Publications
433 results found
Hamlet A, Gaythorpe KAM, Garske T, et al., 2021, Seasonal and inter-annual drivers of yellow fever transmission in South America, PLOS NEGLECTED TROPICAL DISEASES, Vol: 15, ISSN: 1935-2735
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- Citations: 5
Fu H, Wang H, Xi X, et al., 2021, A database for the epidemic trends and control measures during the first wave of COVID-19 in mainland China, International Journal of Infectious Diseases, Vol: 102, Pages: 463-471, ISSN: 1201-9712
Objectives: This data collation effort aims to provide a comprehensive database to describe the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19)across main provinces in China. Methods: From mid-January to March 2020, we extracted publicly available data on the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted a descriptive analysis of the epidemics in the six most-affected provinces. Results: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends were different across provinces. Compared to Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as local transmission of COVID-19 declined, switching the focus of measures to testing and quarantine of inbound travellers could help to sustain the control of the epidemic. Conclusions: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database with these indicators and information on control measures provides useful source for exploring further research and policy planning for response to the COVID-19 epidemic.
Verity R, Okell L, Dorigatti I, et al., 2021, COVID-19 and the difficulty of inferring epidemiological parameters from clinical data Reply, LANCET INFECTIOUS DISEASES, Vol: 21, Pages: 28-28, ISSN: 1473-3099
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- Citations: 1
Flaxman S, Mishra S, Scott J, et al., 2020, The effect of interventions on COVID-19 Reply, NATURE, Vol: 588, Pages: E29-E32, ISSN: 0028-0836
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- Citations: 4
Knock E, Whittles L, Lees J, et al., 2020, Report 41: The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions
England has been severely affected by COVID-19. We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional 2020 surveillance data. Only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier in the first wave it could have reduced mortality by 23,300 deaths on average. The mean infection fatality ratio was initially ~1.3% across all regions except London and halved following clinical care improvements. The infection fatality ratio was two-fold lower throughout in London, even when adjusting for demographics. The infection fatality ratio in care homes was 2.5-times that in the elderly in the community. Population-level infection-induced immunity in England is still far from herd immunity, with regional mean cumulative attack rates ranging between 4.4% and 15.8%.
D'Aeth J, Ghosal S, Grimm F, et al., 2020, Report 40: Optimal scheduling rules for elective care to minimize years of life lost during the SARS-CoV-2 pandemic: an application to England
SummaryCountries have deployed a wide range of policies to prioritize patients to hospital care to address unprecedent surges in demand during the course of the pandemic. Those policies included postponing planned hospital care for non-emergency cases and rationing critical care.We develop a model to optimally schedule elective hospitalizations and allocate hospital general and critical care beds to planned and emergency patients in England during the pandemic. We apply the model to NHS England data and show that optimized scheduling leads to lower years of life lost and costs than policies that reflect those implemented in England during the pandemic. Overall across all disease areas the model enables an extra 50,750 - 5,891,608 years of life gained when compared to standard policies, depending on the scenarios. Especially large gains in years of life are seen for neoplasms, diseases of the digestive system, and injuries & poisoning.
Unwin H, Mishra S, Bradley V, et al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, Vol: 11, Pages: 1-9, ISSN: 2041-1723
As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.
