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1.
BMC Public Health ; 22(1): 504, 2022 03 15.
Article in English | MEDLINE | ID: covidwho-1745471

ABSTRACT

BACKGROUND: The lockdown periods to curb COVID-19 transmission have made it harder for survivors of domestic violence and abuse (DVA) to disclose abuse and access support services. Our study describes the impact of the first COVID-19 wave and the associated national lockdown in England and Wales on the referrals from general practice to the Identification and Referral to Improve Safety (IRIS) DVA programme. We compare this to the change in referrals in the same months in the previous year, during the school holidays in the 3 years preceding the pandemic and the period just after the first COVID-19 wave. School holiday periods were chosen as a comparator, since families, including the perpetrator, are together, affecting access to services. METHODS: We used anonymised data on daily referrals received by the IRIS DVA service in 33 areas from general practices over the period April 2017-September 2020. Interrupted-time series and non-linear regression were used to quantify the impact of the first national lockdown in March-June 2020 comparing analogous months the year before, and the impact of school holidays (01/04/2017-30/09/2020) on number of referrals, reporting Incidence Rate Ratio (IRR), 95% confidence intervals and p-values. RESULTS: The first national lockdown in 2020 led to reduced number of referrals to DVA services (27%, 95%CI = (21,34%)) compared to the period before and after, and 19% fewer referrals compared to the same period in the year before. A reduction in the number of referrals was also evident during the school holidays with the highest reduction in referrals during the winter 2019 pre-pandemic school holiday (44%, 95%CI = (32,54%)) followed by the effect from the summer of 2020 school holidays (20%, 95%CI = (10,30%)). There was also a smaller reduction (13-15%) in referrals during the longer summer holidays 2017-2019; and some reduction (5-16%) during the shorter spring holidays 2017-2019. CONCLUSIONS: We show that the COVID-19 lockdown in 2020 led to decline in referrals to DVA services. Our findings suggest an association between decline in referrals to DVA services for women experiencing DVA and prolonged periods of systemic closure proxied here by both the first COVID-19 national lockdown or school holidays. This highlights the need for future planning to provide adequate access and support for people experiencing DVA during future national lockdowns and during the school holidays.


Subject(s)
COVID-19 , Domestic Violence , COVID-19/epidemiology , COVID-19/prevention & control , Child, Preschool , Communicable Disease Control , Domestic Violence/prevention & control , England/epidemiology , Female , Humans , Referral and Consultation , Wales/epidemiology
2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330107

ABSTRACT

The Omicron wave has left a global imprinting of immunity which changes the COVID landscape. In this study, we simulate six hypothetical variants emerging over the next year and evaluate the impact of existing and improved vaccines. We base our study on South Africa's infection- and vaccination-derived immunity. Our findings illustrate that variant-chasing vaccines will only add value above existing vaccines in the setting where a variant emerges if we can shorten the window between variant introduction and vaccine deployment to under three weeks, an impossible time-frame without significant NPI use. This strategy may have global utility, depending on the rate of spread from setting to setting. Broadly neutralizing and durable next-generation vaccines could avert over three-times as many deaths from an immune-evading variant compared to existing vaccines. Our results suggest it is crucial to develop next-generation vaccines and redress inequities in vaccine distribution to tackle future emerging variants.

3.
Epidemics ; 38: 100547, 2022 03.
Article in English | MEDLINE | ID: covidwho-1700614

ABSTRACT

The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics.


Subject(s)
Pandemics , Forecasting , Uncertainty
4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-318665

