Publications
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Thompson H, Imai N, Dighe A, et 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.
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Report 6: Relative sensitivity of international surveillance, Report 6: Relative sensitivity of international surveillance
Since the start of the COVID-19 epidemic in late 2019, there are now 29 affected countries with over 1000 confirmed cases outside of mainland China. In previous reports, we estimated the likely epidemic size in Wuhan City based on air traffic volumes and the number of detected cases internationally. Here we analysed COVID-19 cases exported from mainland China to different regions and countries, comparing the country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different countries. Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that about two thirds of COVID-19 cases exported from mainland China have remained undetected worldwide, potentially resulting in multiple chains of as yet undetected human-to-human transmission outside mainland China.
Djaafara BA, Imai N, Hamblion E, et al., 2020, A quantitative framework to define the end of an outbreak: application to Ebola Virus Disease
<jats:p>Declaring the end of an outbreak is an important step in controlling infectious disease outbreaks. An objective estimation of the probability of cases arising in the future is important to reduce the risk of post-declaration flare-ups. We developed a simulation-based model to quantify that probability. We tested it on simulated Ebola Virus Disease (EVD) data and found this probability was most sensitive to the instantaneous reproduction number, the reporting rate, and the delay between symptom onset and recovery or death of the last detected case. For EVD, our results suggest that the current WHO criterion of 42 days since the outcome of the last detected case is too short and very sensitive to underreporting. The 90 days of enhanced surveillance period after the end-of-outbreak declaration is therefore crucial to capture potential flare-ups of cases. Hence, we suggest a shift to a preliminary end-of-outbreak declaration after 63 days from the symptom onset day of the last detected case. This should be followed by a 90-day enhanced surveillance, after which the official end-of-outbreak can be declared. This corresponds to less than 5% probability of flare ups in most of the scenarios examined. Our quantitative framework could be adapted to define end-of-outbreak criteria for other infectious diseases.</jats:p>
Volz E, Baguelin M, Bhatia S, et al., 2020, Report 5: Phylogenetic analysis of SARS-CoV-2
Genetic diversity of SARS-CoV-2 (formerly 2019-nCoV), the virus which causes COVID-19, provides information about epidemic origins and the rate of epidemic growth. By analysing 53 SARS-CoV-2 whole genome sequences collected up to February 3, 2020, we find a strong association between the time of sample collection and accumulation of genetic diversity. Bayesian and maximum likelihood phylogenetic methods indicate that the virus was introduced into the human population in early December and has an epidemic doubling time of approximately seven days. Phylodynamic modelling provides an estimate of epidemic size through time. Precise estimates of epidemic size are not possible with current genetic data, but our analyses indicate evidence of substantial heterogeneity in the number of secondary infections caused by each case, as indicated by a high level of over-dispersion in the reproduction number. Larger numbers of more systematically sampled sequences – particularly from across China – will allow phylogenetic estimates of epidemic size and growth rate to be substantially refined.
Gold S, Donnelly C, Nouvellet P, et al., 2020, Rabies virus neutralising antibodies in healthy, unvaccinated individuals: What do they mean for rabies epidemiology?, PLoS Neglected Tropical Diseases, ISSN: 1935-2727
Rabies has been a widely feared disease for thousands of years, with records of rabid dogs as early as ancient Egyptian and Mesopotamian texts. The reputation of rabies as being inevitably fatal, together with its ability to affect all mammalian species, contributes to the fear surrounding this disease. However, the widely held view that exposure to the rabies virus is always fatal has been repeatedly challenged. Although survival following clinical infection in humans has only been recorded on a handful of occasions, a number of studies have reported detection of rabies-specific antibodies in the sera of humans, domestic animals and wildlife which are apparently healthy and unvaccinated. These “seropositive” individuals provide possible evidence of exposure to the rabies virus which has not led to fatal disease. However, the variability in methods of detecting these antibodies and the difficulties of interpreting serology tests have contributed to an unclear picture of their importance. In this review we consider the evidence for rabies-specific antibodies in healthy, unvaccinated individuals as indicators of non-lethal rabies exposure and the potential implications of this for rabies epidemiology. Our findings indicate that while there is substantial evidence that non-lethal rabies exposure does occur, serology studies which do not use appropriate controls and cut-offs are unlikely to provide an accurate estimate of the true prevalence of non-lethal rabies exposure.