Grassly NC, Pons-Salort M, Parker EPK, et al., 2020, Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, Vol: 20, Pages: 1381-1389, ISSN: 1473-3099
BACKGROUND: WHO has called for increased testing in response to the COVID-19 pandemic, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. We aimed to investigate the potential impact of different testing and isolation strategies on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We developed a mathematical model of SARS-CoV-2 transmission based on infectiousness and PCR test sensitivity over time since infection. We estimated the reduction in the effective reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms, and quarantine of contacts of laboratory-confirmed cases identified through test-and-trace protocols. The expected effectiveness of different testing strategies was defined as the percentage reduction in R. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined their implications for the use of so-called immunity passports. FINDINGS: If all individuals with symptoms compatible with COVID-19 self-isolated and self-isolation was 100% effective in reducing onwards transmission, self-isolation of symptomatic individuals would result in a reduction in R of 47% (95% uncertainty interval [UI] 32-55). PCR testing to identify SARS-CoV-2 infection soon after symptom onset could reduce the number of individuals needing to self-isolate, but would also reduce the effectiveness of self-isolation (around 10% would be false negatives). Weekly screening of health-care workers and other high-risk groups irrespective of symptoms by use of PCR testing is estimated to reduce their contribution to SARS-CoV-2 transmission by 23% (95% UI 16-40), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 h. The effectiveness of test and trace depends strongly on coverage and the timelines
Thompson H, Imai N, Dighe A, et al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, Vol: 27, Pages: 1-3, ISSN: 1195-1982
We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.
Mishra S, Scott J, Zhu H, et al., 2020, A COVID-19 Model for Local Authorities of the United Kingdom
<jats:title>Abstract</jats:title><jats:p>We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the level of local authorities. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic, with some important innovations: we model the proportion of infections that result in reported deaths and cases as random variables. This is in contrast to standard frameworks that model the latent infection as a deterministic function of time varying reproduction number, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>. The model is tailored and designed to be updated daily based on publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website, <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://imperialcollegelondon.github.io/covid19local">https://imperialcollegelondon.github.io/covid19local</jats:ext-link>. The model is currently being used by the Scottish government in their decisions on interventions within Scotland [1, issue 24 to now].</jats:p>
Thompson H, Mousa A, Dighe A, et al., 2020, Report 38: SARS-CoV-2 setting-specific transmission rates: a systematic review and meta-analysis
Since the end of 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly across the world. Understanding the drivers of SARS-CoV-2 transmission is crucial for disease control policies but evidence of transmission rates in different settings remains limited. We conducted a systematic review to estimate the secondary attack rate (SAR) and observed reproduction number (Robs) in different settings and to explore differences by age, symptom status, duration of exposure and household size. A total of 97 studies were identified, 45 of which met inclusion criteria for meta-analysis. Households showed the highest transmission rates, with pooled SAR and Robs estimates of 21.1% (95% CI: 17.4%-24.8%) and 0.96 (95% CI: 0.67-1.32), respectively. Household SAR estimates were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of 5 days or less. Attack rates related to familiar and prolonged close contacts, such as social events with family and friends were higher than those related to low-risk casual contacts, such as strangers (SAR of 5.9%, 95% CI: 3.8%-8.1% vs. 1.2%, 95% CI: 0.3%-2.1%). Estimates of SAR for asymptomatic index cases were approximately two thirds of those for symptomatic index (3.5% vs. 12.8%, p<0.001). We find moderate evidence for less transmission both from and to individuals under 20 years of age in the household context, but this difference is less evident when examining all settings. Prolonged contact in households and in settings with familiar close contacts increases the potential for transmission of SARS-CoV-2. Additionally, the differences observed in transmissibility by symptom status of index cases and the potential for age-dependent effects has important implications for outbreak control strategies such as contact tracing, testing and rapid isolation of cases. There was limited data to allow exploration of transmission patterns in workplaces, schools, and care-homes, hig
Gaythorpe K, Bhatia S, Mangal T, et al., 2020, Report 37: Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility
SARS-CoV-2 infections have been reported in all age groups including infants, children, and adolescents. However, the role of children in the COVID-19 pandemic is still uncertain. This systematic review of early studies synthesises evidence on the susceptibility of children to SARS-CoV-2 infection, the severity and clinical outcomes in children with SARS-CoV-2 infection, and the transmissibility of SARS-CoV-2 by children. A systematic literature review was conducted in PubMed. Reviewers extracted data from relevant, peer-reviewed studies published during the first wave of the SARS-CoV-2 outbreak using a standardised form and assessed quality using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. For studies included in the meta-analysis, we used a random effects model to calculate pooled estimates of the proportion of children considered asymptomatic or in a severe or critical state. We identified 2,775 potential studies of which 128 studies met our inclusion criteria; data were extracted from 99, which were then quality assessed. Finally, 29 studies were considered for the meta-analysis that included information of symptoms and/or severity, these were further assessed based on patient recruitment. Our pooled estimate of the proportion of test positive children who were asymptomatic was 21.1% (95% CI: 14.0 - 28.1%), based on 13 included studies, and the proportion of children with severe or critical symptoms was 3.8% (95% CI: 1.5 - 6.0%), based on 14 included studies. We did not identify any studies designed to assess transmissibility in children and found that susceptibility to infection in children was highly variable across studies.Children’s susceptibility to infection and onward transmissibility relative to adults is still unclear and varied widely between studies. However, it is evident that most children experience clinically mild disease or remain asymptomatically infected. More comprehensive contact-tracing studie
McCabe R, Kont M, Schmit N, et al., 2020, Report 36: Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries
The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on healthcare systems, particularly intensive care units (ICUs), with COVID-19 patient care being a key concern of healthcare system planning for winter 2020/21. Ensuring that all patients who require intensive care, irrespective of COVID-19 status, can access it during this time is essential. This study uses an integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients to estimate the spare capacity of key ICU resources under different epidemic scenarios in France, Germany and Italy across the winter period of 2020/21. In particular, we examine the effect of implementing suppression strategies of varying effectiveness, triggered by different numbers of COVID-19 patients in ICU. The use of a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model and the consideration of multiple ICU resources that determine capacity (beds, doctors, nurses and ventilators) and the interdependencies between them, provides a detailed insight into potential capacity constraints this winter. Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource across countries. Lockdowns triggered based on ICU capacity could lead to large improvements in spare capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and implemented at a higher level of suppression. In many cases, maximum deficits are reduced to lower levels which can then be managed by expanding supply-side hospital capacity, to ensure that all patients can receive treatment. The success of such interventions also depends on baseline ICU bed numbers and average non-COVID-19 patient occupancy. We find that lockdowns of longer duration reduce the total number of days in defic
Haw D, Forchini G, Christen P, et al., 2020, Report 35: How can we keep schools and universities open? Differentiating closures by economic sector to optimize social and economic activity while containing SARS-CoV-2 transmission
There is a trade-off between the education sector and other economic sectors in the control of SARS-Cov-2 transmission. Here we integrate a dynamic model of SARS-CoV-2 transmission with a 63-sector economic model reflecting sectoral heterogeneity in transmission and economic interdependence between sectors. We identify COVID-19 control strategies which optimize economic production while keeping schools and universities operational and constraining infections such that emergency hospital capacity is not exceeded. The model estimates an economic gain of between £163bn and £205bn for the United Kingdom compared to a blanket lockdown of non-essential activity over six months, depending on hospital capacity. Sectors identified as potential priorities for closure are contact-intensive and/or less economically productive.
Biggerstaff M, Cowling BJ, Cucunubá ZM, et al., 2020, Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19, Emerging Infectious Diseases, Vol: 26, ISSN: 1080-6040
We report key epidemiologic parameter estimates for coronavirus disease identified in peer-reviewed publications, preprint articles, and online reports. Range estimates for incubation period were 1.8–6.9 days, serial interval 4.0–7.5 days, and doubling time 2.3–7.4 days. The effective reproductive number varied widely, with reductions attributable to interventions. Case burden and infection fatality ratios increased with patient age. Implementation of combined interventions could reduce cases and delay epidemic peak up to 1 month. These parameters for transmission, disease severity, and intervention effectiveness are critical for guiding policy decisions. Estimates will likely change as new information becomes available.
