Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England.

The SARS-CoV-2 lineage B.1.1.7, designated variant of concern (VOC) 202012/01 by Public Health England1, was first identified in the UK in late summer to early autumn 20202. Whole-genome SARS-CoV-2 sequence data collected from community-based diagnostic testing for COVID-19 show an extremely rapid expansion of the B.1.1.7 lineage during autumn 2020, suggesting that it has a selective advantage. Here we show that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that B.1.1.7 has higher transmissibility than non-VOC lineages, even if it has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with cases of B.1.1.7 including a larger share of under 20-year-olds than non-VOC cases. We estimated time-varying reproduction numbers for B.1.1.7 and co-circulating lineages using SGTF and genomic data. The best-supported models did not indicate a substantial difference in VOC transmissibility among different age groups, but all analyses agreed that B.1.1.7 has a substantial transmission advantage over other lineages, with a 50% to 100% higher reproduction number.

The relative contributions of infectious and mitotic spread to HTLV-1 persistence.

Human T-lymphotropic virus type-1 (HTLV-1) persists within hosts via infectious spread (de novo infection) and mitotic spread (infected cell proliferation), creating a population structure of multiple clones (infected cell populations with identical genomic proviral integration sites). The relative contributions of infectious and mitotic spread to HTLV-1 persistence are unknown, and will determine the efficacy of different approaches to treatment. The prevailing view is that infectious spread is negligible in HTLV-1 persistence beyond early infection. However, in light of recent high-throughput data on the abundance of HTLV-1 clones, and recent estimates of HTLV-1 clonal diversity that are substantially higher than previously thought (typically between 104 and 105 HTLV-1+ T cell clones in the body of an asymptomatic carrier or patient with HTLV-1-associated myelopathy/tropical spastic paraparesis), ongoing infectious spread during chronic infection remains possible. We estimate the ratio of infectious to mitotic spread using a hybrid model of deterministic and stochastic processes, fitted to previously published HTLV-1 clonal diversity estimates. We investigate the robustness of our estimates using three alternative estimators. We find that, contrary to previous belief, infectious spread persists during chronic infection, even after HTLV-1 proviral load has reached its set point, and we estimate that between 100 and 200 new HTLV-1 clones are created and killed every day. We find broad agreement between all estimators. The risk of HTLV-1-associated malignancy and inflammatory disease is strongly correlated with proviral load, which in turn is correlated with the number of HTLV-1-infected clones, which are created by de novo infection. Our results therefore imply that suppression of de novo infection may reduce the risk of malignant transformation.

The impact of a COVID-19 lockdown on work productivity under good and poor compliance.

BACKGROUND: In response to the COVID-19 pandemic, governments across the globe have imposed strict social distancing measures. Public compliance to such measures is essential for their success, yet the economic consequences of compliance are unknown. This is the first study to analyze the effects of good compliance compared with poor compliance to a COVID-19 suppression strategy (i.e. lockdown) on work productivity. METHODS: We estimate the differences in work productivity comparing a scenario of good compliance with one of poor compliance to the UK government COVID-19 suppression strategy. We use projections of the impact of the UK suppression strategy on mortality and morbidity from an individual-based epidemiological model combined with an economic model representative of the labour force in Wales and England. RESULTS: We find that productivity effects of good compliance significantly exceed those of poor compliance and increase with the duration of the lockdown. After 3 months of the lockdown, work productivity in good compliance is £398.58 million higher compared with that of poor compliance; 75% of the differences is explained by productivity effects due to morbidity and non-health reasons and 25% attributed to avoided losses due to pre-mature mortality. CONCLUSION: Good compliance to social distancing measures exceeds positive economic effects, in addition to health benefits. This is an important finding for current economic and health policy. It highlights the importance to set clear guidelines for the public, to build trust and support for the rules and if necessary, to enforce good compliance to social distancing measures.

Correction: Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource.

[This corrects the article DOI: 10.2196/28253.].

Quantifying Online News Media Coverage of the COVID-19 Pandemic: Text Mining Study and Resource.

