable to SARS-CoV-2 infections and coronavirus disease 2019 (COVID-19) lethality. However, excess deaths in this population have rarely been documented.

ObjectivesThe primary objective was to assess the number of excess deaths among NH residents during the first wave of the COVID-19 pandemic in France. The secondary objectives were to determine the number of excess deaths as a proportion of the total excess deaths in the general population and determine whether a harvesting effect was present.

DesignWe studied a cohort of 494,753 adults (as of March 1st, 2020) aged 60 and over in 6,515 NHs in mainland France. This cohort was exposed to the first wave of the COVID-19 pandemic (from March 1st to May 31st, 2020) and was compared with the corresponding, reference cohorts from 2014 to 2019 (using data from the French National Health Data System).

Main outcome and measuresThe main outcome was all-cause death. Weekly excess deaths and standardized mortality ratios (SMRs) were estimated.

ResultThere were 13,505 excess deaths among NH residents. Mortality increased by 43% (SMR: 1.43). The mortality excess was higher among males than among females (SMR: 1.51 and 1.38, respectively) and decreased with age (SMRs in females: 1.61 in the 60-74 age group, 1.58 for 75-84, 1.41 for 85-94, and 1.31 for 95 or over; Males: SMRs: 1.59 for 60-74, 1.69 for 75-84, 1.47 for 85-94, and 1.41 for 95 or over). We did not observe a harvesting effect (up until August 30th, 2020). By extrapolating to all NH residents nationally (N=570,003), the latter accounted for 51% of the total excess deaths in the general population (N=15,114 out of 29,563).

ConclusionNH residents accounted for about half of the total excess deaths in France during the first wave of the COVID-19 pandemic. The excess death rate was higher among males than females and among younger residents than among older residents. We did not observe a harvesting effect. A real-time mortality surveillance system and the identification of individual and environmental risk factors might help to design the future model of care for older dependent adults.

Key pointsO_LIDuring the first wave of the COVID-19 pandemic in France, the mortality among nursing home residents increased by 43%.
C_LIO_LINursing home residents accounted for 51% of the total excess deaths in France.
C_LIO_LIThe excess mortality was higher among younger residents than among older residents.
C_LIO_LIThe excess mortality was higher among males than among females.
C_LIO_LIWe did not observe a harvesting effect during the study period (ending on August 30th, 2020, i.e., three months after the end of the first wave).
C_LI


title: Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms

abstract: Unprecedented SARS-CoV-2 infections in farmed minks raised immediate concerns regarding human health which initiated intensive environmental investigations. Air sampling was performed in infected mink farms, at farm premises and at residential sites. A range of other environmental samples were collected from minks housing units including bedding material. Inside the farms, high levels of SARS-CoV-2 RNA were found in airborne dust, on surfaces, and on various other environmental matrices. This warns for occupational exposure which was substantiated by considerable SARS-CoV-2 RNA concentrations in personal air samples. Dispersion of SARS-CoV-2 to outdoor air was found to be limited and SARS-CoV-2 RNA was not detected in air samples collected beyond farm premises, implying a negligible environmental exposure risk for nearby communities. Our occupational and environmental risk assessment is in line with whole genome sequences analyses showing mink-to-human transmission in farm workers, but no indications for direct zoonotic transmission events to nearby communities.

category: occupational and environmental health


title: Lack of evidence for interactions between APOE and Klotho genotypes on cognitive, dementia and brain imaging metrics in UK Biobank

abstract:
ImportanceRecent research has suggested that genetic variation in the Klotho (KL) locus may modify the association between apolipoprotein e (APOE) e4 genotype and cognitive impairment.

ObjectiveLarge-scale testing for associations and interactions between KL and APOE genotypes vs. risk of dementia (n=1,570 cases), cognitive abilities (n=174,513) and brain structure (n = 13,158) in older (60+ years) participants.

Design, setting and participantsCross-sectional and prospective data (UK Biobank).