Okell LC, Verity R, Katzourakis A, et al., 2020, Host or pathogen-related factors in COVID-19 severity? Reply, LANCET, Vol: 396, Pages: 1397-1397, ISSN: 0140-6736
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- Citations: 2
Brazeau N, Verity R, Jenks S, et al., 2020, Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence
The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the current pandemic. Previous estimates have relied on data early in the epidemic, or have not fully accounted for uncertainty in serological test characteristics and delays from onset of infection to seroconversion, death, and antibody waning. After screening 175 studies, we identified 10 representative antibody surveys to obtain updated estimates of the IFR using a modelling framework that addresses the limitations listed above. We inferred serological test specificity from regional variation within serosurveys, which is critical for correctly estimating the cumulative proportion infected when seroprevalence is still low. We find that age-specific IFRs follow an approximately log-linear pattern, with the risk of death doubling approximately every eight years of age. Using these age-specific estimates, we estimate the overall IFR in a typical low-income country, with a population structure skewed towards younger individuals, to be 0.23% (0.14-0.42 95% prediction interval range). In contrast, in a typical high income country, with a greater concentration of elderly individuals, we estimate the overall IFR to be 1.15% (0.78-1.79 95% prediction interval range). We show that accounting for seroreversion, the waning of antibodies leading to a negative serological result, can slightly reduce the IFR among serosurveys conducted several months after the first wave of the outbreak, such as Italy. In contrast, uncertainty in test false positive rates combined with low seroprevalence in some surveys can reconcile apparently low crude fatality ratios with the IFR in other countries. Unbiased estimates of the IFR continue to be critical to policymakers to inform key response decisions. It will be important to continue to monitor the IFR as new treatments are introduced. The code for reproducing these results are av
McCabe R, Schmit N, Christen P, et al., 2020, Adapting hospital capacity to meet changing demands during the COVID-19 pandemic, BMC Medicine, Vol: 18, Pages: 1-12, ISSN: 1741-7015
BackgroundTo calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients.MethodsWe analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators.ResultsNHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated.ConclusionsUnless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surge
Dighe A, Cattarino L, Cuomo-Dannenburg G, et al., 2020, Response to COVID-19 in South Korea and implications for lifting stringent interventions, BMC Medicine, Vol: 18, Pages: 1-12, ISSN: 1741-7015
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 US. 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.MethodsWe 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 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%. ConclusionsWhilst early adoption of testing and contact-tracing are likely to be important for South Korea’s successf
Hogan A, Winskill P, Watson O, et al., 2020, Report 33: Modelling the allocation and impact of a COVID-19 vaccine
Several SARS-CoV-2 vaccine candidates are now in late-stage trials, with efficacy and safety results expected by the end of 2020. Even under optimistic scenarios for manufacture and delivery, the doses available in 2021 are likely to be limited. Here we identify optimal vaccine allocation strategies within and between countries to maximise health (avert deaths) under constraints on dose supply. We extended an existing mathematical model of SARS-CoV-2 transmission across different country settings to model the public health impact of potential vaccines, using a range of target product profiles developed by the World Health Organization. We show that as supply increases, vaccines that reduce or block infection – and thus transmission – in addition to preventing disease have a greater impact than those that prevent disease alone, due to the indirect protection provided to high-risk groups. We further demonstrate that the health impact of vaccination will depend on the cumulative infection incidence in the population when vaccination begins, the duration of any naturally acquired immunity, the likely trajectory of the epidemic in 2021 and the level of healthcare available to effectively treat those with disease. Within a country, we find that for a limited supply (doses for <20% of the population) the optimal strategy is to target the elderly and other high-risk groups. However, if a larger supply is available, the optimal strategy switches to targeting key transmitters (i.e. the working age population and potentially children) to indirectly protect the elderly and vulnerable. Given the likely global dose supply in 2021 (2 billion doses with a two-dose vaccine), we find that a strategy in which doses are allocated to countries in proportion to their population size is close to optimal in averting deaths. Such a strategy also aligns with the ethical principles agreed in pandemic preparedness planning.
