Imperial College London

DrOliverWatson

Faculty of MedicineSchool of Public Health

Research Associate
 
 
 
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Contact

 

+44 (0)7747 434 948o.watson15

 
 
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Location

 

Praed StreetSt Mary's Campus

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Summary

 

Publications

Publication Type
Year
to

78 results found

Smith TP, Flaxman S, Gallinat AS, Kinosian SP, Stemkovski M, Unwin HJT, Watson OJ, Whittaker C, Cattarino L, Dorigatti I, Tristem M, Pearse WDet al., 2021, Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions., Proc Natl Acad Sci U S A, Vol: 118

As COVID-19 continues to spread across the world, it is increasingly important to understand the factors that influence its transmission. Seasonal variation driven by responses to changing environment has been shown to affect the transmission intensity of several coronaviruses. However, the impact of the environment on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains largely unknown, and thus seasonal variation remains a source of uncertainty in forecasts of SARS-CoV-2 transmission. Here we address this issue by assessing the association of temperature, humidity, ultraviolet radiation, and population density with estimates of transmission rate (R). Using data from the United States, we explore correlates of transmission across US states using comparative regression and integrative epidemiological modeling. We find that policy intervention ("lockdown") and reductions in individuals' mobility are the major predictors of SARS-CoV-2 transmission rates, but, in their absence, lower temperatures and higher population densities are correlated with increased SARS-CoV-2 transmission. Our results show that summer weather cannot be considered a substitute for mitigation policies, but that lower autumn and winter temperatures may lead to an increase in transmission intensity in the absence of policy interventions or behavioral changes. We outline how this information may improve the forecasting of COVID-19, reveal its future seasonal dynamics, and inform intervention policies.

Journal article

FitzJohn RG, Knock ES, Whittles LK, Perez-Guzman PN, Bhatia S, Guntoro F, Watson OJ, Whittaker C, Ferguson NM, Cori A, Baguelin M, Lees JAet al., 2021, Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate, Wellcome Open Research, Vol: 5, Pages: 288-288

<ns4:p>State space models, including compartmental models, are used to model physical, biological and social phenomena in a broad range of scientific fields. A common way of representing the underlying processes in these models is as a system of stochastic processes which can be simulated forwards in time. Inference of model parameters based on observed time-series data can then be performed using sequential Monte Carlo techniques. However, using these methods for routine inference problems can be made difficult due to various engineering considerations: allowing model design to change in response to new data and ideas, writing model code which is highly performant, and incorporating all of this with up-to-date statistical techniques. Here, we describe a suite of packages in the R programming language designed to streamline the design and deployment of state space models, targeted at infectious disease modellers but suitable for other domains. Users describe their model in a familiar domain-specific language, which is converted into parallelised C++ code. A fast, parallel, reproducible random number generator is then used to run large numbers of model simulations in an efficient manner. We also provide standard inference and prediction routines, though the model simulator can be used directly if these do not meet the user’s needs. These packages provide guarantees on reproducibility and performance, allowing the user to focus on the model itself, rather than the underlying computation. The ability to automatically generate high-performance code that would be tedious and time-consuming to write and verify manually, particularly when adding further structure to compartments, is crucial for infectious disease modellers. Our packages have been critical to the development cycle of our ongoing real-time modelling efforts in the COVID-19 pandemic, and have the potential to do the same for models used in a number of different domains.</ns4:p>

Journal article

Mangal T, Whittaker C, Nkhoma D, Ng'ambi W, Watson O, Walker P, Ghani A, Revill P, Colbourn T, Phillips A, Hallett T, Mfusto-Bengo Jet al., 2021, The potential impact of intervention strategies on COVID-19 transmission in Malawi: A mathematical modelling study, BMJ Open, ISSN: 2044-6055

BackgroundCOVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity.MethodsThe infection fatality ratios (IFR) were predicted by adjusting reported IFR for China accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions and increases in health system capacity. Findings The predicted population-level IFR in Malawi, adjusted for age and comorbidity prevalence, is lower than estimated for China (0.26%, 95% uncertainty interval [UI] 0.12 – 0.69%, compared with 0.60%, 95% CI 0.4% – 1.3% in China), however the health system constraints increase the predicted IFR to 0.83%, 95% UI 0.49% – 1.39%. The interventions implemented in January 2021 could potentially avert 54,400 deaths (95% UI 26,900 – 97,300) over the course of the epidemic compared with an unmitigated outbreak. Enhanced shielding of people aged ≥ 60 years could avert a further 40,200 deaths (95% UI 25,300 – 69,700) and halve ICU admissions at the peak of the outbreak. A novel therapeutic agent, which reduces mortality by 0.65 and 0.8 for severe and critical cases respectively, in combination with increasing hospital capacity could reduce projected mortality to 2.5 deaths per 1,000 population (95% UI 1.9 – 3.6).ConclusionWe find the interventions currently used in Malawi are unlikely to effectively prevent SARS-CoV-2 transmission but will have a significant impact on mortality. Increases in health system capacity and the introduction of novel therapeutics are likely to further reduce the projected numbers of deaths.

Journal article

Djaafara A, Whittaker C, Watson OJ, Verity R, Brazeau N, Widyastuti, Oktavia D, Adrian V, Salama N, Bhatia S, Nouvellet P, Sherrard-Smith E, Churcher T, Surendra H, Lina RN, Ekawati LL, Lestari KD, Andrianto A, Thwaites G, Baird JK, Ghani A, Elyazar IRF, Walker Pet al., 2021, Using syndromic measures of mortality to capture the dynamics of COVID-19 in Java, Indonesia in the context of vaccination roll-out, BMC Medicine, ISSN: 1741-7015

Background: As in many countries, quantifying COVID-19 spread in Indonesia remains challenging due to testing limitations. In Java, non-pharmaceutical interventions (NPIs) were implemented throughout 2020. However, as a vaccination campaign launches, cases and deaths are rising across the island. Methods: We used modelling to explore the extent to which data on burials in Jakarta using strict COVID-19 protocols (C19P) provide additional insight into the transmissibility of the disease, epidemic trajectory, and the impact of NPIs. We assess how implementation of NPIs in early 2021 will shape the epidemic during the period of likely vaccine roll-out. Results: C19P burial data in Jakarta suggest a death toll approximately 3.3 times higher than reported. Transmission estimates using these data suggest earlier, larger, and more sustained impact of NPIs. Measures to reduce sub-national spread, particularly during Ramadan, substantially mitigated spread to more vulnerable rural areas. Given current trajectory, daily cases and deaths are likely to increase in most regions as the vaccine is rolled-out. Transmission may peak in early 2021 in Jakarta if current levels of control are maintained. However, relaxation of control measures is likely to lead to a subsequent resurgence in the absence of an effective vaccination campaign. Conclusions: Syndromic measures of mortality provide a more complete picture of COVID-19 severity upon which to base decision-making. The high potential impact of the vaccine in Java is attributable to reductions in transmission to date and dependent on these being maintained. Increases in control in the relatively short-term will likely yield large, synergistic increases in vaccine impact.

Journal article

Hogan AB, Winskill P, Watson OJ, Walker PGT, Whittaker C, Baguelin M, Brazeau NF, Charles GD, Gaythorpe KAM, Hamlet A, Knock E, Laydon DJ, Lees JA, Løchen A, Verity R, Whittles LK, Muhib F, Hauck K, Ferguson NM, Ghani ACet al., 2021, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: a mathematical modelling analysis, Vaccine, Vol: 39, Pages: 2995-3006, ISSN: 0264-410X

The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extended a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identified optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We found that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, 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. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.

Journal article

Watson O, Alhaffar M, Mehchy Z, Whittaker C, Akil Z, Brazeau N, Cuomo-Dannenburg G, Hamlet A, Thompson H, Baguelin M, Fitzjohn R, Knock E, Lees J, Whittles L, Mellan T, Winskill P, COVID-19 Response Team IC, Howard N, Clapham H, Checchi F, Ferguson N, Ghani A, Walker P, Beals Eet al., 2021, Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria, Nature Communications, Vol: 12, Pages: 1-10, ISSN: 2041-1723

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% – 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 – 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% – 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.

Journal article

Ragonnet-Cronin M, Boyd O, Geidelberg L, Jorgensen D, Nascimento F, Siveroni I, Johnson R, Baguelin M, Cucunuba Z, Jauneikaite E, Mishra S, Watson O, Ferguson N, Cori A, Donnelly C, Volz Eet al., 2021, Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions, Nature Communications, Vol: 12, Pages: 1-7, ISSN: 2041-1723

Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non- pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced 30 much less severe COVID-19 morbidity and mortality during the period of study.

