439 results found
Redd R, Cooper E, Atchison C, et al., 2021, Behavioural responses to SARS-CoV-2 antibody testing in England: REACT-2 study, Wellcome Open Research, Vol: 6, Pages: 203-203
<ns4:p><ns4:bold>Background: </ns4:bold>This study assesses the behavioural responses to SARS-CoV-2 antibody test results as part of the REal-time Assessment of Community Transmission-2 (REACT-2) research programme, a large community-based surveillance study of antibody prevalence in England.</ns4:p><ns4:p> <ns4:bold>Methods:</ns4:bold> A follow-up survey was conducted six weeks after the SARS-CoV-2 antibody test. The follow-up survey included 4500 people with a positive result and 4039 with a negative result. Reported changes in behaviour were assessed using difference-in-differences models. A nested interview study was conducted with 40 people to explore how they thought through their behavioural decisions.</ns4:p><ns4:p> <ns4:bold>Results:</ns4:bold> While respondents reduced their protective behaviours over the six weeks, we did not find evidence that positive test results changed participant behaviour trajectories in relation to the number of contacts the respondents had, for leaving the house to go to work, or for leaving the house to socialise in a personal place. The qualitative findings supported these results. Most people did not think that they had changed their behaviours because of their test results, however they did allude to some changes in their attitudes and perceptions around risk, susceptibility, and potential severity of symptoms.</ns4:p><ns4:p> <ns4:bold>Conclusions: </ns4:bold>We found limited evidence that knowing your antibody status leads to behaviour change in the context of a research study. While this finding should not be generalised to widespread self-testing in other contexts, it is reassuring given the importance of large prevalence studies, and the practicalities of doing these at scale using self-testing with lateral flow immunoassay (LFIA).</ns4:p>
While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.
ISARIC Clinical Characterisation Group, Hall MD, Baruch J, et al., 2021, Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: an observational cohort., Elife, Vol: 10
Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high density unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly-evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill and Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Chadeau-Hyam M, Eales O, Bodinier B, et al., 2021, REACT-1 round 15 final report: Increased breakthrough SARS-CoV-2 infections among adults who had received two doses of vaccine, but booster doses and first doses in children are providing important protection
Background: It has been nearly a year since the first vaccinations against SARS-CoV-2were delivered in England. The third wave of COVID-19 in England began in May 2021 asthe Delta variant began to outcompete and largely replace other strains. The REal-timeAssessment of Community Transmission-1 (REACT-1) series of community surveys forSARS-CoV-2 infection has provided insights into transmission dynamics since May 2020.Round 15 of the REACT-1 study was carried out from 19 October to 5 November 2021.Methods: We estimated prevalence of SARS-CoV2 infection and used multiple logisticregression to analyse associations between SARS-CoV-2 infection in England anddemographic and other risk factors, based on RT-PCR results from self-administered throatand nose swabs in over 100,000 participants. We estimated (single-dose) vaccineeffectiveness among children aged 12 to 17 years, and among adults comparedswab-positivity in people who had received a third (booster) dose with those who hadreceived two vaccine doses. We used splines to analyse time trends in swab-positivity.Results: During mid-October to early-November 2021, weighted prevalence was 1.57%(1.48%, 1.66%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14).Weighted prevalence increased between rounds 14 and 15 across most age groups(including older ages, 65 years and over) and regions, with average reproduction numberacross rounds of R=1.09 (1.08, 1.11). During round 15, there was a fall in prevalence from amaximum around 20-21 October, with an R of 0.76 (0.70, 0.83), reflecting falls in prevalenceat ages 17 years and below and 18 to 54 years. School-aged children had the highestweighted prevalence of infection: 4.95% (4.39%, 5.58%) in those aged 5 to 12 years and5.21% (4.61%, 5.87%) in those aged 13 to 17 years. In multiple logistic regression, age, sex,key worker status and presence of one or more children in the home were associated withswab positivity. There was evidence of heterogeneity between rounds in
Lushasi K, Hayes S, Ferguson EA, et al., 2021, Reservoir dynamics of rabies in Southeast Tanzania and the roles of cross-species transmission and domestic dog vaccination, Journal of Applied Ecology, Vol: 58, Pages: 2673-2685, ISSN: 0021-8901