Dorigatti I, Okell L, Cori A, et al., 2020, Report 4: Severity of 2019-novel coronavirus (nCoV)
We present case fatality ratio (CFR) estimates for three strata of 2019-nCoV infections. For cases detected in Hubei, we estimate the CFR to be 18% (95% credible interval: 11%-81%). For cases detected in travellers outside mainland China, we obtain central estimates of the CFR in the range 1.2-5.6% depending on the statistical methods, with substantial uncertainty around these central values. Using estimates of underlying infection prevalence in Wuhan at the end of January derived from testing of passengers on repatriation flights to Japan and Germany, we adjusted the estimates of CFR from either the early epidemic in Hubei Province, or from cases reported outside mainland China, to obtain estimates of the overall CFR in all infections (asymptomatic or symptomatic) of approximately 1% (95% confidence interval 0.5%-4%). It is important to note that the differences in these estimates does not reflect underlying differences in disease severity between countries. CFRs seen in individual countries will vary depending on the sensitivity of different surveillance systems to detect cases of differing levels of severity and the clinical care offered to severely ill cases. All CFR estimates should be viewed cautiously at the current time as the sensitivity of surveillance of both deaths and cases in mainland China is unclear. Furthermore, all estimates rely on limited data on the typical time intervals from symptom onset to death or recovery which influences the CFR estimates.
Enticott G, Maye D, Fisher R, et al., 2020, An assessment of risk compensation and spillover behavioural adaptions associated with the use of vaccines in animal disease management, Vaccine, Vol: 38, Pages: 1065-1075, ISSN: 0264-410X
This paper analyses farmers’ behavioural responses to Government attempts toreduce the risk of disease transmission from badgers to cattle through badgervaccination. Evidence for two opposing behavioural adaptions is examined inresponse to the vaccination of badgers to reduce the risk of transmission to farmedcattle. Risk compensation theory suggests that interventions that reduce risk, such asvaccination, are counterbalanced by negative behavioural adaptions. By contrast, thespillover effect suggests that interventions can prompt further positive behaviours.The paper uses data from a longitudinal mixed methods study of farmers’ attitudes tobadger vaccination to prevent the spread of bovine tuberculosis, their reports ofbiosecurity practices, and cattle movement data in 5 areas of England, one of whichexperienced badger vaccination. Analysis finds limited evidence of spilloverbehaviours following vaccination. Lack of spillover is attributed to farmers’ beliefs inthe effectiveness of biosecurity and the lack of similarity between badger vaccinationand vaccination for other animal diseases. Risk compensation behaviours areassociated with farmers’ beliefs as to who should manage animal disease. Ratherthan farmers’ belief in vaccine effectiveness, it is more likely that farmers’ low senseof being able to do anything to prevent disease influences their apparent riskcompensation behaviours. These findings address the gap in the literature relating tofarmers' behavioural adaptions to vaccine use in the management of animal disease.
Imai N, Cori A, Dorigatti I, et al., 2020, Report 3: Transmissibility of 2019-nCoV
Self-sustaining human-to-human transmission of the novel coronavirus (2019-nCov) is the only plausible explanation of the scale of the outbreak in Wuhan. We estimate that, on average, each case infected 2.6 (uncertainty range: 1.5-3.5) other people up to 18th January 2020, based on an analysis combining our past estimates of the size of the outbreak in Wuhan with computational modelling of potential epidemic trajectories. This implies that control measures need to block well over 60% of transmission to be effective in controlling the outbreak. It is likely, based on the experience of SARS and MERS-CoV, that the number of secondary cases caused by a case of 2019-nCoV is highly variable – with many cases causing no secondary infections, and a few causing many. Whether transmission is continuing at the same rate currently depends on the effectiveness of current control measures implemented in China and the extent to which the populations of affected areas have adopted risk-reducing behaviours. In the absence of antiviral drugs or vaccines, control relies upon the prompt detection and isolation of symptomatic cases. It is unclear at the current time whether this outbreak can be contained within China; uncertainties include the severity spectrum of the disease caused by this virus and whether cases with relatively mild symptoms are able to transmit the virus efficiently. Identification and testing of potential cases need to be as extensive as is permitted by healthcare and diagnostic testing capacity – including the identification, testing and isolation of suspected cases with only mild to moderate disease (e.g. influenza-like illness), when logistically feasible.