Journal article

Watson OJ, Gao B, Nguyen TD, Tran TN-A, Penny MA, Smith DL, Okell L, Aguas R, Boni MFet al., 2021, Pre-existing partner-drug resistance facilitates the emergence and spread of artemisinin resistance: a consensus modelling study

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Artemisinin-resistant genotypes have now emerged a minimum of five times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Using a consensus modelling approach with three individual-based mathematical models of <jats:italic>Plasmodium falciparum</jats:italic> transmission, we evaluate the effects of pre-existing partner-drug resistance and ACT deployment on artemisinin resistance evolution. We evaluate settings where dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL) are deployed as first-line therapy. We use time until 0.25 artemisinin resistance allele frequency (the establishment time) as the primary outcome measure.</jats:p></jats:sec><jats:sec><jats:title>Findings</jats:title><jats:p>Higher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all scenarios and pre-existing frequencies of partner-drug resistance explored, a 0.10 increase in partner-drug resistance frequency on average corresponded to 0.7 to 5.0 years loss of artemisinin efficacy. However, the majority of reductions in time to artemisinin establishment were observed after the first increment from 0.0 to 0.10 partner-drug resistance genotype frequency.</jats:p></jats:sec><jats:sec><jats:title>Interpretation</jats:title><jats:p>Partner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public

Journal article

McCabe R, Kont M, Schmit N, Whittaker C, Lochen A, Baguelin M, Knock E, Whittles L, Lees J, Brazeau N, Walker P, Ghani A, Ferguson N, White P, Donnelly C, Hauck K, Watson Oet al., 2021, Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries, International Journal of Epidemiology, ISSN: 0300-5771

Background: The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020/21 is essential.Methods: An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff, and ventilators under different epidemic scenarios in France, Germany, and Italy across the 2020/21 winter period. The effect of implementing lockdowns triggered by different numbers of COVID-19 patients in ICU under varying levels of effectiveness is examined, using a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model.Results: Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource. Reactive lockdowns could lead to large improvements in ICU capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and sustained under a higher level of suppression. The success of such interventions also depends on baseline bed numbers and average non-COVID-19 patient occupancy.Conclusions: Reductions in capacity deficits under different scenarios must be weighed against the feasibility and drawbacks of further lockdowns. Careful, continuous decision-making by national policymakers will be required across the winter period 2020/21.

Journal article

Akala HM, Watson OJ, Mitei KK, Juma DW, Verity R, Ingasia LA, Opot BH, Okoth RO, Chemwor GC, Juma JA, Mwakio EW, Brazeau N, Cheruiyot AC, Yeda RA, Maraka MN, Okello CO, Kateete DP, Managbanag JR, Andagalu B, Ogutu BR, Kamau Eet al., 2021, Plasmodium interspecies interactions during a period of increasing prevalence of Plasmodium ovale in symptomatic individuals seeking treatment: an observational study, The Lancet Microbe, Vol: 2, Pages: e141-e150

Background: The epidemiology and severity of non-falciparum malaria in endemic settings has garnered little attention. We aimed to characterise the prevalence, interaction, clinical risk factors, and temporal trends of non-falciparum Plasmodium species among symptomatic individuals presenting at health-care facilities in endemic settings of Kenya. Methods: We diagnosed and analysed infecting malaria species (Plasmodium falciparum, Plasmodium ovale curtisi, Plasmodium ovale wallikeri, and Plasmodium malariae) via PCR in clinical samples collected between March 1, 2008, and Dec 31, 2016, from six hospitals located in different regions of Kenya. We recruited patients aged 6 months or older who presented at outpatient departments with symptoms of malaria or tested positive for uncomplicated malaria by malaria rapid diagnostic test. Descriptive statistics were used to describe the prevalence and distribution of Plasmodium species. A statistical model was designed and used for estimating the frequency of Plasmodium species and assessing interspecies interactions. Mixed-effect linear regression models with random slopes for each location were used to test for change in prevalence over time. Findings: Samples from 2027 symptomatic participants presenting at care facilities were successfully analysed for all Plasmodium species. 1469 (72·5%) of the samples were P falciparum single-species infections, 523 (25·8%) were mixed infections, and only 35 (1·7%) were single non-falciparum species infections. 452 (22·3%) were mixed infections containing P ovale spp. A likelihood-based model calculation of the population frequency of each species estimated a significant within-host interference between P falciparum and P ovale curtisi. Mixed-effect logistic regression models identified a significant increase in P ovale wallikeri (2·1% per year; p=0·043) and P ovale curtisi (0·7% per year; p=0·0002) species over time, with a recipro