1) Understanding the role of different species in the transmission of multi-host pathogens, such as rabies virus, is vital for effective control strategies. Across most of sub-Saharan Africa domestic dogs (Canis familiaris) are considered the reservoir for rabies, but the role of wildlife has been long debated. Here we explore the multi-host transmission dynamics of rabies across southeast Tanzania. 2) Between January 2011 and July 2019 data on probable rabies cases were collected in the regions of Lindi and Mtwara. Hospital records of animal-bite patients presenting to healthcare facilities were used as sentinels for animal contact tracing. The timing, location and species of probable rabid animals was used to reconstruct transmission trees to infer who infected whom and the relative frequencies of within-and between-species transmission. 3) During the study, 688 probable human rabies exposures were identified, resulting in 47 deaths. Of these exposures, 389 were from domestic dogs (56.5%) and 262 from jackals (38.1%). Over the same period 549 probable animal rabies cases were traced: 303 in domestic dogs (55.2%) and 221 in jackals (40.3%). 4) Although dog-to-dog transmission was most commonly inferred (40.5% of transmission events), a third of inferred events involved wildlife-to-wildlife transmission (32.6%) and evidence suggested some sustained transmission chains within jackal populations. 5) A steady decline in probable rabies cases in both humans and animals coincided with the implementation of widespread domestic dog vaccination during the first six years of the study. Following the lapse of this programme dog rabies cases began to increase in one of the northernmost districts. 6) Synthesis and applications: in southeast Tanzania, despite a relatively high incidence of rabies in wildlife and evidence of wildlife-to-wildlife transmission, domestic dogs remain essential to the reservoir of infection. Continued dog vaccination alongside improved surveillance
Chadeau-Hyam M, Eales O, Bodinier B, et al., 2021, REACT-1 round 15 interim report: Exponential rise in prevalence of SARS-CoV-2 infection in England from end September 2021 followed by dip during October 2021
Background: The third wave of COVID-19 in England coincided with the rapid spread of theDelta variant of SARS-CoV-2 from the end of May 2021. Case incidence data from thenational testing programme (Pillar 2) in England may be affected by changes in testingbehaviour and other biases. Community surveys may provide important contextualinformation to inform policy and the public health response.Methods: We estimated patterns of community prevalence of SARS-CoV-2 infection inEngland using RT-PCR swab-positivity, demographic and other risk factor data from round15 (interim) of the REal-time Assessment of Community Transmission-1 (REACT-1) study(round 15a, carried out from 19 to 29 October 2021). We compared these findings with thosefrom round 14 (9 to 27 September 2021).Results: During mid- to late-October 2021 (round 15a) weighted prevalence was 1.72%(1.61%, 1.84%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14). Theoverall reproduction number (R) from round 14 to round 15a was 1.12 (1.11, 1.14) withincreases in prevalence over this period (September to October) across age groups andregions except Yorkshire and The Humber. However, within round 15a (mid- to late-October)there was evidence of a fall in prevalence with R of 0.76 (0.65, 0.88). The highest weightedprevalence was observed among children aged 5 to 12 years at 5.85% (5.10%, 6.70%) and13 to 17 years at 5.75% (5.02%, 6.57%). At regional level, there was an almost four-foldincrease in weighted prevalence in South West from round 14 at 0.59% (0.43%,0.80%) toround 15a at 2.18% (1.84%, 2.58%), with highest smoothed prevalence at subregional levelalso found in South West in round 15a. Age, sex, key worker status, and presence ofchildren in the home jointly contributed to the risk of swab-positivity. Among the 126sequenced positive swabs obtained up until 23 October, all were Delta variant; 13 (10.3%)were identified as the AY.4.2 sub-lineage.Discussion: We observed the highest overall prevalence of swab-p
Elliott P, Haw D, Wang H, et al., 2021, Exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant, Science, ISSN: 0036-8075
SARS-CoV-2 infections were rising during early summer 2021 in many countries associated with the Delta variant. We assessed RT-PCR swab-positivity in the REal-time Assessment of Community Transmission-1 (REACT-1) study in England. We observed sustained exponential growth with average doubling time (June-July 2021) of 25 days driven by complete replacement of Alpha variant by Delta, and by high prevalence at younger less-vaccinated ages. Unvaccinated people were three times more likely than double-vaccinated people to test positive. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination.
Williams LR, Ferguson NM, Donnelly CA, et al., 2021, Measuring vaccine efficacy against infection and disease in clinical trials: sources and magnitude of bias in COVID-19 vaccine efficacy estimates, Clinical Infectious Diseases, ISSN: 1058-4838
BACKGROUND: Phase III trials have estimated COVID-19 vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. METHODS: We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic and any SARS͏CoV2 infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. RESULTS: VE against asymptomatic infection measured by PCR or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias towards underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4 to 77.1) and 70.9% (95% UI 49.8 to 80.7) respectively. CONCLUSIONS: Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.