ABSTRACT

Background: The COVID-19 pandemic, with the related lockdown periods to curb transmission, has made it harder for survivors of domestic violence and abuse (DVA) to disclose abuse and access support services. Our study describes the impact of the first COVID-19 wave and the associated national lockdown in England and Wales on the referrals from general practice to the IRIS ( I dentification and R eferral to I mprove S afety) DVA programme. We compare this to the change in referrals in the same months in the previous year, during the school holidays in the three years preceding the pandemic and the period just after the first COVID-19 wave. School holiday periods were chosen as a comparator, since families, including the perpetrator, are together, affecting access to services. Methods We used anonymised data on daily referrals received by the IRIS DVA service in 33 areas from general practices over the period April 2017-September 2020. Interrupted-time series and non-linear regression were used to quantify the impact of the first national lockdown in March-June 2020 comparing analogous months the year before, and the impact of school holidays (01/04/2017-30/09/2020) on number of referrals, reporting Incidence Rate Ratio (IRR), 95% confidence intervals and p-values. Results The first national lockdown in 2020 lead to reduced number of referrals to DVA services (27%,95%CI=(21%,34%)) compared to the period before and after, and 19% fewer referrals compared to the same period in the year before. A reduction in the number of referrals was also evident during the school holidays with the highest reduction in referrals during the winter 2019 pre-pandemic school holiday (44%,95%CI=(32%,54%)) followed by the effect from the summer of 2020 school holidays (20%,95%CI=(10%,30%)). There was also a smaller reduction (13%-15%) in referrals during the longer summer holidays 2017–2019;and some reduction (5%-16%) during the shorter spring holidays 2017–2019. Conclusions We show that the COVID-19 lockdown in 2020 led to decline in referrals to DVA services. Our findings suggest an association between decline in referrals to DVA services for woman experiencing DVA and prolonged periods of systemic closure proxied here by both the first COVID-19 national lockdown or school holidays. This highlights the need for future planning to provide adequate access and support for people experiencing DVA during future national lockdowns and during the school holidays.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-314962

ABSTRACT

Background: Testing for COVID-19 with quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) may result in delayed detection of disease. Antigen detection via lateral flow testing (LFT) is faster and amenable to mass testing strategies. Our study assesses the diagnostic accuracy of LFT compared to RT-PCR on the same primary-care patients in Austria.Methods: Prospective dataset of 2,562 patients presenting with mild to moderate flu-like symptoms to 20 practices in the district of Liezen, Austria, between October 22 and November 30, 2020. Symptomatic patients received clinical assessment, including both tests, and were split in two groups: Group 1 (true reactive): Suspected COVID-19 cases with a reactive LFT, who tested RT-PCR positive;and Group 2 (false non-reactive): Suspected COVID-19 cases with a non-reactive LFT, who tested RT-PCR positive. We report the number of cases detected with each test, evaluate the correlation of RT-PCR positivity with reactive LFT and report clinical sensitivity and specificity of LFT, positive predictive value (PPV), negative predictive value (NPV), and pre-test duration of symptoms and RT-PCR cycle threshold (Ct) value across groups. Regression analysis quantifies the association between reactive LFT and symptom duration and Ct value respectively.Findings: Of the 2,562 symptomatic patients, 1,037 were suspected of COVID-19: 826 (79.7%) tested RT-PCR positive 201 (19.8%) RT-PCR negative and 10 (0.5%) with inconclusive RT-PCR. Among patients with positive RT-PCR, 788/826 tested LFT reactive (Group 1) and 38 (4.6%) non-reactive (Group 2);Of those with negative RT-PCR, 179/201 tested LFT non-reactive and 22/201 reactive. Clinical sensitivity (95.4%) and specificity (89.1%), and PPV (97.3%) and NPV (82.5%) were high. Test outcomes of both LFT and RT-PCR were positively correlated (r=0.968,95CI=[0.952,0.985]). Reactive LFT was negatively correlated with Ct value (r=0.2999,p<0.001) and symptom duration (r=-0.1299,p=0.0043) while Ct value was positively correlated with symptom duration (r=0.3733),p<0.001).Interpretation: We show that LFT at scale during early COVID-19 is an accurate alternative to RT-PCR testing and may assist in curbing resurgence of disease. We note the importance of administering LFT properly, here combined with clinical assessment and delivered at scale in primary care. This needs to be considered when applying LFT as part of mass testing strategies.Funding Statement: No funding was available for this study.Declaration of Interests: None declared.Ethics Approval Statement: The study used secondary anonymised data for which approval was granted by the Institute of Advanced Studies Research Ethics Committee, Austria (reference number: CASE002_2021_HEHP).