Main outcomes and measuresKL status was indexed with heterozygosity of the rs9536314 polymorphism (vs. not), in unrelated people with vs. without APOE e4 genotype, using regression and interaction tests. We assessed non-demented cognitive scores (processing speed; reasoning; memory; executive function), multiple structural brain imaging, and clinical dementia outcomes. All tests were corrected for age, sex, assessment centre, eight principal components for population stratification, genotypic array, smoking history, deprivation, and self-reported medication history.

ResultsAPOE e4 presence (vs. not) was associated with increased risk of dementia, worse cognitive abilities and brain structure differences. KL heterozygosity was associated with less frontal lobe grey matter. There were no significant APOE/KL interactions for cognitive, dementia or brain imaging measures (all P>0.05).

Conclusions and relevanceWe found no evidence of APOE/KL interactions on cognitive, dementia or brain imaging outcomes. This could be due to some degree of cognitive test imprecision, generally preserved participant health potentially due to relatively young age, type-1 error in prior studies, or indicative of a significant age-dependent KL effect only in the context of marked AD pathology.

Key pointsO_LIQuestion: Klotho genotype has been previously shown to  offset a substantial amount of the APOE e4/cognitive impairment association. Is this modification effect apparent in large-scale independent data, in terms of non-demented cognitive abilities, brain structure and dementia prevalence?
C_LIO_LIFindings: In aged 60 years and above participants from UK Biobank, we found significant associations of APOE and Klotho genotypes on cognitive, structural brain and dementia outcomes, but no significant interactions.
C_LIO_LIMeaning: This could reflect somewhat healthy participants, prior type 1 error or cognitive/dementia ascertainment imprecision, and/or that Klotho genotypic effects are age and neuropathology dependent.
C_LI


title: Dynamic Prediction of SARS-CoV-2 RT-PCR status on Chest Radiographs using Deep Learning Enabled Radiogenomics

abstract: Reverse Transcription-Polymerase Chain Reaction (RT-PCR) is the gold standard for diagnosis of SARS-CoV-2 infection, but requires specialized equipment and reagents and suffers from long turnaround times. While valuable, chest imaging currently only detects COVID-19 pneumonia, but if it can predict actual RT-PCR SARS-CoV-2 status is unknown. Radiogenomics may provide an effective and accurate RT-PCR-based surrogate. We describe a deep learning radiogenomics (DLR) model (RadGen) that predicts a patient's RT-PCR SARS-CoV-2 status solely from their frontal chest radiograph (CXR).

category: radiology and imaging


title: Genetic insights into the biological mechanisms governing human ovarian ageing

abstract: Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in [~]200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

category: sexual and reproductive health


title: Integrative Omics Reveal Novel Protein Targets For Chronic Obstructive Pulmonary Disease Biomarker Discovery

abstract:
BackgroundLarge genome-wide association studies (GWAS) and other genetic studies have revealed genetic loci that are associated with chronic obstructive pulmonary disease (COPD). However, the proteins responsible for COPD pathogenesis remain elusive. We used integrative-omics by combining genetics of lung function and COPD with genetics of proteome to identify proteins underlying lung function variation and COPD risk.

MethodsWe used summary statistics from the GWAS of human plasma proteome from the INTERVAL cohort (n=3,301) and integrated these data with lung function GWAS results from the UK Biobank cohorts (n=400,102) and COPD GWAS results from the ICGC cohort (35,735 cases and 222,076 controls). We performed in parallel: a proteome-wide Bayesian colocalization, and a proteome-wide Mendelian Randomization (MR) analyses. Next, we selected proteins that colocalized with lung function and/or COPD risk and explored their causal association with lung function and/or COPD using MR analysis (P<0.05).

ResultsWe found 537, 607, and 250 proteins that colocalized with force expiratory volume in one second (FEV1), FEV1/forced vital capacity (FVC), or COPD risk, respectively. Of these, 1,051 were unique proteins. The sRAGE protein demonstrated the strongest colocalization with FEV1/FVC and COPD risk, while QSOX2, FAM3D and F177A proteins had the strongest associations with FEV1. Of these, 37 proteins that colocalized with lung function and/or COPD, also had a significant causal association. These included proteins such as PDE4D, QSOX2 and RGAP1, amongst others.