Imai N, Dorigatti I, Cori A, et al., 2020, Report 2: Estimating the potential total number of novel Coronavirus cases in Wuhan City, China
We estimate that a total of 4,000 cases of 2019-nCoV in Wuhan City (uncertainty range: 1,000 – 9,700) had onset of symptoms by 18th January 2020 (the last reported onset date of any case) [15].Our estimates should not be interpreted as implying the outbreak has doubled in size in the period 12th January to 18th January – delays in confirming and reporting exported cases and incomplete information about dates of symptom onset together with the still very small numbers of exported cases mean we are unable to estimate the epidemic growth rate at the current time.This estimate is based on the following assumptions:• Wuhan International Airport has a catchment population of 19 million individuals [1].• There is a mean 10-day delay between infection and detection, comprising a 5-6 day incubation period [16,17] and a 4-5 day delay from symptom onset to detection/hospitalisation of a case (the cases detected in Thailand and Japan were hospitalised 3 and 7 days after onset, respectively) [4,18].• Total volume of international travel from Wuhan over the last two months has been 3,301 passengers per day. This estimate is derived from the 3,418 foreign passengers per day in the top 20 country destinations based on 2018 IATA data [19], and uses 2016 IATA data held by Imperial College London to correct for the travel surge at Chinese New Year present in the latter data (which has not happened yet this year) and for travel to countries outside the top 20 destination list.• Exit screening (which reportedly came into force on the 15th January [13]) had no impact on exported cases reported up to 16th January. Exit screening may have reduced exports in recent days, in which case our baseline prediction may be an underestimate of the true number of cases in Wuhan.• We assume all cases in travellers flying to destinations outside mainland China are being detected at those destinations. This may well not be the case. If cases are being missed in other
Riley S, Atchison C, Ashby D, et al., 2020, REal-time Assessment of Community Transmission (REACT) of SARS-CoV-2 virus: Study protocol [version 1; peer review: 1 approved, 1 approved with reservations], Wellcome Open Research, Vol: 5, Pages: 1-17
Background: England, UK has one of the highest rates of confirmed COVID-19 mortality globally. Until recently, testing for the SARS-CoV-2 virus focused mainly on healthcare and care home settings. As such, there is far less understanding of community transmission. Protocol: The REal-time Assessment of Community Transmission (REACT) programme is a major programme of home testing for COVID-19 to track progress of the infection in the community. REACT-1 involves cross-sectional surveys of viral detection (virological swab for RT-PCR) tests in repeated samples of 100,000 to 150,000 randomly selected individuals across England. This examines how widely the virus has spread and how many people are currently infected. The age range is 5 years and above. Individuals are sampled from the England NHS patient list. REACT-2 is a series of five sub-studies towards establishing the seroprevalence of antibodies to SARS-CoV-2 in England as an indicator of historical infection. The main study (study 5) uses the same design and sampling approach as REACT-1 using a self-administered lateral flow immunoassay (LFIA) test for IgG antibodies in repeated samples of 100,000 to 200,000 adults aged 18 years and above. To inform study 5, studies 1-4 evaluate performance characteristics of SARS-CoV-2 LFIAs (study 1) and different aspects of feasibility, usability and application of LFIAs for home-based testing in different populations (studies 2-4). Ethics and dissemination: The study has ethical approval. Results are reported using STROBE guidelines and disseminated through reports to public health bodies, presentations at scientific meetings and open access publications. Conclusions: This study provides robust estimates of the prevalence of both virus (RT-PCR, REACT-1) and seroprevalence (antibody, REACT-2) in the general population in England. We also explore acceptability and usability of LFIAs for self-administered testing for SARS-CoV-2 antibody in a home-based setting, not done before at
Ward H, Cooke G, Atchison C, et al., 2020, Declining prevalence of antibody positivity to SARS-CoV-2: a community study of 365,000 adults