Journal article

Mesa DO, Hogan A, Watson O, Charles G, Hauck K, Ghani AC, Winskill Pet al., 2021, Quantifying the impact of vaccine hesitancy in prolonging the need for Non-Pharmaceutical Interventions to control the COVID-19 pandemic

<jats:title>Abstract</jats:title> <jats:p>Vaccine hesitancy – a delay in acceptance or refusal of vaccines despite availability – has the potential to threaten the successful roll-out of SARS-CoV-2 vaccines globally. Here, we evaluate the potential impact of vaccine hesitancy on the control of the pandemic and the relaxation of non-pharmaceutical interventions (NPIs) by combining an epidemiological model of SARS-CoV-2 transmission with data on vaccine hesitancy from population surveys. Our findings suggest that the mortality over a 2-year period could be up to 8 times higher in countries with high vaccine hesitancy compared to an ideal vaccination uptake if NPIs are relaxed. Alternatively, high vaccine hesitancy could prolong the need for NPIs to remain in place. Addressing vaccine hesitancy with behavioural interventions is therefore an important priority in the control of the COVID-19 pandemic.</jats:p>

Journal article

Olivera Mesa D, Hogan A, Watson O, Charles G, Hauck K, Ghani A, Winskill Pet al., 2021, Report 43: Quantifying the impact of vaccine hesitancy in prolonging the need for Non-Pharmaceutical Interventions to control the COVID-19 pandemic

Vaccine hesitancy – a delay in acceptance or refusal of vaccines despite availability 1 – has the potential to threaten the successful roll-out of SARS-CoV-2 vaccines globally 2 . Here, we evaluate the potential impact of vaccine hesitancy on the control of the pandemic and the relaxation of non-pharmaceutical interventions (NPIs) by combining an epidemiological model of SARS-CoV-2 transmission 3 with data on vaccine hesitancy from population surveys. Our findings suggest that the mortality over a 2-year period could be up to 8 times higher in countries with high vaccine hesitancy compared to an ideal vaccination uptake if NPIs are relaxed. Alternatively, high vaccine hesitancy could prolong the need for NPIs to remain in place. Addressing vaccine hesitancy with behavioural interventions is therefore an important priority in the control of the COVID-19 pandemic.

Report

Hogan AB, Winskill P, Watson OJ, Walker PGT, Whittaker C, Baguelin M, Brazeau NF, Charles GD, Gaythorpe KAM, Hamlet A, Knock E, Laydon DJ, Lees JA, Løchen A, Verity R, Whittles LK, Muhib F, Hauck K, Ferguson NM, Ghani ACet al., 2021, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: a mathematical modelling analysis, Publisher: Cold Spring Harbor Laboratory

The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extended a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identified optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We found that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, 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. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.

Working paper

Favas C, Jarrett P, Ratnayake R, Watson OJ, Checchi Fet al., 2021, Country differences in transmissibility, age distribution and case-fatality of SARS-CoV-2: a global ecological analysis

<jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>SARS-CoV-2 has spread rapidly across the world yet the first pandemic waves in many low-income countries appeared milder than initially forecasted through mathematical models. Hypotheses for this observed difference include under-ascertainment of cases and deaths, country population age structure, and immune modulation secondary to exposure to endemic parasitic infections. We conducted a country-level ecological study to describe patterns in key SARS-CoV-2 outcomes by country and region and to explore possible associations of the potential explanatory factors with these outcomes.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We collected publicly available data at country level and compared them using standardisation techniques. We then explored the association between exposures and outcomes using alternative approaches: random forest (RF) regression and linear (LM) regression. We adjusted for potential confounders and plausible effect modifications.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Altogether, data on the mean time-varying reproduction number (mean <jats:italic>R<jats:sub>t</jats:sub></jats:italic>) were available for 153 countries, but standardised averages for the age of cases and deaths and for the case-fatality ratio (CFR) could only be computed for 61, 39 and 31 countries respectively. While mean <jats:italic>R<jats:sub>t</jats:sub></jats:italic> was highest in the WHO Europe and Americas regions, median age of death was lower in the Africa region even after standardisation, with broadly similar CFR. Population age was strongly associated with mean <jats:italic>R<jats:sub>t</jats:sub></jats:italic> and the age-standardised median age of ob