BACKGROUND: Before the advent of an effective vaccine, nonpharmaceutical interventions, such as mask-wearing, social distancing, and lockdowns, have been the primary measures to combat the COVID-19 pandemic. Such measures are highly effective when there is high population-wide adherence, which requires information on current risks posed by the pandemic alongside a clear exposition of the rules and guidelines in place. OBJECTIVE: Here we analyzed online news media coverage of COVID-19. We quantified the total volume of COVID-19 articles, their sentiment polarization, and leading subtopics to act as a reference to inform future communication strategies. METHODS: We collected 26 million news articles from the front pages of 172 major online news sources in 11 countries (available online at SciRide). Using topic detection, we identified COVID-19-related content to quantify the proportion of total coverage the pandemic received in 2020. The sentiment analysis tool Vader was employed to stratify the emotional polarity of COVID-19 reporting. Further topic detection and sentiment analysis was performed on COVID-19 coverage to reveal the leading themes in pandemic reporting and their respective emotional polarizations. RESULTS: We found that COVID-19 coverage accounted for approximately 25.3% of all front-page online news articles between January and October 2020. Sentiment analysis of English-language sources revealed that overall COVID-19 coverage was not exclusively negatively polarized, suggesting wide heterogeneous reporting of the pandemic. Within this heterogenous coverage, 16% of COVID-19 news articles (or 4% of all English-language articles) can be classified as highly negatively polarized, citing issues such as death, fear, or crisis. CONCLUSIONS: The goal of COVID-19 public health communication is to increase understanding of distancing rules and to maximize the impact of governmental policy. The extent to which the quantity and quality of information from different communication channels (eg, social media, government pages, and news) influence public understanding of public health measures remains to be established. Here we conclude that a quarter of all reporting in 2020 covered COVID-19, which is indicative of information overload. In this capacity, our data and analysis form a quantitative basis for informing health communication strategies along traditional news media channels to minimize the risks of COVID-19 while vaccination is rolled out.

Response to COVID-19 in South Korea and implications for lifting stringent interventions.

BACKGROUND: After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their "test, trace, isolate" strategy. However, it is important to understand the epidemiological peculiarities of South Korea's outbreak and characterise their response before attempting to emulate these measures elsewhere. METHODS: We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. RESULTS: We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent "lockdown" measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. CONCLUSIONS: Whilst early adoption of testing and contact tracing is likely to be important for South Korea's successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.

The Long-Term Safety, Public Health Impact, and Cost-Effectiveness of Routine Vaccination with a Recombinant, Live-Attenuated Dengue Vaccine (Dengvaxia): A Model Comparison Study.