Monod M, Blenkinsop A, Xi X, et al., 2020, Report 32: Targeting interventions to age groups that sustain COVID-19 transmission in the United States, Pages: 1-32
Following inial declines, in mid 2020, a resurgence in transmission of novel coronavirus disease (COVID-19) has occurred in the United States and parts of Europe. Despite the wide implementaon of non-pharmaceucal inter-venons, it is sll not known how they are impacted by changing contact paerns, age and other demographics. As COVID-19 disease control becomes more localised, understanding the age demographics driving transmission and how these impact the loosening of intervenons such as school reopening is crucial. Considering dynamics for the United States, we analyse aggregated, age-specific mobility trends from more than 10 million individuals and link these mechaniscally to age-specific COVID-19 mortality data. In contrast to previous approaches, we link mobility to mortality via age specific contact paerns and use this rich relaonship to reconstruct accurate trans-mission dynamics. Contrary to anecdotal evidence, we find lile support for age-shis in contact and transmission dynamics over me. We esmate that, unl August, 63.4% [60.9%-65.5%] of SARS-CoV-2 infecons in the United States originated from adults aged 20-49, while 1.2% [0.8%-1.8%] originated from children aged 0-9. In areas with connued, community-wide transmission, our transmission model predicts that re-opening kindergartens and el-ementary schools could facilitate spread and lead to considerable excess COVID-19 aributable deaths over a 90-day period. These findings indicate that targeng intervenons to adults aged 20-49 are an important con-sideraon in halng resurgent epidemics, and prevenng COVID-19-aributable deaths when kindergartens and elementary schools reopen.
van Elsland S, Watson O, Alhaffar M, et al., 2020, Report 31: Estimating the burden of COVID-19 in Damascus, Syria: an analysis of novel data sources to infer mortality under-ascertainment
The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported substantially lower mortality rates than in Europe and the Americas. One hypothesis is that these countries have been ‘spared’, but another is that deaths have been under-ascertained (deaths that have been unreported due to any number of reasons, for instance due to limited testing capacity). However, the scale of under-ascertainment is difficult to assess with currently available data. In this analysis, we estimate the potential under-ascertainment of COVID-19 mortality in Damascus, Syria, where all-cause mortality data has been reported between 25th July and 1st August. We fit a mathematical model of COVID-19 transmission to reported COVID-19 deaths in Damascus since the beginning of the pandemic and compare the model-predicted deaths to reported excess deaths. Exploring a range of different assumptions about under-ascertainment, we estimate that only 1.25% of deaths (sensitivity range 1% - 3%) due to COVID-19 are reported in Damascus. Accounting for under-ascertainment also corroborates local reports of exceeded hospital bed capacity. To validate the epidemic dynamics inferred, we leverage community-uploaded obituary certificates as an alternative data source, which confirms extensive mortality under-ascertainment in Damascus between July and August. This level of under-ascertainment suggests that Damascus is at a much later stage in its epidemic than suggested by surveillance reports, which have repo. We estimate that 4,340 (95% CI: 3,250 - 5,540) deaths due to COVID-19 in Damascus may have been missed as of 2nd September 2020. Given that Damascus is likely to have the most robust surveillance in Syria, these findings suggest that other regions of the country could have experienced similar or worse mortality rates due to COVID-19.
Candido DS, Claro IM, de Jesus JG, et al., 2020, Evolution and epidemic spread of SARS-CoV-2 in Brazil, Science, Vol: 369, Pages: 1255-1260, ISSN: 0036-8075
Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.