Dankwa EA, Donnelly CA, Brouwer AF, et al., 2021, Estimating vaccination threshold and impact in the 2017-2019 hepatitis A virus outbreak among persons experiencing homelessness or who use drugs in Louisville, Kentucky, United states., Vaccine
BACKGROUND: Between September 2017 and June 2019, an outbreak of hepatitis A virus (HAV) occurred in Louisville, Kentucky, resulting in 501 cases and 6 deaths, predominantly among persons who experience homelessness or who use drugs (PEH/PWUD). The critical vaccination threshold (Vc) required to achieve herd immunity in this population is unknown. We investigated Vc and vaccination impact using epidemic modeling. METHODS: To determine which population subgroups had high infection risks, we employed a technique based on comparing the proportion of cases arising before and after the epidemic peak, across subgroups. We also developed a dynamic deterministic model of HAV transmission among PEH/PWUD to estimate the basic reproduction number (R0), herd immunity threshold, Vc and the effect of timing of the vaccination intervention on epidemic and economic outcomes. RESULTS: Of the 501 confirmed or probable cases, 385 (76.8%) were among PEH/PWUD. Among PEH/PWUD and within the general population, homelessness was a significant risk factor for infection in the initial stages of the outbreak (odds ratios for homeless versus not homeless: 2.62; 95% confidence interval (CI): 1.62-4.25 for PEH/PWUD and 2.39; 95% CI: 1.51-3.78 for all detected cases). Our estimate for R0 ranges between 2.85 and 3.54, corresponding to an estimate of 69% (95% CI: 65-72) for herd immunity threshold and 76% (95% CI: 72%-80%) for Vc, assuming a vaccine with 90% efficacy. The observed vaccination program was estimated to have averted 30 hospitalizations (95% CI: 19-43), associated with over US$490 000 (95% CI: $310 000-700 000) in hospitalization cost. Greater impact was observed with earlier and faster vaccination implementation. CONCLUSIONS: Vaccination coverage of at least 77% is likely required to prevent outbreaks of HAV among PEH/PWUD in Louisville, assuming a 90% vaccine efficacy. Proactive hepatitis A vaccination programs among PEH/PWUD will maximize health and economic benefits of these progra
Chadeau-Hyam M, Wang H, Eales O, et al., 2021, REACT-1 study round 14: High and increasing prevalence of SARS-CoV-2 infection among school-aged children during September 2021 and vaccine effectiveness against infection in England
Background: England experienced a third wave of the COVID-19 epidemic from end May2021 coinciding with the rapid spread of Delta variant. Since then, the population eligible forvaccination against COVID-19 has been extended to include all 12-15-year-olds, and abooster programme has been initiated among adults aged 50 years and over, health careand care home workers, and immunocompromised people. Meanwhile, schoolchildren havereturned to school often with few COVID-19-related precautions in place.Methods: In the REal-time Assessment of Community Transmission-1 (REACT-1) study,throat and nose swabs were sent to non-overlapping random samples of the populationaged 5 years and over in England. We analysed prevalence of SARS-CoV-2 using reversetranscription-polymerase chain reaction (RT-PCR) swab-positivity data from REACT-1 round14 (between 9 and 27 September 2021). We combined results for round 14 with round 13(between 24 June and 12 July 2021) and estimated vaccine effectiveness and prevalence ofswab-positivity among double-vaccinated individuals. Unlike all previous rounds, in round 14,we switched from dry swabs transported by courier on a cold chain to wet swabs usingsaline. Also, at random, 50% of swabs (not chilled until they reached the depot) weretransported by courier and 50% were sent through the priority COVID-19 postal service.Results: We observed stable or rising prevalence (with an R of 1.03 (0.94, 1.14) overall)during round 14 with a weighted prevalence of 0.83% (0.76%, 0.89%). The highest weightedprevalence was found in children aged 5 to 12 years at 2.32% (1.96%, 2.73%) and 13 to 17years at 2.55% (2.11%, 3.08%). All positive virus samples analysed correspond to the Deltavariant or sub-lineages of Delta with one instance of the E484K escape mutation detected.The epidemic was growing in those aged 17 years and under with an R of 1.18 (1.03, 1.34),but decreasing in those aged 18 to 54 years with an R of 0.81 (0.68, 0.97). For allparticipants and all vaccin
McCabe R, Donnelly C, 2021, Disease transmission and control modelling at the science-policy interface, Interface Focus, Vol: 11, Pages: 1-13, ISSN: 2042-8901
The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed government’s decisions to implement non-pharmaceutical interventions to control the spread of the virus.In this article we explore the complex relationships between models, decision-making, the media and the public during the COVID-19 pandemic in the United Kingdom of Great Britain and Northern Ireland (UK). Doing so not only provides important historical context of COVID-19 modelling and how it has shaped the UK response, but as the pandemic continues and looking towards future pandemic preparedness, understanding these relationships and how they might be improved is critical. As such, we have synthesised information gathered via three methods: a survey to publicly listed attendees of SAGE, SPI-M and other comparable advisory bodies, interviews with science communication experts and former scientific advisors, and reviewing some of the key COVID-19 modelling literature from 2020. Our research highlights the desire for increased bidirectional communication between modellers, decision-makers and the public, as well as the need to convey uncertainty inherent in transmission models in a clear manner. These aspects should be considered carefully ahead of the next emergency response.
