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1.
Wellcome Open Res ; 5: 78, 2020.
Article in English | MEDLINE | ID: covidwho-2297273

ABSTRACT

We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.

2.
BMC Med ; 21(1): 97, 2023 03 16.
Article in English | MEDLINE | ID: covidwho-2277101

ABSTRACT

BACKGROUND: Understanding the overall effectiveness of non-pharmaceutical interventions to control the COVID-19 pandemic and reduce the burden of disease is crucial for future pandemic planning. However, quantifying the effectiveness of specific control measures and the extent of missed infections, in the absence of early large-scale serological surveys or random community testing, has remained challenging. METHODS: Combining data on notified local COVID-19 cases with known and unknown sources of infections in Singapore with a branching process model, we reconstructed the incidence of missed infections during the early phase of the wild-type SARS-CoV-2 and Delta variant transmission. We then estimated the relative effectiveness of border control measures, case finding and contact tracing when there was no or low vaccine coverage in the population. We compared the risk of ICU admission and death between the wild-type SARS-CoV-2 and the Delta variant in notified cases and all infections. RESULTS: We estimated strict border control measures were associated with 0.2 (95% credible intervals, CrI 0.04-0.8) missed imported infections per notified case between July and December 2020, a decline from around 1 missed imported infection per notified case in the early phases of the pandemic. Contact tracing was estimated to identify 78% (95% CrI 62-93%) of the secondary infections generated by notified cases before the partial lockdown in Apr 2020, but this declined to 63% (95% CrI 56-71%) during the lockdown and rebounded to 78% (95% CrI 58-94%) during reopening in Jul 2020. The contribution of contact tracing towards overall outbreak control also hinges on ability to find cases with unknown sources of infection: 42% (95% CrI 12-84%) of such cases were found prior to the lockdown; 10% (95% CrI 7-15%) during the lockdown; 47% (95% CrI 17-85%) during reopening, due to increased testing capacity and health-seeking behaviour. We estimated around 63% (95% CrI 49-78%) of the wild-type SARS-CoV-2 infections were undetected during 2020 and around 70% (95% CrI 49-91%) for the Delta variant in 2021. CONCLUSIONS: Combining models with case linkage data enables evaluation of the effectiveness of different components of outbreak control measures, and provides more reliable situational awareness when some cases are missed. Using such approaches for early identification of the weakest link in containment efforts could help policy makers to better redirect limited resources to strengthen outbreak control.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/prevention & control , Contact Tracing , Communicable Disease Control , Pandemics/prevention & control
3.
Elife ; 92020 08 24.
Article in English | MEDLINE | ID: covidwho-2155737

ABSTRACT

A key unknown for SARS-CoV-2 is how asymptomatic infections contribute to transmission. We used a transmission model with asymptomatic and presymptomatic states, calibrated to data on disease onset and test frequency from the Diamond Princess cruise ship outbreak, to quantify the contribution of asymptomatic infections to transmission. The model estimated that 74% (70-78%, 95% posterior interval) of infections proceeded asymptomatically. Despite intense testing, 53% (51-56%) of infections remained undetected, most of them asymptomatic. Asymptomatic individuals were the source for 69% (20-85%) of all infections. The data did not allow identification of the infectiousness of asymptomatic infections, however low ranges (0-25%) required a net reproduction number for individuals progressing through presymptomatic and symptomatic stages of at least 15. Asymptomatic SARS-CoV-2 infections may contribute substantially to transmission. Control measures, and models projecting their potential impact, need to look beyond the symptomatic cases if they are to understand and address ongoing transmission.


Subject(s)
Asymptomatic Diseases , Coronavirus Infections/transmission , Pneumonia, Viral/therapy , Ships/statistics & numerical data , Betacoronavirus/isolation & purification , COVID-19 , Calibration , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Humans , Incidence , Models, Statistical , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2
4.
Proc Natl Acad Sci U S A ; 119(37): e2203019119, 2022 09 13.
Article in English | MEDLINE | ID: covidwho-2017027

ABSTRACT

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society's responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak.


Subject(s)
Disease Outbreaks , Pandemics , Respiratory Tract Infections , Schools , COVID-19/prevention & control , COVID-19/transmission , Child , Computer Simulation , Disease Outbreaks/prevention & control , Humans , Influenza, Human/prevention & control , Influenza, Human/transmission , Pandemics/prevention & control , Respiratory Tract Infections/prevention & control , Respiratory Tract Infections/transmission
6.
Nat Commun ; 13(1): 1956, 2022 04 12.
Article in English | MEDLINE | ID: covidwho-1788286