BACKGROUND: Large Phase III trials across Asia and Latin America have recently demonstrated the efficacy of a recombinant, live-attenuated dengue vaccine (Dengvaxia) over the first 25 mo following vaccination. Subsequent data collected in the longer-term follow-up phase, however, have raised concerns about a potential increase in hospitalization risk of subsequent dengue infections, in particular among young, dengue-naïve vaccinees. We here report predictions from eight independent modelling groups on the long-term safety, public health impact, and cost-effectiveness of routine vaccination with Dengvaxia in a range of transmission settings, as characterised by seroprevalence levels among 9-y-olds (SP9). These predictions were conducted for the World Health Organization to inform their recommendations on optimal use of this vaccine. METHODS AND FINDINGS: The models adopted, with small variations, a parsimonious vaccine mode of action that was able to reproduce quantitative features of the observed trial data. The adopted mode of action assumed that vaccination, similarly to natural infection, induces transient, heterologous protection and, further, establishes a long-lasting immunogenic memory, which determines disease severity of subsequent infections. The default vaccination policy considered was routine vaccination of 9-y-old children in a three-dose schedule at 80% coverage. The outcomes examined were the impact of vaccination on infections, symptomatic dengue, hospitalised dengue, deaths, and cost-effectiveness over a 30-y postvaccination period. Case definitions were chosen in accordance with the Phase III trials. All models predicted that in settings with moderate to high dengue endemicity (SP9 ≥ 50%), the default vaccination policy would reduce the burden of dengue disease for the population by 6%-25% (all simulations: -3%-34%) and in high-transmission settings (SP9 ≥ 70%) by 13%-25% (all simulations: 10%- 34%). These endemicity levels are representative of the participating sites in both Phase III trials. In contrast, in settings with low transmission intensity (SP9 ≤ 30%), the models predicted that vaccination could lead to a substantial increase in hospitalisation because of dengue. Modelling reduced vaccine coverage or the addition of catch-up campaigns showed that the impact of vaccination scaled approximately linearly with the number of people vaccinated. In assessing the optimal age of vaccination, we found that targeting older children could increase the net benefit of vaccination in settings with moderate transmission intensity (SP9 = 50%). Overall, vaccination was predicted to be potentially cost-effective in most endemic settings if priced competitively. The results are based on the assumption that the vaccine acts similarly to natural infection. This assumption is consistent with the available trial results but cannot be directly validated in the absence of additional data. Furthermore, uncertainties remain regarding the level of protection provided against disease versus infection and the rate at which vaccine-induced protection declines. CONCLUSIONS: Dengvaxia has the potential to reduce the burden of dengue disease in areas of moderate to high dengue endemicity. However, the potential risks of vaccination in areas with limited exposure to dengue as well as the local costs and benefits of routine vaccination are important considerations for the inclusion of Dengvaxia into existing immunisation programmes. These results were important inputs into WHO global policy for use of this licensed dengue vaccine.

Rapid dissemination of human T-lymphotropic virus type 1 during primary infection in transplant recipients.

BACKGROUND: Human T-lymphotropic virus type 1 (HTLV-1) infects an estimated 10 million persons globally with transmission resulting in lifelong infection. Disease, linked to high proviral load, occurs in a minority. In established infection HTLV-1 replicates through infectious spread and clonal expansion of infected lymphocytes. Little is known about acute HTLV-1 infection. The kinetics of early HTLV-1 infection, following transplantation-acquired infection in three recipients from one HTLV-1 infected donor, is reported. The recipients were treated with two HTLV-1 enzyme inhibitors 3 weeks post exposure following the detection of HTLV-1 provirus at low level in each recipient. HTLV-1 infection was serially monitored by serology, quantification of proviral load and HTLV-1 2LTR DNA circles and by HTLV-1 unique integration site analysis. RESULTS: HTLV-1 antibodies were first detected 16-39 days post-transplantation. HTLV-1 provirus was detected by PCR on day 16-23 and increased by 2-3 log by day 38-45 with a peak proviral doubling time of 1.4 days, after which steady state was reached. The rapid proviral load expansion was associated with high frequency of HTLV-1 2LTR DNA circles. The number of HTLV-1 unique integration sites was high compared with established HTLV-1 infection. Clonal expansion of infected cells was detected as early as day 37 with high initial oligoclonality index, consistent with early mitotic proliferation. CONCLUSIONS: In recipients infected through organ transplantation HTLV-1 disseminated rapidly despite early anti-HTLV-1 treatment. Proviral load set point was reached within 6 weeks. Seroconversion was not delayed. Unique integration site analysis and HTLV-1 2LTR DNA circles indicated early clonal expansion and high rate of infectious spread.

Clonality of HTLV-2 in natural infection.

Human T-lymphotropic virus type 1 (HTLV-1) and type 2 (HTLV-2) both cause lifelong persistent infections, but differ in their clinical outcomes. HTLV-1 infection causes a chronic or acute T-lymphocytic malignancy in up to 5% of infected individuals whereas HTLV-2 has not been unequivocally linked to a T-cell malignancy. Virus-driven clonal proliferation of infected cells both in vitro and in vivo has been demonstrated in HTLV-1 infection. However, T-cell clonality in HTLV-2 infection has not been rigorously characterized. In this study we used a high-throughput approach in conjunction with flow cytometric sorting to identify and quantify HTLV-2-infected T-cell clones in 28 individuals with natural infection. We show that while genome-wide integration site preferences in vivo were similar to those found in HTLV-1 infection, expansion of HTLV-2-infected clones did not demonstrate the same significant association with the genomic environment of the integrated provirus. The proviral load in HTLV-2 is almost confined to CD8+ T-cells and is composed of a small number of often highly expanded clones. The HTLV-2 load correlated significantly with the degree of dispersion of the clone frequency distribution, which was highly stable over ∼8 years. These results suggest that there are significant differences in the selection forces that control the clonal expansion of virus-infected cells in HTLV-1 and HTLV-2 infection. In addition, our data demonstrate that strong virus-driven proliferation per se does not predispose to malignant transformation in oncoretroviral infections.