Mo Y, Eyre DW, Lumley SF, et al., 2021, Transmission of community- and hospital-acquired SARS-CoV-2 in hospital settings in the UK: A cohort study, PLoS Medicine, Vol: 18, ISSN: 1549-1277
BACKGROUND: Nosocomial spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been widely reported, but the transmission pathways among patients and healthcare workers (HCWs) are unclear. Identifying the risk factors and drivers for these nosocomial transmissions is critical for infection prevention and control interventions. The main aim of our study was to quantify the relative importance of different transmission pathways of SARS-CoV-2 in the hospital setting. METHODS AND FINDINGS: This is an observational cohort study using data from 4 teaching hospitals in Oxfordshire, United Kingdom, from January to October 2020. Associations between infectious SARS-CoV-2 individuals and infection risk were quantified using logistic, generalised additive and linear mixed models. Cases were classified as community- or hospital-acquired using likely incubation periods of 3 to 7 days. Of 66,184 patients who were hospitalised during the study period, 920 had a positive SARS-CoV-2 PCR test within the same period (1.4%). The mean age was 67.9 (±20.7) years, 49.2% were females, and 68.5% were from the white ethnic group. Out of these, 571 patients had their first positive PCR tests while hospitalised (62.1%), and 97 of these occurred at least 7 days after admission (10.5%). Among the 5,596 HCWs, 615 (11.0%) tested positive during the study period using PCR or serological tests. The mean age was 39.5 (±11.1) years, 78.9% were females, and 49.8% were nurses. For susceptible patients, 1 day in the same ward with another patient with hospital-acquired SARS-CoV-2 was associated with an additional 7.5 infections per 1,000 susceptible patients (95% credible interval (CrI) 5.5 to 9.5/1,000 susceptible patients/day) per day. Exposure to an infectious patient with community-acquired Coronavirus Disease 2019 (COVID-19) or to an infectious HCW was associated with substantially lower infection risks (2.0/1,000 susceptible patients/day, 95% CrI 1.6 to 2.2). As for
Hillis S, Blenkinsop A, Villaveces A, et al., 2021, COVID-19-associated orphanhood and caregiver death in the United States, Pediatrics, ISSN: 0031-4005
Background: Most COVID-19 deaths occur among adults, not children, and attention has focused on mitigating COVID-19 burden among adults. However, a tragic consequence of adult deaths is that high numbers of children might lose their parents and caregivers to COVID-19-associated deaths.Methods: We quantified COVID-19-associated caregiver loss and orphanhood in the US and for each state using fertility and excess and COVID-19 mortality data. We assessed burden and rates of COVID-19-associated orphanhood and deaths of custodial and co-residing grandparents, overall and by race/ethnicity. We further examined variations in COVID-19-associated orphanhood by race/ethnicity for each state. Results: We found that from April 1, 2020 through June 30, 2021, over 140,000 children in the US experienced the death of a parent or grandparent caregiver. The risk of such loss was 1.1 to 4.5 times higher among children of racial and ethnic minorities, compared to Non-Hispanic White children. The highest burden of COVID-19-associated death of parents and caregivers occurred in Southern border states for Hispanic children, Southeastern states for Black children, and in states with tribal areas for American Indian/Alaska Native populations.Conclusions: We found substantial disparities in distributions of COVID-19-associated death of parents and caregivers across racial and ethnic groups. Children losing caregivers to COVID-19 need care and safe, stable, and nurturing families with economic support, quality childcare and evidence-based parenting support programs. There is an urgent need to mount an evidence-based comprehensive response focused on those children at greatest risk, in the states most affected.
