Drivers of epidemic dynamics in real time from daily digital COVID-19 measurements.

Understanding the drivers of respiratory pathogen spread is challenging, particularly in a timely manner during an ongoing epidemic. In this work, we present insights that we obtained using daily data from the National Health Service COVID-19 app for England and Wales and that we shared with health authorities in almost real time. Our indicator of the reproduction number R(t) was available days earlier than other estimates, with an innovative capability to decompose R(t) into contact rates and probabilities of infection. When Omicron arrived, the main epidemic driver switched from contacts to transmissibility. We separated contacts and transmissions by day of exposure and setting and found pronounced variability over days of the week and during Christmas holidays and events. For example, during the Euro football tournament in 2021, days with England matches showed sharp spikes in exposures and transmissibility. Digital contact-tracing technologies can help control epidemics not only by directly preventing transmissions but also by enabling rapid analysis at scale and with unprecedented resolution.

Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic.

Background: The COVID-19 pandemic both relied and placed significant burdens on the experts involved from research and public health sectors. The sustained high pressure of a pandemic on responders, such as healthcare workers, can lead to lasting psychological impacts including acute stress disorder, post-traumatic stress disorder, burnout, and moral injury, which can impact individual wellbeing and productivity. Methods: As members of the infectious disease modelling community, we convened a reflective workshop to understand the professional and personal impacts of response work on our community and to propose recommendations for future epidemic responses. The attendees represented a range of career stages, institutions, and disciplines. This piece was collectively produced by those present at the session based on our collective experiences. Results: Key issues we identified at the workshop were lack of institutional support, insecure contracts, unequal credit and recognition, and mental health impacts. Our recommendations include rewarding impactful work, fostering academia-public health collaboration, decreasing dependence on key individuals by developing teams, increasing transparency in decision-making, and implementing sustainable work practices. Conclusions: Despite limitations in representation, this workshop provided valuable insights into the UK COVID-19 modelling experience and guidance for future public health crises. Recognising and addressing the issues highlighted is crucial, in our view, for ensuring the effectiveness of epidemic response work in the future.

Integrated transcriptome and cell phenotype analysis suggest involvement of PARP1 cleavage, Hippo/Wnt, TGF-ß and MAPK signaling pathways in ovarian cancer cells response to cannabis and PARP1 inhibitor treatment.

Introduction: Cannabis sativa is utilized mainly for palliative care worldwide. Ovarian cancer (OC) is a lethal gynecologic cancer. A particular cannabis extract fraction ('F7') and the Poly(ADP-Ribose) Polymerase 1 (PARP1) inhibitor niraparib act synergistically to promote OC cell apoptosis. Here we identified genetic pathways that are altered by the synergistic treatment in OC cell lines Caov3 and OVCAR3. Materials and methods: Gene expression profiles were determined by RNA sequencing and quantitative PCR. Microscopy was used to determine actin arrangement, a scratch assay to determine cell migration and flow cytometry to determine apoptosis, cell cycle and aldehyde dehydrogenase (ALDH) activity. Western blotting was used to determine protein levels. Results: Gene expression results suggested variations in gene expression between the two cell lines examined. Multiple genetic pathways, including Hippo/Wnt, TGF-ß/Activin and MAPK were enriched with genes differentially expressed by niraparib and/or F7 treatments in both cell lines. Niraparib + F7 treatment led to cell cycle arrest and endoplasmic reticulum (ER) stress, inhibited cell migration, reduced the % of ALDH positive cells in the population and enhanced PARP1 cleavage. Conclusion: The synergistic effect of the niraparib + F7 may result from the treatment affecting multiple genetic pathways involving cell death and reducing mesenchymal characteristics.

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.

How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps1,2 recorded measurements of proximity3 and duration between nearby smartphones. Contacts-individuals exposed to confirmed cases-were notified according to public health policies such as the 2 m, 15 min guideline4,5, despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4-1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4-28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks.