Hogan A, Jewell B, Sherrard-Smith E, et al., 2020, Potential impact of the COVID-19 pandemic on HIV, TB and malaria in low- and middle-income countries: a modelling study, The Lancet Global Health, Vol: 8, Pages: e1132-e1141, ISSN: 2214-109X
Background: COVID-19 has the potential to cause substantial disruptions to health services, including by cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions in services for human immunodeficiency virus (HIV), tuberculosis (TB) and malaria in low- and middle-income countries with high burdens of those disease could lead to additional loss of life. Methods: We constructed plausible scenarios for the disruptions that could be incurred during the COVID-19 pandemic and used established transmission models for each disease to estimate the additional impact on health that could be caused in selected settings.Findings: In high burden settings, HIV-, TB- and malaria-related deaths over five years may increase by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 pandemic. We estimate the greatest impact on HIV to be from interruption to antiretroviral therapy, which may occur during a period of high health system demand. For TB, we estimate the greatest impact is from reductions in timely diagnosis and treatment of new cases, which may result from any prolonged period of COVID-19 suppression interventions. We estimate that the greatest impact on malaria burden could come from interruption of planned net campaigns. These disruptions could lead to loss of life-years over five years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV/TB epidemics.Interpretation: Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 pandemic.Funding: Bill & Melinda Gates Foundation, The Wellcome Trust, DFID, MRC
Lavezzo E, Franchin E, Ciavarella C, et al., 2020, Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo', Nature, Vol: 584, Pages: 425-429, ISSN: 0028-0836
On the 21st of February 2020 a resident of the municipality of Vo', a small town near Padua, died of pneumonia due to SARS-CoV-2 infection1. This was the first COVID-19 death detected in Italy since the emergence of SARS-CoV-2 in the Chinese city of Wuhan, Hubei province2. In response, the regional authorities imposed the lockdown of the whole municipality for 14 days3. We collected information on the demography, clinical presentation, hospitalization, contact network and presence of SARS-CoV-2 infection in nasopharyngeal swabs for 85.9% and 71.5% of the population of Vo' at two consecutive time points. On the first survey, which was conducted around the time the town lockdown started, we found a prevalence of infection of 2.6% (95% confidence interval (CI) 2.1-3.3%). On the second survey, which was conducted at the end of the lockdown, we found a prevalence of 1.2% (95% Confidence Interval (CI) 0.8-1.8%). Notably, 42.5% (95% CI 31.5-54.6%) of the confirmed SARS-CoV-2 infections detected across the two surveys were asymptomatic (i.e. did not have symptoms at the time of swab testing and did not develop symptoms afterwards). The mean serial interval was 7.2 days (95% CI 5.9-9.6). We found no statistically significant difference in the viral load of symptomatic versus asymptomatic infections (p-values 0.62 and 0.74 for E and RdRp genes, respectively, Exact Wilcoxon-Mann-Whitney test). This study sheds new light on the frequency of asymptomatic SARS-CoV-2 infection, their infectivity (as measured by the viral load) and provides new insights into its transmission dynamics and the efficacy of the implemented control measures.
Flaxman S, Mishra S, Gandy A, et al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, Vol: 584, Pages: 257-261, ISSN: 0028-0836
Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or subnational variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behavior. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number Rt below 1 (probability Rt< 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries, between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.
Perez Guzman PN, Daunt A, Mukherjee S, et al., 2020, Clinical characteristics and predictors of outcomes of hospitalized patients with COVID-19 in a multi-ethnic London NHS Trust: a retrospective cohort study, Clinical Infectious Diseases, Vol: 2020, Pages: 1-11, ISSN: 1058-4838
Background: Emerging evidence suggests ethnic minorities are disproportionatelyaffected by COVID-19. Detailed clinical analyses of multi-cultural hospitalized patientcohorts remain largely undescribed.Methods: We performed regression, survival andcumulative competing risk analyses to evaluate factors associated with mortality inpatients admitted for COVID-19 in three large London hospitals between February 25and April 5, censored as of May 1, 2020.Results: Of 614 patients (median age 69years, (IQR 25) and 62% male), 381 (62%) had been discharged alive, 178 (29%)died and 55 (9%) remained hospitalized at censoring. Severe hypoxemia (aOR 4.25,95%CI 2.36-7.64), leukocytosis (aOR 2.35, 95%CI 1.35-4.11), thrombocytopenia (aOR1.01, 95%CI 1.00-1.01, increase per 10x9decrease), severe renal impairment (aOR5.14, 95%CI 2.65-9.97), and low albumin (aOR 1.06, 95%CI 1.02-1.09, increase per gdecrease) were associated with death. Forty percent (244) were from black, Asian andother minority ethnic (BAME) groups, 38% (235) white and for 22% (135) ethnicity wasunknown. BAME patients were younger and had fewer comorbidities. Whilst theunadjusted odds of death did not differ by ethnicity, when adjusting for age, sex andcomorbidities, black patients were at higher odds of death compared to whites (aOR1.69, 95%CI 1.00-2.86). This association was stronger when further adjusting foradmission severity (aOR 1.85 95% CI 1.06-3.24). Conclusions: BAME patients were over-represented in our cohort and, whenaccounting for demographic and clinical profile of admission, black patients were atincreased odds of death. Further research is needed into biologic drivers of differencesin COVID-19 outcomes by ethnicity.