Hillis SD, Blenkinsop A, Villaveces A, et al., 2021, COVID-19-Associated Orphanhood and Caregiver Death in the United States., Pediatrics
Redding DW, Gibb R, Dan-Nwafor CC, et al., 2021, Geographical drivers and climate-linked dynamics of Lassa fever in Nigeria, Nature Communications, Vol: 12, Pages: 1-10, ISSN: 2041-1723
Lassa fever is a longstanding public health concern in West Africa. Recent molecular studies have confirmed the fundamental role of the rodent host (Mastomysnatalensis) in driving human infections, but control and prevention efforts remain hampered by a limited baseline understanding of the disease’s true incidence, geographical distribution and underlying drivers. Here, we show that Lassa fever occurrence and incidence is influenced by climate, poverty, agriculture and urbanisation factors. However, heterogeneous reporting processes and diagnostic laboratory access also appear to be important drivers of the patchy distribution of observed disease incidence. Using spatiotemporal predictive models we show that including climatic variability added retrospective predictive value over a baseline model (11% decrease in out-of-sample predictive error). However, predictions for 2020 show that a climate-driven model performs similarly overall to the baseline model. Overall, with ongoing improvements in surveillance there may be potential for forecasting Lassa fever incidence to inform health planning.
Marks C, Abramovitz D, Donnelly C, et al., 2021, Identifying counties at risk of high overdose mortality burden throughout the emerging fentanyl epidemic in the united states: a predictive statistical modeling study, The Lancet Public Health, Vol: 6, Pages: e720-e728, ISSN: 2468-2667
Background. The emergence of fentanyl around 2013 represented a new, deadly stage in the US opioid epidemic. We developed a statistical regression approach to identify counties at the highest risk of high overdose mortality in the next year by predicting annual county-level overdose death rates across the contiguous US and validated it against observed overdose mortality data from 2013 to 2018.Methods. We fit mixed effects negative binomial regression models to predict next year’s county-level overdose death rates for the years 2013 to 2018. We used publicly available county-level data related to healthcare access, drug markets, socio-demographics, and the geographic spread of opioid overdose as model predictors. The crude number of county-level overdose deaths was extracted from restricted Centers for Disease Control and Prevention mortality records. To predict county-level overdose rates for the year 201X: 1) a model was trained on county-level predictor data for the years 2010-201(X-2) paired with county-level overdose deaths for the year 2011-201(X-1); 2) county-level predictor data for the year 201(X-1) was then fed into the model to predict the 201(X) county-level crude number of overdose deaths; and 3) the latter was converted to a population-adjusted rate. For comparison, we generated a benchmark set of predictions by applying the observed slope of change in overdose death rates in the previous year to 201(X-1) rates. To assess the predictive performance of the model, we compared predicted values (of both the model and benchmark) to observed values by 1) calculating the mean average error, root mean squared error, and Spearman’s correlation coefficient and 2) assessing the proportion of counties in the top decile (10%) of overdose death rates that were correctly predicted as such. Finally, in a post-hoc analysis, we sought to identify variables with greatest predictive utility.Findings. Across the entire US and through time, our modeling approach
Forna A, Dorigatti I, Nouvellet P, et al., 2021, Comparison of machine learning methods for estimating case fatality ratios: an Ebola outbreak simulation study, PLoS One, Vol: 16, ISSN: 1932-6203
BackgroundMachine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.MethodsUsing simulated data, we use a ML algorithmic framework to evaluate data imputation performance and the resulting case fatality ratio (CFR) estimates, focusing on the scale and type of data missingness (i.e., missing completely at random—MCAR, missing at random—MAR, or missing not at random—MNAR).ResultsAcross ML methods, dataset sizes and proportions of training data used, the area under the receiver operating characteristic curve decreased by 7% (median, range: 1%–16%) when missingness was increased from 10% to 40%. Overall reduction in CFR bias for MAR across methods, proportion of missingness, outbreak size and proportion of training data was 0.5% (median, range: 0%–11%).ConclusionML methods could reduce bias and increase the precision in CFR estimates at low levels of missingness. However, no method is robust to high percentages of missingness. Thus, a datacentric approach is recommended in outbreak settings—patient survival outcome data should be prioritised for collection and random-sample follow-ups should be implemented to ascertain missing outcomes.