The role of HTLV-1 clonality, proviral structure, and genomic integration site in adult T-cell leukemia/lymphoma.

Adult T-cell leukemia/lymphoma (ATL) occurs in ∼5% of human T-lymphotropic virus type 1 (HTLV-1)-infected individuals and is conventionally thought to be a monoclonal disease in which a single HTLV-1(+) T-cell clone progressively outcompetes others and undergoes malignant transformation. Here, using a sensitive high-throughput method, we quantified clonality in 197 ATL cases, identified genomic characteristics of the proviral integration sites in malignant and nonmalignant clones, and investigated the proviral features (genomic structure and 5' long terminal repeat methylation) that determine its capacity to express the HTLV-1 oncoprotein Tax. Of the dominant, presumed malignant clones, 91% contained a single provirus. The genomic characteristics of the integration sites in the ATL clones resembled those of the frequent low-abundance clones (present in both ATL cases and carriers) and not those of the intermediate-abundance clones observed in 24% of ATL cases, suggesting that oligoclonal proliferation per se does not cause malignant transformation. Gene ontology analysis revealed an association in 6% of cases between ATL and integration near host genes in 3 functional categories, including genes previously implicated in hematologic malignancies. In all cases of HTLV-1 infection, regardless of ATL, there was evidence of preferential survival of the provirus in vivo in acrocentric chromosomes (13, 14, 15, 21, and 22).

HTLV-1 drives vigorous clonal expansion of infected CD8(+) T cells in natural infection.

BACKGROUND: Human T-lymphotropic Virus Type I (HTLV-1) is a retrovirus that persistently infects 5-10 million individuals worldwide and causes disabling or fatal inflammatory and malignant diseases. The majority of the HTLV-1 proviral load is found in CD4(+) T cells, and the phenotype of adult T cell leukemia (ATL) is typically CD4(+). HTLV-1 also infects CD8(+) cells in vivo, but the relative abundance and clonal composition of the two infected subpopulations have not been studied. We used a high-throughput DNA sequencing protocol to map and quantify HTLV-1 proviral integration sites in separated populations of CD4(+) cells, CD8(+) cells and unsorted peripheral blood mononuclear cells from 12 HTLV-1-infected individuals. RESULTS: We show that the infected CD8(+) cells constitute a median of 5% of the HTLV-1 proviral load. However, HTLV-1-infected CD8(+) clones undergo much greater oligoclonal proliferation than the infected CD4(+) clones in infected individuals, regardless of disease manifestation. The CD8(+) clones are over-represented among the most abundant clones in the blood and are redetected even after several years. CONCLUSIONS: We conclude that although they make up only 5% of the proviral load, the HTLV-1-infected CD8(+) T-cells make a major impact on the clonal composition of HTLV-1-infected cells in the blood. The greater degree of oligoclonal expansion observed in the infected CD8(+) T cells, contrasts with the CD4(+) phenotype of ATL; cases of CD8(+) adult T-cell leukaemia/lymphoma are rare. This work is consistent with growing evidence that oligoclonal expansion of HTLV-1-infected cells is not sufficient for malignant transformation.

Genome-wide determinants of proviral targeting, clonal abundance and expression in natural HTLV-1 infection.