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

During an infectious disease outbreak, tracing who infected whom allows public health scientists to see how a pathogen is spreading and to establish effective control measures. Traditionally, this involves identifying the individuals an infected person comes into contact with and monitoring whether they also become unwell. However, this information is not always available and can be inaccurate. One alternative is to track the genetic data of pathogens as they spread. Over time, pathogens accumulate mutations in their genes that can be used to distinguish them from one another. Genetically similar pathogens are more likely to have spread during the same outbreak, while genetically dissimilar pathogens may have come from different outbreaks. However, there are limitations to this approach. For example, some pathogens accumulate genetic mutations very slowly and may not change enough during an outbreak to be distinguishable from one another. Additionally, some pathogens can spread rapidly, leaving less time for mutations to occur between transmission events. To overcome these challenges, Torres Ortiz et al. developed a more sensitive approach to pathogen genetic testing that took advantage of the multiple pathogen populations that often coexist in an infected patient. Rather than tracking only the most dominant genetic version of the pathogen, this method also looked at the less dominant ones. Torres Ortiz et al. performed genome sequencing of SARS-CoV-2 (the virus that causes COVID-19) samples from 451 healthcare workers, patients, and patient contacts at participating London hospitals. Analysis showed that it was possible to detect multiple genetic populations of the virus within individual patients. These subpopulations were often more similar in patients that had been in contact with one another than in those that had not. Tracking the genetic data of all viral populations enabled Torres Ortiz et al. to trace transmission more accurately than if only the dominant population was used. More accurate genetic tracing could help public health scientists better track pathogen transmission and control outbreaks. This may be especially beneficial in hospital settings where outbreaks can be smaller, and it is important to understand if transmission is occurring within the hospital or if the pathogen is imported from the community. Further research will help scientists understand how pathogen population genetics evolve during outbreaks and may improve the detection of subpopulations present at very low frequencies.

Environmental temperature influences ophidiomycosis progression and survival in experimentally challenged prairie rattlesnakes (Crotalus viridis).

Ophidiomycosis is a prevalent and intermittently pervasive disease of snakes globally caused by the opportunistic fungal pathogen, Ophidiomyces ophidiicola. Host response has yet to be fully explored, including the role of temperature in disease progression and hematologic changes. This study enrolled twelve adult prairie rattlesnakes (Crotalus viridis) in an experimental challenge with O. ophidiicola at two temperatures, 26°C (n = 6) and 20°C (n = 6). Each temperature cohort included four inoculated and two control snakes. Assessments involving physical exams, lesion swabbing, and hematology were performed weekly. Differences were observed between inoculated and control snakes in survival, behavior, clinical signs, ultraviolet (UV) fluorescence, hematologic response, and histologic lesions. All inoculated snakes held at 20°C were euthanized prior to study end date due to severity of clinical signs while only one inoculated animal in the 26°C trial met this outcome. In both groups, qPCR positive detection preceded clinical signs with regards to days post inoculation (dpi). However, the earliest appearance of gross lesions occurred later in the 20°C snakes (20 dpi) than the 26°C snakes (13 dpi). Relative leukocytosis was observed in all inoculated snakes and driven by heterophilia in the 20°C snakes, and azurophilia in the 26°C group. Histologically, 20°C snakes had more severe lesions, a lack of appropriate inflammatory response, and unencumbered fungal proliferation and invasion. In contrast, 26°C snakes had marked granulomatous inflammation with encapsulation of fungi and less invasion and dissemination. The results of this study identified that O. ophidiicola-infected rattlesnakes exposed to lower temperatures have decreased survival and more robust hematologic change, though minimal and ineffective inflammatory response at site of infection. Ophidiomycosis is a complex disease with host, pathogen, and environmental factors influencing disease presentation, progression, and ultimately, survival. This study highlighted the importance of temperature as an element impacting the host response to O. ophidiicola.

Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year.

The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app's epidemiological impacts varied according to changing social and epidemic characteristics throughout the app's first year. We describe the interaction and complementarity of manual and digital contact tracing approaches. Results of our statistical analyses of anonymised, aggregated app data include that app users who were recently notified were more likely to test positive than app users who were not recently notified, by a factor that varied considerably over time. We estimate that the app's contact tracing function alone averted about 1 million cases (sensitivity analysis 450,000-1,400,000) during its first year, corresponding to 44,000 hospital cases (SA 20,000-60,000) and 9,600 deaths (SA 4600-13,000).

Distinguishing imported cases from locally acquired cases within a geographically limited genomic sample of an infectious disease.

MOTIVATION: The ability to distinguish imported cases from locally acquired cases has important consequences for the selection of public health control strategies. Genomic data can be useful for this, for example, using a phylogeographic analysis in which genomic data from multiple locations are compared to determine likely migration events between locations. However, these methods typically require good samples of genomes from all locations, which is rarely available. RESULTS: Here, we propose an alternative approach that only uses genomic data from a location of interest. By comparing each new case with previous cases from the same location, we are able to detect imported cases, as they have a different genealogical distribution than that of locally acquired cases. We show that, when variations in the size of the local population are accounted for, our method has good sensitivity and excellent specificity for the detection of imports. We applied our method to data simulated under the structured coalescent model and demonstrate relatively good performance even when the local population has the same size as the external population. Finally, we applied our method to several recent genomic datasets from both bacterial and viral pathogens, and show that it can, in a matter of seconds or minutes, deliver important insights on the number of imports to a geographically limited sample of a pathogen population. AVAILABILITY AND IMPLEMENTATION: The R package DetectImports is freely available from https://github.com/xavierdidelot/DetectImports. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Phytocannabinoid Compositions from Cannabis Act Synergistically with PARP1 Inhibitor against Ovarian Cancer Cells In Vitro and Affect the Wnt Signaling Pathway.

Ovarian cancer (OC) is the single most lethal gynecologic malignancy. Cannabis sativa is used to treat various medical conditions, and is cytotoxic to a variety of cancer types. We sought to examine the effectiveness of different combinations of cannabis compounds against OC. Cytotoxic activity was determined by XTT assay on HTB75 and HTB161 cell lines. Apoptosis was determined by flow cytometry. Gene expression was determined by quantitative PCR and protein localization by confocal microscopy. The two most active fractions, F5 and F7, from a high Δ9-tetrahydrocannabinol (THC) cannabis strain extract, and their standard mix (SM), showed cytotoxic activity against OC cells and induced cell apoptosis. The most effective phytocannabinoid combination was THC+cannabichromene (CBC)+cannabigerol (CBG). These fractions acted in synergy with niraparib, a PARP inhibitor, and were ~50-fold more cytotoxic to OC cells than to normal keratinocytes. The F7 and/or niraparib treatments altered Wnt pathway-related gene expression, epithelial-mesenchymal transition (EMT) phenotype and ß-catenin cellular localization. The niraparib+F7 treatment was also effective on an OC patient's cells. Given the fact that combinations of cannabis compounds and niraparib act in synergy and alter the Wnt signaling pathway, these phytocannabinoids should be examined as effective OC treatments in further pre-clinical studies and clinical trials.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks.

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches to reconstruct outbreaks exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is stable among repeated serial samples from the same host, is transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Incorporating estimands into clinical trial statistical analysis plans.