ABSTRACT

The emergence of highly transmissible SARS-CoV-2 variants has created a need to reassess the risk posed by increasing social contacts as countries resume pre-pandemic activities, particularly in the context of resuming large-scale events over multiple days. To examine how social contacts formed in different activity settings influences interventions required to control Delta variant outbreaks, we collected high-resolution data on contacts among passengers and crew on cruise ships and combined the data with network transmission models. We found passengers had a median of 20 (IQR 10-36) unique close contacts per day, and over 60% of their contact episodes were made in dining or sports areas where mask wearing is typically limited. In simulated outbreaks, we found that vaccination coverage and rapid antigen tests had a larger effect than mask mandates alone, indicating the importance of combined interventions against Delta to reduce event risk in the vaccine era.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , Disease Outbreaks/prevention & control , Humans , Ships
7.
Science ; 375(6587): 1349-1350, 2022 03 25.
Article in English | MEDLINE | ID: covidwho-1759269

ABSTRACT

Community testing studies can provide insights as SARS-CoV-2 evolves.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans
8.
PLoS Biol ; 20(2): e3001531, 2022 02.
Article in English | MEDLINE | ID: covidwho-1686076

ABSTRACT

Identifying the potential for SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders and the choice of baseline time point, and show how to account for both in reinfection analysis.


Subject(s)
Antibodies, Viral/blood , COVID-19/immunology , Reinfection/immunology , Adolescent , Adult , Aged , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Nucleic Acid Testing , COVID-19 Serological Testing , Humans , Logistic Models , Middle Aged , Polymerase Chain Reaction , Prospective Studies , Reinfection/prevention & control , SARS-CoV-2/immunology , Seroepidemiologic Studies , Time Factors , United States/epidemiology , Workplace/statistics & numerical data , Young Adult
9.
Euro Surveill ; 27(1)2022 01.
Article in English | MEDLINE | ID: covidwho-1613510

ABSTRACT

We estimate the potential remaining COVID-19 hospitalisation and death burdens in 19 European countries by estimating the proportion of each country's population that has acquired immunity to severe disease through infection or vaccination. Our results suggest many European countries could still face high burdens of hospitalisations and deaths, particularly those with lower vaccination coverage, less historical transmission and/or older populations. Continued non-pharmaceutical interventions and efforts to achieve high vaccination coverage are required in these countries to limit severe COVID-19 outcomes.


Subject(s)
COVID-19 , Europe/epidemiology , Hospitalization , Humans , SARS-CoV-2 , Vaccination
10.
Cell ; 184(25): 6010-6014, 2021 12 09.
Article in English | MEDLINE | ID: covidwho-1553721

ABSTRACT

The COVID-19 information epidemic, or "infodemic," demonstrates how unlimited access to information may confuse and influence behaviors during a health emergency. However, the study of infodemics is relatively new, and little is known about their relationship with epidemics management. Here, we discuss unresolved issues and propose research directions to enhance preparedness for future health crises.


Subject(s)
COVID-19/psychology , Infodemic , Information Dissemination/ethics , COVID-19/epidemiology , Epidemics/psychology , Humans , Information Dissemination/methods , Public Health , Research/trends , SARS-CoV-2
11.
Viruses ; 13(11)2021 11 06.
Article in English | MEDLINE | ID: covidwho-1502534

ABSTRACT

Obesity is a key correlate of severe SARS-CoV-2 outcomes while the role of obesity on risk of SARS-CoV-2 infection, symptom phenotype, and immune response remain poorly defined. We examined data from a prospective SARS-CoV-2 cohort study to address these questions. Serostatus, body mass index, demographics, comorbidities, and prior COVID-19 compatible symptoms were assessed at baseline and serostatus and symptoms monthly thereafter. SARS-CoV-2 immunoassays included an IgG ELISA targeting the spike RBD, multiarray Luminex targeting 20 viral antigens, pseudovirus neutralization, and T cell ELISPOT assays. Our results from a large prospective SARS-CoV-2 cohort study indicate symptom phenotype is strongly influenced by obesity among younger but not older age groups; we did not identify evidence to suggest obese individuals are at higher risk of SARS-CoV-2 infection; and remarkably homogenous immune activity across BMI categories suggests immune protection across these groups may be similar.


Subject(s)
Antibodies, Viral/blood , COVID-19/complications , COVID-19/immunology , Obesity/complications , Obesity/immunology , Spike Glycoprotein, Coronavirus/immunology , Adolescent , Adult , Age Factors , Body Mass Index , COVID-19/epidemiology , COVID-19/physiopathology , Female , Humans , Immunoglobulin G/blood , Male , Middle Aged , Risk Factors , SARS-CoV-2/immunology , Young Adult
12.
Science ; 372(6538)2021 04 09.
Article in English | MEDLINE | ID: covidwho-1476375

ABSTRACT

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in September 2020 and is rapidly spreading toward fixation. Using a variety of statistical and dynamic modeling approaches, we estimate that this variant has a 43 to 90% (range of 95% credible intervals, 38 to 130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine rollout, COVID-19 hospitalizations and deaths across England in the first 6 months of 2021 were projected to exceed those in 2020. VOC 202012/01 has spread globally and exhibits a similar transmission increase (59 to 74%) in Denmark, Switzerland, and the United States.