Parag KV, Donnelly CA, 2021, Fundamental limits on inferring epidemic resurgence in real time using effective reproduction numbers
<jats:title>Abstract</jats:title><jats:p>We find that epidemic resurgence, defined as an upswing in the effective reproduction number (<jats:italic>R</jats:italic>) of the contagion from subcritical to supercritical values, is fundamentally difficult to detect in real time. Inherent latencies in pathogen transmission, coupled with smaller and intrinsically noisier case incidence across periods of subcritical spread, mean that resurgence cannot be reliably detected without significant delays of the order of the generation time of the disease, even when case reporting is perfect. This belies epidemic suppression (where <jats:italic>R</jats:italic> falls from supercritical to subcritical values), which may be ascertained 5–10 times more rapidly due to the naturally larger incidence at which control actions are applied. We prove that these innate limits on detecting resurgence only worsen when spatial or demographic heterogeneities are incorporated. Consequently, we argue that resurgence is more effectively handled proactively, at the expense of false alarms. Responses to recrudescent infections or emerging variants of concern will more likely be timely if informed by improved syndromic surveillance systems than by optimised mathematical models of epidemic spread.</jats:p>
Bhatia S, Parag K, Wardle J, et al., 2021, Global predictions of short- to medium-term COVID-19 transmission trends : a retrospective assessment
<jats:title>Abstract</jats:title> <jats:p>From 8th March to 29th November 2020, we produced weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for 81 countries with evidence of sustained transmission. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. We evaluated the robustness of the forecasts using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3\% and 45.6\% of the observations lying in the 50\% Credible Interval in 1-week and 4-week ahead forecasts respectively. We could accurately characterise the overall phase of the epidemic up to 4-weeks ahead in 84.9\% of country-days. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.</jats:p>
Eales O, Walters C, Wang H, et al., 2021, Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2
BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administeredthroat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community.MethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines.ResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportionof positive individuals detected on first swab, was found to be higher 𝑃 for those with an 0 initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in socialdistancing measures.DiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has hig
Dorigatti I, Lavezzo E, Manuto L, et al., 2021, SARS-CoV-2 antibody dynamics and transmission from community-wide serological testing in the Italian municipality of Vo' (vol 12, 4383, 2021), NATURE COMMUNICATIONS, Vol: 12
Mishra S, Scott JA, Laydon DJ, et al., 2021, Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling, SCIENTIFIC REPORTS, Vol: 11, Pages: 1-9, ISSN: 2045-2322
The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.
Redd R, Cooper E, Atchison C, et al., 2021, Behavioural responses to SARS-CoV-2 antibody testing in England: REACT-2 study, Wellcome Open Research, Vol: 6, Pages: 1-10, ISSN: 2398-502X
Background: This study assesses the behavioural responses to SARS-CoV-2 antibody test results as part of the REal-time Assessment of Community Transmission-2 (REACT-2) research programme, a large community-based surveillance study of antibody prevalence in England.Methods: A follow-up survey was conducted six weeks after the SARS-CoV-2 antibody test. The follow-up survey included 4500 people with a positive result and 4039 with a negative result. Reported changes in behaviour were assessed using difference-in-differences models. A nested interview study was conducted with 40 people to explore how they thought through their behavioural decisions.Results: While respondents reduced their protective behaviours over the six weeks, we did not find evidence that positive test results changed participant behaviour trajectories in relation to the number of contacts the respondents had, for leaving the house to go to work, or for leaving the house to socialise in a personal place. The qualitative findings supported these results. Most people did not think that they had changed their behaviours because of their test results, however they did allude to some changes in their attitudes and perceptions around risk, susceptibility, and potential severity of symptoms.Conclusions: We found limited evidence that knowing your antibody status leads to behaviour change in the context of a research study. While this finding should not be generalised to widespread self-testing in other contexts, it is reassuring given the importance of large prevalence studies, and the practicalities of doing these at scale using self-testing with lateral flow immunoassay (LFIA).