Background The prevalence and persistence of antibodies following a peak SARS-CoV-2 infection provides insights into its spread in the community, the likelihood of reinfection and potential for some level of population immunity.Methods Prevalence of antibody positivity in England, UK (REACT2) with three cross-sectional surveys between late June and September 2020. 365104 adults used a self-administered lateral flow immunoassay (LFIA) test for IgG. A laboratory comparison of LFIA results to neutralization activity in panel of sera was performed.Results There were 17,576 positive tests over the three rounds. Antibody prevalence, adjusted for test characteristics and weighted to the adult population of England, declined from 6.0% [5.8, 6.1], to 4.8% [4.7, 5.0] and 4.4% [4.3, 4.5], a fall of 26.5% [-29.0, −23.8] over the three months of the study. There was a decline between rounds 1 and 3 in all age groups, with the highest prevalence of a positive result and smallest overall decline in positivity in the youngest age group (18-24 years: −14.9% [-21.6, −8.1]), and lowest prevalence and largest decline in the oldest group (75+ years: −39.0% [-50.8, −27.2]); there was no change in antibody positivity between rounds 1 and 3 in healthcare workers (+3.45% [-5.7, +12.7]).The decline from rounds 1 to 3 was largest in those who did not report a history of COVID-19, (−64.0% [-75.6, −52.3]), compared to −22.3% ([-27.0, −17.7]) in those with SARS-CoV-2 infection confirmed on PCR.Discussion These findings provide evidence of variable waning in antibody positivity over time such that, at the start of the second wave of infection in England, only 4.4% of adults had detectable IgG antibodies using an LFIA. Antibody positivity was greater in those who reported a positive PCR and lower in older people and those with asymptomatic infection. These data suggest the possibility of decreasing population immunity and increasing risk of rei
Riley S, Atchison C, Ashby D, et al., 2020, REal-time Assessment of Community Transmission (REACT) of SARS-CoV-2 virus: Study protocol., Wellcome open research, Vol: 5, ISSN: 2398-502X
<b>Background:</b> England, UK has one of the highest rates of confirmed COVID-19 mortality globally. Until recently, testing for the SARS-CoV-2 virus focused mainly on healthcare and care home settings. As such, there is far less understanding of community transmission. <b>Protocol:</b> The REal-time Assessment of Community Transmission (REACT) programme is a major programme of home testing for COVID-19 to track progress of the infection in the community. REACT-1 involves cross-sectional surveys of viral detection (virological swab for RT-PCR) tests in repeated samples of 100,000 to 150,000 randomly selected individuals across England. This examines how widely the virus has spread and how many people are currently infected. The age range is 5 years and above. Individuals are sampled from the England NHS patient list. REACT-2 is a series of five sub-studies towards establishing the seroprevalence of antibodies to SARS-CoV-2 in England as an indicator of historical infection. The main study (study 5) uses the same design and sampling approach as REACT-1 using a self-administered lateral flow immunoassay (LFIA) test for IgG antibodies in repeated samples of 100,000 to 200,000 adults aged 18 years and above. To inform study 5, studies 1-4 evaluate performance characteristics of SARS-CoV-2 LFIAs (study 1) and different aspects of feasibility, usability and application of LFIAs for home-based testing in different populations (studies 2-4). <b>Ethics and dissemination:</b> The study has ethical approval. Results are reported using STROBE guidelines and disseminated through reports to public health bodies, presentations at scientific meetings and open access publications. <b>Conclusions:</b> This study provides robust estimates of the prevalence of both virus (RT-PCR, REACT-1) and seroprevalence (antibody, REACT-2) in the general population in England. We also explore acceptability and usability of LFIAs for self-administered
Bhatia S, Imai N, Cuomo-Dannenburg G, et al., 2020, Estimating the number of undetected COVID-19 cases among travellers from mainland China., Wellcome open research, Vol: 5, Pages: 143-143, ISSN: 2398-502X
Background: As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide.Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries.Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries.Conclusions: Our analysis shows that a large number of COVID-19 cases remain undetected across the world. These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
Lee VJ, Aguilera X, Heymann D, et al., 2020, Preparedness for emerging epidemic threats: a Lancet Infectious Diseases Commission., Lancet Infect Dis, Vol: 20, Pages: 17-19
Jeffrey B, Walters CE, Ainslie KEC, et al., 2020, Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK., Wellcome open research, Vol: 5, ISSN: 2398-502X
<b>Background:</b> Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. <b>Methods:</b> Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. <b>Results:</b> We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. <b>Conclusions:</b> These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.
