title: Prognostic significance of circRNAs expression in breast carcinoma patients: A meta-analysis

abstract:
ObjectiveThe aim of our study was to systematically evaluate the prognostic effects of various circrnas and to explore the prognostic value of circRNAs in breast cancer patients.

MethodsA systematical search was conducted on PubMed, Scopus, EMBASE, and the Cochrane Library databases. Eligible studies reporting on the association among circRNAs and prognostic values of breast cancer patients were included. Fixed-effects and random effects models were used to calculate the pooled hazard ratio values of overall survival and disease free survival. In addition, funnel plots were used to qualitatively analyze the publication bias.

Results28 studies were included in our meta-analysis. The pooled hazard ratio values of overall survival and disease free survival related to different circRNAs expression in breast cancer patients were 1.68 (1.44-1.97), 2.63 (1.95-3.53).We have identified a total of 28 circRNAs including 19 significantly up-regulated expression circRNAs and 9 significantly down-regulated expression circRNAs in BC(breast cancer) patients. Moreover, all of them revealed mechanisms and have the function of promoting or inhibiting the proliferation, metastasis or invasion of breast cancer cells by acting on the corresponding target.

ConclusionOverall, specific circRNAs are significantly associated with the prognosis of BC patients and potentially eligible for the prediction of patients survival. It also provides a potential value for clinical decision-making development and may serve as a promising circRNAs-based target therapy waiting for further elucidation.


title: Whole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program

abstract: The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome and exome arrays, resulting in over 100 associated variants. We extended this work with a high-coverage whole genome sequencing (WGS) analysis from fifteen cohorts in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. More than 23,000 non-diabetic individuals from five self-reported race/ethnicities (African, Asian, European, Hispanic and Samoan) were included for each trait. We analyzed 60M variants in race/ethnicity-specific and pooled single variant and rare variant aggregate tests. Twenty-two variants across sixteen gene regions were found significantly associated with FG or FI, eight of which were rare (Minor Allele Frequency, MAF<0.05). Functional annotation from resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. Near the G6PC2 locus we identified a distinct FG signal at rare variant rs2232326 (MAF=0.01) after conditioning on known common variants. Functional annotations show rs2232326 to be disruptive and likely damaging while being weakly transcribed in islets. A pair of FG-associated variants were identified near the SLC30A8 locus. These variants, one of which was rare (MAF=0.001) and Asian race/ethnicity-specific, were shown to be in islet-specific active enhancer regions. Other associated regions include rare variants near ROBO1 and PTPRT, and common variants near MTNR1B, GCK, GCKR, FOXA2, APOB, TCF7L2, and ADCY5. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions down to a minor allele count of 20, creating a foundation for future sequencing-based investigation of glycemic traits.

category: genetic and genomic medicine


title: Identification of Cognitive Impairment in Cardiovascular Rehabilitation: A Cross-Sectional Study Protocol.

abstract:
IntroductionCardiac Rehabilitation is a multidisciplinary intervention for people after an adverse cardiac event to improve their physical, psychological and social functioning. The risk factors of cardiac disease and dementia are similar. This cross sectional study aims to determine whether adding memory assessment to a cardiac rehabilitation program would improve early detection of cognitive impairment.

Methods and AnalysisParticipants will undergo cognitive assessment by using Addenbrookes Cognitive Examination (ACE-III). The data obtained will be divided into: - 1- Participants who had a history of memory problems before and after the adverse cardiac event. 2-Participants with no history of memory problems before and currently presents with cognitive impairment. 3-Participants with no memory problems before and after the adverse cardiac event.

Ethics and disseminationStudy ethical approval has been granted by Sheffield Research Ethics Committee (reference 20/YH/0146) and the NHS Health Research Authority (project reference 273763).

category: geriatric medicine


title: One Shot Model For The Prediction of COVID-19 and Lesions Segmentation In Chest CT Scans Through The Affinity Among Lesion Mask Features

abstract: We introduce a model that segments lesions and predicts COVID-19 from chest CT scans through the derivation of an affinity matrix between lesion masks. The novelty of the methodology is based on the computation of the affinity between the lesion masks features extracted from the image. First, a batch of vectorized lesion masks is constructed. Then, the model learns the parameters of the affinity matrix that captures the relationship between features in each vector. Finally, the affinity is expressed as a single vector of pre-defined length. Without any complicated data manipulation, class balancing tricks, and using only a fraction of the training data, we achieve a 91.74% COVID-19 sensitivity, 85.35% common pneumonia sensitivity, 97.26% true negative rate and 91.94% F1-score. Ablation studies show that the method can quickly generalize to new datasets. All source code, models and results are publicly available on https://github.com/AlexTS1980/COVID-Affinity-Model.

category: health informatics


title: Effect of public health interventions during the first epidemic wave of COVID-19 in Cyprus: a modelling study

abstract:
BackgroundCyprus addressed the first wave of SARS CoV-2 (COVID-19) by implementing non-pharmaceutical interventions. The aims of this study were: a) to estimate epidemiological parameters of this wave including infection attack ratio, infection fatality ratio, and case ascertainment ratio, b) to assess the impact of public health interventions, and c) to examine what would have happened if those interventions had not been implemented.

MethodsA dynamic, stochastic, individual-based Susceptible-Exposed-Infected-Recovered (SEIR) model was developed to simulate COVID-19 transmission and progression in the population of the Republic of Cyprus. The model was fitted to the observed trends in COVID-19 deaths and intensive care unit (ICU) bed use.

ResultsBy May 8 2020th, the infection attack ratio was 0.31% (95% Credible Interval (CrI): 0.15%, 0.54%), the infection fatality ratio was 0.71% (95% CrI: 0.44%, 1.61%), and the case ascertainment ratio was 33.2% (95% CrI: 19.7%, 68.7%). If Cyprus had not implemented any public health measure, the healthcare system would have been overwhelmed by April 14th. The interventions averted 715 (95% CrI: 339, 1235) deaths. If Cyprus had only increased ICU beds, without any social distancing measure, the healthcare system would have been overwhelmed by April 19th.

ConclusionsThe decision of the Cypriot authorities to launch early non-pharmaceutical interventions limited the burden of the first wave of COVID-19. The findings of these analyses could help address the next waves of COVID-19 in Cyprus and other similar settings.

category: health policy


title: Use of Diagnosis Codes to Find Blood Transfusion Adverse Events in Electronic Health Records

abstract:
BackgroundElectronic health records (EHRs) and big data tools offer the opportunity for surveillance of adverse events (patient harm associated with medical care). We chose the case of transfusion adverse events (TAEs) and potential TAEs (PTAEs) because 1.) real dates were obscured in the study data, and 2.) there was emerging recognition of new types during the study data period.

ObjectiveWe aimed to use the structured data in electronic health records (EHRs) to find TAEs and PTAEs among adults.

MethodsWe used 49,331 adult admissions involving critical care at a major teaching hospital, 2001-2012, in the MIMIC-III EHRs database. We formed a T (defined as packed red blood cells, platelets, or plasma) group of 21,443 admissions vs. 25,468 comparison (C) admissions. The ICD-9-CM diagnosis codes were compared for T vs. C, described, and tested with statistical tools.

ResultsTAEs such as transfusion associated circulatory overload (TACO; 12 T cases; rate ratio (RR) 15.61; 95% CI 2.49 to 98) were found. There were also PTAEs similar to TAEs, such as fluid overload disorder (361 T admissions; RR 2.24; 95% CI 1.88 to 2.65), similar to TACO. Some diagnoses could have been sequelae of TAEs, including nontraumatic compartment syndrome of abdomen (52 T cases; RR 6.76; 95% CI 3.40 to 14.9) possibly being a consequence of TACO.

ConclusionsSurveillance for diagnosis codes that could be TAE sequelae or unrecognized TAE might be useful supplements to existing medical product adverse event programs.

category: health systems and quality improvement


title: How vaccination and contact isolation might interact to suppress transmission of Covid-19: a DCM study

abstract: This report describes a dynamic causal model that could be used to address questions about the rollout and efficacy of vaccines in the United Kingdom. For example, is suppression of community transmission a realistic aspiration? And, if not, what kind of endemic equilibrium might be achieved? What percentage of the population needs to be vaccinated? And over what timescale? It focuses on the synergies among (i) vaccination, (ii) the supported isolation of contacts of confirmed cases and (iii) restrictions on contact rates (i.e., lockdown and social distancing). To model these mitigations, we used a dynamic causal model that embeds an epidemiological model into agent-based behavioural model. The model structure and parameters were optimised to best explain responses--to the first and subsequent waves--enabling predictions over the forthcoming year under counterfactual scenarios. Illustrative analyses suggest that the full potential of vaccination is realised by increasing the efficacy of contact tracing: for example, under idealised (best case) assumptions--of an effective vaccine and efficient isolation of infected pre-symptomatic cases-- suppression of community transmission would require 50% herd immunity by vaccinating 22% by the end of 2021; i.e., 15 million people or about 50,000 per day. With no change in the isolation of contacts, 36% would require vaccination, i.e., 25 million people. These figures should not be read as estimates of the actual number of people requiring vaccination; however, they illustrate the potential of this kind of model to quantify interactions among public health interventions. We anticipate using this model in a few months--to estimate the average effectiveness of vaccines when more data become available.

category: infectious diseases


title: Real-World Clinical Performance of the Abbott Panbio with Nasopharyngeal, Throat and Saliva Swabs Among Symptomatic Individuals with COVID-19

abstract:
BACKGROUNDPoint of Care Testing (POCT) SARS-CoV-2 antigen tests, such as the Abbott Panbio, have great potential to help combat the COVID-19 pandemic. The Panbio is Health Canada approved for the detection of SARS-CoV-2 in symptomatic individuals within the first 7 days of COVID-19 symptom onset(s).