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, NASCIMENTO F, Fitzjohn R, Gaythorpe K, Geidelberg L, green W, Hamlet A, Hauck K, Hinsley W, Imai N, Jeffrey, 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., 2021, Reduction in mobility and COVID-19 transmission, Nature Communications, Vol: 12, ISSN: 2041-1723

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts.Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world.Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation.In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

Journal article

Djaafara BA, Whittaker C, Watson OJ, Verity R, Brazeau NF, Oktavia D, Adrian V, Salama N, Bhatia S, Nouvellet P, Sherrard-Smith E, Churcher TS, Surendra H, Lina RN, Ekawati LL, Lestari KD, Andrianto A, Thwaites G, Baird JK, Ghani A, Elyazar IRF, Walker Pet al., 2021, Quantifying the Dynamics of COVID-19 Burden and Impact of Interventions in Java, Indonesia, SSRN Electronic Journal

Journal article

Knock ES, Whittles LK, Lees JA, Perez-Guzman PN, Verity R, FitzJohn RG, Gaythorpe KAM, Imai N, Hinsley W, Okell LC, Rosello A, Kantas N, Walters CE, Bhatia S, Watson OJ, Whittaker C, Cattarino L, Boonyasiri A, Djaafara BA, Fraser K, Fu H, Wang H, Xi X, Donnelly CA, Jauneikaite E, Laydon DJ, White PJ, Ghani AC, Ferguson NM, Cori A, Baguelin Met al., 2021, The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

<jats:title>Abstract</jats:title><jats:p>We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Among control measures implemented, only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier it could have reduced first wave deaths from 36,700 to 15,700 (95%CrI: 8,900–26,800). Improved clinical care reduced the infection fatality ratio from 1.25% (95%CrI: 1.18%–1.33%) to 0.77% (95%CrI: 0.71%–0.84%). The infection fatality ratio was higher in the elderly residing in care homes (35.9%, 95%CrI: 29.1%–43.4%) than those residing in the community (10.4%, 95%CrI: 9.1%–11.5%). England is still far from herd immunity, with regional cumulative infection incidence to 1st December 2020 between 4.8% (95%CrI: 4.4%–5.1%) and 15.4% (95%CrI: 14.9%–15.9%) of the population.</jats:p><jats:sec><jats:title>One-sentence summary</jats:title><jats:p>We fit a mathematical model of SARS-CoV-2 transmission to surveillance data from England, to estimate transmissibility, severity, and the impact of interventions</jats:p></jats:sec>

Journal article

Barnett-Howell Z, Watson OJ, Mobarak AM, 2021, The benefits and costs of social distancing in high- and low-income countries, Transactions of the Royal Society of Tropical Medicine and Hygiene, Vol: traa140, ISSN: 0035-9203

BackgroundWidespread social distancing and lockdowns of everyday activity have been the primary policy prescription across many countries throughout the coronavirus disease 2019 (COVID-19) pandemic. Despite their uniformity, these measures may be differentially valuable for different countries.MethodsWe use a compartmental epidemiological model to project the spread of COVID-19 across policy scenarios in high- and low-income countries. We embed estimates of the welfare value of disease avoidance into the epidemiological projections to estimate the return to more stringent lockdown policies.ResultsSocial distancing measures that ‘flatten the curve’ of the disease provide immense welfare value in upper-income countries. However, social distancing policies deliver significantly less value in lower-income countries that have younger populations, which are less vulnerable to COVID-19. Equally important, social distancing mandates a trade-off between disease risk and economic activity. Poorer people are less able to make those economic sacrifices.ConclusionsThe epidemiological and welfare value of social distancing is smaller in lower-income countries and such policies may exact a heavy toll on the poorest and most vulnerable. Workers in the informal sector often lack the resources and social protections that enable them to isolate themselves until the virus passes. By limiting these households’ ability to earn a living, social distancing can lead to an increase in hunger, deprivation, and related mortality and morbidity.

