Publications
104 results found
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
Ainslie K, Walters C, Fu H, et al., 2020, Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment, Wellcome Open Research, ISSN: 2398-502X
Background : The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods : Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results : Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.
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.
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.
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
Forchini G, Lochen A, Hallett T, et al., 2020, Report 28: Excess non-COVID-19 deaths in England and Wales between 29th February and 5th June 2020
There were 189,403 deaths from any cause reported in England from 29th February to 5th June 2020 inclusive, and 11,278 all-cause deaths in Wales over the same period. Of those deaths, 44,736 (23.6%) registered COVID-19 on the death certificate in England, and 2,294 (20.3%) in Wales, while 144,667 (76.4%) were not recorded as having been due to COVID-19 in England, and 8,984 (79.7%) in Wales. However, it could be that some of the ‘non-COVID-19’ deaths have in fact also been caused by COVID-19, either as the direct cause of death, or indirectly through provisions for the pandemic impeding access to care for other conditions. There is uncertainty in how many of the non-COVID-19 deaths were directly or indirectly caused by the pandemic. We estimated the excess deaths that were not recorded as associated with COVID-19 in the death certificate (excess non-COVID-19 deaths) as the deaths for which COVID-19 was not reported as the cause, compared to those we would have expected to occur had the pandemic not happened. Expected deaths were forecast with an analysis of historic trends in deaths between 2010 and April 2020 using data by the Office of National Statistics and a statistical time series model. According to the model, we expected 136,294 (95% CI 133,882 - 138,696) deaths in England, and 8,983 (CI 8,051 - 9,904) in Wales over this period, significantly fewer than the number of deaths reported. This means that there were 8,983 (95% CI 5,971 - 10,785) total excess non-COVID-19 deaths in England. For every 100 COVID-19 deaths during the period from 29th February to 5th June 2020 there were between 13 and 24 cumulative excess non-COVID-19 deaths. The proportion of cumulative excess non-COVID-19 deaths of all reported deaths during this period was 4.4% (95% CI 3.2% - 5.7%) in England, with small regional variations. Excess deaths were highest in the South East at 2,213 (95% CI 327 - 4,047) and in London at 1,937 (95% CI 896 - 3,010), respectively. There is no e
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Estimating the number of undetected COVID-19 cases among travellers from mainland China, Publisher: F1000 Research Ltd
Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China.Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries.Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore; 75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected.Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
McCabe R, Schmit N, Christen P, et al., 2020, Report 27 Adapting hospital capacity to meet changing demands during the COVID-19 pandemic
To meet the growing demand for hospital care due to the COVID-19 pandemic, England implemented a range of hospital provision interventions including the procurement of equipment, the establishment of additional hospital facilities and the redeployment of staff and other resources. Additionally, to further release capacity across England’s National Health Service (NHS), elective surgery was cancelled in March 2020, leading to a backlog of patients requiring care. This created a pressure on the NHS to reintroduce elective procedures, which urgently needs to be addressed. Population-level measures implemented in March and April 2020 reduced transmission of SARS-CoV-2, prompting a gradual decline in the demand for hospital care by COVID-19 patients after the peak in mid-April. Planning capacity to bring back routine procedures for non-COVID-19 patients whilst maintaining the ability to respond to any potential future increases in demand for COVID-19 care is the challenge currently faced by healthcare planners.In this report, we aim to calculate hospital capacity for emergency treatment of COVID-19 and other patients during the pandemic surge in April and May 2020; to evaluate the increase in capacity achieved via five interventions (cancellation of elective surgery, field hospitals, use of private hospitals, and deployment of former and newly qualified medical staff); and to determine how to re-introduce elective surgery considering continued demand from COVID-19 patients. We do this by modelling the supply of acute NHS hospital care, considering different capacity scenarios, namely capacity before the pandemic (baseline scenario) and after the implementation of capacity expansion interventions that impact available general and acute (G&A) and critical care (CC) beds, staff and ventilators. Demand for hospital care is accounted for in terms of non-COVID-19 and COVID-19 patients. Our results suggest that NHS England would not have had sufficient daily capacity
Walker PGT, Whittaker C, Watson OJ, et al., 2020, The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries, Science, Vol: 369, Pages: 413-422, ISSN: 0036-8075
The ongoing COVID-19 pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower income countries may reduce overall risk but limited health system capacity coupled with closer inter-generational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower income countries due to the poorer health care available. Of countries that have undertaken suppression to date, lower income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being and economies of these countries.