METHODSSymptomatic adults recently diagnosed with COVID-19 in the community were recruited into the study. Paired nasopharyngeal (NP), throat, and saliva swabs were collected, with one paired swab tested immediately with the Panbio, and the other transported in universal transport media and tested using reverse-transcriptase polymerase chain reaction (RT-PCR). Positive percent agreement (PPA) was calculated. Subsequently, individuals within 7 days of symptom onset who presented to community assessment centres for SARS-CoV-2 testing had Panbio testing completed and paired with RT-PCR results from parallel NP or throat swabs.

RESULTS145 individuals were included in the study. Collection of throat and saliva was stopped early due to poor performance (throat PPA 57.7%, n=61, and saliva PPA 2.6%, n=41). NP swab PPA was 87.7% [n=145, 95% confidence interval 81.0% - 92.7%]. There were 1,641 symptomatic individuals tested by Panbio in community assessment centres, with 268/1641 (16.3%) positive for SARS-CoV-2. There were 37 false negatives, corresponding to a PPA of 86.2% [81.5% - 90.1%].

CONCLUSIONSThe Panbio test reliably detects most cases of SARS-CoV-2 from adults in the POCT community setting presenting within 7 days of symptom onset using nasopharyngeal swabs. Throat and saliva swabs are not reliable specimens for the Panbio.


title: Implications in the quantitation of SARS-CoV2 copies in concurrent nasopharyngeal swabs, whole mouth fluid and respiratory droplets

abstract:
ImportanceThe nasopharyngeal swab (NPS) is considered the ideal diagnostic specimen for Covid-19, while WMF is recently promoted due to collection simplicity and importance in disease transmission. There is limited knowledge on the relative viral load in these samples - NPS, whole mouth fluid (WMF) and respiratory droplets (RD; another important source in transmission), on how the loads vary with disease severity and on how much virus is shed.

ObjectiveTo quantify and compare SARS-CoV2 copies in the NPS, WMF and RD samples, and correlate with disease severity.

DesignCross sectional study.

SettingTertiary care multi-speciality hospital with limited resources in a low-to-middle income country.

ParticipantsEighty suspected COVID-19 patients were recruited from the COVID-19 out-patient clinic and hospital isolation wards.

InterventionConcurrent NPS, WMF and RD samples were collected from all the recruited patients and tested for SARS-CoV2 copies by quantitative reverse transcriptase-polymerase chain reaction (RT-PCR).

Main outcomes and measuresThe main outcome was COVID-19 measured by SARS-CoV2 quantitative RT-PCR in NPS samples. COVID-19 disease severity was determined according to NIH criteria. Virus shedding was defined as the presence of SARS-CoV2 copies in the WMF and RD samples.

ResultsSARS-CoV2 was detected in 55/80 (69%) of the NPS samples. Of these 55, WMF and RD samples were positive in 44 (80%) and 17 (31%), respectively. The concordance of WMF with NPS was 84% (p=0.02). SARS-CoV2 copy numbers were comparable in the NPS (median: 8.74x10^5) and WMF (median: 3.07x10^4), but lower in RD samples (median: 3.60x10^2). Patients with mild disease had higher copies in the NPS (median: 3.46x10^6), while patients with severe disease had higher copies in the WMF (median: 1.34x10^6) and RD samples (median: 4.29x10^4). The 25-75% interquartile range of NPS SARS-CoV2 copies was significantly higher in the WMF (p=0.0001) and RD (p=0.01) positive patients.

Conclusion and relevanceSARS-CoV2 copies are highest in NPS samples. WMF is a reliable surrogate sample for diagnosis. High copy numbers in the NPS imply initial virological phase and higher risk of virus shedding via WMF and RD.

Key pointsO_ST_ABSQuestionC_ST_ABSHow the numbers of SARS-CoV2 copies in nasopharyngeal swab (NPS) samples might reflectvirus shedding from the whole upper aerodigestive tract and indicatedisease severity?

FindingsIn this cross-sectional study involving 80 suspected COVID-19 patients, the data indicate higher SARS-CoV2 copies in NPS samples of patients with mild disease,and in the whole mouth fluid (WMF) and respiratory droplet (RD) samples of patients with severe disease. Patients with higher SARS-CoV2 copies in the NPS shed the virus in the WMF and RD samples at statistically higher levels.

MeaningHigh SARS-CoV2 copies in NPS samples imply initial virological phase withhigh levels of shedding through both WMF and RD.


title: Sub-5-minute Detection of SARS-CoV-2 RNA using a Reverse Transcriptase-Free Exponential Amplification Reaction, RTF-EXPAR

abstract: We report a rapid isothermal method for detecting SARS-CoV-2, the virus responsible for COVID-19. The procedure uses a novel reverse transcriptase-free (RTF) approach for converting RNA into DNA, which triggers a rapid amplification using the Exponential Amplification Reaction (EXPAR). Deploying the RNA-to-DNA conversion and amplification stages of the RTF-EXPAR assay in a single step results in the detection of a sample of patient SARS-CoV-2 RNA in under 5 minutes.


title: The Joint Impact of COVID-19 Vaccination and Non-Pharmaceutical Interventions on Infections, Hospitalizations, and Mortality: An Agent-Based Simulation

abstract:
BackgroundVaccination against SARS-CoV-2 has the potential to significantly reduce transmission and morbidity and mortality due to COVID-19. This modeling study simulated the comparative and joint impact of COVID-19 vaccine efficacy and coverage with and without non-pharmaceutical interventions (NPIs) on total infections, hospitalizations, and deaths.

MethodsAn agent-based simulation model was employed to estimate incident SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths over 18 months for the State of North Carolina, a population of roughly 10.5 million. Vaccine efficacy of 50% and 90% and vaccine coverage of 25%, 50%, and 75% (at the end of a 6-month distribution period) were evaluated. Six vaccination scenarios were simulated with NPIs (i.e., reduced mobility, school closings, face mask usage) maintained and removed during the period of vaccine distribution.

ResultsIn the worst-case vaccination scenario (50% efficacy and 25% coverage), 2,231,134 new SARS-CoV-2 infections occurred with NPIs removed and 799,949 infections with NPIs maintained. In contrast, in the best-case scenario (90% efficacy and 75% coverage), there were 450,575 new infections with NPIs maintained and 527,409 with NPIs removed. When NPIs were removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared to the worst-case scenario (absolute risk reduction 13% and 8%, respectively).

ConclusionSimulation results suggest that premature lifting of NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared to more efficacious vaccines at lower coverage. Our findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many pre-pandemic activities can be resumed.


title: THE INFLUENCE OF HLA GENOTYPE ON SUSCEPTIBILITY TO, AND SEVERITY OF, COVID-19 INFECTION

abstract:
BackgroundThe impact of COVID-19 varies markedly, not only between individual patients but also between different populations. We hypothesised that differences in human leukocyte antigen (HLA) genes might influence this variation.

MethodsUsing next generation sequencing, we analysed the class I and class II classical HLA genes of 147 white British patients with variable clinical outcomes. 49 of these patients were admitted to hospital with severe COVID infection. They had no significant pre-existing comorbidities. We compared the results to those obtained from a group of 69 asymptomatic hospital workers who evidence of COVID exposure based on blood antibody testing. Allelic frequencies in both the severe and asymptomatic groups were compared to local and national healthy controls with adjustments made for age and sex. With the inclusion of hospital staff who had reported localised symptoms only (limited to loss of smell/taste, n=13) or systemic symptoms not requiring hospital treatment (n=16), we carried out ordinal logistic regression modelling to determine the relative influence of age, BMI, sex and the presence of specific HLA genes on symptomatology.

FindingsWe found a significant difference in the allelic frequency of HLA-DRB1*04:01 in the severe patient compared to the asymptomatic staff group (5.1% versus 16.7%, p=0.003 after adjustment for age and sex). There was a significantly lower frequency of the haplotype DQA1*01:01/DQB1*05:01/DRB1*01:01 in the asymptomatic group compared to the background population (p=0.007). Ordinal logistic regression modelling confirmed the significant influence of DRB1*04:01 on the clinical severity of COVID-19 observed in the cohorts.

InterpretationThis study provides evidence that patient age, sex, BMI and HLA genotype interact to determine the clinical outcome of COVID-19 infection.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSHLA genes are implicated in host resistance or susceptibility to a range of pathogens. No studies thus far have compared HLA allele frequencies in patients requiring hospital admission following COVID-19 exposure to a group of asymptomatic individuals.

Added value of this studyThe results indicate that the presence of HLA-DRB1*04:01 might confer protection from the development of respiratory failure following exposure to COVID. Individuals remaining asymptomatic following exposure to COVID are less likely to carry the haplotype DQA1*01:01/DQB1*05:01/DRB1*01:01 compared to the background population. This may indicate a host defence pathway not primarily dependent on an IgG response for clearance of infection. These findings conflict with larger genome wide association studies which compared HLA allelic frequencies of severely unwell patients with the background population.

Implications of all the available evidenceThe findings could have implications for targeted vaccination regimes as well as helping assess the impact of social restrictions on mortality rates in different populations.


title: High rates of diabetes and pre-diabetes in postpartum period in Indian GDM women

abstract:
AimTo investigate postpartum glucose intolerance in South Asian Indian GDM women within 1 year of delivery.

MethodsBetween 2001-2005, 220 women were treated for GDM at the Diabetes Unit, King Edward Memorial Hospital, Pune. GDM was diagnosed by 75g OGTT [WHO 1999 pregnancy criteria]. OGTT was repeated 3 months to 1 year postpartum. One hundred and nineteen non-GDM women were also studied.