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308681

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) is resurgent in the UK and health and economic costs of the epidemic continue to rise. There is a need to understand the health and economic costs of different courses of action. Methods: We combine modelling, economic analysis and a user-friendly interface to contrast the impact and costs of different testing strategies: two levels of testing within the current test-trace-isolate (TTI) strategy (testing symptomatic people, tracing and isolating everyone) and a strategy where TTI is combined with universal testing (UT;i.e. additional population testing to identify asymptomatic cases). We also model effective coverage of face masks. Results: Increased testing is necessary to suppress the virus after lockdown. Partial reopening accompanied by scaled-up TTI (at 50% test and trace levels), full isolation and moderately effective coverage of masks (30% reduction in overall transmission) can reduce the current resurgence of the virus and protect the economy in the UK. Additional UT from December 2020 reduces the epidemic dramatically by Jan 2021 when combined with enhanced TTI (70% test-trace levels) and full isolation. UT could then be stopped;continued TTI would prevent rapid recurrence. This TTI+UT combination can suppress the virus further to save ~20,000 more lives and avoid ~£90bn economic losses, though costs ~£8bn more to deliver. We assume that all traced and lab-confirmed cases are isolated. The flexible interface we have developed allows exploration of additional scenarios, including different levels of reopening of society after the second lockdown in England as well as different levels of effective mask coverage. Conclusions: Our findings suggest that increased TTI is necessary to suppress the virus and protect the economy after the second lockdown in England. Additional UT from December 2020 reduces the epidemic dramatically by Jan 2021 and could then be stopped, as continued TTI would prevent rapid recurrence.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308142

ABSTRACT

Background: As England is starting to ease lockdown restrictions in a phased manner, it is important to determine the level of social distancing compliance, quantified here as the daily number of social contacts per person, i.e. the daily contact rate, needed to maintain control of the COVID-19 epidemic and not exceed acute bed capacity in case of a secondary wave later this year. This work uses mathematical modelling to simulate the levels of COVID-19 in North East London (NEL) and inform the level of social distancing necessary to protect the public and the healthcare demand from a secondary COVID-19 wave during 2020. Methods: : We used a Susceptible-Exposed-Infected-Removed (SEIR) model describing the transmission of SARS-CoV-2 in North East London (NEL), calibrated to data on confirmed COVID-19 associated hospitalisations, hospital discharges and in-hospital deaths in NEL. To account for the uncertainty in both the infectiousness period and the proportion of symptomatic infection, we simulated nine scenarios for different combinations of infectiousness period (1, 3 and 5 days) and proportion of symptomatic infection (70%, 50% and 25% of all infections). Across all scenarios, the calibrated model was used to assess the risk of occurrence and forecast the strength and timing of a second COVID-19 wave under varying levels of daily contact rate from July 04, 2020. Specifically, the daily contact rate required to suppress the epidemic and prevent resurgence of COVID-19 cases, and the daily contact rate required to stay within the acute bed capacity of the NEL system without any additional intervention measures after July 2020, were determined across the nine different scenarios. Results: : Our results caution against a full relaxing of the lockdown, predicting that a return to pre-COVID-19 levels of social contact from July 04, 2020 may induce a second wave up to eight times the original wave. With different levels of social distancing continuing into next year, the second wave can be avoided or the strength of the second wave can be mitigated. Keeping the daily contact rate lower than 5 or 6, depending on scenarios, for the rest of this year, can prevent increase in the number of COVID-19 cases, could keep the effective reproduction number R below 1 and a second COVID-19 wave may be avoided in NEL. A daily contact rate between 6 and 7, across scenarios, is likely to increase R above 1 and result in a secondary COVID-19 wave with significantly increased COVID-19 cases and associated deaths, but with demand for hospital based care remaining within the bed capacity of the NEL health and care system. In contrast, an increase in daily contact rate above 8 to 9, depending on scenarios, will likely exceed the acute bed capacity in NEL and may potentially require additional lockdowns. This scenario is associated with significantly increased COVID-19 cases and deaths, and acute COVID-19 care demand is likely to require significant scaling down of the usual operation of the health and care system, and should be avoided. Conclusions: : Our findings suggest that to avoid a second COVID-19 wave and to stay within the acute bed capacity of the NEL health and care system, phased relaxing of the social distancing in NEL is advised with a view to limiting the average number of social interactions in the population. Increasing the social interaction rapidly could result in a second COVID-19 wave that will likely exceed the acute bed capacity in the system, and depending on the strength of the resurgence may require additional lockdown measures.