The regulation of proviral latency is a central problem in retrovirology. We postulate that the genomic integration site of human T lymphotropic virus type 1 (HTLV-1) determines the pattern of expression of the provirus, which in turn determines the abundance and pathogenic potential of infected T cell clones in vivo. We recently developed a high-throughput method for the genome-wide amplification, identification and quantification of proviral integration sites. Here, we used this protocol to test two hypotheses. First, that binding sites for transcription factors and chromatin remodelling factors in the genome flanking the proviral integration site of HTLV-1 are associated with integration targeting, spontaneous proviral expression, and in vivo clonal abundance. Second, that the transcriptional orientation of the HTLV-1 provirus relative to that of the nearest host gene determines spontaneous proviral expression and in vivo clonal abundance. Integration targeting was strongly associated with the presence of a binding site for specific host transcription factors, especially STAT1 and p53. The presence of the chromatin remodelling factors BRG1 and INI1 and certain host transcription factors either upstream or downstream of the provirus was associated respectively with silencing or spontaneous expression of the provirus. Cells expressing HTLV-1 Tax protein were significantly more frequent in clones of low abundance in vivo. We conclude that transcriptional interference and chromatin remodelling are critical determinants of proviral latency in natural HTLV-1 infection.

Strongyloidiasis and infective dermatitis alter human T lymphotropic virus-1 clonality in vivo.

Human T-lymphotropic Virus-1 (HTLV-1) is a retrovirus that persists lifelong by driving clonal proliferation of infected T-cells. HTLV-1 causes a neuroinflammatory disease and adult T-cell leukemia/lymphoma. Strongyloidiasis, a gastrointestinal infection by the helminth Strongyloides stercoralis, and Infective Dermatitis associated with HTLV-1 (IDH), appear to be risk factors for the development of HTLV-1 related diseases. We used high-throughput sequencing to map and quantify the insertion sites of the provirus in order to monitor the clonality of the HTLV-1-infected T-cell population (i.e. the number of distinct clones and abundance of each clone). A newly developed biodiversity estimator called "DivE" was used to estimate the total number of clones in the blood. We found that the major determinant of proviral load in all subjects without leukemia/lymphoma was the total number of HTLV-1-infected clones. Nevertheless, the significantly higher proviral load in patients with strongyloidiasis or IDH was due to an increase in the mean clone abundance, not to an increase in the number of infected clones. These patients appear to be less capable of restricting clone abundance than those with HTLV-1 alone. In patients co-infected with Strongyloides there was an increased degree of oligoclonal expansion and a higher rate of turnover (i.e. appearance and disappearance) of HTLV-1-infected clones. In Strongyloides co-infected patients and those with IDH, proliferation of the most abundant HTLV-1⁺ T-cell clones is independent of the genomic environment of the provirus, in sharp contrast to patients with HTLV-1 infection alone. This implies that new selection forces are driving oligoclonal proliferation in Strongyloides co-infection and IDH. We conclude that strongyloidiasis and IDH increase the risk of development of HTLV-1-associated diseases by increasing the rate of infection of new clones and the abundance of existing HTLV-1⁺ clones.

Quantification of HTLV-1 clonality and TCR diversity.

Estimation of immunological and microbiological diversity is vital to our understanding of infection and the immune response. For instance, what is the diversity of the T cell repertoire? These questions are partially addressed by high-throughput sequencing techniques that enable identification of immunological and microbiological "species" in a sample. Estimators of the number of unseen species are needed to estimate population diversity from sample diversity. Here we test five widely used non-parametric estimators, and develop and validate a novel method, DivE, to estimate species richness and distribution. We used three independent datasets: (i) viral populations from subjects infected with human T-lymphotropic virus type 1; (ii) T cell antigen receptor clonotype repertoires; and (iii) microbial data from infant faecal samples. When applied to datasets with rarefaction curves that did not plateau, existing estimators systematically increased with sample size. In contrast, DivE consistently and accurately estimated diversity for all datasets. We identify conditions that limit the application of DivE. We also show that DivE can be used to accurately estimate the underlying population frequency distribution. We have developed a novel method that is significantly more accurate than commonly used biodiversity estimators in microbiological and immunological populations.

HTLV-1 proviral integration sites differ between asymptomatic carriers and patients with HAM/TSP.