Nouvellet P, Bhatia S, Cori A, et al., 2020, Report 26: Reduction in mobility and COVID-19 transmission
In response to the COVID-19 pandemic, countries have sought to control transmission of SARS-CoV-2by restricting population movement through social distancing interventions, reducing the number ofcontacts.Mobility data represent an important proxy measure of social distancing. Here, we develop aframework to infer the relationship between mobility and the key measure of population-level diseasetransmission, the reproduction number (R). The framework is applied to 53 countries with sustainedSARS-CoV-2 transmission based on two distinct country-specific automated measures of humanmobility, Apple and Google mobility data.For both datasets, the relationship between mobility and transmission was consistent within andacross countries and explained more than 85% of the variance in the observed variation intransmissibility. We quantified country-specific mobility thresholds defined as the reduction inmobility necessary to expect a decline in new infections (R<1).While social contacts were sufficiently reduced in France, Spain and the United Kingdom to controlCOVID-19 as of the 10th of May, we find that enhanced control measures are still warranted for themajority of countries. We found encouraging early evidence of some decoupling of transmission andmobility in 10 countries, a key indicator of successful easing of social-distancing restrictions.Easing social-distancing restrictions should be considered very carefully, as small increases in contactrates are likely to risk resurgence even where COVID-19 is apparently under control. Overall, strongpopulation-wide social-distancing measures are effective to control COVID-19; however gradualeasing of restrictions must be accompanied by alternative interventions, such as efficient contacttracing, to ensure control.
Verity R, Okell LC, Dorigatti I, et al., 2020, Estimates of the severity of coronavirus disease 2019: a model-based analysis., Lancet Infectious Diseases, Vol: 20, Pages: 669-677, ISSN: 1473-3099
BACKGROUND: In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. METHODS: We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. FINDINGS: Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9-19·2) and to hospital discharge to be 24·7 days (22·9-28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for cen
Dighe A, Cattarino L, Cuomo-Dannenburg G, et al., 2020, Report 25: Response to COVID-19 in South Korea and implications for lifting stringent interventions, 25
While South Korea experienced a sharp growth in COVID-19 cases early in the global pandemic, it has since rapidly reduced rates of infection and now maintains low numbers of daily new cases. Despite using less stringent “lockdown” measures than other affected countries, strong social distancing measures have been advised in high incidence areas and a 38% national decrease in movement occurred voluntarily between February 24th - March 1st. Suspected and confirmed cases were isolated quickly even during the rapid expansion of the epidemic and identification of the Shincheonji cluster. South Korea swiftly scaled up testing capacity and was able to maintain case-based interventions throughout. However, individual case-based contact tracing, not associated with a specific cluster, was a relatively minor aspect of their control program, with cluster investigations accounting for a far higher proportion of cases: the underlying epidemic was driven by a series of linked clusters, with 48% of all cases in the Shincheonji cluster and 20% in other clusters. Case-based contacts currently account for only 11% of total cases. The high volume of testing and low number of deaths suggests that South Korea experienced a small epidemic of infections relative to other countries. Therefore, caution is needed in attempting to duplicate the South Korean response in settings with larger more generalized epidemics. Finding, testing and isolating cases that are linked to clusters may be more difficult in such settings.
Jeffrey B, Walters C, Ainslie K, et al., 2020, Report 24: Mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK, 24
Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of socialdistancing policies, which have resulted in reduced mobility across different regions. Crowd level dataon mobile phone usage can be used as a proxy for actual population mobility patterns and provide away of quantifying the impact of social distancing measures on changes in mobility. Here, we use twomobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from theFacebook app on mobile phones) to assess changes in average mobility, both overall and broken downinto high and low population density areas, and changes in the distribution of journey lengths. Weshow that there was a substantial overall reduction in mobility with the most rapid decline on the 24thMarch 2020, the day after the Prime Minister’s announcement of an enforced lockdown. Thereduction in mobility was highly synchronized across the UK. Although mobility has remained low since26th March 2020, we detect a gradual increase since that time. We also show that the two differentdatasets produce similar trends, albeit with some location-specific differences. We see slightly largerreductions in average mobility in high-density areas than in low-density areas, with greater variationin mobility in the high-density areas: some high-density areas eliminated almost all mobility. We areonly able to observe populations living in locations where sufficient number of people use Facebookor a device connected to the relevant provider’s network such that no individual is identifiable. Theseanalyses form a baseline with which to monitor changes in behaviour in the UK as social distancing iseased.