Elliott P, Haw D, Wang H, et al., 2021, REACT-1 round 13 final report: exponential growth, high prevalence of SARS-CoV-2 and vaccine effectiveness associated with Delta variant in England during May to July 2021
BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness andhospitalisations despite high levels of vaccination, with the proportion of cases caused by theDelta lineage increasing in many populations. As vaccination programs roll out globally andsocial distancing is relaxed, future SARS-CoV-2 trends are uncertain.MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerasechain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment ofCommunity Transmission-1 (REACT-1) study, with swabs sent to non-overlapping randomsamples of the population ages 5 years and over in England.ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15%(0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth acrossand within rounds appears to have been driven by complete replacement of Alpha variant byDelta, and by the high prevalence in younger less-vaccinated age groups, with a nine-foldincrease between rounds 12 and 13 among those aged 13 to 17 years. Prevalence amongthose who reported being unvaccinated was three-fold higher than those who reported beingfully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinatedindividuals, reflecting imperfect vaccine effectiveness against infection despite high overalllevels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccineeffectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cyclethreshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness againstsymptomatic infection of 59% (23%, 78%), with any one of three common COVID-19symptoms reported
Hillis S, Unwin H, Chen Y, et al., 2021, Global minimum estimates of children affected by COVID-19-associated orphanhood and deaths of caregivers: a modelling study, The Lancet, Vol: 398, Pages: 391-402, ISSN: 0140-6736
Background: The COVID-19 pandemic response has focused on prevention, detection, and response. Beyond morbidity and mortality, pandemics carry secondary impacts, such as children orphaned or bereft of their caregivers. Such children often face adverse consequences, including poverty, abuse, and institutionalization. We provide estimates for the magnitude of this problem resulting from COVID-19 and describe the need for resource allocation.Methods: We use mortality and fertility data to model minimum estimates and rates of COVID-19-associated orphanhood (death of 1 or both parents) and deaths of custodial and co-residing grandparents for 21 countries. We use these estimates to model global extrapolations for the number of children experiencing COVID-19-associated deaths of parents and grandparents ages 60-84.Results: Globally, from March 1, 2020-March 31, 2021, we estimate 974,000 children experienced death of primary caregivers, including parents or custodial grandparents; >1.3 million experienced death of primary caregivers and co-residing grandparents (or kin). Countries with rates of primary caregiver deaths >1/1000 children included Peru, South Africa, Mexico, Colombia, Brazil, I.R. Iran, U.S.A., and Russia (range, 1.0-8.5/1000). Numbers of children orphaned exceeded numbers of deaths among those aged 15 – 44; 2 – 5 times more children had deceased fathers than deceased mothers. Conclusions: Orphanhood and caregiver deaths are a hidden pandemic resulting from COVID-19-associated deaths. Accelerating equitable vaccine delivery is key to prevention. Psychosocial and economic support can help families nurture children bereft of caregivers and help ensure institutionalization is avoided. These data demonstrate the need for an additional pillar of our response: prevent, detect, respond, and care for children.
Ward H, Atchison C, Whitaker M, et al., 2021, Increasing SARS-CoV-2 antibody prevalence in England at the start of the second wave: REACT-2 Round 4 cross-sectional study in 160,000 adults
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>REACT-2 Study 5 is a population survey of the prevalence of SARS-CoV-2 antibodies in the community in England.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We contacted a random sample of the population by sending a letter to named individuals aged 18 or over from the NHS GP registrations list. We then sent respondents a lateral flow immunoassay (LFIA) kit for SARS-CoV-2 antibody self-testing and asked them to perform the test at home and complete a questionnaire, including reporting of their test result. Overall, 161,537 adults completed questionnaires and self-administered LFIA tests for IgG against SARS-CoV-2 between 27 October and 10 November 2020.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The overall adjusted and weighted prevalence was 5.6% (95% CI 5.4-5.7). This was an increase from 4.4% (4.3-4.5) in round 3 (September), a relative increase of 26.9% (24.0-29.9).The largest increase by age was in the 18 to 24 year old age group, which increased (adjusted and weighted) from 6.7% (6.3-7.2) to 9.9% (9.3-10.4), and in students, (adjusted, unweighted) from 5.9% (4.8-7.1) to 12.1% (10.8-13.5). Prevalence increased most in Yorkshire and The Humber, from 3.4% (3.0-3.8) to 6.3% (5.9-6.8) and the North West from 4.5% (4.2-4.9) to 7.7% (7.2-8.1). In contrast, the prevalence in London was stable, at 9.5% (9.0-9.9) and 9.5% (9.1-10.0) in rounds 3 and 4 respectively. We found the highest prevalence in people of Bangladeshi 15.1% (10.9-20.5), Pakistani 13.9% (11.2-17.2) and African 13.5% (10.7-16.8) ethnicity, and lowest in those of white British ethnicity at 4.2% (4.0-4.3).</jats:p></jats:sec><jats:sec><jats:title>Interpretation</jats:title><jats:p>The second wave of infection in England is apparen
Gold S, Donnelly C, Woodroffe R, et al., 2021, Modelling the influence of naturally acquired immunity from subclinical infection on outbreak dynamics and persistence of rabies in domestic dogs, PLoS Neglected Tropical Diseases, Vol: 15, Pages: 1-19, ISSN: 1935-2727
A number of mathematical models have been developed for canine rabies to explore dynamics and inform control strategies. A common assumption of these models is that naturally acquired immunity plays no role in rabies dynamics. However, empirical studies have detected rabies-specific antibodies in healthy, unvaccinated domestic dogs, potentially due to immunizing, non-lethal exposure. We developed a stochastic model for canine rabies, parameterised for Laikipia County, Kenya, to explore the implications of different scenarios for naturally acquired immunity to rabies in domestic dogs. Simulating these scenarios using a non-spatial model indicated that low levels of immunity can act to limit rabies incidence and prevent depletion of the domestic dog population, increasing the probability of disease persistence. However, incorporating spatial structure and human response to high rabies incidence allowed the virus to persist in the absence of immunity. While low levels of immunity therefore had limited influence under a more realistic approximation of rabies dynamics, high rates of exposure leading to immunizing non-lethal exposure were required to produce population-level seroprevalences comparable with those reported in empirical studies. False positives and/or spatial variation may contribute to high empirical seroprevalences. However, if high seroprevalences are related to high exposure rates, these findings support the need for high vaccination coverage to effectively control this disease.