BACKGROUND: International Council for Harmonisation (ICH) E9 Statistical Principles for Clinical Trials was developed as a consensus guidance document to encourage worldwide harmonization of the principles of statistical methodology in clinical trials. Addendum E9 (R1) clarified and extended ICH E9 with a focus on estimands and sensitivity analyses. Since the release of E9 (R1), clinical trial protocols have included estimands, but there is variation in how they are presented. Statistical analysis plans (SAPs) are increasingly becoming publicly available (e.g. posting on ClinicalTrials.gov) and present an opportunity to link estimands with planned analyses to present the alignment of trial objectives, design, conduct, and analysis. METHODS: A table format was used to create a template for inclusion in SAPs that satisfies ICH E9 (R1) guidance to align statistical analysis to the estimand. The template provides a consistent structure for presentation of estimands and the associated analysis, and is applicable to a wide range of trial designs. We illustrate use of the template with a hypothetical clinical trial in HIV-1. RESULTS: The estimand-to-analysis table template starts with the study objective describing the clinical question of interest as written in the trial protocol. The remainder of the table describes each attribute of the estimand (treatment, target population, variable, intercurrent events, and population-level summary) in the left column (ESTIMAND), while the right column describes how each attribute will be handled using the data collected in the clinical trial (ANALYSIS). The template was applied to a hypothetical, early-phase single-arm trial, modeled after a pediatric trial in HIV, where the objective was to determine the safety of a new antiretroviral drug as part of a combination antiretroviral treatment regimen in the pediatric population. Three intercurrent events were illustrated in the table: death, premature treatment discontinuation before 24 weeks, and pregnancy. An estimand-to-analysis table from a grant application that addresses the primary objective of a placebo-controlled randomized trial is also presented to demonstrate an alternative usage. CONCLUSION: We found the template to be useful in study design, providing a snapshot of the objective, target population, potential intercurrent events, analysis plan, and considerations for missing data in one place and facilitating discussion among stakeholders. The proposed standardized presentation of estimand attributes and analysis considerations in SAPs will provide guidance to SAP authors and consistency across studies to facilitate reviews.

Pharmacogenetics of interaction between depot medroxyprogesterone acetate and efavirenz, rifampicin, and isoniazid during treatment of HIV and tuberculosis.

OBJECTIVE: In AIDS Clinical Trials Group study A5338, concomitant rifampicin, isoniazid, and efavirenz was associated with more rapid plasma medroxyprogesterone acetate (MPA) clearance compared to historical controls without tuberculosis or HIV therapy. We characterized the pharmacogenetics of this interaction. METHODS: In A5338, women receiving efavirenz-based HIV therapy and rifampicin plus isoniazid for tuberculosis underwent pharmacokinetic evaluations over 12 weeks following a 150-mg intramuscular injection of depot MPA. Data were interpreted with nonlinear mixed-effects modelling. Associations between individual pharmacokinetic parameters and polymorphisms relevant to rifampicin, isoniazid, efavirenz, and MPA were assessed. RESULTS: Of 62 A5338 participants in four African countries, 44 were evaluable for pharmacokinetic associations, with 17 CYP2B6 normal, 21 intermediate, and 6 poor metabolizers, and 5 NAT2 rapid, 20 intermediate, and 19 slow acetylators. There were no associations between either CYP2B6 or NAT2 genotype and MPA Cmin at week 12, apparent clearance, Cmax, area under the concentration-time curve (AUC) or half-life, or unexplained interindividual variability in clearance, and uptake rate constant or mean transit time of the slow-release fraction (P > 0.05 for each). In exploratory analyses, none of 28 polymorphisms in 14 genes were consistently associated with MPA pharmacokinetic parameters, and none withstood correction for multiple testing. CONCLUSIONS: Study A5338 suggested that more frequent depot MPA dosing may be appropriate for women receiving rifampicin, isoniazid, and efavirenz. The present results suggest that knowledge of CYP2B6 metabolizer or NAT2 acetylator status does not inform individualized DMPA dosing in this setting.

Safety and Pharmacokinetics of Double-Dose Lopinavir/Ritonavir + Rifampin Versus Lopinavir/Ritonavir + Daily Rifabutin for Treatment of Human Immunodeficiency Virus-Tuberculosis Coinfection.