ResultsOf 220 GDM women [30years, BMI 26.0kg/m2] 9 women continued to be diabetic after delivery and a further 111 attended OGTT within one year of delivery. Two had IFG, 16 IGT and 23 diabetes [WHO 1999], thus 50[42%] women were glucose intolerant. Of the non-GDM, 1 had IFG, 8 IGT and 3 diabetes (10% glucose intolerant). Those who were hyperglycemic at follow up had stronger family history of diabetes [64% vs. 58%], were shorter [154.6 vs. 156.5cm], had higher FPG concentrations during pregnancy [5.27 vs. 4.99 mmol/L], and higher BMI [26.3 vs.25.0kg/m2] and waist circumference [88.0 vs. 82.3cm] at follow up compared to normoglycemic women. Hyperglycemia was not associated with GAD antibody positivity (4 vs 3 in normoglycemic).

ConclusionWe describe one of the highest rates of postpartum hyperglycemia within a short time after delivery in young urban GDM women from India. Majority of risk factors for GDM were present from before pregnancy, and we propose that metabolic disturbances were also likely present. This has implications for peri-conceptional epigenetic programming of diabetes in the offspring. Pre-pregnancy screening and treatment of glucose intolerance and its risk factors in the high-risk populations could be an important measure for primordial prevention of diabetes.

Key messagesO_LIWe describe one of the highest rates of postpartum hyperglycemia in young urban GDM women from India within a short time after delivery.
C_LIO_LIOur results invite further research and policy discussion for screening and treatment of glucose intolerance before pregnancy in high-risk populations.
C_LI

category: endocrinology


title: Race/ethnicity differences in vitamin D levels and impact on cardiovascular disease, bone health, and oral health

abstract: Vitamin D and its biomarker 25(OH)D are known to vary by race/ethnicity with African Americans (AAs) having significantly lower levels than non-Hispanic whites (white Americans). However, AAs have better bone mineral density (BMD) and less arterial calcification, one marker of cardiovascular risk, than white Americans, with some studies showing higher vit. D levels harmful to AAs. This study analyzes NHANES data from 2011 to 2014, NHANES being a biennially published national survey of nearly 10,000 people, with interview, examination, and lab data components. The analyses, using count regression and linear regression models to avoid thresholding of variables, find that abdominal aortic calcification scores rise with 24(OH)D in white Americans, with no statistically significant effect in AAs; femoral BMD falls with 25(OH)D in both groups; osteoporotic fracture risks fall with 25(OH)D in white Americans; and periodontal attachment loss falls with rising 25(OH)D in both groups. Overall, higher 25(OH)D seems protective for oral and skeletal health in white Americans, protective for periodontal health in AAs, negative for their skeletal health, and negative for arterial calcification in white Americans, after controlling for the demographic factors of age and sex, the physiological elements of blood pressure and BMI, the biochemical variables of LDL and cholesterol levels, the socioeconomic indicators of income-to-poverty-level ratio and education levels, and the environmental influence of the season. As periodontitis is low on the disease hazard scale compared to arterial calcification and skeletal health, the results point to a lack of significant protection with rising OH(D) levels in AAs, even after their low base levels, and some harmful impact from those higher levels. That combination should trigger a closer look at the single population-wide vitamin D threshold of 30 to 50 ng/mL currently recommended in the US.


title: Analysis of the intensity of the COVID-19 epidemic in Berlin towards an universal prognostic relationship

abstract:
The present work is a continuation and development of research on prediction and analysis of the spread of the COVID-19 epidemic.

The proposed model adequately describes the development of the coronavirus epidemic with insufficient adherence to quarantine and social distancing. The transition from the absolute number of infected persons to their relative number per inhabitant of a settlement makes it possible to obtain universal calculation ratios.

In performing the calculations, the choice of the date of the beginning of the epidemic is of great importance. Recommendations are given on how to determine the date of the beginning of the epidemic based on the analysis of statistical data on the spread of the epidemic. The coefficient of virus transmission rate k included in the calculated prognostic relation depends on the population size and the type of virus strain in the settlement in question. A simple ratio for calculating this coefficient as a function of population size is proposed.

Control calculations performed using only a single empirical coefficient showed high accuracy. The calculated curves for Germany, Berlin, and its districts agree well with the corresponding statistical data. The correlation coefficients between the corresponding curves reach values of 0.93 to 0.97. The further development of the model should thus go in the direction of identifying causal links between the intensity of the epidemic and the main factors affecting this process. Some of these factors are related to the characteristics of the populations behaviour and the infrastructure of cities. The increase in the incidence in areas with a large percentage of the population rooted in Islamic countries is one of the main factors determining the development of the epidemic in Berlin. In order to explain and clarify this conclusion, it is necessary to make further assumptions about the possible emergence of a new strain of coronavirus in Berlin and in Germany and, accordingly, about the possibility of new epidemic waves. A preliminary ratio for predicting the spread of the epidemic under conditions of simultaneous existence of both strains of coronavirus is given.

Simplicity of the proposed prognostic method and high accuracy of the results allow to recommend it as an effective tool for operative analysis of various measures aimed to control the spread of COVID-19 epidemic including mass vaccination of population.

category: epidemiology


title: Age-seroprevalence curves for the multi-strain structure of influenza A virus

abstract: The relationship between age and seroprevalence provides the simplest and least expensive approach to computing the annual attack rate of an infectious disease. However, many pathogens circulate as multiple serologically distinct strains, with no single assay able to determine seropositivity or seronegativity to an entire clade or family of co-circulating pathogens. An approach is needed to describe population exposure to an antigenically variable group of pathogens without focusing on any particular strain or serotype in the group. In this study, we focus on the two-subtype multi-strain taxonomy of human influenza A virus. We describe a data set of 24,402 general-population serum samples collected in central and southern Vietnam between 2009 to 2015, and assayed for influenza HA1 antibodies to eleven different strains of human influenza A (both H3 and H1 subtypes). We find that a principal components decomposition of the data results in the first principal component PC1 being an appropriate surrogate for seroprevalence (or composite antibody titer) which can be further decomposed for H1 and H3 contribution to the serological profile. Using this approach, we are able to provide the first ELISA-based standardized measurements of serology to reconstruct population exposure history, which correlates well with known influenza epidemiology. Annual attack rates in Vietnam are estimated at 25.6% (95% CI: 24.1% - 27.1%) for H3 and 16.0% (95% CI: 14.7% - 17.3%) for H1, with some variation in location-specific attack rates. The remaining principal components act as descriptors of influenza history and sort the population by birth year. The novel contributions of this analysis are (1) the introduction of dimensionality reduction on human antibody profiles to construct an age-seroprevalence relationship for an antigenically variable pathogen, (2) an analysis of >24,000 individuals, using >260,000 serological data points in total, allowing us to construct age-seroprevalence relationships with the precision of modern big data studies, and (3) a description of long-term attack rates in a non-vaccinated setting showing the natural history of influenza A virus in a densely-populated tropical country.


title: Changes in COVID-19-related outcomes and the impacts of the potential risk factors over time: a follow-up analysis

abstract:
ImportanceCharacteristics of COVID-19 patients changed over the course of the pandemic. Understanding how risk factors changed over time can enhance the coordination of healthcare resources and protect the vulnerable.

ObjectiveTo investigate the overall trend of severe COVID-19-related outcomes over time since the start of the pandemic, and to evaluate whether the impacts of potential risk factors, such as race/ethnic groups, changed over time.

DesignThis retrospective cohort study included patients tested or treated for COVID-19 at Michigan Medicine (MM) from March 10, 2020, to September 2, 2020. According to the quarter in which they first tested positive, the COVID-19-positive cohort were stratified into three groups: Q1, March 1, 2020 - March 31, 2020; Q2, April 1, 2020 - June 30, 2020; Q3, July 1, 2020 - September 2, 2020.

SettingsLarge, academic medical center.

ParticipantsIndividuals tested or treated for COVID-19.

ExposureExamined potential risk factors included age, race/ethnicity, smoking status, alcohol consumption, comorbidities, body mass index (BMI), and residential-level socioeconomic characteristics.

Main Outcomes and MeasuresThe main outcomes included COVID-19-related hospitalization, intensive care unit (ICU) admission, and mortality, which were identified from the electronic health records from MM.

ResultsThe study cohort consisted of 53,853 patients tested or treated for COVID-19 at MM, with mean (SD) age of 44.8 (23.1), mean (SD) BMI of 29.1 (7.6), and 23,814 (44.2%) males. Among the 2,582 patients who tested positive, 719 (27.8%) were hospitalized, 377 (14.6%) were admitted to ICU, and 129 (5.0%) died. The overall COVID-positive hospitalization rate decreased from 41.5% in Q1 to 12.6% in Q3, and the overall ICU admission rate decreased from 24.5% to 5.3%. Black patients had significantly higher (unadjusted) overall hospitalization rate (265 [41.1%] vs 326 [23.2%]), ICU admission rate (139 [21.6%] vs 172 [12.2%]), and mortality rate (42 [6.5%] vs 56 [4.0%]) than White patients. Each quarter, the hospitalization rate remained higher for Black patients compared to White patients, but this difference was attenuated over time for the (unadjusted) odds ratios (Q1: OR=1.9, 95% CI [1.25, 2.90]; Q2: OR=1.42, 95% CI [1.02, 1.98]; Q3: OR=1.36, 95% CI [0.67, 2.65]). Similar decreasing patterns were observed for ICU admission and mortality. Adjusting for age, sex, socioeconomic status, and comorbidity score, the racial disparities in hospitalization between White and Black patients were not significant in each quarter of the year (Q1: OR=1.43, 95% CI [0.75, 2.71]; Q2: OR=1.25, 95% CI [0.79, 1.98]; Q3: OR=1.76 95% CI [0.81, 3.85]), in contrast to what was observed in the full cohort (OR=1.85, 95% CI [1.39, 2.47]). Additionally, significant association of hospitalization with living in densely populated area was identified in the first quarter (OR= 664, 95% CI [20.4, 21600]), but such association disappeared in the second and third quarters (Q2: OR= 1.72 95% CI [0.22, 13.5]; Q3: OR=3.69, 95% CI [0.103, 132]). Underlying liver diseases were positively associated with hospitalization in White patients (OR=1.60, 95% CI [1.01, 2.55], P=.046), but not in Black patients (OR=0.49, 95% CI [0.23, 1.06], P=.072, Pint=.013). Similar results were obtained for the effect of liver diseases on ICU admission in White and Black patients (White: OR=1.75, 95% CI [1.01, 3.05], P=.047; Black: OR=0.46, 95% CI [0.17, 1.26], P=.130, Pint=.030).

