Imperial College London

Amy Dighe

Faculty of MedicineSchool of Public Health

Research Postgraduate
 
 
 
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a.dighe16

 
 
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Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

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19 results found

Dighe A, Cattarino L, Cuomo-Dannenburg G, Skarp J, Imai N, Bhatia S, Gaythorpe K, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cooper L, Coupland H, Cucunuba Perez Z, Dorigatti I, Eales O, van Elsland S, Fitzjohn R, Green W, Haw D, Hinsley W, Knock E, Laydon D, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Pons Salort M, Thompson H, Unwin H, Verity R, Vollmer M, Walters C, Watson O, Whittaker C, Whittles L, Ghani A, Donnelly C, Ferguson N, Riley Set 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

Journal article

Hogan A, Jewell B, Sherrard-Smith E, Watson O, Whittaker C, Hamlet A, Smith J, Winskill P, Verity R, Baguelin M, Lees J, Whittles L, Ainslie K, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Eaton J, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Haw D, Hayes S, Hinsley W, Imai N, Laydon D, Mangal T, Mellan T, Mishra S, Parag K, Thompson H, Unwin H, Vollmer M, Walters C, Wang H, Ferguson N, Okell L, Churcher T, Arinaminpathy N, Ghani A, Walker P, Hallett Tet 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

Journal article

Flaxman S, Mishra S, Gandy A, Unwin HJT, Mellan TA, Coupland H, Whittaker C, Zhu H, Berah T, Eaton JW, Monod M, Perez Guzman PN, Schmit N, Cilloni L, Ainslie K, Baguelin M, Boonyasiri A, Boyd O, Cattarino L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, van Elsland S, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hallett T, Hamlet A, Hinsley W, Jeffrey B, Knock E, Laydon D, Nedjati Gilani G, Nouvellet P, Parag K, Siveroni I, Thompson H, Verity R, Volz E, Walters C, Wang H, Watson O, Winskill P, Xi X, Walker P, Ghani AC, Donnelly CA, Riley SM, Vollmer MAC, Ferguson NM, Okell LC, Bhatt Set 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.

Journal article

Prete CA, Buss L, Porto VB, Candido DDS, Ghilardi F, Dighe A, Donnelly CA, Pybus OG, Brady O, Croda JHR, Faria NR, Sabino EC, Nascimento VHet al., 2020, Serial Interval Distribution of SARS-CoV-2 Infection in Brazil, Journal of Travel Medicine, ISSN: 1195-1982

<jats:p>Using 65 transmission pairs of SARS-CoV-2 reported to the Brazilian Ministry of Health we estimate the mean and standard deviation for the serial interval to be 2.97 and 3.29 days respectively. We also present a model for the serial interval probability distribution using only two parameters.</jats:p>

Journal article

Nouvellet P, Bhatia S, Cori A, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, Eales O, van Elsland S, Nscimento F, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hamlet A, Hauck K, Hinsley W, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Nedjati Gilani G, Parag K, Pons Salort M, Ragonnet-Cronin M, Riley S, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Wang H, Watson O, Whittaker C, Whittles L, Xi X, Ferguson N, Donnelly Cet 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.

Report

Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, Cuomo-Dannenburg G, Thompson H, Walker PGT, Fu H, Dighe A, Griffin JT, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunubá Z, FitzJohn R, Gaythorpe K, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Riley S, van Elsland S, Volz E, Wang H, Wang Y, Xi X, Donnelly CA, Ghani AC, Ferguson NMet 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

Journal article

Dighe A, Cattarino L, Cuomo-Dannenburg G, Skarp J, Imai N, Bhatia S, Gaythorpe K, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Charles G, Cooper L, Coupland H, Cucunuba Perez Z, Djaafara A, Dorigatti I, Eales O, Eaton J, van Elsland S, Ferreira Do Nascimento F, Fitzjohn R, Flaxman S, Fraser K, Geidelberg L, Green W, Hallett T, Hamlet A, Hauck K, Haw D, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag K, Pons Salort M, Ragonnet-Cronin M, Thompson H, Unwin H, Verity R, Whittaker C, Whittles L, Xi X, Ghani A, Donnelly C, Ferguson N, Riley Set 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.