Journal article

Fu H, Wang H, Xi X, Boonyasiri A, Wang Y, Hinsley W, Fraser KJ, McCabe R, Olivera Mesa D, Skarp J, Ledda A, Dewé T, Dighe A, Winskill P, van Elsland SL, Ainslie KEC, Baguelin M, Bhatt S, Boyd O, Brazeau NF, Cattarino L, Charles G, Coupland H, Cucunubá ZM, Cuomo-Dannenburg G, Donnelly CA, Dorigatti I, Eales OD, Fitzjohn RG, Flaxman S, Gaythorpe KAM, Ghani AC, Green WD, Hamlet A, Hauck K, Haw DJ, Jeffrey B, Laydon DJ, Lees JA, Mellan T, Mishra S, Nedjati Gilani G, Nouvellet P, Okell L, Parag KV, Ragonnet-Cronin M, Riley S, Schmit N, Thompson HA, Unwin HJT, Verity R, Vollmer MAC, Volz E, Walker PGT, Walters CE, Waston OJ, Whittaker C, Whittles LK, Imai N, Bhatia S, Ferguson NMet al., 2021, A database for the epidemic trends and control measures during the first wave of COVID-19 in mainland China, International Journal of Infectious Diseases, Vol: 102, Pages: 463-471, ISSN: 1201-9712

Objectives: This data collation effort aims to provide a comprehensive database to describe the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19)across main provinces in China. Methods: From mid-January to March 2020, we extracted publicly available data on the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted a descriptive analysis of the epidemics in the six most-affected provinces. Results: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends were different across provinces. Compared to Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as local transmission of COVID-19 declined, switching the focus of measures to testing and quarantine of inbound travellers could help to sustain the control of the epidemic. Conclusions: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database with these indicators and information on control measures provides useful source for exploring further research and policy planning for response to the COVID-19 epidemic.

Journal article

Witmer K, Dahalan F, Delves M, Yahiya S, Watson O, Straschil U, Chiwcharoen D, Sorboon B, Pukrittayakamee S, Pearson R, Howick V, Lawniczak M, White N, Dondorp A, Okell L, Chotivanich K, Ruecker A, Baum Jet al., 2021, Transmission of artemisinin-resistant malaria parasites to mosquitoes under antimalarial drug pressure, Antimicrobial Agents and Chemotherapy, Vol: 65, Pages: 1-17, ISSN: 0066-4804

Resistance to artemisinin-based combination therapy (ACT) in the Plasmodium falciparum parasite is threatening to reverse recent gains in reducing global deaths from malaria. Whilst resistance manifests as delayed parasite clearance in patients the phenotype can only spread geographically via the sexual stages and mosquito transmission. In addition to their asexual killing properties, artemisinin and its derivatives sterilise sexual male gametocytes. Whether resistant parasites overcome this sterilising effect has not, however, been fully tested. Here, we analysed P. falciparum clinical isolates from the Greater Mekong Subregion, each demonstrating delayed clinical clearance and known resistance-associated polymorphisms in Kelch13 (PfK13var). As well as demonstrating reduced asexual sensitivity to drug, certain PfK13var isolates demonstrated a marked reduction in sensitivity to artemisinin in an in vitro male gamete formation assay. Importantly, this same reduction in sensitivity was observed when the most resistant isolate was tested directly in mosquito feeds. These results indicate that, under artemisinin drug pressure, whilst sensitive parasites are blocked, resistant parasites continue transmission. This selective advantage for resistance transmission could favour acquisition of additional host-specificity or polymorphisms affecting partner drug sensitivity in mixed infections. Favoured resistance transmission under ACT coverage could have profound implications for the spread of multidrug resistant malaria beyond Southeast Asia.

Journal article

Knock E, Whittles L, Lees J, Perez Guzman P, Verity R, Fitzjohn R, Gaythorpe K, Imai N, Hinsley W, Okell L, Rosello A, Kantas N, Walters C, Bhatia S, Watson O, Whittaker C, Cattarino L, Boonyasiri A, Djaafara A, Fraser K, Fu H, Wang H, Xi X, Donnelly C, Jauneikaite E, Laydon D, White P, Ghani A, Ferguson N, Cori A, Baguelin Met al., 2020, Report 41: The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

England has been severely affected by COVID-19. We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional 2020 surveillance data. Only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier in the first wave it could have reduced mortality by 23,300 deaths on average. The mean infection fatality ratio was initially ~1.3% across all regions except London and halved following clinical care improvements. The infection fatality ratio was two-fold lower throughout in London, even when adjusting for demographics. The infection fatality ratio in care homes was 2.5-times that in the elderly in the community. Population-level infection-induced immunity in England is still far from herd immunity, with regional mean cumulative attack rates ranging between 4.4% and 15.8%.