Conclusions and RelevanceThese findings suggest that the COVID-19-related hospitalization, ICU admission, and mortality rates were decreasing over the course of the pandemic. Although racial disparities persisted, the magnitude of the differences in hospitalization and ICU admission rates diminished over time.

Key PointsO_ST_ABSQuestionsC_ST_ABSHow did the overall hospitalization and intensive care unit (ICU) admission rates change over the course of the pandemic and how did they vary by race?

FindingsIn this cohort study of 2,582 patients testing positive for COVID-19, the unadjusted hospitalization rate decreased from 50.5% in Q1 (March 10, 2020, to March 31, 2020) to 17.9% in Q3 (July 1, 2020, to September 2, 2020) for Black patients, and from 23.2% in Q1 to 13.8% in Q3 for White patients. After adjusting for age, sex, sociodemographic factors, and comorbidity conditions, the odds ratios of hospitalization between White and Black patients were not significant in each quarter of the year 2020. No significant associations between ICU admission and race/ethnic groups were identified in each quarter or the entire three quarters.

MeaningThese findings suggests an appreciable decline in hospitalization and ICU admission rates among COVID-19 positive patients. The hospitalization and ICU admission rates across race/ethnic groups became closer over time.


title: Diagnostic performance and clinical implications of rapid SARS-CoV-2 antigen testing in Mexico using real-world nationwide COVID-19 registry data

abstract:
BACKGROUNDSARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico.

METHODSWe analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n=6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n=216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality.

RESULTSRapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and [≥]7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course.

CONCLUSIONSRapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.


title: Can Catastrophe Theory explain expansion and contagious of Covid-19?

abstract:
Since SARS-Cov-2 started spreading in China and turned into a pandemic disease called Covid-19, many articles about prediction with mathematical model have appeared in the literature. In addition to models in specialized journals, a significant amount of software was made available, presenting with dashboards spreading of the pandemic for each new. These models are solved by computer simulation of traditional exponential models as a representation of the growth of cases and deaths. Some more accurate models are based on existing variations of SIR model (Susceptible, Infected and Recovered). A third class of study is developed in spatial or probabilistic models as a way of forecasting the effect of Covid-19 around the world. Data on the number of positive cases in all countries, show that SARS-Cov-2 shows great resistance even after strategies of lockdown or social distancing. The purpose of this article is to show how the bifurcation theory, known as Catastrophe Theory, can help to understand why Covid-19 expansion rates change so much and even with low values for a longtime trigger contagion quickly and abruptly.

The Catastrophe Theory was conceived by the mathematician Rene Thom in the 60s with wide applications in works in the 70s. The outbreak of spruce budworm in Canada revealed a very interesting opportunity to test Catastrophe Theory whose explanation for the phenomenon was widely debated in the academic world. Inspired by the same mathematical approach to this phenomenon in Canada in the 1970s, we applied the Catastrophe Theory in the current Covid-19 pandemic. We observed that sudden outbreaks occur when the carrying capacity and the rate of expansion of the virus reach a region of bifurcation on the cusp surface. With actual Covid-19 data obtained from WHO, we fitted the dynamic model using the particle swarm technique and compared the results in the bifurcation plan with the Covid-19 outbreaks in different regions of the world. It is possible in many cases to observe the trajectory of the parameters between limit points in the bistable region and the consequent explosion of cases observed for each country assessed.


title: Survival analysis of all critically ill patients with COVID-19 admitted to the main hospital in Mogadishu, Somalia, 30 March to 12 June 2020: what interventions are proving effective?

abstract:
OBJECTIVESTo determine risk factors for death in patients with COVID-19 admitted to the main public sector hospital in Somalia and identify interventions contributing to improved clinical outcome in a low-resource and fragile setting.

SETTINGMain public sector tertiary hospital in Mogadishu, Somalia.

PARTICIPANTSAll 131 laboratory-confirmed COVID-19 patients admitted to the main public tertiary hospital in Somalia between 30 March and 12 June 2020.

MAIN OUTCOME MEASURESWe extracted demographic and clinical data from hospital records of all 131 COVID-19 patients admitted to hospital until their death or recovery. We used Kaplan-Meier statistics to estimate survival probabilities and the log-rank test to assess significant differences in survival between groups. We used the Cox proportional hazard model to estimate likelihood of death and assess the effect of risk factors on survival.

RESULTSOf the 131 patients, 52 (40%) died in the hospital and 79 (60%) survived to discharge. The factors independently associated with increased risk of in-hospital death were: age [≥] 60 years - survival probability on day 21 in patients < 60 years was 0.789 (95% confidence interval (CI): 0.658-0.874) compared with 0.339 (95% CI: 0.205-0.478) in patients [≥] 60 years; cardiovascular disease (survival probability 0.478 (95% CI: 0.332-0.610) in patients with cardiovascular disease compared with 0.719 (95% CI: 0.601-0.807) in patients without cardiovascular disease); and non-invasive ventilation on admission - patients who were not ventilated were significantly more likely to survive than those who were (P < 0.001).

CONCLUSIONOur study, which includes the largest cohort of COVID-19 patients admitted to a single hospital in a sub-Saharan African country, confirms that underlying conditions and age are associated with increased risk of in-hospital death in patients with COVID-19. Our results show the advantage of medical oxygen over non-invasive ventilation in the treatment of patients with severe COVID-19 symptoms.


title: Implementing Building-Level SARS-CoV-2 Wastewater Surveillance on a University Campus

abstract: The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long term care facilities, schools, and, of course, residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the universitys fall residential semester. In multiple cases, wastewater surveillance enabled identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with total resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.


title: Stages of COVID-19 pandemic and paths to herd immunity by vaccination: dynamical model comparing Austria, Luxembourg and Sweden

abstract:
BackgroundWorldwide more than 72 million people have been infected and 1.6 million died with SARS-CoV-2 by 15th December 2020. Non-pharmaceutical interventions which decrease social interaction have been implemented to reduce the spread of SARS-CoV-2 and to mitigate stress on healthcare systems and prevent deaths. The pandemic has been tackled with disparate strategies by distinct countries resulting in different epidemic dynamics. However, with vaccines now becoming available, the current urgent open question is how the interplay between vaccination strategies and social interaction will shape the pandemic in the next months.

MethodsTo address this question, we developed an extended Susceptible-Exposed-Infectious-Removed (SEIR) model including social interaction, undetected cases and the progression of patients trough hospitals, intensive care units (ICUs) and death. We calibrated our model to data of Luxem-bourg, Austria and Sweden, until 15th December 2020. We incorporated the effect of vaccination to investigate under which conditions herd immunity would be achievable in 2021.

ResultsThe model reveals that Sweden has the highest fraction of undetected cases, Luxembourg displays the highest fraction of infected population, and all three countries are far from herd immunity as of December 2020. The model quantifies the level of social interactions, and allows to assess the level which would keep Reff (t) below 1. In December 2020, this level is around 1/3 of what it was before the pandemic for all the three countries. The model allows to estimate the vaccination rate needed for herd immunity and shows that 2700 vaccinations/day are needed in Luxembourg to reach it by mid of April and 45,000 for Austria and Sweden. The model estimates that vaccinating the whole countrys population within 1 year could lead to herd immunity by July in Luxembourg and by August in Austria and Sweden.

ConclusionThe model allows to shed light on the dynamics of the epidemics in different waves and countries. Our results emphasize that vaccination will help considerably but not immediately and therefore social measures will remain important for several months before they can be fully alleviated.


title: Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity

abstract:
ObjectiveGoogle Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results.

MethodsWe extracted the relative GT search volume for keywords associated with COVID-19 symptoms, and evaluated their Granger-causality to weekly COVID-19 positivity in eight English-speaking countries and Japan. In addition, the impact of media coverage on keywords with significant Granger-causality was further evaluated using Japanese regional data.

ResultsOur Granger causality-based approach largely decreased (by up to approximately one-third) the number of keywords identified as having a significant temporal relationship with the COVID-19 trend when compared to those identified by the Pearson correlation-based approach. "Sense of smell" and "loss of smell" were the most reliable GT keywords across all the evaluated countries; however, when adjusted with their media coverage, these keyword trends did not Granger-cause the COVID-19 positivity trends (in Japan).

ConclusionOur results suggest that some of the search keywords reported as candidate predictive measures in earlier GT-based COVID-19 studies may potentially be unreliable; therefore, caution is necessary when interpreting published GT-based study results.


title: Divergences on expected pneumonia cases during the COVID-19 epidemic in Catalonia: A time-series analysis of primary care electronic health records covering about 6 million people.

abstract:
BackgroundPneumonia is one of the complications of COVID-19. Primary care electronic health records (EHR) have shown the utility as a surveillance system.

AimTo analyze the trends of pneumonia during two waves of COVID-19 pandemic in order to use it as a clinical surveillance system and an early indicator of severity.

MethodsTime series analysis of pneumonia cases, January 2014-December 2020. We collected pneumonia diagnoses from primary care EHR, covering >6 million people in Catalonia (Spain). We compared the trend of pneumonia in the season 2019-2020 with that in the previous years. We estimated the expected pneumonia cases with data from 2014 to 2018 using a time series regression adjusted by seasonality and influenza epidemics.

ResultsBetween 4 March and 5 May 2020, 11,704 excess pneumonia cases (95% CI: 9,909 to 13,498) were identified. We observed a second excess pneumonia period from 22 october to 15 november of 1,377 excess cases (95% CI: 665 to 2,089). In contrast, we observed two great periods with reductions of pneumonia cases in children, accounting for 131 days and 3,534 less pneumonia cases (95% CI: 1,005 to 6,064) from March to July; and 54 days and 1,960 less pneumonia cases (95% CI 917 to 3,002) from October to December.