Winskill P, Whittaker C, Walker P, et al., 2020, Report 22: Equity in response to the COVID-19 pandemic: an assessment of the direct and indirect impacts on disadvantaged and vulnerable populations in low- and lower middle-income countries, 22
The impact of the COVID-19 pandemic in low-income settings is likely to be more severe due to limited healthcare capacity. Within these settings, however, there exists unfair or avoidable differences in health among different groups in society – health inequities – that mean that some groups are particularly at risk from the negative direct and indirect consequences of COVID-19. The structural determinants of these are often reflected in differences by income strata, with the poorest populations having limited access to preventative measures such as handwashing. Their more fragile income status will also mean that they are likely to be employed in occupations that are not amenable to social-distancing measures, thereby further reducing their ability to protect themselves from infection. Furthermore, these populations may also lack access to timely healthcare on becoming ill. We explore these relationships by using large-scale household surveys to quantify the differences in handwashing access, occupation and hospital access with respect to wealth status in low-income settings. We use a COVID-19 transmission model to demonstrate the impact of these differences. Our results demonstrate clear trends that the probability of death from COVID-19 increases with increasing poverty. On average, we estimate a 32.0% (2.5th-97.5th centile 8.0%-72.5%) increase in the probability of death in the poorest quintile compared to the wealthiest quintile from these three factors alone. We further explore how risk mediators and the indirect impacts of COVID-19 may also hit these same disadvantaged and vulnerable the hardest. We find that larger, inter-generational households that may hamper efforts to protect the elderly if social distancing are associated with lower-income countries and, within LMICs, lower wealth status. Poorer populations are also more susceptible to food security issues - with these populations having the highest levels under-nourishment whilst also being
Vollmer M, Mishra S, Unwin J, et al., 2020, A sub-national analysis of the rate of transmission of COVID-19 in Italy, medRxiv
Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could le
Mellan T, Hoeltgebaum H, Mishra S, et al., 2020, Report 21: Estimating COVID-19 cases and reproduction number in Brazil
Brazil is an epicentre for COVID-19 in Latin America. In this report we describe the Brazilian epidemicusing three epidemiological measures: the number of infections, the number of deaths and the reproduction number. Our modelling framework requires sufficient death data to estimate trends, and wetherefore limit our analysis to 16 states that have experienced a total of more than fifty deaths. Thedistribution of deaths among states is highly heterogeneous, with 5 states—São Paulo, Rio de Janeiro,Ceará, Pernambuco and Amazonas—accounting for 81% of deaths reported to date. In these states, weestimate that the percentage of people that have been infected with SARS-CoV-2 ranges from 3.3% (95%CI: 2.8%-3.7%) in São Paulo to 10.6% (95% CI: 8.8%-12.1%) in Amazonas. The reproduction number (ameasure of transmission intensity) at the start of the epidemic meant that an infected individual wouldinfect three or four others on average. Following non-pharmaceutical interventions such as school closures and decreases in population mobility, we show that the reproduction number has dropped substantially in each state. However, for all 16 states we study, we estimate with high confidence that thereproduction number remains above 1. A reproduction number above 1 means that the epidemic isnot yet controlled and will continue to grow. These trends are in stark contrast to other major COVID19 epidemics in Europe and Asia where enforced lockdowns have successfully driven the reproductionnumber below 1. While the Brazilian epidemic is still relatively nascent on a national scale, our resultssuggest that further action is needed to limit spread and prevent health system overload.
Vollmer M, Mishra S, Unwin H, et al., 2020, Report 20: A sub-national analysis of the rate of transmission of Covid-19 in Italy
Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28; 238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a
Sherrard-Smith E, Hogan A, Hamlet A, et al., 2020, Report 18: The potential public health impact of COVID-19 on malaria in Africa.