Dorigatti I, Lavezzo E, Manuto L, et al., 2021, SARS-CoV-2 antibody dynamics and transmission from community-wide serological testing in the Italian municipality of Vo’, Nature Communications, Vol: 12, Pages: 1-11, ISSN: 2041-1723
In February and March 2020, two mass swab testing campaigns were conducted in Vo’, Italy. In May 2020, we tested 86% of the Vo’ population with three immuno-assays detecting antibodies against the spike and nucleocapsid antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November. Here we report on the results of the analysis of the May and November surveys. We estimate a seroprevalence of 3.5% (95% Credible Interval (CrI): 2.8%-4.3%) in May. In November, 98.8% (95% Confidence Interval (CI): 93.7%-100.0%) of sera which tested positive in May still reacted against at least one antigen; 18.6% (95%CI:11.0%-28.5%) showed an increase of antibody or neutralisation reactivity from May. Analysis of the serostatus of the members of 1,118 households indicates a 26.0% (95%CrI:17.2%-36.9%) Susceptible-Infectious Transmission Probability. Contact tracing had limited impact on epidemic suppression.
Ward H, Whitaker M, Tang SN, et al., 2021, Vaccine uptake and SARS-CoV-2 antibody prevalence among 207,337 adults during May 2021 in England: REACT-2 study
Background The programme to vaccinate adults in England has been rapidly implementedsince it began in December 2020. The community prevalence of SARS-CoV-2 anti-spikeprotein antibodies provides an estimate of total cumulative response to natural infection andvaccination. We describe the distribution of SARS-CoV-2 IgG antibodies in adults inEngland in May 2021 at a time when approximately 7 in 10 adults had received at least onedose of vaccine.Methods Sixth round of REACT-2 (REal-time Assessment of Community Transmission-2),a cross-sectional random community survey of adults in England, from 12 to 25 May 2021;207,337 participants completed questionnaires and self-administered a lateral flowimmunoassay test producing a positive or negative result.Results Vaccine coverage with one or more doses, weighted to the adult population inEngland, was 72.9% (95% confidence interval 72.7-73.0), varying by age from 25.1% (24.5-25.6) of those aged 18 to 24 years, to 99.2% (99.1-99.3) of those 75 years and older. Inadjusted models, odds of vaccination were lower in men (odds ratio [OR] 0.89 [0.85-0.94])than women, and in people of Black (0.41 [0.34-0.49]) compared to white ethnicity. Therewas higher vaccine coverage in the least deprived and highest income households. Peoplewho reported a history of COVID-19 were less likely to be vaccinated (OR 0.61 [0.55-0.67]).There was high coverage among health workers (OR 9.84 [8.79-11.02] and care workers (OR4.17 [3.20-5.43]) compared to non-key workers, but lower in hospitality and retail workers(OR 0.73 [0.64-0.82] and 0.77 [0.70-0.85] respectively) after adjusting for age and keycovariates.
Knock ES, Whittles LK, Lees JA, et al., 2021, Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England, Science Translational Medicine, Vol: 13, Pages: 1-12, ISSN: 1946-6234
We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff ) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900-38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%-1.21%) to 0.79% (95%CrI: 0.63%-0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%-35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%-10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%-10.2%) and 22.3% (95%CrI: 19.4%-25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission.
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