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Knock ES, Whittles LK, Perez-Guzman PN, Bhatia S, Guntoro F, Watson OJ, Whittaker C, Ferguson NM, Cori A, Baguelin M, FitzJohn RG, Lees JAet al., 2020, Reproducible parallel inference and simulation of stochastic state space models using odin, dust, and mcstate, Wellcome Open Research, Vol: 5, Pages: 288-288

<ns4:p>State space models, including compartmental models, are used to model physical, biological and social phenomena in a broad range of scientific fields. A common way of representing the underlying processes in these models is as a system of stochastic processes which can be simulated forwards in time. Inference of model parameters based on observed time-series data can then be performed using sequential Monte Carlo techniques. However, using these methods for routine inference problems can be made difficult due to various engineering considerations: allowing model design to change in response to new data and ideas, writing model code which is highly performant, and incorporating all of this with up-to-date statistical techniques. Here, we describe a suite of packages in the R programming language designed to streamline the design and deployment of state space models, targeted at infectious disease modellers but suitable for other domains. Users describe their model in a familiar domain-specific language, which is converted into parallelised C++ code. A fast, parallel, reproducible random number generator is then used to run large numbers of model simulations in an efficient manner. We also provide standard inference and prediction routines, though the model simulator can be used directly if these do not meet the user’s needs. These packages provide guarantees on reproducibility and performance, allowing the user to focus on the model itself, rather than the underlying computation. The ability to automatically generate high-performance code that would be tedious and time-consuming to write and verify manually, particularly when adding further structure to compartments, is crucial for infectious disease modellers. Our packages have been critical to the development cycle of our ongoing real-time modelling efforts in the COVID-19 pandemic, and have the potential to do the same for models used in a number of different domains.</ns4:p>

Journal article

Unwin H, Mishra S, Bradley V, Gandy A, Mellan T, Coupland H, Ish-Horowicz J, Vollmer M, Whittaker C, Filippi S, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie K, Baguelin M, Boonyasiri A, Brazeau N, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales O, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag K, Siveroni I, Thompson H, Walker P, Walters C, Watson O, Whittles L, Ghani A, Ferguson N, Riley S, Donnelly C, Bhatt S, Flaxman Set al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, Vol: 11, Pages: 1-9, ISSN: 2041-1723

As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

Journal article

Watson O, Abdelmagid N, Ahmed A, Ahmed Abd Elhameed AE, Whittaker C, Brazeau N, Hamlet A, Walker P, Hay J, Ghani A, Checchi F, Dahab Met al., 2020, Report 39: Characterising COVID-19 epidemic dynamics and mortality under-ascertainment in Khartoum, Sudan

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Grassly NC, Pons-Salort M, Parker EPK, White PJ, Ferguson NM, Imperial College COVID-19 Response Teamet al., 2020, Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study, Lancet Infectious Diseases, Vol: 20, Pages: 1381-1389, ISSN: 1473-3099

BACKGROUND: WHO has called for increased testing in response to the COVID-19 pandemic, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. We aimed to investigate the potential impact of different testing and isolation strategies on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We developed a mathematical model of SARS-CoV-2 transmission based on infectiousness and PCR test sensitivity over time since infection. We estimated the reduction in the effective reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms, and quarantine of contacts of laboratory-confirmed cases identified through test-and-trace protocols. The expected effectiveness of different testing strategies was defined as the percentage reduction in R. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined their implications for the use of so-called immunity passports. FINDINGS: If all individuals with symptoms compatible with COVID-19 self-isolated and self-isolation was 100% effective in reducing onwards transmission, self-isolation of symptomatic individuals would result in a reduction in R of 47% (95% uncertainty interval [UI] 32-55). PCR testing to identify SARS-CoV-2 infection soon after symptom onset could reduce the number of individuals needing to self-isolate, but would also reduce the effectiveness of self-isolation (around 10% would be false negatives). Weekly screening of health-care workers and other high-risk groups irrespective of symptoms by use of PCR testing is estimated to reduce their contribution to SARS-CoV-2 transmission by 23% (95% UI 16-40), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 h. The effectiveness of test and trace depends strongly on coverage and the timelines