ConclusionsDiagnoses of pneumonia from the EHR could be used as an early and low cost surveillance system to monitor the spread of COVID-19.


title: A MULTI-MINERAL INTERVENTION TO MODULATE COLONIC MUCOSAL PROTEIN PROFILE: Results from a 90-day trial in healthy human subjects

abstract:
The overall goal of this study was to determine if Aquamin(R), a calcium- and magnesium-rich natural product, would alter the expression of proteins involved in growth-regulation, differentiation and barrier formation in the colon. Thirty healthy human subjects were enrolled in a three-arm, 90-day interventional trial in which Aquamin(R) (provided daily to deliver 800-mg of calcium per day) was compared to calcium alone and placebo. Before and after the 90-day interventional period, colonic biopsies were obtained. Biopsies were evaluated by immunohistology for expression of Ki67 (a proliferation marker) and for CK20 and p21 (differentiation markers). Tandem mass tag-mass spectrometry-based detection was used to assess levels of multiple proteins. As compared to placebo or calcium, Aquamin(R) reduced the level of Ki67 expression (20%). Neither intervention altered CK20 expression, while a trend toward increased p21 was observed with calcium and Aquamin(R) (117% and 99% respectively). In the proteomic screen, Aquamin(R) treatment resulted in many more proteins being upregulated or downregulated (1.5 fold-change with [≤]2% false-discovery rate) than placebo. Included among the upregulated proteins were cytokeratins, cell-cell adhesion molecules and components of the basement membrane. Many of the downregulated proteins were those involved in proliferation and nucleic acid metabolism. Calcium alone also altered the expression of many of the same proteins but not to the same extent as Aquamin(R). We conclude that daily Aquamin(R) ingestion alters protein expression profile in the colon that could be beneficial to colonic health. These data warrant additional studies with a larger sample size to validate these findings.

Prevention RelevanceA multi-mineral approach reduced proliferation and induced differentiation in ex vivo settings and has been shown to decrease colon polyp incidence in mouse (polyp-prevention) studies. The findings from a 90-day trial in human subjects (presented here) demonstrated improved biomarker-modulation efficacy, warranting to conduct the polyp-prevention trial in at-risk human subjects.

category: gastroenterology


title: Bayesian forecasting for intravenous tobramycin dosing in adults with Cystic Fibrosis using one versus two serum concentrations in a dosing interval

abstract:
BackgroundIntravenous tobramycin requires therapeutic drug monitoring (TDM) to ensure safety and efficacy when used for prolonged treatment, as in infective exacerbations of Cystic Fibrosis (CF). The 24 hour area under the concentration time curve (AUC24) is widely used to guide dosing, however there remains variability in practice around methods for its estimation.

ObjectivesTo determine the potential for a sparse sampling strategy using a single post-infusion tobramycin concentration and Bayesian forecasting, to assess the AUC24 in routine practice.

MethodsAdults with CF receiving once daily tobramycin had paired concentrations measured 2 hours (c1) and 6 hours (c2) following end of infusion as routine monitoring. We estimated AUC24 exposures using Tucuxi, a Bayesian forecasting application incorporating a validated population pharmacokinetic model. We performed simulations to estimate AUC24 using the full dataset using c1 and c2, compared to estimates using depleted datasets (c1 or c2 only), with and without concentration data from earlier in the course. We assessed agreement between each simulation condition and the reference graphically, and numerically using median difference ({Delta}) AUC24, and (relative) root mean square error (rRMSE) as measures of bias and accuracy respectively.

Results55 patients contributed 512 concentrations from 95 tobramycin courses and 256 TDM episodes. Single concentration methods performed well, with median {Delta}AUC24 <2 mg.h.l-1 and rRMSE of <15% for sequential c1 and c2 conditions.

ConclusionsBayesian forecasting, using single post-infusion concentrations taken 2-6 hours following tobramycin administration can adequately estimate true exposure in this patient group and are suitable for routine TDM practice.

Key Points- In stable adult patients with Cystic fibrosis without significant renal impairment, Bayesian forecasting allows accurate estimation of tobramycin AUC24 using a single blood sample taken 2-6 hours post-infusion with acceptable accuracy, especially when including prior measured concentrations.
- A single sample approach with Bayesian forecasting is logistically less complicated than a two-sample approach, and could facilitate best-practice TDM in the outpatient setting.
- A more intensive sampling strategy with Bayesian forecasting using two tobramycin concentrations in a dosing interval should be considered in unstable patients, or where observed concentrations deviate significantly from model predictions.

category: pharmacology and therapeutics


title: Assessing psychosis risk using quantitative markers of disorganised speech

abstract: Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that end, several automated measures to quantify disorganisation of transcribed speech have been proposed. However, it remains unclear which measures are most predictive of psychosis-onset, how different measures relate to each other and what the best strategies are to elicit disorganised speech from participants. Here, we assessed the ability of twelve automated Natural Language Processing markers to differentiate transcribed speech excerpts from subjects at clinical high risk for psychosis (N=25), first episode psychosis patients (N=16) and healthy control subjects (N=13; N=54 in total). In-line with previous work, several of these measures showed significant differences between groups, including semantic coherence and speech graph connectivity. We also proposed two additional measures of repetition and whether speech was on topic, the latter of which exhibited significant group differences and outperformed the prior, related measure of tangentiality. Most measures examined were only weakly related to each other, suggesting they provide complementary information and that combining different measures could provide additional power to predict the onset of psychotic illness. Finally, we compared the ability of transcribed speech generated using different tasks to differentiate the groups. Speech generated from picture descriptions of the Thematic Apperception Test and a story re-telling task outperformed free speech, suggesting that choice of speech generation method may be an important consideration. Overall, quantitative speech markers represent a promising direction for future diagnostic applications for psychosis risk.

category: psychiatry and clinical psychology


title: Covid-19 Pandemic and Behavioural Response To Self-Medication Practice In Western Uganda

abstract:
BackgroundSelf-medication has become is a serious public health problem globally posing great risks, especially with the increasing number of cases of COVID-19 disease in Uganda. This is may be partly because of the absence of a recognized treatment for the disease, however, the prevalence and nature differ from country to country which may influence human behavioural responses.

AimThis study aimed to investigated the beharioural response of the community towards self- medication practices during this COVID-19 pandemic and lockdown.

MethodsA cross sectional household and online survey was conducted during the months of June-to- August. The study was conducted among adult between age 18 above in communities of western Uganda who consented to participate in the study. Study participants were selected using a convenience sampling technique and sampling was done by sending a structured online questionnaire via Google forms and a printed copies questionnaire made available to other participants that did not use the online questionnaire

ResultsThe percentage of respondents that know about self-medication is (97%) and those that practice self-medication are approximately (88%). 97% of respondents have heard about self-medication either through health workers, media, family members, friends and/or school while 3% said they have not heard about self-medication. The percentage of respondents who practiced self- medication during COVID-19 pandemic is 57% while those that did not is 43%. There is statistically difference in the number of those that practice self-medication and those that do not p < 0.005 at 95% confidence interval. Also there was a statistically significant decrease in the number of respondents that practice self-medication during COVID-19 pandemic lockdown compare to the practice before the pandemic lockdown p < 0.05 at 95% confidence interval.

ConclusionOur investigation showed adequate knowledge of self-medication and high level of self- medication practice with a decrease in self-medication practices during the COVID-19 pandemic lockdown compared to the practice before the lockdown.

category: public and global health


title: Knowledge, attitude and practice toward COVID-19 among healthcare workers in public health facilities, Eastern Ethiopia

abstract:
On 13 March 2020, Ethiopia reported the first confirmed case of COVID-19 in Addis Ababa. COVID-19 is likely to overwhelm an already fragile health-care delivery system and reduce the availability of services for endemic health concerns such as malaria and diarrheal diseases.

Cross sectional study was conducted on heath care workers in three public health facilities in Somali region to assess knowledge, attitude and practice towards COVID-19. T-test and ANOVA were used to analyze the relationship between the dependent, and independent variables. Spearmans correlation was used to assess the relationship between mean knowledge and attitude scores.

A vast majority of the participants were male (n = 293, 67.5%), with a mean age of 27.6 (SD: 5.3) years. The mean knowledge score was 13.7 (SD: 2.6) and the mean attitude score 10.5 (SD: 4.1). Only 45.2 % (n = 196) of the participants had a good attitude toward COVID-19. There was a negative correlation between knowledge scores, attitude scores (r=-0.295, P<0.001) and practice (r=-0.298, P<0.001).

The overall level of knowledge was good. However, the attitude and practice were relatively low. We recommend strategies for enhancing the capacity of healthcare workers to develop positive attitude and practice.


title: Do school closures reduce community transmission of COVID-19? A systematic review of observational studies

abstract:
BackgroundSchool closures are associated with significant negative consequences and exacerbate inequalities. They were implemented worldwide to control SARS-CoV-2 in the first half of 2020, but their effectiveness, and the effects of lifting them, remain uncertain. This review summarises observational evidence of the effect of school closures and school reopenings on SARS-CoV-2 community transmission.

MethodsThe study protocol was registered on Prospero (ID:CRD42020213699). On 07 January 2021 we searched PubMed, Web of Science, Scopus, CINAHL, the WHO Global COVID-19 Research Database, ERIC, the British Education Index, the Australian Education Index, and Google. We included observational studies with quantitative estimates of the effect of school closures/reopenings on SARS-CoV-2 community transmission. We excluded prospective modelling studies and intra-school transmission studies. We performed a narrative synthesis due to data heterogeneity. We used the ROBINS-I tool to assess risk of bias.