BACKGROUND: Protease inhibitor-based antiretroviral therapy may be used in resource-limited settings in persons with human immunodeficiency virus and tuberculosis (HIV-TB). Data on safety, pharmacokinetics/pharmacodynamics (PK/PD), and HIV-TB outcomes for lopinavir/ritonavir (LPV/r) used with rifampin (RIF) or rifabutin (RBT) are limited. METHODS: We randomized adults with HIV-TB from July 2013 to February 2016 to arm A, LPV/r 400 mg/100 mg twice daily + RBT 150 mg/day; arm B, LPV/r 800 mg/200 mg twice daily + RIF 600 mg/day; or arm C, LPV/r 400 mg/100 mg twice daily + raltegravir (RAL) 400 mg twice daily + RBT 150 mg/day. All received two nucleoside reverse transcriptase inhibitors and other TB drugs. PK visits occurred on day 12 ± 2. Within-arm HIV-TB outcomes were summarized using proportions and 95% CIs; PK were compared using Wilcoxon tests. RESULTS: Among 71 participants, 52% were women; 72% Black; 46% Hispanic; median age, 37 years; median CD4+ count, 130 cells/mm3; median HIV-1 RNA, 4.6 log10 copies/mL; 46% had confirmed TB. LPV concentrations were similar across arms. Pooled LPV AUC12 (157 203 hours × ng/mL) and Ctrough (9876 ng/mL) were similar to historical controls; RBT AUC24 (7374 hours × ng/mL) and Ctrough (208 ng/mL) were higher, although 3 participants in arm C had RBT Cmax <250 ng/mL. Proportions with week 48 HIV-1 RNA <400 copies/mL were 58%, 67%, and 61%, respectively, in arms A, B, and C. CONCLUSIONS: Double-dose LPV/r+RIF and LPV/r+RBT 150mg/day had acceptable safety, PK and TB outcomes; HIV suppression was suboptimal but unrelated to PK. Faster RBT clearance and low Cmax in 3 participants on RBT+RAL requires further study.

OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing.

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.

A Semimechanistic Pharmacokinetic Model for Depot Medroxyprogesterone Acetate and Drug-Drug Interactions With Antiretroviral and Antituberculosis Treatment.

Depot medroxyprogesterone acetate is an injectable hormonal contraceptive, widely used by women of childbearing potential living with HIV and/or tuberculosis. As medroxyprogesterone acetate is a cytochrome P450 (CYP3A4) substrate, drug-drug interactions (DDIs) with antiretroviral or antituberculosis treatment may lead to subtherapeutic medroxyprogesterone acetate concentrations (< 0.1 ng/mL), resulting in contraception failure, when depot medroxyprogesterone is dosed at 12-week intervals. A pooled population pharmacokinetic analysis with 744 plasma medroxyprogesterone acetate concentrations from 138 women treated with depot medroxyprogesterone and antiretroviral/antituberculosis treatment across three clinical trials was performed. Monte Carlo simulations were performed to predict the percentage of participants with subtherapeutic medroxyprogesterone acetate concentrations and to derive alternative dosing strategies. Medroxyprogesterone acetate clearance increased by 24.7% with efavirenz coadministration. Efavirenz plus antituberculosis treatment (rifampicin + isoniazid) increased clearance by 52.4%. Conversely, lopinavir/ritonavir and nelfinavir decreased clearance (28.7% and 15.8%, respectively), but lopinavir/ritonavir also accelerated medroxyprogesterone acetate's appearance into the systemic circulation, thus shortening the terminal half-life. A higher risk of subtherapeutic medroxyprogesterone acetate concentrations at Week 12 was predicted on a typical 60-kg woman on efavirenz (4.99%) and efavirenz with antituberculosis treatment (6.08%) when compared with medroxyprogesterone acetate alone (2.91%). This risk increased in women with higher body weight. Simulations show that re-dosing every 8 to 10 weeks circumvents the risk of subtherapeutic medroxyprogesterone acetate exposure associated with these DDIs. Dosing depot medroxyprogesterone every 8 to 10 weeks should eliminate the risk of subtherapeutic medroxyprogesterone acetate exposure caused by coadministered efavirenz and/or antituberculosis treatment, thus reducing the risk of contraceptive failure.