Jeffrey B, Walters CE, Ainslie KEC, et al., 2020, Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK., Wellcome Open Res, Vol: 5, ISSN: 2398-502X
Background: Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which have resulted in reduced mobility across different regions. Crowd level data on mobile phone usage can be used as a proxy for actual population mobility patterns and provide a way of quantifying the impact of social distancing measures on changes in mobility. Methods: Here, we use two mobile phone-based datasets (anonymised and aggregated crowd level data from O2 and from the Facebook app on mobile phones) to assess changes in average mobility, both overall and broken down into high and low population density areas, and changes in the distribution of journey lengths. Results: We show that there was a substantial overall reduction in mobility, with the most rapid decline on the 24th March 2020, the day after the Prime Minister's announcement of an enforced lockdown. The reduction in mobility was highly synchronized across the UK. Although mobility has remained low since 26th March 2020, we detect a gradual increase since that time. We also show that the two different datasets produce similar trends, albeit with some location-specific differences. We see slightly larger reductions in average mobility in high-density areas than in low-density areas, with greater variation in mobility in the high-density areas: some high-density areas eliminated almost all mobility. Conclusions: These analyses form a baseline from which to observe changes in behaviour in the UK as social distancing is eased and inform policy towards the future control of SARS-CoV-2 in the UK.
Riley S, Atchison C, Ashby D, et al., 2020, REal-time Assessment of Community Transmission (REACT) of SARS-CoV-2 virus: Study protocol., Wellcome Open Res, Vol: 5, ISSN: 2398-502X
Background: England, UK has one of the highest rates of confirmed COVID-19 mortality globally. Until recently, testing for the SARS-CoV-2 virus focused mainly on healthcare and care home settings. As such, there is far less understanding of community transmission. Protocol: The REal-time Assessment of Community Transmission (REACT) programme is a major programme of home testing for COVID-19 to track progress of the infection in the community. REACT-1 involves cross-sectional surveys of viral detection (virological swab for RT-PCR) tests in repeated samples of 100,000 to 150,000 randomly selected individuals across England. This examines how widely the virus has spread and how many people are currently infected. The age range is 5 years and above. Individuals are sampled from the England NHS patient list. REACT-2 is a series of five sub-studies towards establishing the seroprevalence of antibodies to SARS-CoV-2 in England as an indicator of historical infection. The main study (study 5) uses the same design and sampling approach as REACT-1 using a self-administered lateral flow immunoassay (LFIA) test for IgG antibodies in repeated samples of 100,000 to 200,000 adults aged 18 years and above. To inform study 5, studies 1-4 evaluate performance characteristics of SARS-CoV-2 LFIAs (study 1) and different aspects of feasibility, usability and application of LFIAs for home-based testing in different populations (studies 2-4). Ethics and dissemination: The study has ethical approval. Results are reported using STROBE guidelines and disseminated through reports to public health bodies, presentations at scientific meetings and open access publications. Conclusions: This study provides robust estimates of the prevalence of both virus (RT-PCR, REACT-1) and seroprevalence (antibody, REACT-2) in the general population in England. We also explore acceptability and usability of LFIAs for self-administered testing for SARS-CoV-2 antibody in a home-based setting, not done before at
Hawryluk I, Mellan TA, Hoeltgebaum H, et al., 2020, Inference of COVID-19 epidemiological distributions from Brazilian hospital data, Journal of The Royal Society Interface, Vol: 17, Pages: 20200596-20200596, ISSN: 1742-5662
Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (N = 21 000 − 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2 and 17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalized lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.
Dorigatti I, Morrison S, Donnelly C, et al., 2019, Risk of yellow fever virus importation into the United States from Brazil, outbreak years 2016–2017 and 2017–2018, Scientific Reports, Vol: 9, ISSN: 2045-2322
Southeast Brazil has experienced two large yellow fever (YF) outbreaks since 2016. While the 2016–2017 outbreak mainly affected the states of Espírito Santo and Minas Gerais, the 2017–2018 YF outbreak primarily involved the states of Minas Gerais, São Paulo, and Rio de Janeiro, the latter two of which are highly populated and popular destinations for international travelers. This analysis quantifies the risk of YF virus (YFV) infected travelers arriving in the United States via air travel from Brazil, including both incoming Brazilian travelers and returning US travelers. We assumed that US travelers were subject to the same daily risk of YF infection as Brazilian residents. During both YF outbreaks in Southeast Brazil, three international airports—Miami, New York-John F. Kennedy, and Orlando—had the highest risk of receiving a traveler infected with YFV. Most of the risk was observed among incoming Brazilian travelers. Overall, we found low risk of YFV introduction into the United States during the 2016-2017 and 2017-2018 outbreaks. Decision makers can use these results to employ the most efficient and least restrictive actions and interventions.