BACKGROUND: HTLV-1 causes proliferation of clonal populations of infected T cells in vivo, each clone defined by a unique proviral integration site in the host genome. The proviral load is strongly correlated with odds of the inflammatory disease HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). There is evidence that asymptomatic HTLV-1 carriers (ACs) have a more effective CD8 + T cell response, including a higher frequency of HLA class I alleles able to present peptides from a regulatory protein of HTLV-1, HBZ. We have previously shown that specific features of the host genome flanking the proviral integration site favour clone survival and spontaneous expression of the viral transactivator protein Tax in naturally infected PBMCs ex vivo. However, the previous studies were not designed or powered to detect differences in integration site characteristics between ACs and HAM/TSP patients. Here, we tested the hypothesis that the genomic environment of the provirus differs systematically between ACs and HAM/TSP patients, and between individuals with strong or weak HBZ presentation. METHODS: We used our recently described high-throughput protocol to map and quantify integration sites in 95 HAM/TSP patients and 68 ACs from Kagoshima, Japan, and 75 ACs from Kumamoto, Japan. Individuals with 2 or more HLA class I alleles predicted to bind HBZ peptides were classified 'strong' HBZ binders; the remainder were classified 'weak binders'. RESULTS: The abundance of HTLV-1-infected T cell clones in vivo was correlated with proviral integration in genes and in areas with epigenetic marks associated with active regulatory elements. In clones of equivalent abundance, integration sites in genes and active regions were significantly more frequent in ACs than patients with HAM/TSP, irrespective of HBZ binding and proviral load. Integration sites in genes were also more frequent in strong HBZ binders than weak HBZ binders. CONCLUSION: Clonal abundance is correlated with integration in a transcriptionally active genomic region, and these regions may promote cell proliferation. A clone that reaches a given abundance in vivo is more likely to be integrated in a transcriptionally active region in individuals with a more effective anti-HTLV-1 immune response, such those who can present HBZ peptides or those who remain asymptomatic.

The interaction of disease transmission, mortality, and economic output over the first 2 years of the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has caused over 7.02 million deaths as of January 2024 and profoundly affected most countries' Gross Domestic Product (GDP). Here, we study the interaction of SARS-CoV-2 transmission, mortality, and economic output between January 2020 and December 2022 across 25 European countries. METHODS: We use a Bayesian mixed effects model with auto-regressive terms to estimate the temporal relationships between disease transmission, excess deaths, changes in economic output, transit mobility and non-pharmaceutical interventions (NPIs) across countries. RESULTS: Disease transmission intensity (logRt) decreases GDP and increases excess deaths, where the latter association is longer-lasting. Changes in GDP as well as prior week transmission intensity are both negatively associated with each other (-0.241, 95% CrI: -0.295 - -0.189). We find evidence of risk-averse behaviour, as changes in transit and prior week transmission intensity are negatively associated (-0.055, 95% CrI: -0.074 to -0.036). Our results highlight a complex cost-benefit trade-off from individual NPIs. For example, banning international travel is associated with both increases in GDP (0.014, 0.002-0.025) and decreases in excess deaths (-0.014, 95% CrI: -0.028 - -0.001). Country-specific random effects, such as the poverty rate, are positively associated with excess deaths while the UN government effectiveness index is negatively associated with excess deaths. INTERPRETATION: The interplay between transmission intensity, excess deaths, population mobility and economic output is highly complex, and none of these factors can be considered in isolation. Our results reinforce the intuitive idea that significant economic activity arises from diverse person-to-person interactions. Our analysis quantifies and highlights that the impact of disease on a given country is complex and multifaceted. Long-term economic impairments are not fully captured by our model, as well as long-term disease effects (Long COVID).

Pre-morbid human T-lymphotropic virus type I proviral load, rather than percentage of abnormal lymphocytes, is associated with an increased risk of aggressive adult T-cell leukemia/lymphoma.