ConclusionIntegrative-omics reveals new proteins related to lung function. These proteins may play important roles in the pathogenesis of COPD.

category: genetic and genomic medicine


title: A Viral Fragmentation Signature for SARS-CoV-2 in Clinical Samples Correlating with Contagiousness

abstract: The viral load of SARS-CoV-2 in clinical samples as measured by the primary diagnostic tool of RT-PCR is an imperfect readout for infection potential as most targeted assays designed for sensitivity, indiscriminately detect short and long RNA fragments, although infectivity is embodied only in the whole virus and its intact genome. Here, we used next-generation sequencing (NGS) to characterize 155 clinical samples and show sensitive and quantitative detection of viral RNA which confirmed subgenomic RNA in 57.6% of samples and provided a novel method to determine relative integrity of viral RNA in samples. The relative abundance of long fragments quantified as a viral fragmentation score was positively associated with viral load and inversely related to time from disease onset. An empirically determined score cut-off for presence of substantially fragmented RNA was able to identify 100% of samples collected after 8 days of illness with poor infection potential in line with current clinical understanding of infectiousness of SARS-CoV-2. The quantification of longer fragments in addition to existing short targets in an NGS or RT-PCR-based assay could provide a valuable readout of infection potential simultaneous to the detection of any fragments of SARS-CoV-2 RNA in test samples.


title: Toward Assessing Clinical Trial Publications for Reporting Transparency

abstract:
ObjectiveTo annotate a corpus of randomized controlled trial (RCT) publications with the checklist items of CONSORT reporting guidelines and using the corpus to develop text mining methods for RCT appraisal.

MethodsWe annotated a corpus of 50 RCT articles at the sentence level using 37 fine-grained CONSORT checklist items. A subset (31 articles) was double-annotated and adjudicated, while 19 were annotated by a single annotator and reconciled by another. We calculated inter-annotator agreement at the article and section level using MASI (Measuring Agreement on Set-Valued Items) and at the CONSORT item level using Krippendorffs . We experimented with two rule-based methods (phrase-based and section header-based) and two supervised learning approaches (support vector machine and BioBERT-based neural network classifiers), for recognizing 17 methodology-related items in the RCT Methods sections.

ResultsWe created CONSORT-TM consisting of 10,709 sentences, 4,845 (45%) of which were annotated with 5,246 labels. A median of 28 CONSORT items (out of possible 37) were annotated per article. Agreement was moderate at the article and section levels (average MASI: 0.60 and 0.64, respectively). Agreement varied considerably among individual checklist items (Krippendorffs = 0.06-0.96). The model based on BioBERT performed best overall for recognizing methodology-related items (micro-precision: 0.82, micro-recall: 0.63, micro-F1: 0.71). Combining models using majority vote and label aggregation further improved precision and recall, respectively.

ConclusionOur annotated corpus, CONSORT-TM, contains more fine-grained information than earlier RCT corpora. Low frequency of some CONSORT items made it difficult to train effective text mining models to recognize them. For the items commonly reported, CONSORT-TM can serve as a testbed for text mining methods that assess RCT transparency, rigor, and reliability, and support methods for peer review and authoring assistance. Minor modifications to the annotation scheme and a larger corpus could facilitate improved text mining models. CONSORT-TM is publicly available at https://github.com/kilicogluh/CONSORT-TM.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/21249695v1_ufig1.gif" ALT="Figure 1">
View larger version (25K):
org.highwire.dtl.DTLVardef@6a6230org.highwire.dtl.DTLVardef@545939org.highwire.dtl.DTLVardef@1adae60org.highwire.dtl.DTLVardef@19359e7_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIWe constructed a corpus of RCT publications annotated with CONSORT checklist items.
C_LIO_LIWe developed text mining methods to identify methodology-related check-list items.
C_LIO_LIA BioBERT-based model performs best in recognizing adequately reported items.
C_LIO_LIA phrase-based method performs best in recognizing infrequently reported items.
C_LIO_LIThe corpus and the text mining methods can be used to address reporting transparency.
C_LI


title: An Informatics Consult approach for generating clinical evidence for treatment decisions