8.
Epidemics ; 38: 100546, 2022 03.
Article in English | MEDLINE | ID: covidwho-1676726

ABSTRACT

Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Humans , SARS-CoV-2
10.
J Infect ; 84(3): 361-382, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1587235

ABSTRACT

BACKGROUND: The role of children and young people (CYP) in transmission of SARS-CoV-2 in household and educational settings remains unclear. We undertook a systematic review and meta-analysis of contact-tracing and population-based studies at low risk of bias. METHODS: We searched 4 electronic databases on 28 July 2021 for contact-tracing studies and population-based studies informative about transmission of SARS-CoV-2 from 0 to 19 year olds in household or educational settings. We excluded studies at high risk of bias, including from under-ascertainment of asymptomatic infections. We undertook multilevel random effects meta-analyses of secondary attack rates (SAR: contact-tracing studies) and school infection prevalence, and used meta-regression to examine the impact of community SARS-CoV-2 incidence on school infection prevalence. FINDINGS: 4529 abstracts were reviewed, resulting in 37 included studies (16 contact-tracing; 19 population studies; 2 mixed studies). The pooled relative transmissibility of CYP compared with adults was 0.92 (0.68, 1.26) in adjusted household studies. The pooled SAR from CYP was lower (p = 0.002) in school studies 0.7% (0.2, 2.7) than household studies (7.6% (3.6, 15.9) . There was no difference in SAR from CYP to child or adult contacts. School population studies showed some evidence of clustering in classes within schools. School infection prevalence was associated with contemporary community 14-day incidence (OR 1.003 (1.001, 1.004), p<0.001). INTERPRETATION: We found no difference in transmission of SARS-CoV-2 from CYP compared with adults within household settings. SAR were markedly lower in school compared with household settings, suggesting that household transmission is more important than school transmission in this pandemic. School infection prevalence was associated with community infection incidence, supporting hypotheses that school infections broadly reflect community infections. These findings are important for guiding policy decisions on shielding, vaccination school and operations during the pandemic.


Subject(s)
COVID-19 , SARS-CoV-2 , Adolescent , Adult , COVID-19/epidemiology , Child , Contact Tracing , Humans , Pandemics , Schools
11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-297053

ABSTRACT

Background: The role of children and young people (CYP) in transmission of SARS-CoV-2 in household and educational settings remains unclear. We undertook a systematic review and meta-analysis of contact-tracing and population-based studies at low risk of bias. Methods We searched 4 electronic databases on 28 July 2021 for contact-tracing studies and population-based studies informative about transmission of SARS-CoV-2 from 0-19 year olds in household or educational settings. We excluded studies at high risk of bias, including from under-ascertainment of asymptomatic infections. We undertook multilevel random effects meta-analyses of secondary attack rates (SAR: contact-tracing studies) and school infection prevalence, and used meta-regression to examine the impact of community SARS-CoV-2 incidence on school infection prevalence. Findings 4529 abstracts were reviewed, resulting in 37 included studies (16 contact-tracing;19 population studies;2 mixed studies). The pooled relative transmissibility of CYP compared with adults was 0.92 (0.68, 1.26) in adjusted household studies. The pooled SAR from CYP was lower (p=0.002) in school studies 0.7% (0.2, 2.7) than household studies (7.6% (3.6, 15.9) . There was no difference in SAR from CYP to child or adult contacts. School population studies showed some evidence of clustering in classes within schools. School infection prevalence was associated with contemporary community 14-day incidence (OR 1.003 (1.001, 1.004), p<0.001). Interpretation We found no difference in transmission of SARS-CoV-2 from CYP compared with adults within household settings. SAR were markedly lower in school compared with household settings, suggesting that household transmission is more important than school transmission in this pandemic. School infection prevalence was associated with community infection incidence, supporting hypotheses that school infections broadly reflect community infections. These findings are important for guiding policy decisions on shielding, vaccination school and operations during the pandemic.

12.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296251

ABSTRACT

Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they don't allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory.

13.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296241

ABSTRACT

The evolution of the SARS-CoV-2 pandemic continuously produces new variants, which warrant timely epidemiological characterisation. Here we use the dense genomic surveillance generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of sub-epidemics that peaked in the early autumn of 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. Alpha grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed Alpha and eliminated nearly all other lineages in early 2021. However, a series of variants (mostly containing the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. Accounting for sustained introductions, however, indicates that their transmissibility is unlikely to have exceeded that of Alpha. Finally, B.1.617.2/Delta was repeatedly introduced to England and grew rapidly in the early summer of 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on June 26.