Report

Mellan T, Hoeltgebaum H, Mishra S, Whittaker C, Schnekenberg R, Gandy A, Unwin H, Vollmer M, Coupland H, Hawryluk I, Rodrigues Faria N, Vesga J, Zhu H, Hutchinson M, Ratmann O, Monod M, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Fraser K, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Okell L, Dorigatti I, Walker P, Ghani A, Riley S, Ferguson N, Donnelly C, Flaxman S, Bhatt Set 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.

Report

Vollmer M, Mishra S, Unwin H, Gandy A, Melan T, Bradley V, Zhu H, Coupland H, Hawryluk I, Hutchinson M, Ratmann O, Monod M, Walker P, Whittaker C, Cattarino L, Ciavarella C, Cilloni L, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Ghani A, Riley S, Okell L, Donnelly C, Ferguson N, Dorigatti I, Flaxman S, Bhatt Set 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

Report

Hogan A, Jewell B, Sherrard-Smith E, Vesga J, Watson O, Whittaker C, Hamlet A, Smith J, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Charles G, Cooper L, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Dorigatti I, Eaton J, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Haw D, Hayes S, Hinsley W, Imai N, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Ower A, Parag K, Pickles M, Stopard I, Thompson H, Unwin H, Verity R, Vollmer M, Walters C, Wang H, Wang Y, Whittles L, Winskill P, Xi X, Ferguson N, Churcher T, Arinaminpathy N, Ghani A, Walker P, Hallett Tet al., 2020, Report 19: The potential impact of the COVID-19 epidemic on HIV, TB and malaria in low- and middle-income countries

COVID-19 has the potential to cause disruptions to health services in different ways; through the health system becoming overwhelmed with COVID-19 patients, through the intervention used to slow transmission of COVID-19 inhibiting access to preventative interventions and services, and through supplies of medicine being interrupted. We aim to quantify the extent to which such disruptions in services for HIV, TB and malaria in high burden low- and middle-income countries could lead to additional loss of life. In high burden settings, HIV, TB and malaria related deaths over 5 years may be increased by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 epidemic. We estimate the greatest impact on HIV to be from interruption to ART, which may occur during a period of high or extremely 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 a long period of COVID-19 suppression interventions; for malaria, we estimate that the greatest impact could come from reduced prevention activities including interruption of planned net campaigns, through all phases of the COVID-19 epidemic. In high burden settings, the impact of each type of disruption could be significant and lead to a 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. Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 epidemic.

Report

Ainslie KEC, Walters CE, Fu H, Bhatia S, Wang H, Xi X, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cucunuba Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, van Elsland SL, FitzJohn R, Gaythorpe K, Ghani AC, Green W, Hamlet A, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Nedjati-Gilani G, Okell LC, Siveroni I, Thompson HA, Unwin HJT, Verity R, Vollmer M, Walker PGT, Wang Y, Watson OJ, Whittaker C, Winskill P, Donnelly CA, Ferguson NM, Riley Set 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.

Journal article

Grassly N, Pons Salort M, Parker E, White P, Ainslie K, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Ciavarella C, Cooper L, Coupland H, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Dorigatti I, van Elsland S, Ferreira Do Nascimento F, Fitzjohn R, Fu H, Gaythorpe K, Geidelberg L, Green W, Hallett T, Hamlet A, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Ower A, Parag K, Pickles M, Ragonnet-Cronin M, Stopard I, Thompson H, Unwin H, Verity R, Vollmer M, Volz E, Walker P, Walters C, Wang H, Wang Y, Watson O, Whittaker C, Whittles L, Winskill P, Xi X, Ferguson Net 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.

Report

Flaxman S, Mishra S, Gandy A, Unwin H, Coupland H, Mellan T, Zhu H, Berah T, Eaton J, Perez Guzman P, Schmit N, Cilloni L, Ainslie K, Baguelin M, Blake I, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hallett T, Hamlet A, Hinsley W, Jeffrey B, Jorgensen D, Knock E, Laydon D, Nedjati Gilani G, Nouvellet P, Parag K, Siveroni I, Thompson H, Verity R, Volz E, Walters C, Wang H, Wang Y, Watson O, Winskill P, Xi X, Whittaker C, Walker P, Ghani A, Donnelly C, Riley S, Okell L, Vollmer M, Ferguson N, Bhatt Set al., 2020, Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproducti

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Walker P, Whittaker C, Watson O, Baguelin M, Ainslie K, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Donnelly C, Dorigatti I, van Elsland S, Fitzjohn R, Flaxman S, Fu H, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hamlet A, Hauck K, Haw D, Hayes S, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Mishra S, Nedjati Gilani G, Okell L, Riley S, Thompson H, Unwin H, Verity R, Vollmer M, Walters C, Wang H, Wang Y, Winskill P, Xi X, Ferguson N, Ghani Aet al., 2020, Report 12: The global impact of COVID-19 and strategies for mitigation and suppression

The world faces a severe and acute public health emergency due to the ongoing COVID-19 global pandemic. How individual countries respond in the coming weeks will be critical in influencing the trajectory of national epidemics. Here we combine data on age-specific contact patterns and COVID-19 severity to project the health impact of the pandemic in 202 countries. We compare predicted mortality impacts in the absence of interventions or spontaneous social distancing with what might be achieved with policies aimed at mitigating or suppressing transmission. Our estimates of mortality and healthcare demand are based on data from China and high-income countries; differences in underlying health conditions and healthcare system capacity will likely result in different patterns in low income settings. We estimate that in the absence of interventions, COVID-19 would have resulted in 7.0 billion infections and 40 million deaths globally this year. Mitigation strategies focussing on shielding the elderly (60% reduction in social contacts) and slowing but not interrupting transmission (40% reduction in social contacts for wider population) could reduce this burden by half, saving 20 million lives, but we predict that even in this scenario, health systems in all countries will be quickly overwhelmed. This effect is likely to be most severe in lower income settings where capacity is lowest: our mitigated scenarios lead to peak demand for critical care beds in a typical low-income setting outstripping supply by a factor of 25, in contrast to a typical high-income setting where this factor is 7. As a result, we anticipate that the true burden in low income settings pursuing mitigation strategies could be substantially higher than reflected in these estimates. Our analysis therefore suggests that healthcare demand can only be kept within manageable levels through the rapid adoption of public health measures (including testing and isolation of cases and wider social distancing meas

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Ainslie K, Walters C, Fu H, Bhatia S, Wang H, Baguelin M, Bhatt S, Boonyasiri A, Boyd O, Cattarino L, Ciavarella C, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, van Elsland S, Fitzjohn R, Gaythorpe K, Geidelberg L, Ghani A, Green W, Hamlet A, Hinsley W, Imai N, Jorgensen D, Knock E, Laydon D, Nedjati Gilani G, Okell L, Siveroni I, Thompson H, Unwin H, Verity R, Vollmer M, Walker P, Wang Y, Watson O, Whittaker C, Winskill P, Xi X, Donnelly C, Ferguson N, Riley Set al., 2020, Report 11: Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment

The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. As of 20 March 2020, over 254,000 cases and 10,000 deaths had been reported worldwide. The outbreak began in the Chinese city of Wuhan in December 2019. In response to the fast-growing epidemic, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. At the peak of the outbreak in China (early February), there were between 2,000 and 4,000 new confirmed cases per day. For the first time since the outbreak began there have been no new confirmed cases caused by local transmission in China reported for five consecutive days up to 23 March 2020. This is an indication that the social distancing measures enacted in China have led to control of COVID-19 in China. These interventions have also impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic is not yet clear. Here, we estimate transmissibility from reported cases and compare those estimates with daily data on within-city movement, as a proxy for economic activity. Initially, within-city movement and transmission were very strongly correlated in the 5 provinces most affected by the epidemic and Beijing. However, that correlation is no longer apparent even though within-city movement has started to increase. A similar analysis for Hong Kong shows that intermediate levels of local activity can be maintained while avoiding a large outbreak. These results do not preclude future epidemics in China, nor do they allow us to estimate the maximum proportion of previous within-city activity that will be recovered in the medium term. However, they do suggest that after very intense social distancing which resulted in containment, China has successfully exited their stringent social distancing policy to some degree. Globally, China is at a more advanced stage of the pandemic. Policies implemented to reduce the spread of CO

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Ferguson N, Laydon D, Nedjati Gilani G, Imai N, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Dorigatti I, Fu H, Gaythorpe K, Green W, Hamlet A, Hinsley W, Okell L, van Elsland S, Thompson H, Verity R, Volz E, Wang H, Wang Y, Walker P, Walters C, Winskill P, Whittaker C, Donnelly C, Riley S, Ghani Aet al., 2020, Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand

The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally requi

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Gaythorpe K, Imai N, Cuomo-Dannenburg G, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunuba Perez Z, Dighe A, Dorigatti I, Fitzjohn R, Fu H, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati Gilani G, Okell L, Riley S, Thompson H, van Elsland S, Volz E, Wang H, Wang Y, Whittaker C, Xi X, Donnelly C, Ghani A, Ferguson Net al., 2020, Report 8: Symptom progression of COVID-19

The COVID-19 epidemic was declared a Public Health Emergency of International Concern (PHEIC) by WHO on 30th January 2020 [1]. As of 8 March 2020, over 107,000 cases had been reported. Here, we use published and preprint studies of clinical characteristics of cases in mainland China as well as case studies of individuals from Hong Kong, Japan, Singapore and South Korea to examine the proportional occurrence of symptoms and the progression of symptoms through time.We find that in mainland China, where specific symptoms or disease presentation are reported, pneumonia is the most frequently mentioned, see figure 1. We found a more varied spectrum of severity in cases outside mainland China. In Hong Kong, Japan, Singapore and South Korea, fever was the most frequently reported symptom. In this latter group, presentation with pneumonia is not reported as frequently although it is more common in individuals over 60 years old. The average time from reported onset of first symptoms to the occurrence of specific symptoms or disease presentation, such as pneumonia or the use of mechanical ventilation, varied substantially. The average time to presentation with pneumonia is 5.88 days, and may be linked to testing at hospitalisation; fever is often reported at onset (where the mean time to develop fever is 0.77 days).

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Thompson H, Imai N, Dighe A, Baguelin M, Bhatia S, Boonyasiri A, Cori A, Cucunuba Perez Z, Cuomo-Dannenburg G, Dorigatti I, Fitzjohn R, Fu H, Gaythorpe K, Ghani A, Green W, Hamlet A, Hinsley W, Laydon D, Nedjati Gilani G, Okell L, Riley S, van Elsland S, Volz E, Wang H, Yuanrong W, Whittaker C, Xi X, Donnelly C, Ferguson Net al., 2020, Report 7: Estimating infection prevalence in Wuhan City from repatriation flights

Since the end of January 2020, in response to the growing COVID-19 epidemic, 55 countries have repatriated over 8000 citizens from Wuhan City, China. In addition to quarantine measures for returning citizens, many countries implemented PCR screening to test for infection regardless of symptoms. These flights therefore give estimates of infection prevalence in Wuhan over time. Between 30th January and 1st February (close to the peak of the epidemic in Wuhan), infection prevalence was 0.87% (95% CI: 0.32% - 1.89%). As countries now start to repatriate citizens from Iran and northern Italy, information from repatriated citizens could help inform the level of response necessary to help control the outbreaks unfolding in newly affected areas.

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Dighe A, Jombart T, Van Kerkhove MD, Ferguson Net al., 2019, A systematic review of MERS-CoV seroprevalence and RNA prevalence in dromedary camels: implications for animal vaccination, Epidemics, Vol: 29, ISSN: 1755-4365

Human infection with Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is driven by recurring dromedary-to-human spill-over events, leading decision-makers to consider dromedary vaccination. Dromedary vaccine candidates in the development pipeline are showing hopeful results, but gaps in our understanding of the epidemiology of MERS-CoV in dromedaries must be addressed to design and evaluate potential vaccination strategies. We aim to bring together existing measures of MERS-CoV infection in dromedary camels to assess the distribution of infection, highlighting knowledge gaps and implications for animal vaccination. We systematically reviewed the published literature on MEDLINE, EMBASE and Web of Science that reported seroprevalence and/or prevalence of active MERS-CoV infection in dromedary camels from both cross-sectional and longitudinal studies. 60 studies met our eligibility criteria. Qualitative syntheses determined that MERS-CoV seroprevalence increased with age up to 80–100% in adult dromedaries supporting geographically widespread endemicity of MERS-CoV in dromedaries in both the Arabian Peninsula and countries exporting dromedaries from Africa. The high prevalence of active infection measured in juveniles and at sites where dromedary populations mix should guide further investigation – particularly of dromedary movement – and inform vaccination strategy design and evaluation through mathematical modelling.

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