abstract: An Informatics Consult has been proposed in which clinicians request novel evidence from large scale health data resources, tailored to the treatment of a specific patient, with return of results in clinical timescales. However, the availability of such consultations is lacking. We seek to provide an Informatics Consult for a situation where a treatment indication and contraindication coexist in the same patient, i.e., anti-coagulation use for stroke prevention in a patient with both atrial fibrillation (AF) and liver cirrhosis. We examined four sources of evidence for the effect of warfarin on stroke risk (efficacy) or all-cause mortality (safety) from: (i) randomised controlled trials (RCTs), (ii) meta- analysis of prior observational studies, (iii) trial emulation (using population electronic health records (N = 3,854,710) and (iv) genetic evidence (Mendelian randomisation). We developed prototype forms to request an Informatics Consult and return of results in electronic health record systems. We found 0 RCT reports and 0 trials recruiting for patients with AF and cirrhosis. We found broad concordance across the three new sources of evidence we generated. Meta-analysis of prior observational studies showed that warfarin use was associated with lower stroke risk (hazard ratio [HR] = 0.71). In a target trial emulation, warfarin was associated with lower all-cause mortality (HR = 0.61) and ischaemic stroke (HR = 0.27). Mendelian randomisation served as a drug target validation where we found that lower levels of vitamin K1 (warfarin is a vitamin K1 antagonist) are associated with lower stroke risk. A pilot survey with an independent sample of 34 clinicians revealed that 85% of clinicians found information on prognosis useful and that 79% thought that they should have access to the Informatics Consult as a service within their healthcare systems. We identified candidate steps for automation to scale evidence generation and to accelerate the return of results within clinical timescales.


title: Intermediate-dose anticoagulation, aspirin, and in-hospital mortality in COVID-19: a propensity score-matched analysis

abstract:
BackgroundThrombotic complications occur at high rates in hospitalized patients with COVID-19, yet the impact of intensive antithrombotic therapy on mortality is uncertain.

Research QuestionHow does in-hospital mortality compare with intermediate-versus prophylactic-dose anticoagulation, and separately with in-hospital aspirin versus no antiplatelet therapy, in treatment of COVID-19?

Study Design and MethodsUsing data from 2785 hospitalized adult COVID-19 patients, we established two separate, nested cohorts of patients (1) who received intermediate- or prophylactic-dose anticoagulation ("anticoagulation cohort", N = 1624), or (2) who were not on home antiplatelet therapy and received either in-hospital aspirin or no antiplatelet therapy ("aspirin cohort", N = 1956). Propensity score matching utilizing various markers of illness severity and other patient-specific covariates yielded treatment groups with well-balanced covariates in each cohort. The primary outcome was cumulative incidence of in-hospital death.

ResultsAmong propensity score-matched patients in the anticoagulation cohort (N = 382), in a multivariable regression model, intermediate-compared to prophylactic-dose anticoagulation was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.518 [0.308-0.872]). Among propensity-score matched patients in the aspirin cohort (N = 638), in a multivariable regression model, in-hospital aspirin compared to no antiplatelet therapy was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.522 [0.336-0.812]).

InterpretationIn this propensity score-matched, observational study of COVID-19, intermediate-dose anticoagulation and aspirin were each associated with a lower cumulative incidence of in-hospital death.

Summary conflict of interest statementsNo conflict of interest exists for any author on this manuscript.

category: hematology


title: Differential T cell reactivity to seasonal coronaviruses and SARS-CoV-2 in community and health care workers

abstract: Herein we measured CD4+ T cell responses against common cold corona (CCC) viruses and SARS-CoV-2 in high-risk health care workers (HCW) and community controls. We observed higher levels of CCC reactive T cells in SARS-CoV-2 seronegative HCW compared to community donors, consistent with potential higher occupational exposure of HCW to CCC. We further show that SARS-CoV-2 reactivity of seronegative HCW was higher than community controls and correlation between CCC and SARS-CoV-2 responses is consistent with cross-reactivity and not associated with recent in vivo activation. Surprisingly, CCC reactivity was decreased in SARS-CoV-2 infected HCW, suggesting that exposure to SARS-CoV-2 might interfere with CCC responses, either directly or indirectly. This result was unexpected, but consistently detected in independent cohorts derived from Miami and San Diego.


title: Increased infections, but not viral burden, with a new SARS-CoV-2 variant

abstract:
BackgroundA new variant of SARS-CoV-2, B.1.1.7/VOC202012/01, was identified in the UK in December-2020. Direct estimates of its potential to enhance transmission are limited.