Out of 153 newly referred human T-lymphotropic virus type I infected patients, 42 (27%) had 5% or more abnormal lymphocytes, consistent with the diagnosis of smoldering adult T-cell leukemia/lymphoma. The abnormal lymphocyte percentage was higher in patients with human T-lymphotropic virus type I associated inflammatory disease compared with asymptomatic carriers (P=0.006). Over 4.5 years median follow up, 4 patients, all with 10 or more human T-lymphotropic virus type I DNA copies/100 peripheral blood mononuclear cells at presentation, but only one with 5% or more abnormal lymphocytes at presentation, developed adult T-cell leukemia/lymphoma. Thus, high pre-morbid human T-lymphotropic virus type I proviral load, rather than fulfilment of the classification criteria for smoldering adult T-cell leukemia/lymphoma, was associated with an increased risk of developing aggressive adult T-cell leukemia/lymphoma.

Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study.

BACKGROUND: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers. METHODS: Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies. FINDINGS: The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds. INTERPRETATION: Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available. FUNDING: UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.

Intrinsic randomness in epidemic modelling beyond statistical uncertainty.

Uncertainty can be classified as either aleatoric (intrinsic randomness) or epistemic (imperfect knowledge of parameters). The majority of frameworks assessing infectious disease risk consider only epistemic uncertainty. We only ever observe a single epidemic, and therefore cannot empirically determine aleatoric uncertainty. Here, we characterise both epistemic and aleatoric uncertainty using a time-varying general branching process. Our framework explicitly decomposes aleatoric variance into mechanistic components, quantifying the contribution to uncertainty produced by each factor in the epidemic process, and how these contributions vary over time. The aleatoric variance of an outbreak is itself a renewal equation where past variance affects future variance. We find that, superspreading is not necessary for substantial uncertainty, and profound variation in outbreak size can occur even without overdispersion in the offspring distribution (i.e. the distribution of the number of secondary infections an infected person produces). Aleatoric forecasting uncertainty grows dynamically and rapidly, and so forecasting using only epistemic uncertainty is a significant underestimate. Therefore, failure to account for aleatoric uncertainty will ensure that policymakers are misled about the substantially higher true extent of potential risk. We demonstrate our method, and the extent to which potential risk is underestimated, using two historical examples.

Quantifying Changes in Vaccine Coverage in Mainstream Media as a Result of the COVID-19 Outbreak: Text Mining Study.

Background: Achieving herd immunity through vaccination depends upon the public's acceptance, which in turn relies on their understanding of its risks and benefits. The fundamental objective of public health messaging on vaccines is therefore the clear communication of often complex information and, increasingly, the countering of misinformation. The primary outlet shaping public understanding is mainstream online news media, where coverage of COVID-19 vaccines was widespread. Objective: We used text-mining analysis on the front pages of mainstream online news to quantify the volume and sentiment polarization of vaccine coverage. Methods: We analyzed 28 million articles from 172 major news sources across 11 countries between July 2015 and April 2021. We employed keyword-based frequency analysis to estimate the proportion of overall articles devoted to vaccines. We performed topic detection using BERTopic and named entity recognition to identify the leading subjects and actors mentioned in the context of vaccines. We used the Vader Python module to perform sentiment polarization quantification of all collated English-language articles. Results: The proportion of front-page articles mentioning vaccines increased from 0.1% to 4% with the outbreak of COVID-19. The number of negatively polarized articles increased from 6698 in 2015-2019 to 28,552 in 2020-2021. However, overall vaccine coverage before the COVID-19 pandemic was slightly negatively polarized (57% negative), whereas coverage during the pandemic was positively polarized (38% negative). Conclusions: Throughout the pandemic, vaccines have risen from a marginal to a widely discussed topic on the front pages of major news outlets. Mainstream online media has been positively polarized toward vaccines, compared with mainly negative prepandemic vaccine news. However, the pandemic was accompanied by an order-of-magnitude increase in vaccine news that, due to low prepandemic frequency, may contribute to a perceived negative sentiment. These results highlight important interactions between the volume of news and overall polarization. To the best of our knowledge, our work is the first systematic text mining study of front-page vaccine news headlines in the context of COVID-19.