Parag KV, Donnelly CA, 2019, Optimising Renewal Models for Real-Time Epidemic Prediction and Estimation
<jats:title>Abstract</jats:title><jats:p>The effective reproduction number, <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>, is an important prognostic for infectious disease epidemics. Significant changes in <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> can forewarn about new transmissions or predict the efficacy of interventions. The renewal model infers <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> from incidence data and has been applied to Ebola virus disease and pandemic influenza outbreaks, among others. This model estimates <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> using a sliding window of length <jats:italic>k</jats:italic>. While this facilitates real-time detection of statistically significant <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> fluctuations, inference is highly <jats:italic>k</jats:italic> -sensitive. Models with too large or small <jats:italic>k</jats:italic> might ignore meaningful changes or over-interpret noise-induced ones. No principled <jats:italic>k</jats:italic> -selection scheme exists. We develop a practical yet rigorous scheme using the accumulated prediction error (APE) metric from information theory. We derive exact incidence prediction distributions and integrate these within an APE framework to identify the <jats:italic>k</jats:italic> best supported by available data. We find that this <jats:italic>k</jats:italic> optimises short-term prediction accuracy and expose how common, heuristic <jats:italic>k</jats:italic> -choices, which seem sensible, could be misleading.</jats:p>
Ham C, Donnelly C, Astley K, et al., 2019, Effect of culling on individual badger (Meles meles) behaviour: potential implications for bovine tuberculosis transmission, Journal of Applied Ecology, Vol: 56, Pages: 2390-2399, ISSN: 0021-8901
1. Culling wildlife as a form of disease management can have unexpected and sometimes counterproductive outcomes. In the UK, badgers (Meles meles) are culled in efforts to reduce badger-to-cattle transmission of Mycobacterium bovis, the causative agent of bovine tuberculosis (TB). However, culling has previously been associated with both increased and decreased incidence of M. bovis infection in cattle.2. The adverse effects of culling have been linked to cull-induced changes in badger ranging, but such changes are not well documented at the individual level. Using GPS-collars, we characterised individual badger behaviour within an area subjected to widespread industry-led culling, comparing it with the same area before culling and with three unculled areas.3. Culling was associated with a 61% increase (95% CI 27-103%) in monthly home range size, a 39% increase (95% CI 28-51%) in nightly maximum distance from the sett, and a 17% increase (95% CI 11-24%) in displacement between successive GPS-collar locations recorded at 20-minute intervals. Despite travelling further, we found a 91.2 minute (95% CI 67.1-115.3 minute) reduction in the nightly activity time of individual badgers associated with culling. These changes became apparent while culls were ongoing and persisted after culling ended.4. Expanded ranging in culled areas was associated with individual badgers visiting 45% (95% CI 15-80%) more fields each month, suggesting that surviving individuals had the opportunity to contact more cattle. Moreover, surviving badgers showed a 19.9-fold increase (95% CI 10.8-36.4 increase) in the odds of trespassing into neighbouring group territories, increasing opportunities for intergroup contact.5. Synthesis and Applications: Badger culling was associated with behavioural changes among surviving badgers which potentially increased opportunities for both badger-to-badger and badger-to-cattle transmission of M. bovis. Furthermore, by reducing the time badgers spent active, cu
Downs S, Prosser A, Ashton A, et al., 2019, Assessing effects from four years of industry-led badger culling in England on the incidence of bovine tuberculosis in cattle, 2013-2017, Scientific Reports, Vol: 9, ISSN: 2045-2322
The objective was to measure the association between badger culling and bovine tuberculosis (TB) incidents in cattle herds in three areas of England between 2013–2017 (Gloucestershire and Somerset) and 2015–2017 (Dorset). Farming industry-selected licensed culling areas were matched to comparison areas. A TB incident was detection of new Mycobacterium bovis infection (post-mortem confirmed) in at least one animal in a herd. Intervention and comparison area incidence rates were compared in central zones where culling was conducted and surrounding buffer zones, through multivariable Poisson regression analyses. Central zone incidence rates in Gloucestershire (Incidence rate ratio (IRR) 0.34 (95% CI 0.29 to 0.39, p < 0.001) and Somerset (IRR 0.63 (95% CI 0.58 to 0.69, p < 0.001) were lower and no different in Dorset (IRR 1.10, 95% CI 0.96 to 1.27, p = 0.168) than comparison central zone rates. The buffer zone incidence rate was lower for Gloucestershire (IRR 0.64, 95% CI 0.58 to 0.70, p < 0.001), no different for Somerset (IRR 0.97, 95% CI 0.80 to 1.16, p = 0.767) and lower for Dorset (IRR 0.45, 95% CI 0.37 to 0.54, p < 0.001) than comparison buffer zone rates. Industry-led culling was associated with reductions in cattle TB incidence rates after four years but there were variations in effects between areas.