FindingsWe identified 7,474 articles, of which 40 were included, with data from 150 countries. Of these 32 studies assessed school closures, and 11 examined reopenings. There was substantial heterogeneity between school closure studies, with half of the studies at lower risk of bias reporting reduced community transmission by up to 60%, and half reporting null findings. The majority (n=3 out of 4) of school reopening studies at lower risk of bias reported no associated increases in transmission.

ConclusionsSchool closure studies were at risk of confounding and collinearity from other non-pharmacological interventions implemented around the same time as school closures, and the effectiveness of closures remains uncertain. School reopenings, in areas of low transmission and with appropriate mitigation measures, were generally not accompanied by increasing community transmission. With such varied evidence on effectiveness, and the harmful effects, policymakers should take a measured approach before implementing school closures; and should look to reopen schools in times of low transmission, with appropriate mitigation measures.


title: Do school closures and school reopenings affect community transmission of COVID-19? A systematic review of observational studies


title: COVID-19 Vaccine Acceptance Among Health Care Workers in the United States

abstract:
BackgroundAcceptance of the COVID-19 vaccine will play a major role in combating the pandemic. Healthcare workers (HCWs) are amongst the first group to receive vaccination, so it is important to consider their attitudes about COVID-19 vaccination to better address barriers to widespread vaccination acceptance.

MethodsWe conducted a cross sectional study to assess the attitude of HCWs toward COVID-19 vaccination. Data was collected between October 7th and November 9th, 2020. We received 4080 responses out of which 3479 were complete responses and were included in final analysis.

Results36% of respondents were willing to take the vaccine as soon as it became available while 56% were not sure or would wait to review more data. Vaccine acceptance increased with increasing age, education, and income level. Lower acceptance was noted in females (31%), Black (10%), Latinx (30%) and Conservative/Republican (21%) HCWs, and those working in a rural setting (26%). Direct medical care providers had higher vaccine acceptance (49%). Safety (69%), effectiveness (69%) and speed of development/approval (74%) were noted as the most common concerns regarding COVID-19 vaccination in our survey.

ConclusionImmediate acceptance of a COVID-19 vaccine is low, with the majority of HCWs choosing to wait to review more data before deciding on personal vaccination. Overall attitudes toward vaccination were positive but specific concerns regarding COVID-19 vaccine are prevalent. Differences in vaccine acceptance were noted between individual and group characteristics which should be addressed to avoid exacerbating health inequities.


title: Spatial-temporal relationship between population mobility and COVID-19 outbreaks in South Carolina: A time series forecasting analysis

abstract:
BackgroundPopulation mobility is closely associated with coronavirus 2019 (COVID-19) transmission, and it could be used as a proximal indicator to predict future outbreaks, which could inform proactive non-pharmaceutical interventions for disease control. South Carolina (SC) is one of the states which reopened early and then suffered from a sharp increase of COVID-19.

ObjectiveTo examine the spatial-temporal relationship between population mobility and COVID-19 outbreaks and use population mobility to predict daily new cases at both state- and county- levels in SC.

MethodsThis longitudinal study used disease surveillance data and Twitter-based population mobility data from March 6 to November 11, 2020 in SC and its top five counties with the largest number of cumulative confirmed cases. Daily new case was calculated by subtracting the cumulative confirmed cases of previous day from the total cases. Population mobility was assessed using the number of users with travel distance larger than 0.5 mile which was calculated based on their geotagged twitters. Poisson count time series model was employed to carry out the research goals.

ResultsPopulation mobility was positively associated with state-level daily COVID-19 incidence and those of the top five counties (i.e., Charleston, Greenville, Horry, Spartanburg, Richland). At the state-level, final model with time window within the last 7-day had the smallest prediction error, and the prediction accuracy was as high as 98.7%, 90.9%, and 81.6% for the next 3-, 7-, 14- days, respectively. Among Charleston, Greenville, Horry, Spartanburg, and Richland counties, the best predictive models were established based on their observations in the last 9-, 14-, 28-, 20-, and 9- days, respectively. The 14-day prediction accuracy ranged from 60.3% to 74.5%.

ConclusionsPopulation mobility was positively associated with COVID-19 incidences at both state- and county- levels in SC. Using Twitter-based mobility data could provide acceptable prediction for COVID-19 daily new cases. Population mobility measured via social media platform could inform proactive measures and resource relocations to curb disease outbreaks and their negative influences.


title: Burden of predominant psychological reactions among the healthcare workers and general during COVID-19 pandemic phase: a systematic review and meta-analysis

abstract:
AimPresent systematic review and meta-analysis examined the burden of psychological reactions predominantly anxiety, depression, stress and insomnia during novel COVID-19 pandemic phase among the frontline healthcare, non-frontline healthcare and general.

MethodologyPubMed, EMBASE and SCOPUS were searched for studies between Jan 1, 2020 to May 25, 2020. Brief protocol of the systematic review was registered with the PROSPERO database, (CRD42020186229).Any study that reported the burden of at least one of psychological reactions including anxiety or depression or stress or insomnia was eligible. Heterogeneity was assessed using I2 statistic and results were synthesized using random effect meta-analysis.

ResultsOut of 52eligible studies, 43 reported anxiety, 43 reported depression, 20 reported stress and 11 reported insomnia. Overall prevalence for anxiety, depression, stress and insomnia were 26.6%, 26.2%,26.2% and 34.4% respectively. Anxiety and depression were found highest among the COVID-19 patients (43.3% and 51.75 respectively). Apart from COVID-19 patients, prevalence of anxiety, depression, stress and insomnia were found highest among the frontline healthcare (27.2%, 32.1%,55.6% and 34.4% respectively) as compared to general healthcare workers (26.9%, 15.7%, 7.0% and 34.0% respectively) and general population (25.9%, 25.9%,25.4% and 29.4% respectively).

ConclusionAnxiety and depression were found highest among the COVID-19 patients. Apart from COVID-19 patients, the anxiety, depression, stress and insomnia were more prevalent among frontline healthcare workers compared to general. Such increased prevalence is prompting towards the global mental health emergency. Therefore a call of urgent attention and pan-region effective mental-health intervention are required to mitigate these psychological reactions.


title: Brazilian model estimation for SARS-CoV-2 peak contagion (BMESPC): first and second wave

abstract: With newer data for SARS-CoV-2 and entering the second wave of contagion required the improvement of the forecasting model, structuring its model to forecast the peak of the first and second contagion wave in Brazil. The Brazilian model estimation for SARS-CoV-2 peak contagion (BMESPC) was structured, capable of estimating the peak of contagion for SARS-CoV-2 in the first and second waves, as the main objective of this work. Using the BMESPC model, it was possible to estimate, with a certain reliability degree, the peak of contagion for the first and second waves in Brazil, with one day difference from the real to the forecast. While at the state level, the calculated confidence interval proved to be more accurate. In this way, it is possible to use BMESPC to forecast the peak of contagion for several regions, provided that the necessary structure and calibration are respected.


title: Brazilian model estimation for SARS-CoV-2 peak contagion (BMESPC)


title: Expectancy-Value-Cost motivational theory to explore final year medical students' research intentions and past research experience: a multicentre cross-sectional questionnaire study

abstract:
ObjectivesConducting research during medical school is a commonly described way to strengthen the physician-scientists workforce. The aim of this study is to compare the strength of association of Expectancy, Value and Cost regarding a research activity with future research intentions, and to explore differences between students with or without research experience during medical school.

Design, setting and participantsAn online questionnaire was sent to final-year medical students - who had already chosen their specialty - in three French-speaking Belgian universities with non-mandatory research programmes. Exploratory factor analysis (EFA) and multiple regression analysis were conducted.

Main measuresResearch intention (outcome measure) was assessed using a 3-item scale. The motivational beliefs were assessed using a 10-item scale adapted from a validated scale based on the Expectancy-Value- Cost theory. Responses were recorded on a 6-point Likert scale.

ResultsParticipation rate was 28% (n=237). EFA revealed 4 factors with high internal consistency. 21.5% of students had positive research intentions (score 5 or above). Our model explained 82.8% of research intention variance (p < 0.001), of which three motivational beliefs had statistically significant coefficients: i) Value given to a research activity ({beta} = 0.72, p < 0.001); ii) perceived Cost of a research activity ({beta} = -0.11, p < 0.01); iii) Expectancy of success ({beta} = 0.10, p < 0.05). Students with a positive research experience or students without research experience but who had strongly considered achieving one were 11.5 times more likely (95% CI, 5.0 - 26.2) to have positive research intentions at the end of medical school than other students.

ConclusionsValue given to a research activity is the key factor regarding students motivation to undertake research. Our study confirms the positive relationship between non-mandatory research and future research intentions, although some students without a research experience showed high motivation as well.

category: medical education


title: Deep learning driven quantification of interstitial fibrosis in kidney biopsies

abstract:
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA estimation using computational techniques can reduce this variability and provide quantitative assessment by capturing the pathologic features. Using trichrome-stained whole slide images (WSIs) processed from human renal biopsies, we developed a deep learning (DL) framework that captured finer pathological structures at high resolution and overall context at the WSI-level to predict IFTA grade. WSIs (n=67) were obtained from The Ohio State University Wexner Medical Center (OSUWMC). Five nephropathologists independently reviewed them and provided fibrosis scores that were converted to IFTA grades: <=10% (None or minimal), 11-25% (Mild), 26-50% (Moderate), and >50% (Severe). The model was developed by associating the WSIs with the IFTA grade determined by majority voting (reference estimate). Model performance was evaluated on WSIs (n=28) obtained from the Kidney Precision Medicine Project (KPMP). There was good agreement on the IFTA grading between the pathologists and the reference estimate (Kappa=0.622{+/-}0.071). The accuracy of the DL model was 71.8{+/-}5.3% on OSUWMC and 65.0{+/-}4.2% on KPMP datasets, respectively. Identification of salient image regions by combining microscopic and WSI-level pathological features yielded visual representations that were consistent with the pathologist-based IFTA grading. Our approach to analyzing microscopic- and WSI-level changes in renal biopsies attempts to mimic the pathologist and provides a regional and contextual estimation of IFTA. Such methods can assist clinicopathologic diagnosis.