14.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296102

ABSTRACT

One of the difficulties in monitoring an ongoing pandemic is deciding on the metric that best describes its status when multiple highly inter-correlated measurements are available. Having a single measure, such as whether the effective reproduction number R, has been useful in tracking whether the epidemic is on the incline or the decline and for imposing policy interventions to curb the increase. We propose an additional metric for tracking the UK epidemic across all four nations, that can capture the different spatial scales. This paper illustrates how to derive the principal scores from a weighted Principal Component Analysis using publicly available data. We show the detectable impact of interventions on the state of the epidemic and suggest that there is a single dominant trend observable through the principal score, but this is different across nations and waves. For example, the epidemic status can be tracked by cases in Scotland at a countrywide scale, whereas across waves and disjoint nations, hospitalisations are the dominant contributor to principal scores. Thus, our results suggest that hospitalisations may be an additional useful metric for ongoing tracking of the epidemic status across the UK nations alongside R and growth rate.

15.
Vaccine ; 38(33): 5163-5170, 2020 07 14.
Article in English | MEDLINE | ID: covidwho-1452421

ABSTRACT

The nature and timing of the next influenza pandemic is unknown. This makes it difficult for policy makers to assess whether spending money now to prepare for mass immunisation in the event of a pandemic is worthwhile. We used simple epidemiological modelling and health economic analysis to identify the range of pandemic and policy scenarios under which plans to immunise the general UK population would have net benefit if a stockpiled vaccine or, alternatively, a responsively purchased vaccine were used. Each scenario we studied comprised a combination of pandemic, vaccine and immunisation programme characteristics in presence or absence of access to effective antivirals, with the chance of there being a pandemic each year fixed. Monetarised health benefits and cost savings from any influenza cases averted were set against the option, purchase, storage, distribution, administration, and disposal costs relevant for each scenario to give a discounted net present value over 10 years for planning to immunise, accounting for the possibility that there may be no pandemic over the period considered. To support understanding and exploration of model output, an interactive visualisation tool was devised and made available online. We evaluated over 29 million combinations of pandemic and policy characteristics. Preparedness plans incorporating mass immunisation show positive net present value for a wide range of scenarios, predominantly in the absence of effective antivirals. Plans based on the responsive purchase of vaccine have wider benefit than plans reliant on the purchase and maintenance of a stockpile if immunisation can start without extensive delays. This finding is not dependent on responsively purchased vaccine being more effective than stockpiled vaccine, but rather is driven by avoiding the costs of storing and replenishing a stockpile.


Subject(s)
Influenza Vaccines , Influenza, Human , Humans , Influenza, Human/epidemiology , Influenza, Human/prevention & control , Mass Vaccination , Pandemics/prevention & control , United Kingdom/epidemiology
16.
Nature ; 600(7889): 506-511, 2021 12.
Article in English | MEDLINE | ID: covidwho-1467111

ABSTRACT

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral/genetics , Genomics , SARS-CoV-2/genetics , Amino Acid Substitution , COVID-19/transmission , England/epidemiology , Epidemiological Monitoring , Humans , Molecular Epidemiology , Mutation , Quarantine/statistics & numerical data , SARS-CoV-2/classification , Spatio-Temporal Analysis , Spike Glycoprotein, Coronavirus/genetics
17.
Stat Methods Med Res ; : 9622802211037079, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1438210

ABSTRACT

Since the beginning of the COVID-19 pandemic, the reproduction number R has become a popular epidemiological metric used to communicate the state of the epidemic. At its most basic, R is defined as the average number of secondary infections caused by one primary infected individual. R seems convenient, because the epidemic is expanding if R>1 and contracting if R<1. The magnitude of R indicates by how much transmission needs to be reduced to control the epidemic. Using R in a naïve way can cause new problems. The reasons for this are threefold: (1) There is not just one definition of R but many, and the precise definition of R affects both its estimated value and how it should be interpreted. (2) Even with a particular clearly defined R, there may be different statistical methods used to estimate its value, and the choice of method will affect the estimate. (3) The availability and type of data used to estimate R vary, and it is not always clear what data should be included in the estimation. In this review, we discuss when R is useful, when it may be of use but needs to be interpreted with care, and when it may be an inappropriate indicator of the progress of the epidemic. We also argue that careful definition of R, and the data and methods used to estimate it, can make R a more useful metric for future management of the epidemic.