Gaythorpe KAM, Hamlet A, Cibrelus L, et al., 2020, The effect of climate change on yellow fever disease burden in Africa, eLife, Vol: 9, ISSN: 2050-084X
Yellow Fever (YF) is an arbovirus endemic in tropical regions of South America and Africa and it is estimated to cause 78,000 deaths a year in Africa alone. Climate change may have substantial effects on the transmission of YF and we present the first analysis of the potential impact on disease burden. We extend an existing model of YF transmission to account for rainfall and a temperature suitability index and project transmission intensity across the African endemic region in the context of four climate change scenarios. We use these transmission projections to assess the change in burden in 2050 and 2070. We find disease burden changes heterogeneously across the region. In the least severe scenario, we find a 93.0%[95%CI(92.7, 93.2%)] chance that annual deaths will increase in 2050. This change in epidemiology will complicate future control efforts. Thus, we may need to consider the effect of changing climatic variables on future intervention strategies.
Fu H, Xi X, Wang H, et al., 2020, Report 30: The COVID-19 epidemic trends and control measures in mainland China
Vollmer M, Radhakrishnan S, Kont M, et al., 2020, Report 29: The impact of the COVID-19 epidemic on all-cause attendances to emergency departments in two large London hospitals: an observational study
The health care system in England has been highly affected by the surge in demand due to patients afflicted by COVID-19. Yet the impact of the pandemic on the care seeking behaviour of patients and thus on Emergency department (ED) services is unknown, especially for non-COVID-19 related emergencies. In this report, we aimed to assess how the reorganisation of hospital care and admission policies to respond to the COVID-19 epidemic affected ED attendances and emergency hospital admissions. We performed time-series analyses of present year vs historic (2015-2019) trends of ED attendances between March 12 and May 31 at two large central London hospitals part of Imperial College Healthcare NHS Trust (ICHNT) and compared these to regional and national trends. Historic attendances data to ICHNT and publicly available NHS situation reports were used to calibrate time series auto-regressive integrated moving average (ARIMA) forecasting models. We thus predicted the (conterfactual) expected number of ED attendances between March 12 (when the first public health measure leading to lock-down started in England) to May 31, 2020 (when the analysis was censored) at ICHNT, at all acute London Trusts and nationally. The forecasted trends were compared to observed data for the same periods of time. Lastly, we analysed the trends at ICHNT disaggregating by mode of arrival, distance from postcode of patient residence to hospital and primary diagnosis amongst those that were subsequently admitted to hospital and compared these data to an average for the same period of time in the years 2015 to 2019.During the study period (January 1 to May 31, 2020) there was an overall decrease in ED attendances of 35% at ICHNT, of 50% across all London NHS Trusts and 53% nationally. For ICHNT, the decrease in attendances was mainly amongst those aged younger than 65 and those arriving by their own means (e.g. personal or public transport). Increasing distance (km) from postcode of residence to hospi
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