Translational statementPathologists rely on interstitial fibrosis and tubular atrophy (IFTA) to indicate chronicity in kidney biopsies and provide a prognostic indicator of renal survival. Although guidelines for evaluation of IFTA exist, there is variability in IFTA estimation among pathologists. In this work, digitized kidney biopsies were independently reviewed by five nephropathologists and majority voting on their ratings was used to determine the IFTA grade. Using this information, a deep learning model was developed that captured microscopic and holistic features on the digitized biopsies and accurately predicted the IFTA grade. The study illustrates that deep learning can be utilized effectively to perform IFTA grading, thus enhancing conventional clinicopathologic diagnosis.

category: nephrology


title: Humoral and cell-mediated response in colostrum after exposure to severe acute respiratory syndrome coronavirus 2

abstract:
BackgroundColostrum provides an immune sharing between a mother and her infant. The transfer in colostrum of antibodies against SARS-CoV-2 and the elicited cytokines may provide crucial protection to the infant. There is limited literature on the immune response to SARS-CoV-2 present in colostrum.

ObjectiveTo evaluate the presence of antibodies specific to SARS-CoV-2 and the associated cytokines in colostrum from women who tested positive for the virus.

Study DesignBetween March and September 2020 we obtained bilateral colostrum samples collected on spot cards within 48 hours of delivery from 15 new mothers who had previously tested positive for SARS-CoV-2. Five of these 15 COVID-19 positive women also provided bilateral liquid colostrum within 1-2 days of providing the spot card samples. Archived bilateral colostrum samples collected from 8 women during 2011-2013 were used as pre-COVID-19 controls. All samples were tested for reactivity to the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein using an ELISA that measures SARS-CoV-2 RBD-specific IgA, IgG, and IgM, and for concentrations of 10 inflammatory cytokines (IFN{gamma}, TNF, IL-1{beta}, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-13) using a multiplex electrochemiluminescent sandwich assay.

ResultsBilateral colostrum samples from 73%, 73% and 33% of the 15 COVID-19 mothers exhibited IgA, IgG, and IgM reactivity to RBD respectively. Colostrum samples from two of the 8 pre-pandemic controls showed IgA and IgG reactivity to RBD. Additionally, COVID-19 mothers had significantly higher levels of 9 of the 10 inflammatory markers (all except IFN{gamma}) as compared to the pre-COVID-19 controls. Comparable results were obtained with both the spot card-eluates and liquid samples.

ConclusionsA strong humoral immune response is present in the colostrum of women who were infected with SARS-CoV-2 before delivering. High levels of 9 inflammatory markers were also present in the colostrum. The evolution and duration of the antibody response, as well as dynamics of the cytokine response, remain to be determined. Our results also indicate that future large-scale studies can be conducted with milk easily collected on paper spot cards.

category: obstetrics and gynecology


title: Do improved biomass cookstove interventions improve indoor air quality and blood pressure? A systematic review and meta-analysis.

abstract:
BackgroundHousehold air pollution (HAP) kills 4 million annually, with access to clean cooking being a challenge for 37% of the worlds population. Whilst there have been advancements in improved biomass cookstove (ICS) technologies, reviews on the impact of these ICS on HAP are now more than three years old.

ObjectivesThis review and meta-analysis examines the most recent evidence on the impact of ICS on HAP and blood pressure (BP).

MethodsA literature search was conducted using scientific literature databases and grey literature. Studies were included if they were published between January 2012 and June 2020, reported impact of ICS interventions in non-pregnant adults in low/middle-income countries, and reported post-intervention results along with baseline of traditional cookstoves. Outcomes included 24- or 48-hour averages of kitchen area fine particulate matter (PM2.5), carbon monoxide (CO), mean systolic BP (SBP) and mean diastolic BP (DBP). Meta-analyses estimated weighted mean differences between baseline and post-intervention values for all outcome measures.

ResultsNine studies were included; eight contributed estimates for HAP and three for BP. Interventions lead to significant reductions in PM2.5 (-0.28 mg/m3, 95% CI: -0.46, -0.10), CO (-6.59ppm, 95%CI: - 10.73, -2.46) and SBP (-2.82mmHg, 95% CI: -5.53, -0.11); and a non-significant reduction in DBP (-0.80 mmHg, 95%CI: -2.33, 0.73), when compared to baseline of traditional cookstoves. Except for DBP, greatest reductions in all outcomes came from standard combustion ICS with a chimney, compared to ICS without a chimney and advanced combustion ICS. WHO air quality targets were met by post-intervention values for CO but not for PM2.5.

ConclusionOur review suggests that ICS with a chimney results in the greatest reductions in HAP and BP. Further research on qualitative impact of such ICS on end-users is required to understand feasibility of adoption at scale.

category: occupational and environmental health


title: Saving Lives with Pre-Financed Rules-Based Disaster Aid: Evidence from Mexico

abstract: Developing economies are not disproportionately exposed to natural disasters, but they experience significantly more deaths. Exploiting a discontinuity in the eligibility rules to Mexicos pre-financed indexed disaster fund (Fonden), I show that accelerated reconstruction of public infrastructure can fully reduce postdisaster excess mortality in the short-run and up to 75 percent two years after. I also find that Fondens impact is concentrated in areas with medical infrastructure and among conditions responsive to basic medical interventions. These findings suggest that Fonden operates by restoring access to health services after a disaster. Annual benefits from Fonden amount to 197 thousand life-years saved. (JEL: G22, H12, H84, Q54, I15, O18.)

category: health economics


title: Nested pool testing strategy for the reliable identification of individuals infected with SARS-CoV-2

abstract:
The progress of the SARS-CoV-2 pandemic requires the design of cost-effective testing programs at large scale. To this end, pooling multiple samples can provide a solution. Defining a cost-effective strategy requires the establishment of an efficient deconvolution and re-testing procedure that eventually allows the identifcation of the carrier. Based on Dorfmans algorithm, we developed an adaptive nested strategy for which we have, for a given prevalence, simple analytic expressions of the optimal number of samples in the starting pool, of the number of partitioning steps (stages) in the optimal path, of the pool sizes in each of these stages and of the expected average number of tests needed to identify the infected individuals. In this paper we analyze the strategy in detail focusing on its practical implementation when there are restrictions that prevent the use of the optimum. More specifically, we analyze how to proceed when the infection prevalence is poorly known a priori or when the optimal requires starting with pool sizes that are too large for the reliable detection of an infected sample. The sensitivity of the RT-qPCR assay, the gold standard RNA detection method, is a major concern in the case of SARS-CoV-2: it is estimated that half of the infected individuals give false negative results. Recently, droplet digital PCR (ddPCR) was shown to be 10 - 100 times more sensitive than RT-qPCR, making this technology suitable for pool testing. ddPCR has the added value of providing the direct quantification of the RNA content at the end of the test. In the paper we show how this feature can be used for verification purposes. The analyses and strategies presented here should be useful to those considering the adoption of a pooling approach for RNA detection, particularly, for the identification of individuals infected with SARS-CoV-2.

Author summaryThe progress of the SARS-CoV-2 pandemic requires the design of cost-effective testing programs at large scale. Running tests on pooled samples can provide a solution if the tests sensitivity is high enough. In the case of SARS-CoV-2, the current gold standard test, RT-qPCR, has shown some limitations that only allow the use of pools with relatively few samples. In this regard, Droplet digital PCR (ddPCR) has been shown to be 10 - 100 times more sensitive than RT-qPCR, making it suitable for test pooling. In this paper we describe a nested pool testing method in which the properties that make it optimal are simple analytic functions of the infection prevalence. We discuss how to proceed in practical implementations of the strategy, particularly when there are constraints that prevent the use of the optimal. We also show how its nested nature can be combined with the direct RNA quantification that the ddPCR test provides to identify the presence of unviable samples in the pools and for self-consistency tests. The studies of this paper should be useful for those considering the adoption of test pooling for RNA detection.


title: Implementation Science Protocol for a participatory, theory-informed implementation research programme in the context of health system strengthening in sub-Saharan Africa (ASSET-ImplementER)

abstract:
BackgroundASSET (Health System Strengthening in Sub-Saharan Africa) is a health system strengthening (HSS) programme that aims to develop and evaluate effective and sustainable solutions that support high-quality care that involve eight work packages across four sub-Saharan African countries. Here we present the protocol for the implementation science (IS) theme within ASSET that aims to (1) understand what HSS interventions work, for whom and how; and (2) how implementation science methodologies can be adapted to improve the design and evaluation of HSS interventions within resource-poor contexts.

MethodsO_ST_ABSPre-implementation phaseC_ST_ABSThe IS theme, jointly with ASSET work-packages, applies IS determinant frameworks to identify factors that influence the effectiveness of delivering evidence-informed care. Determinants are used to select a set of HSS interventions for further evaluation, where work packages also theorise selective mechanisms to achieve the expected outcomes.

Piloting phase and rolling implementation phaseWork-packages pilot the HSS interventions. An iterative process then begins involving evaluation, refection and adaptation. Throughout this phase, IS determinant frameworks are applied to monitor and identify barriers and enablers to implementation in a series of workshops, surveys and interviews. Selective mechanisms of action are also investigated. In a final workshop, ASSET teams come together, to reflect and explore the utility of the selected IS methods and provide suggestions for future use.

Structured templates are used to organise and analyse common and heterogeneous patterns across work-packages. Qualitative data are analysed using thematic analysis and quantitative data is analysed using means and proportions.

ConclusionsWe use a novel combination of implementation science methods at a programmatic level to facilitate comparisons of determinants and mechanisms that influence the effectiveness of HSS interventions in achieving implementation outcomes across different contexts. The study will also contribute conceptual development and clarification at the underdeveloped interface of implementation science, HSS and global health.