18.
EClinicalMedicine ; 38: 101011, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1375928

ABSTRACT

BACKGROUND: Testing for COVID-19 with quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) may result in delayed detection of disease. Antigen detection via lateral flow testing (LFT) is faster and amenable to population-wide testing strategies. Our study assesses the diagnostic accuracy of LFT compared to RT-PCR on the same primarycare patients in Austria. METHODS: Patients with mild to moderate flu-like symptoms attending a general practice network in an Austrian district (October 22 to November 30, 2020) received clinical assessment including LFT. All suspected COVID-19 cases obtained additional RT-PCR and were divided into two groups: Group 1 (true reactive): suspected cases with reactive LFT and positive RT-PCR; and Group 2 (false non-reactive): suspected cases with a non-reactive LFT but positive RT-PCR. FINDINGS: Of the 2,562 symptomatic patients, 1,037 were suspected of COVID-19 and 826 (79.7%) patients tested RT-PCR positive. Among patients with positive RT-PCR, 788/826 tested LFT reactive (Group 1) and 38 (4.6%) non-reactive (Group 2). Overall sensitivity was 95.4% (95%CI: [94%,96.8%]), specificity 89.1% (95%CI: [86.3%, 91.9%]), positive predictive value 97.3% (95%CI:[95.9%, 98.7%]) and negative predictive value 82.5% (95%CI:[79.8%, 85.2%]). Reactive LFT and positive RT-PCR were positively correlated (r = 0.968,95CI=[0.952,0.985] and κ = 0.823 , 95%CI=[0.773,0.866]). Reactive LFT was negatively correlated with Ct-value ( r  = -0.2999, p  < 0.001) and pre-test symptom duration (r = -0.1299,p = 0.0043) while Ct-value was positively correlated with pre-test symptom duration (r = 0.3733),p < 0.001). INTERPRETATION: We show that LFT is an accurate alternative to RT-PCR testing in primary care. We note the importance of administering LFT properly, here combined with clinical assessment in symptomatic patients. FUNDING: Thomas Czypionka received funding from the European Union's Horizon 2020 Research and Innovation Programe under the grant agreement No 101016233 (PERISCOPE). No further funding was available for this study.

19.
BMJ Open ; 11(8): e045225, 2021 08 02.
Article in English | MEDLINE | ID: covidwho-1338867

ABSTRACT

OBJECTIVES: We explore the importance of SARS-CoV-2 sentinel surveillance testing in primary care during a regional COVID-19 outbreak in Austria. DESIGN: Prospective cohort study. SETTING: A single sentinel practice serving 22 829 people in the ski-resort of Schladming-Dachstein. PARTICIPANTS: All 73 patients presenting with mild-to-moderate flu-like symptoms between 24 February and 03 April, 2020. INTERVENTION: Nasopharyngeal sampling to detect SARS-CoV-2 using real-time reverse transcriptase-quantitative PCR (RT-qPCR). OUTCOME MEASURES: We compared RT-qPCR at presentation with confirmed antibody status. We split the outbreak in two parts, by halving the period from the first to the last case, to characterise three cohorts of patients with confirmed infection: early acute (RT-qPCR reactive) in the first half; and late acute (reactive) and late convalescent (non-reactive) in the second half. For each cohort, we report the number of cases detected, the accuracy of RT-qPCR, the duration and variety of symptoms, and the number of viral clades present. RESULTS: Twenty-two patients were diagnosed with COVID-19 (eight early acute, seven late acute and seven late convalescent), 44 patients tested SARS-CoV-2 negative and 7 were excluded. The sensitivity of RT-qPCR was 100% among all acute cases, dropping to 68.1% when including convalescent. Test specificity was 100%. Mean duration of symptoms for each group were 2 days (range 1-4) among early acute, 4.4 days (1-7) among late acute and 8 days (2-12) among late convalescent. Confirmed infection was associated with loss of taste. Acute infection was associated with loss of taste, nausea/vomiting, breathlessness, sore throat and myalgia; but not anosmia, fever or cough. Transmission clusters of three viral clades (G, GR and L) were identified. CONCLUSIONS: RT-qPCR testing in primary care can rapidly and accurately detect SARS-CoV-2 among people with flu-like illness in a heterogeneous viral outbreak. Targeted testing in primary care can support national sentinel surveillance of COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , Austria , Cohort Studies , Humans , Primary Health Care , Prospective Studies , Sensitivity and Specificity
20.
PLoS Comput Biol ; 17(7): e1009149, 2021 07.
Article in English | MEDLINE | ID: covidwho-1325366

ABSTRACT

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.


Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , Systems Analysis , Basic Reproduction Number , COVID-19/etiology , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Testing , COVID-19 Vaccines , Computational Biology , Computer Simulation , Contact Tracing , Disease Progression , Hand Disinfection , Host Microbial Interactions , Humans , Masks , Mathematical Concepts , Pandemics , Physical Distancing , Quarantine , Software
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