MethodsNose and throat swabs from 28-September-2020 to 2-January-2021 in the UKs nationally representative surveillance study were tested by RT-PCR for three genes (N, S and ORF1ab). Those positive only on ORF1ab+N, S-gene target failures (SGTF), are compatible with B.1.1.7/VOC202012/01. We investigated cycle threshold (Ct) values (a proxy for viral load), percentage of positives, population positivity and growth rates in SGTF vs non-SGTF positives.

Results15,166(0.98%) of 1,553,687 swabs were PCR-positive, 8,545(56%) with three genes detected and 3,531(23%) SGTF. SGTF comprised an increasing, and triple-gene positives a decreasing, percentage of infections from late-November in most UK regions/countries, e.g. from 15% to 38% to 81% over 1.5 months in London. SGTF Ct values correspondingly declined substantially to similar levels to triple-gene positives. Population-level SGTF positivity remained low (<0.25%) in all regions/countries until late-November, when marked increases with and without self-reported symptoms occurred in southern England (to 1.5-3%), despite stable rates of non-SGTF cases. SGTF positivity rates increased on average 6% more rapidly than rates of non-SGTF positives (95% CI 4-9%) supporting addition rather than replacement with B.1.1.7/VOC202012/01. Excess growth rates for SGTF vs non-SGTF positives were similar in those up to high school age (5% (1-8%)) and older individuals (6% (4-9%)).

ConclusionsDirect population-representative estimates show that the B.1.1.7/VOC202012/01 SARS-CoV-2 variant leads to higher infection rates, but does not seem particularly adapted to any age group.


title: Genomic surveillance at scale is required to detect newly emerging strains at an early timepoint

abstract: Genomic surveillance in the setting of the coronavirus disease 2019 (COVID-19) pandemic has the potential to identify emerging SARS-CoV-2 strains that may be more transmissible, virulent, evade detection by standard diagnostic tests, or vaccine escapes. The rapid spread of the SARS-CoV-2 B.1.1.7 strain from southern England to other parts of the country and globe is a clear example of the impact of such strains. Early discovery of the B.1.1.7 strain was enabled through the proactive COVID-19 Genomics UK (COG-UK) program and the UKs commitment to genomic surveillance, sequencing about 10% of positive samples.1 In order to enact more aggressive public health measures to minimize the spread of such strains, genomic surveillance needs to be of sufficient scale to detect early emergence and expansion in the broader virus population. By modeling common performance characteristics of available diagnostic and sequencing tests, we developed a model that assesses the sampling required to detect emerging strains when they are less than 1% of all strains in a population. This model demonstrates that 5% sampling of all positive tests allows the detection of emerging strains when they are a prevalence of 0.1% to 1.0%. While each country will determine their risk tolerance for the emergence of novel strains, as vaccines are distributed and we work to end the pandemic and prevent future SARS-CoV-2 outbreaks, genomic surveillance will be an integral part of success.


title: Impact of COVID-19 shelter-in-place order on transmission of gastrointestinal pathogens in Northern California

abstract: Society-wide cessation of human interaction outside the household due to the COVID-19 shelter-in-place created a unique opportunity in modern history to reexamine the transmission of communicable gastrointestinal pathogens. We conducted a quasi-experimental study from January 1, 2018 to Sept 30, 2020 to investigate the effect of Californias COVID-19 shelter-in-place order on the community transmission of viral, bacterial, and parasitic gastrointestinal pathogens detected with the FilmArray GI Panel (BioFire Diagnostics, Salt Lake City, UT). The incidence of viral causes of gastroenteritis, enteroaggregative/enteropathogenic/enterotoxigenic Escherichia coli, Shigella, and Cyclospora cayetanensis decreased sharply after shelter-in place took effsect, whilst Salmonella, Campylobacter, shiga toxin-producing E. coli (O157 and non-O157) and other bacterial and parasitic causes of gastroenteritis were largely unaffected. Findings suggest community spread of viral gastroenteritis, pathogenic E. coli (except for shiga toxin-producing E. coli), Shigella, and Cyclospora is more susceptible to changes associated with shelter-in-place than other gastrointestinal pathogens.