Donnelly CA, Mateos-Corral D, 2019, THE CANADIAN MARITIME CYSTIC FIBROSIS NEWBORN SCREENING PROGRAM: A 5-YEAR REVIEW, Publisher: WILEY, Pages: S239-S240, ISSN: 8755-6863
Watson C, Ferguson N, Donnelly C, et al., 2019, Design of Vaccine Efficacy Trials for Priority Emerging and Epidemic Diseases, Publisher: BMC
Eneanya O, Fronterre C, Anagbogu I, et al., 2019, Mapping the baseline prevalence of lymphatic filariasis across Nigeria, Parasites & Vectors, Vol: 12, ISSN: 1756-3305
Introduction: The baseline endemicity profile of lymphatic filariasis (LF) is a keybenchmark for planning control programmes, monitoring their impact on transmissionand assessing the feasibility of achieving elimination. Presented in this work is themodelled serological and parasitological prevalence of LF prior to the scale-up of massdrug administration (MDA) in Nigeria using a machine learning based approach.Methods: LF prevalence data generated by the Nigeria Lymphatic Filariasis ControlProgramme during country-wide mapping surveys conducted between 2000 and 2013were used to build the models. The dataset comprised of 1103 community-levelsurveys based on the detection of filarial antigenaemia using rapidimmunochromatographic card tests (ICT) and 184 prevalence surveys testing for thepresence of microfilaria (Mf) in blood. Using a suite of climate and environmentalcontinuous gridded variables and compiled site-level prevalence data, a quantileregression forest (QRF) model was fitted for both antigenaemia and microfilaraemia LFprevalence. Model predictions were projected across a continuous 5 × 5 km griddedmap of Nigeria. The number of individuals potentially infected by LF prior to MDAinterventions was subsequently estimated.Results: Maps presented predict a heterogeneous distribution of LF antigenaemia andmicrofilaraemia in Nigeria. The North-Central, North-West, and South-East regionsdisplayed the highest predicted LF seroprevalence, whereas predicted Mf prevalencewas highest in the southern regions. Overall, 8.7 million and 3.3 million infections werepredicted for ICT and Mf, respectively.Conclusions: QRF is a machine learning-based algorithm capable of handling high-dimensional data and fitting complex relationships between response and predictorvariables. Our models provide a benchmark through which the progress of ongoing LF control efforts can be monitored.
Donnelly CA, Malik MR, Elkholy A, et al., 2019, Worldwide reduction in MERS cases and deaths since 2016, Emerging Infectious Diseases, Vol: 25, Pages: 1758-1760, ISSN: 1080-6040
Since 2012, Middle East respiratory syndrome (MERS) coronavirus has infected 2,442 persons worldwide. Case-based data analysis suggests that since 2016, as many as 1,465 cases and 293–520 deaths might have been averted. Efforts to reduce the global MERS threat are working, but countries must maintain vigilance to prevent further infections.