Strengths and limitations of this studyO_LIThe purpose of this protocol paper is to describe the methodology for the implementation science theme within ASSET (ASSET-ImplementER).
C_LIO_LIThe overall aim of the ASSET-ImplementER theme is to advance our understanding of how to design and evaluate HSS interventions using a systems level approach informed by implementation science, across different health systems and contexts.
C_LIO_LIThis is one of the first large-scale implementation research programmes for health system strengthening in Sub-Saharan Africa that spanning three care platforms (primary care for the integrated treatment of chronic conditions in adults, maternal and newborn care, surgical care), involving eight work packages in four sub-Saharan African countries that aims to apply robust, implementation science and other theory-informed approaches to understand what works for whom and how. Equally as important, we aim to improve implementation science methodologies to design and evaluate HSS interventions within LMIC settings.
C_LIO_LIAlthough our programme is theory-informed through the use of ToC workshops and
C_LIO_LIimplementation science determinant frameworks, we have not used implementation science theories or other middle-range theories to guide the design and evaluate of ASSET as a programme. This is a pragmatic approach given many of the work-packages teams were unfamiliar with implementation science methods at the time of ASSET set-up.
C_LIO_LITo mitigate the effects of this approach to our research, we work with the different work packages throughout the different phases of research, to theorise and conceptualise how the selected determinants interact with mechanisms introduced by the selected HSS on implementation outcomes.
C_LIO_LIAlthough there are limitations to our approach, we expect to begin advance our understanding of what HSS work for whom, and how. It is also hoped that we will start to address the issues in understanding the complexity surrounding how to effectively strengthen health systems in resource-poor contexts within LMICs.
C_LI


title: T cell Homeostatic Imbalance in Placentae from Women Infected with HIV in the absence of Vertical Transmission.

abstract:
BackgroundImplementation of universal antiretroviral therapy (ART) has significantly lowered vertical transmission rates but has also increased numbers of HIV-exposed uninfected children (HEU), who remain vulnerable to morbidities. Here, we investigated whether T cell alterations in the placenta contribute to altered immune status in HEU.

MethodsWe analyzed T cells from term placentae decidua and villous tissue and paired cord blood from pregnant women with HIV (PWH) who initiated ART late in pregnancy (n=21) with pregnant women not living with HIV (PWNH) (n=9).

ResultsPlacentae from PWH showed inverted CD4:CD8 ratios and higher proportions of tissue resident CD8+ T cells in villous tissue relative to control placentae. CD8+ T cells in the fetal capillaries, which were of fetal origin, positively correlated with maternal plasma viraemia prior to ART initiation, implying that imbalanced T cells persisted throughout pregnancy. Additionally, the expanded memory differentiation of CD8+ T cells was confined to the fetal placental compartment and cord blood but was not observed in the maternal decidua.

ConclusionsT cell homeostatic imbalance in the blood circulation of PWH is reflected in the placenta. The placenta may be a causal link between HIV-induced maternal immune changes during gestation and altered immunity in newborn infants in the absence of vertical transmission.

Lay SummaryThe effective prevention of HIV transmission during pregnancy with the rollout of antiretroviral therapy (ART) has resulted in increased numbers of HIV-exposed uninfected children (HEU). These children are vulnerable to infections and health problems and have distorted cellular immune systems at birth. We investigated whether these immune alterations originate in the placenta, as this fetal organ maintains life during pregnancy. After collecting placentae at term from pregnant women living with HIV (PWH), who started ART in the third trimester (n=21) and from pregnant women not living with HIV (PWNH) (n=9), we isolated T cells from dissected placental tissue and matching cord blood. Placentae from PWH showed inverted CD4:CD8 ratios in the placenta and cord blood with higher numbers of CD8+ T cells in the fetal part of the placenta. These CD8+ T cells mirrored events in the blood circulation of the mother and the altered balance of T cell immunity in the PWH was reflected in the placenta. Accordingly, the placenta may be a pivotal link between HIV-induced maternal immune changes and altered immunity in newborn infants in the absence of vertical transmission.

category: hiv aids


title: Evaluation of serological lateral flow assays for severe acute respiratory syndrome coronavirus-2

abstract:
BackgroundCOVID-19 has resulted in significant morbidity and mortality worldwide. Lateral flow assays can detect anti-Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) antibodies to monitor transmission. However, standardized evaluation of their accuracy and tools to aid in interpreting results are needed.

MethodsWe evaluated 20 IgG and IgM assays selected from available tests in April 2020. We evaluated the assays performance using 56 pre-pandemic negative and 56 SARS-CoV-2-positive plasma samples, collected 10-40 days after symptom onset, confirmed by a molecular test and analyzed by an ultra-sensitive immunoassay. Finally, we developed a user-friendly web app to extrapolate the positive predictive values based on their accuracy and local prevalence.

ResultsCombined IgG+IgM sensitivities ranged from 33.9% to 94.6%, while combined specificities ranged from 92.6% to 100%. The highest sensitivities were detected in Lumiquick for IgG (98.2%), BioHit for both IgM (96.4%), and combined IgG+IgM sensitivity (94.6%). Furthermore, 11 LFAs and 8 LFAs showed perfect specificity for IgG and IgM, respectively, with 15 LFAs showing perfect combined IgG+IgM specificity. Lumiquick had the lowest estimated limit-of-detection (LOD) (0.1 g/mL), followed by a similar LOD of 1.5 g/mL for CareHealth, Cellex, KHB, and Vivachek.

ConclusionWe provide a public resource of the accuracy of select lateral flow assays with potential for home testing. The cost-effectiveness, scalable manufacturing process, and suitability for self-testing makes LFAs an attractive option for monitoring disease prevalence and assessing vaccine responsiveness. Our web tool provides an easy-to-use interface to demonstrate the impact of prevalence and test accuracy on the positive predictive values.


title: The SARS-CoV-2 antibody landscape is lower in magnitude for structural proteins, diversified for accessory proteins and stable long-term in children

abstract:
BackgroundChildren are less clinically affected by SARS-CoV-2 infection than adults with the majority of cases being mild or asymptomatic and the differences in infection outcomes are poorly understood. The kinetics, magnitude and landscape of the antibody response may impact the clinical severity and serological diagnosis of COVID-19. Thus, a comprehensive investigation of the antibody landscape in children and adults is needed.

MethodsWe tested 254 plasma from 122 children with symptomatic and asymptomatic SARS-CoV-2 infections in Hong Kong up to 206 days post symptom onset, including 146 longitudinal samples from 58 children. Adult COVID-19 patients and pre-pandemic controls were included for comparison. We assessed antibodies to a 14-wide panel of SARS-CoV-2 structural and accessory proteins by Luciferase Immunoprecipitation System (LIPS).

FindingsChildren have lower levels of Spike and Nucleocapsid antibodies than adults, and their cumulative humoral response is more expanded to accessory proteins (NSP1 and Open Reading Frames (ORFs)). Sensitive serology using the three N, ORF3b, ORF8 antibodies can discriminate COVID-19 in children. Principal component analysis revealed distinct serological signatures in children and the highest contribution to variance were responses to non-structural proteins ORF3b, NSP1, ORF7a and ORF8. Longitudinal sampling revealed maintenance or increase of antibodies for at least 6 months, except for ORF7b antibodies which showed decline. It was interesting to note that children have higher antibody responses towards known IFN antagonists: ORF3b, ORF6 and ORF7a. The diversified SARS-CoV-2 antibody response in children may be an important factor in driving control of SARS-CoV-2 infection.


title: Autoimmune anti-DNA antibodies predict disease severity in COVID-19 patients

abstract:
COVID-19 can lead to severe disease and death, however the mechanisms of pathogenesis in these patients remain poorly understood. High levels of autoimmune antibodies have been observed frequently in COVID-19 patients but their specific contribution to disease severity and clinical manifestations remain unknown.

We performed a retrospective study of 115 COVID-19 hospitalized patients with different degrees of severity to analyze the generation of autoimmune antibodies to common antigens: a lysate of erythrocytes, the lipid phosphatidylserine (PS) and DNA.

High levels of IgG autoantibodies against erythrocyte lysates were observed in a large percentage (up to 41%) of patients. Anti-DNA antibodies determined upon hospital admission correlated strongly with later development of severe disease, showing a positive predictive value of 89.5% and accounting for 22% of total severe cases. Statistical analysis identified strong correlations between anti-DNA antibodies and markers of cell injury, coagulation, neutrophil levels and erythrocyte size.

Anti-DNA autoantibodies may play an important role in the pathogenesis of COVID-19 and could be developed as a predictive biomarker for disease severity and specific clinical manifestations.


title: SARS-CoV-2 induces a durable and antigen specific humoral immunity after asymptomatic to mild COVID-19 infection

abstract: Current SARS-CoV-2 serological assays generate discrepant results, and the longitudinal characteristics of antibodies targeting various antigens after asymptomatic to mild COVID-19 are yet to be established. This longitudinal cohort study including 1965 healthcare workers, of which 381 participants exhibited antibodies against the SARS-CoV-2 spike antigen at study inclusion, reveal that these antibodies remain detectable in most participants, 96%, at least four months post infection, despite having had no or mild symptoms. Virus neutralization capacity was confirmed by microneutralization assay in 91% of study participants at least four months post infection. Contrary to antibodies targeting the spike protein, antibodies against the nucleocapsid protein were only detected in 80% of previously anti-nucleocapsid IgG positive healthcare workers. Both anti-spike and anti-nucleocapsid IgG levels were significantly higher in previously hospitalized COVID-19 patients four months post infection than in healthcare workers four months post infection (p=2*10-23 and 2*10-13 respectively). Although the magnitude of humoral response was associated with disease severity, our findings support a durable and functional humoral response after SARS-CoV-2 infection even after no or mild symptoms. We further demonstrate differences in antibody kinetics depending on the antigen, arguing against the use of the nucleocapsid protein as target antigen in population-based SARS-CoV-2 serological surveys.