title: From SARS and MERS to COVID-19: a review of the quality and responsiveness of clinical management guidelines in outbreak settings

abstract:
ObjectiveTo assess the responsiveness and quality of clinical management guidelines (CMGs) in SARS, MERS and COVID-19 and determine whether this has improved over time.

DesignRapid literature review, quality assessment and focus group consultation.

Data Sources- Google and Google Scholar were systematically searched from inception to 6th June 2020.This was supplemented with hand searches of national and international public health agency and infectious disease society websites as well as directly approaching clinical networks in regions where few CMGs had been identified via the primary search.

Eligibility CriteriaCMGs for the treatment of COVID-19/SARS/MERS providing recommendations on supportive care and/or specific treatment.

MethodsData extraction was performed using a standardised form. The Appraisal of Guidelines for Research and Evaluation (AGREE-II) tool was used to evaluate the quality of the CMGs. Six COVID-19 treatments were selected to assess the responsiveness of a subset of guidelines and their updates to 20th November 2020. We ran two sessions of focus groups with patient advocates to elicit their views on guideline development.

ResultsWe included 37 COVID-19, six SARS, and four MERS CMGs. Evidence appraisals in CMGs generally focused on novel drugs rather than basic supportive care; where evidence for the latter was provided it was generally of a low quality. Most CMGs had major methodological flaws (only two MERS-CoV and four COVID-19 CMGs were recommended for use by both reviewers without modification) and there was no evidence of improvement in quality over time. CMGs scored lowest in the following AGREE-II domains: scope and purpose, editorial independence, stakeholder engagement, and rigour of development. Of the COVID-19 CMGs, only eight included specific guidance for the management of elderly patients and only ten for high-risk groups; a further eight did not specify the target patient group at all. Early in the pandemic, multiple guidelines recommended unproven treatments and whilst in general findings of major clinical trials were eventually adopted, this was not universally the case. Eight guidelines recommended that use of unproven agents should be considered on a case-by-case basis. Patient representatives expressed concern about the lack of engagement with them in CMG development and that these documents are not accessible to non-experts.

ConclusionThe quality of most CMGs produced in coronaviridae outbreaks is poor and we have found no evidence of improvement over time, highlighting that current development frameworks must be improved. There is an need to strengthen the evidence base surrounding basic supportive care and develop methods to engage patients in CMG development from the beginning in outbreak settings.

Systematic review registrationPROSPERO CRD42020167361


title: Isolation of SARS-CoV-2 from the air in a car driven by a COVID patient with mild illness

abstract: We used a Sioutas personal cascade impactor sampler (PCIS) to screen for SARS-CoV-2 in a car driven by a COVID-19 patient. SARS-CoV-2 was detectable at all PCIS stages by PCR and was cultured from the section of the sampler collecting particles in the 0.25 to 0.50 {square}m size range.


title: Emergence of multiple SARS-CoV-2 mutations in an immunocompromised host

abstract:
Prolonged shedding of infectious SARS-CoV-2 has recently been reported in a number of immunosuppressed individuals with COVID-19. Here, we describe the detection of high levels of replication-competent SARS-CoV-2 in specimens taken from the respiratory tract of a B-cell depleted patient up to 154 days after initial COVID-19 diagnosis concomitant with the development of high mutation rate. In this patient, a total of 11 nonsynonymous mutations were detected in addition to the Y144 deletion in the spike protein of SARS-CoV-2.

Virus evolution studies revealed a dramatic diversification in viral population coinciding with treatment with convalescent plasma and clinical respiratory deterioration. Our findings highlight the urgent need for continuous real-time surveillance of genetic changes of SARS-CoV-2 adaptation alongside immunological investigations in patients with severely compromised humoral responses who may shed infectious virus over prolonged periods of time.