Subject(s)
COVID-19/transmission , COVID-19/virology , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , Basic Reproduction Number , COVID-19/epidemiology , COVID-19/mortality , COVID-19 Vaccines , Child , Child, Preschool , Communicable Disease Control , England/epidemiology , Europe/epidemiology , Female , Humans , Infant , Male , Middle Aged , Models, Theoretical , Mutation , SARS-CoV-2/genetics , SARS-CoV-2/growth & development , SARS-CoV-2/pathogenicity , Severity of Illness Index , Socioeconomic Factors , United States/epidemiology , Viral Load , Young Adult
14.
Elife ; 92020 02 24.
Article in English | MEDLINE | ID: covidwho-1344521

ABSTRACT

Traveller screening is being used to limit further spread of COVID-19 following its recent emergence, and symptom screening has become a ubiquitous tool in the global response. Previously, we developed a mathematical model to understand factors governing the effectiveness of traveller screening to prevent spread of emerging pathogens (Gostic et al., 2015). Here, we estimate the impact of different screening programs given current knowledge of key COVID-19 life history and epidemiological parameters. Even under best-case assumptions, we estimate that screening will miss more than half of infected people. Breaking down the factors leading to screening successes and failures, we find that most cases missed by screening are fundamentally undetectable, because they have not yet developed symptoms and are unaware they were exposed. Our work underscores the need for measures to limit transmission by individuals who become ill after being missed by a screening program. These findings can support evidence-based policy to combat the spread of COVID-19, and prospective planning to mitigate future emerging pathogens.


Subject(s)
Asymptomatic Infections , Betacoronavirus , Coronavirus Infections/diagnosis , Mass Screening , Pneumonia, Viral/diagnosis , Travel , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Disease Outbreaks , Humans , Infection Control , Mass Screening/methods , Mass Screening/standards , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Risk Assessment , SARS-CoV-2
15.
PLoS Comput Biol ; 17(7): e1009162, 2021 07.
Article in English | MEDLINE | ID: covidwho-1305574

ABSTRACT

On March 23 2020, the UK enacted an intensive, nationwide lockdown to mitigate transmission of COVID-19. As restrictions began to ease, more localized interventions were used to target resurgences in transmission. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to targeting interventions at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. We found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance connections central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.


Subject(s)
COVID-19 , Communicable Disease Control/statistics & numerical data , Travel/statistics & numerical data , Algorithms , COVID-19/epidemiology , COVID-19/prevention & control , Computational Biology , Human Activities/statistics & numerical data , Humans , SARS-CoV-2 , Social Media/statistics & numerical data , United Kingdom
16.
Euro Surveill ; 26(20)2021 05.
Article in English | MEDLINE | ID: covidwho-1290660

ABSTRACT

We assess the feasibility of reaching the herd immunity threshold against SARS-CoV-2 through vaccination, considering vaccine effectiveness (VE), transmissibility of the virus and the level of pre-existing immunity in populations, as well as their age structure. If highly transmissible variants of concern become dominant in areas with low levels of naturally-acquired immunity and/or in populations with large proportions of < 15 year-olds, control of infection without non-pharmaceutical interventions may only be possible with a VE ≥ 80%, and coverage extended to children.


Subject(s)
COVID-19 , SARS-CoV-2 , Child , Humans , Immunity, Herd , Vaccination
17.
BMC Med ; 19(1): 106, 2021 04 27.
Article in English | MEDLINE | ID: covidwho-1204075

ABSTRACT

BACKGROUND: Routine asymptomatic testing using RT-PCR of people who interact with vulnerable populations, such as medical staff in hospitals or care workers in care homes, has been employed to help prevent outbreaks among vulnerable populations. Although the peak sensitivity of RT-PCR can be high, the probability of detecting an infection will vary throughout the course of an infection. The effectiveness of routine asymptomatic testing will therefore depend on testing frequency and how PCR detection varies over time. METHODS: We fitted a Bayesian statistical model to a dataset of twice weekly PCR tests of UK healthcare workers performed by self-administered nasopharyngeal swab, regardless of symptoms. We jointly estimated times of infection and the probability of a positive PCR test over time following infection; we then compared asymptomatic testing strategies by calculating the probability that a symptomatic infection is detected before symptom onset and the probability that an asymptomatic infection is detected within 7 days of infection. RESULTS: We estimated that the probability that the PCR test detected infection peaked at 77% (54-88%) 4 days after infection, decreasing to 50% (38-65%) by 10 days after infection. Our results suggest a substantially higher probability of detecting infections 1-3 days after infection than previously published estimates. We estimated that testing every other day would detect 57% (33-76%) of symptomatic cases prior to onset and 94% (75-99%) of asymptomatic cases within 7 days if test results were returned within a day. CONCLUSIONS: Our results suggest that routine asymptomatic testing can enable detection of a high proportion of infected individuals early in their infection, provided that the testing is frequent and the time from testing to notification of results is sufficiently fast.