The COVID-19 pandemic is likely to severely interrupt health systems in Sub-Saharan Africa (SSA) over the coming weeks and months. Approximately 90% of malaria deaths occur in this region of the world, with an estimated 380,000 deaths from malaria in 2018. Much of the gain made in malaria control over the last decade has been due to the distribution of long-lasting insecticide treated nets (LLINs). Many SSA countries planned to distribute these in 2020. We used COVID-19 and malaria transmission models to understand the likely impact that disruption to these distributions, alongside other core health services, could have on the malaria burden. Results indicate that if all malaria-control activities are highly disrupted then the malaria burden in 2020 could more than double that in the previous year, resulting in large malaria epidemics across the region. These will depend on the course of the COVID-19 epidemic and how it interrupts local health system. Our results also demonstrate that it is essential to prioritise the LLIN distributions either before or as soon as possible into local COVID-19 epidemics to mitigate this risk. Additional planning to ensure other malaria prevention activities are continued where possible, alongside planning to ensure basic access to antimalarial treatment, will further minimise the risk of substantial additional malaria mortality.
MRC Centre for Global Infectious Disease Analysis, Ghani A, Walker P, 2020, COVID-19 Scenario Analysis Tool
COVID-19 Scenario Analysis Tool. MRC Centre for Global Infectious Disease Analysis, Imperial College London. Available at: covidsim.org. The COVID-19 Scenario Analysis Tool enables users to quickly and easily generate calibrated forward scenarios of the COVID-19 epidemic in individual countries under different control scenarios.The tool utilises an age-structured SEIR model incorporating explicit passage through disease severity settings and healthcare. Details of the model and its baseline parameters are given below. The work builds from the work reported in Report 12 – “The global impact of COVID-19 and strategies for mitigation and suppression”. A parallel R package – squire – is available from the MRC Centre for Infectious Disease Analysis GitHub site for academic purposes. The model is calibrated to the cumulative COVID-19 deaths reported to date, obtained from the European Centres for Disease Control. The COVID-19 Scenario Analysis Tool uses an age-structured SEIR model, with the infectious class divided into different stages reflecting progression through different disease severity pathways.
Perez Guzman PN, Daunt A, Mukherjee S, et al., 2020, Report 17: Clinical characteristics and predictors of outcomes of hospitalised patients with COVID-19 in a London NHS Trust: a retrospective cohort study
Clinical characteristics and determinants of outcomes for hospitalised COVID-19 patients in the UK remain largely undescribed and emerging evidence suggests ethnic minorities might be disproportionately affected. We describe the characteristics and outcomes of patients hospitalised for COVID-19 in three large London hospitals with a multi-ethnic catchment population.We performed a retrospective cohort study on all patients hospitalised with laboratory-confirmed SARS-CoV-2 infection at Imperial College Healthcare NHS Trust between February 25 and April 5, 2020. Outcomes were recorded as of April 19, 2020. Logistic regression models, survival analyses and cumulative competing risk analyses were performed to evaluate factors associated with COVID-19 hospital mortality.Of 520 patients in this cohort (median age 67 years, (IQR 26) and 62% male), 302 (68%) had been discharged alive, 144 (32%) died and 74 (14%) were still hospitalised at the time of censoring. Increasing age (adjusted odds ratio [aOR] 2·16, 95%CI 1·50-3·12), severe hypoxia (aOR 3·75, 95%CI 1·80-7·80), low platelets (aOR 0·65, 95%CI 0.49·0·85), reduced estimated glomerular filtration rate (aOR 4·11, 95%CI 1·58-10·69), bilirubin >21mmol/L (aOR 2·32, 95%CI 1·05-5·14) and low albumin (aOR 0·77, 9%%CI 0·59-1·01) were associated with increased risk of in-hospital mortality. Individual comorbidities were not independently associated with risk of death. Regarding ethnicity, 209 (40%) were from a black and Asian minority, for 115 (22%) ethnicity was unknown and 196 (38%) patients were white. Compared to the latter, black patients were significantly younger and had less comorbidities. Whilst the crude OR of death of black compared to white patients was not significant (1·14, 95%CI 0·69-1·88, p=0.62), adjusting for age and comorbidity showed a trend towards significance
Ainslie KEC, Walters CE, Fu H, et al., 2020, Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment [version 1; peer review: 2 approved], Wellcome Open Res, Vol: 5, ISSN: 2398-502X
Background: The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods: Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results: Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.
Grassly N, Pons Salort M, Parker E, et al., 2020, Report 16: Role of testing in COVID-19 control
The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups.