Journal article

Thompson H, Imai N, Dighe A, Ainslie K, Baguelin M, Bhatia S, Bhatt S, Boonyasiri A, Boyd O, Brazeau N, Cattarino L, Cooper L, Coupland H, Cucunuba Z, Cuomo-Dannenburg G, Djaafara B, Dorigatti I, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Hallett T, Hamlet A, Haw D, Hayes S, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mellan T, Mishra S, Mousa A, Nedjati-Gilani G, Nouvellet P, Okell L, Parag K, Ragonnet-Cronin M, Riley S, 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, Donnelly C, Ferguson Net al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, Vol: 27, Pages: 1-3, ISSN: 1195-1982

We estimated SARS-CoV-2 infection prevalence in cohorts of repatriated citizens from Wuhan to be 0.44% (95% CI: 0.19%–1.03%). Although not representative of the wider population we believe these estimates are helpful in providing a conservative estimate of infection prevalence in Wuhan City, China, in the absence of large-scale population testing early in the epidemic.

Journal article

Moser KA, Madebe RA, Aydemir O, Chiduo MG, Mandara CI, Rumisha SF, Chaky F, Denton M, Marsh PW, Verity R, Watson OJ, Ngasala B, Mkude S, Molteni F, Njau R, Warsame M, Mandike R, Kabanywanyi AM, Mahende MK, Kamugisha E, Ahmed M, Kavishe RA, Greer G, Kitojo CA, Reaves EJ, Mlunde L, Bishanga D, Mohamed A, Juliano JJ, Ishengoma DS, Bailey JAet al., 2020, Describing the current status of Plasmodium falciparum population structure and drug resistance within mainland Tanzania using molecular inversion probes, MOLECULAR ECOLOGY, Vol: 30, Pages: 100-113, ISSN: 0962-1083

Journal article

McCabe R, Kont M, Schmit N, Whittaker C, Lochen A, Baguelin M, Knock E, Whittles L, Lees J, Walker P, Ghani A, Ferguson N, White P, Donnelly C, Hauck K, Watson Oet al., 2020, Report 36: Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries

The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on healthcare systems, particularly intensive care units (ICUs), with COVID-19 patient care being a key concern of healthcare system planning for winter 2020/21. Ensuring that all patients who require intensive care, irrespective of COVID-19 status, can access it during this time is essential. This study uses an integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients to estimate the spare capacity of key ICU resources under different epidemic scenarios in France, Germany and Italy across the winter period of 2020/21. In particular, we examine the effect of implementing suppression strategies of varying effectiveness, triggered by different numbers of COVID-19 patients in ICU. The use of a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model and the consideration of multiple ICU resources that determine capacity (beds, doctors, nurses and ventilators) and the interdependencies between them, provides a detailed insight into potential capacity constraints this winter. Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource across countries. Lockdowns triggered based on ICU capacity could lead to large improvements in spare capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and implemented at a higher level of suppression. In many cases, maximum deficits are reduced to lower levels which can then be managed by expanding supply-side hospital capacity, to ensure that all patients can receive treatment. The success of such interventions also depends on baseline ICU bed numbers and average non-COVID-19 patient occupancy. We find that lockdowns of longer duration reduce the total number of days in defic

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Edejer TT-T, Hanssen O, Mirelman A, Verboom P, Lolong G, Watson OJ, Boulanger LL, Soucat Aet al., 2020, Projected health-care resource needs for an effective response to COVID-19 in 73 low-income and middle-income countries: a modelling study, LANCET GLOBAL HEALTH, Vol: 8, Pages: E1372-E1379, ISSN: 2214-109X

Journal article

Okell LC, Verity R, Katzourakis A, Volz EM, Watson OJ, Mishra S, Walker P, Whittaker C, Donnelly CA, Riley S, Ghani AC, Gandy A, Flaxman S, Ferguson NM, Bhatt Set al., 2020, Host or pathogen-related factors in COVID-19 severity? Reply, LANCET, Vol: 396, Pages: 1397-1397, ISSN: 0140-6736

Journal article

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