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19/diagnosis , Polymerase Chain Reaction/methods , Bayes Theorem , COVID-19/pathology , Female , Humans , Male
18.
Science ; 371(6538):149-149, 2021.
Article in English | Academic Search Complete | ID: covidwho-1181922

ABSTRACT

The article discusses about the novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused COVID-19. One of these variant of concern was B.1.1.7 which was first detected in southeast England and spread to become the dominant lineage in the United Kingdom in just a few months.

19.
Wellcome Open Res ; 5: 239, 2020.
Article in English | MEDLINE | ID: covidwho-1175762

ABSTRACT

Introduction: Contact tracing has the potential to control outbreaks without the need for stringent physical distancing policies, e.g. civil lockdowns. Unlike forward contact tracing, backward contact tracing identifies the source of newly detected cases. This approach is particularly valuable when there is high individual-level variation in the number of secondary transmissions (overdispersion). Methods: By using a simple branching process model, we explored the potential of combining backward contact tracing with more conventional forward contact tracing for control of COVID-19. We estimated the typical size of clusters that can be reached by backward tracing and simulated the incremental effectiveness of combining backward tracing with conventional forward tracing. Results: Across ranges of parameter values consistent with dynamics of SARS-CoV-2, backward tracing is expected to identify a primary case generating 3-10 times more infections than a randomly chosen case, typically increasing the proportion of subsequent cases averted by a factor of 2-3. The estimated number of cases averted by backward tracing became greater with a higher degree of overdispersion. Conclusion: Backward contact tracing can be an effective tool for outbreak control, especially in the presence of overdispersion as is observed with SARS-CoV-2.

20.
Lancet Public Health ; 6(3): e175-e183, 2021 03.
Article in English | MEDLINE | ID: covidwho-1164723

ABSTRACT

BACKGROUND: In most countries, contacts of confirmed COVID-19 cases are asked to quarantine for 14 days after exposure to limit asymptomatic onward transmission. While theoretically effective, this policy places a substantial social and economic burden on both the individual and wider society, which might result in low adherence and reduced policy effectiveness. We aimed to assess the merit of testing contacts to avert onward transmission and to replace or reduce the length of quarantine for uninfected contacts. METHODS: We used an agent-based model to simulate the viral load dynamics of exposed contacts, and their potential for onward transmission in different quarantine and testing strategies. We compared the performance of quarantines of differing durations, testing with either PCR or lateral flow antigen (LFA) tests at the end of quarantine, and daily LFA testing without quarantine, against the current 14-day quarantine strategy. We also investigated the effect of contact tracing delays and adherence to both quarantine and self-isolation on the effectiveness of each strategy. FINDINGS: Assuming moderate levels of adherence to quarantine and self-isolation, self-isolation on symptom onset alone can prevent 37% (95% uncertainty interval [UI] 12-56) of onward transmission potential from secondary cases. 14 days of post-exposure quarantine reduces transmission by 59% (95% UI 28-79). Quarantine with release after a negative PCR test 7 days after exposure might avert a similar proportion (54%, 95% UI 31-81; risk ratio [RR] 0·94, 95% UI 0·62-1·24) to that of the 14-day quarantine period, as would quarantine with a negative LFA test 7 days after exposure (50%, 95% UI 28-77; RR 0·88, 0·66-1·11) or daily testing without quarantine for 5 days after tracing (50%, 95% UI 23-81; RR 0·88, 0·60-1·43) if all tests are returned negative. A stronger effect might be possible if individuals isolate more strictly after a positive test and if contacts can be notified faster. INTERPRETATION: Testing might allow for a substantial reduction in the length of, or replacement of, quarantine with a small excess in transmission risk. Decreasing test and trace delays and increasing adherence will further increase the effectiveness of these strategies. Further research is required to empirically evaluate the potential costs (increased transmission risk, false reassurance) and benefits (reduction in the burden of quarantine, increased adherence) of such strategies before adoption as policy. FUNDING: National Institute for Health Research, UK Research and Innovation, Wellcome Trust, EU Horizon 2021, and the Bill & Melinda Gates Foundation.


Subject(s)
COVID-19 Testing/methods , COVID-19/prevention & control , Contact Tracing , Quarantine , COVID-19/epidemiology , Humans , Models, Theoretical
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