The epidemiological impact of the NHS COVID-19 app.

The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.

Genomic Epidemiology Analysis of Infectious Disease Outbreaks Using TransPhylo.

Comparing the pathogen genomes from several cases of an infectious disease has the potential to help us understand and control outbreaks. Many methods exist to reconstruct a phylogeny from such genomes, which represents how the genomes are related to one another. However, such a phylogeny is not directly informative about transmission events between individuals. TransPhylo is a software tool implemented as an R package designed to bridge the gap between pathogen phylogenies and transmission trees. TransPhylo is based on a combined model of transmission between hosts and pathogen evolution within each host. It can simulate both phylogenies and transmission trees jointly under this combined model. TransPhylo can also reconstruct a transmission tree based on a dated phylogeny, by exploring the space of transmission trees compatible with the phylogeny. A transmission tree can be represented as a coloring of a phylogeny where each color represents a different host of the pathogen, and TransPhylo provides convenient ways to plot these colorings and explore the results. This article presents the basic protocols that can be used to make the most of TransPhylo. © 2021 The Authors. Basic Protocol 1: First steps with TransPhylo Basic Protocol 2: Simulation of outbreak data Basic Protocol 3: Inference of transmission Basic Protocol 4: Exploring the results of inference.

Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis.

Background: In May 2020, the UK National Health Service (NHS) Test and Trace programme was launched in England in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included version 1 of the NHS contact tracing app. The aim of the study was to make a preliminary assessment of the epidemiological impact of the Test and Trace programme using publicly available data. Methods: We used COVID-19 daily case data from Public Health England to infer incidence of new infections and estimate the reproduction number (R) for each of the 150 Upper-Tier Local Authorities (UTLAs) in England and nationally, before and after the launch of the Test and Trace programme on the Isle of Wight. We used Bayesian and maximum-likelihood methods to estimate R and compared the Isle of Wight with other UTLAs using a synthetic control method. Findings: We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch of the Test and Trace programme. The Isle of Wight had a marked reduction in R, from 1·3 before the Test and Trace programme to 0·5 after by one of our measures, and went from having the third highest R before the Test and Trace programme, to the twelfth lowest afterwards compared with other UTLAs. Interpretation: Our results show that the epidemic on the Isle of Wight was controlled quickly and effectively after the launch of Test and Trace. Our findings highlight the need for further research to determine the causes of the reduction in the spread of the disease, as these could be translated into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination for COVID-19 becomes available. Funding: Li Ka Shing Foundation and UK Economic and Social Research Council.

Using mixed methods to understand women's parenting practices related to their child's outdoor play and physical activity among families living in diverse neighborhood environments.

A convergent parallel mixed methods design was used to understand parenting practices for outdoor play, their influence on adolescent's physical activity and outdoor play and the role of the neighborhood and child's sex. Adolescents (n = 263) and their parents completed questionnaires and wore accelerometers. Parents (n = 30) participated in in-depth interviews. Parenting practices were examined by neighborhood disadvantage and child's sex in quantitative (Chi-square and T-tests) and qualitative (comparative thematic analysis) samples. Multi-level linear mixed models examined the associations between parenting practices and two adolescent outcomes: physical activity and outdoor play. Parents in high disadvantage neighborhoods and of female adolescents imposed more restrictions on outdoor play. Restrictive parenting practices were negatively associated with outdoor play, but not physical activity. Policy and environment change that improves neighborhood conditions may be necessary to reduce parents' fear and lessen restrictions on outdoor play.