Parag KV, Donnelly CA, 2019, Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models
<jats:title>Abstract</jats:title><jats:p>Estimating temporal changes in a target population from phylogenetic or count data is an important problem in ecology and epidemiology. Reliable estimates can provide key insights into the climatic and biological drivers influencing the diversity or structure of that population and evidence hypotheses concerning its future growth or decline. In infectious disease applications, the individuals infected across an epidemic form the target population. The renewal model estimates the effective reproduction number,<jats:italic>R</jats:italic>, of the epidemic from counts of its observed cases. The skyline model infers the effective population size,<jats:italic>N</jats:italic>, underlying a phylogeny of sequences sampled from that epidemic. Practically,<jats:italic>R</jats:italic>measures ongoing epidemic growth while<jats:italic>N</jats:italic>informs on historical caseload. While both models solve distinct problems, the reliability of their estimates depends on<jats:italic>p</jats:italic>-dimensional piecewise-constant functions. If<jats:italic>p</jats:italic>is misspecified, the model might underfit significant changes or overfit noise and promote a spurious understanding of the epidemic, which might misguide intervention policies or misinform forecasts. Surprisingly, no transparent yet principled approach for optimising<jats:italic>p</jats:italic>exists. Usually,<jats:italic>p</jats:italic>is heuristically set, or obscurely controlled via complex algorithms. We present a computable and interpretable<jats:italic>p</jats:italic>-selection method based on the minimum description length (MDL) formalism of information theory. Unlike many standard model selection techniques, MDL accounts for the additional statistical complexity induced by how parameters interact. As a result, our method optimises<jats:itali
Dean NE, Gsell P-S, Brookmeyer R, et al., 2019, Design of vaccine efficacy trials during public health emergencies, Science Translational Medicine, Vol: 11, ISSN: 1946-6234
Public Health Emergencies (PHEs) provide a complex and challenging environment for vaccine evaluation. Under the R&D Blueprint Plan of Action, the World Health Organization (WHO) has convened a group of experts to agree on standard procedures to rapidly evaluate experimental vaccines during PHEs while maintaining the highest scientific and ethical standards. The Blueprint priority diseases, selected for their likelihood to cause PHEs and the lack of adequate medical countermeasures,were used to frame our methodological discussions. Here, we outline major vaccine study designs to be used in PHEs and summarize high-level recommendations for their use in this setting. We recognize that the epidemiology and transmission dynamics of the Blueprint priority diseasesmay be highly uncertain and that the unique characteristics of the vaccines and outbreak settings may affect our study design. To address these challenges, our group underscores the need for novel, flexible,and responsive trial designs. We conclude that assignment to study groups using randomization is a key principle underlying rigorous study design and should be utilized except in exceptional circumstances. Advance planning for vaccine trial designs is critical for rapid and effective response to a PHE and to advance knowledge to address and mitigate future PHEs.
Donnelly C, Malik M, Elkholy A, et al., 2019, Important reductions in the global number of MERS cases and deaths since 2016, Emerging Infectious Diseases, ISSN: 1080-6040
Since 2012, the Middle East Respiratory syndrome coronavirus (MERS-CoV) has infected more than 2250 people worldwide. The number of MERS-CoV infections reported annually dropped substantially from 2016. Our analysis of case-based data suggests that 1465 MERS cases and 293-520 deaths might have been averted since 2016.
Eneanya O, Garske T, Donnelly C, 2019, The social, physical and economic impact of lymphedema and hydrocele: A matched cross-sectional study in rural Nigeria, BMC Infectious Diseases, Vol: 19, ISSN: 1471-2334
BackgroundLymphatic filariasis (LF) is a mosquito-borne parasitic disease and a major cause of disability worldwide. To effectively plan morbidity management programmes, it is important to estimate disease burden and evaluate the needs of patients. This study aimed to estimate patient numbers and characterise the physical, social and economic impact of LF in in rural Nigeria.MethodsThis is a matched cross-sectional study which identified lymphedema and hydrocele patients with the help of district health officers and community-directed distributors of mass drug administration programmes. A total of 52 cases were identified and matched to 52 apparently disease-free controls, selected from the same communities and matched by age and sex. Questionnaires and narrative interviews were used to characterise the physical, social and economic impact of lymphedema and hydrocele.ResultsForty-eight cases with various stages of lower limb lymphedema, and 4 with hydrocele were identified. 40% of all cases reported feeling stigma and were 36 times (95% CI: 5.18–1564.69) more likely to avoid forms of social participation. Although most cases engaged in some form of income-generating activity, these were low paid employment, and on average cases spent significantly less time than controls working. The economic effects of lower income were exacerbated by increased healthcare spending, as cases were 86 times (95% CI: 17.48–874.90) more likely to spend over US $125 on their last healthcare payment.ConclusionThis study highlights the importance of patient-search as a means of estimating the burden of LF morbidity in rural settings. Findings from this work also confirm that LF causes considerable psychosocial and economic suffering, all of which adversely affect the mental health of patients. It is therefore important to incorporate mental health care as a major component of morbidity management programmes.
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