Christen P, D'Aeth J, Lochen A, et al., 2020, Report 15: Strengthening hospital capacity for the COVID-19 pandemic
Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for COVID-19, and other conditions, is one of the most challenging tasks facing healthcare commissioners and care providers during the pandemic. Due to uncertainty in expected patient numbers requiring care, as well as evolving needs day by day, planning hospital capacity is challenging. Health systems that are well prepared for the pandemic can better cope with large and sudden changes in demand by implementing strategies to ensure adequate access to care. Thereby the burden of the pandemic can be mitigated, and many lives saved. This report presents the J-IDEA pandemic planner, a hospital planning tool to calculate how much capacity in terms of beds, staff and ventilators is obtained by implementing healthcare provision interventions affecting the management of patient care in hospitals. We show how to assess baseline capacity, and then calculate how much capacity is gained by various healthcare interventions using impact estimates that are generated as part of this study. Interventions are informed by a rapid review of policy decisions implemented or being considered in 12 European countries over the past few months , an evaluation of the impact of the interventions on capacity using a variety of research methods, and by a review of key parameters in the care of COVID-19 patients.The J-IDEA planner is publicly available, interactive and adaptable to different and changing circumstances and newly emerging evidence. The planner estimates the additional number of beds, medical staff and crucial medical equipment obtained under various healthcare interventions using flexible inputs on assumptions of existing capacities, the number of hospitalisations, beds-to-staff ratios, and staff absences due to COVID-19. A detailed user guide accompanies the planner. The planner was developed rapidly and has limitations which we will address in future iterations. It support
Pristera P, Papageorgiou V, Kaur M, et al., 2020, Report 14: Online community involvement in COVID-19 research & outbreak response: early insights from a UK perspective
The Patient Experience Research Centre (PERC) at Imperial College London is developing research to explore and understand people’s views about, experiences of and behavioural responses to the outbreak in the UK and elsewhere. To guide that effort and to help inform COVID-19 research and responses more broadly - for example in mathematical modelling and policy - PERC launched an online community involvement initiative that sought rapid, early insight from members of the public and aimed to establish a network for ongoing community engagement.Priority areas for COVID-19 research Vaccine development was considered the most urgent research priority for many respondents. Social studies exploring the public’s experiences, risk perceptions and behaviours during this outbreak were necessary and important according to 95% of the respondents. Such research could:Improve the way the current outbreak response is planned and implemented;Improve the way information and guidance is provided to and understood by the public;Optimise the support provided to communities and vulnerable groups; andImprove future outbreak preparedness.Other recommended areas of research included:Understanding the role of the media in influencing how people react and respond;Furthering our basic understanding of the virus – how it spreads, who it affects the most and why, and whether people achieve and maintain immunity after being infected;Critiquing the UK’s response to the pandemic against that of other countries; andEnsuring lessons can be learnt from this outbreak to better equip us for future outbreaks, and public health emergencies in general.Key unmet needs amongst communities The main challenges described by respondents were ineffective communication, including access to information and information overload; and conflicting guidance and misinformation. Respondents’ described feelings of concern, confusion and, in some cases, panic as a result of these communication a
Imai N, Gaythorpe KAM, Abbott S, et al., 2020, Adoption and impact of non-pharmaceutical interventions for COVID-19, Wellcome Open Research, Vol: 5, ISSN: 2398-502X
Background: Several non-pharmaceutical interventions (NPIs) have been implemented across the world to control the coronavirus disease (COVID-19) pandemic. Social distancing (SD) interventions applied so far have included school closures, remote working and quarantine. These measures have been shown to have large impacts on pandemic influenza transmission. However, there has been comparatively little examination of such measures for COVID-19.Methods: We examined the existing literature, and collated data, on implementation of NPIs to examine their effects on the COVID-19 pandemic so far. Data on NPIs were collected from official government websites as well as from media sources.Results: Measures such as travel restrictions have been implemented in multiple countries and appears to have slowed the geographic spread of COVID-19 and reduced initial case numbers. We find that, due to the relatively sparse information on the differences with and without interventions, it is difficult to quantitatively assess the efficacy of many interventions. Similarly, whilst the comparison to other pandemic diseases such as influenza can be helpful, there are key differences that could affect the efficacy of similar NPIs.Conclusions: The timely implementation of control measures is key to their success and must strike a balance between early enough application to reduce the peak of the epidemic and ensuring that they can be feasibly maintained for an appropriate duration. Such measures can have large societal impacts and they need to be appropriately justified to the population. As the pandemic of COVID-19 progresses, quantifying the impact of interventions will be a vital consideration for the appropriate use of mitigation strategies.
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