RESUMO
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.
Assuntos
COVID-19/psicologia , Infodemia , Disseminação de Informação/ética , COVID-19/epidemiologia , Epidemias/psicologia , Humanos , Disseminação de Informação/métodos , Saúde Pública , Pesquisa/tendências , SARS-CoV-2RESUMO
The emergence of successive Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) during 2020 to 2022, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics-such as varying levels of immunity-can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform Coronavirus Disease 2019 (COVID-19) planning and response and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both interindividual variation in Ct values and complex host characteristics-such as vaccination status, exposure history, and age-we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least 5 prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs. Trial Registration: The Legacy study is a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening for SARS-CoV-2 at University College London Hospitals or at the Francis Crick Institute (NCT04750356) (22,23). The Legacy study was approved by London Camden and Kings Cross Health Research Authority Research and Ethics committee (IRAS number 286469). The Legacy study was approved by London Camden and Kings Cross Health Research Authority Research and Ethics committee (IRAS number 286469) and is sponsored by University College London Hospitals. Written consent was given by all participants.
Assuntos
COVID-19 , SARS-CoV-2 , Adulto , Humanos , SARS-CoV-2/genética , Teorema de Bayes , COVID-19/epidemiologia , Estudos ProspectivosRESUMO
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.
Assuntos
Anticorpos Antivirais/sangue , COVID-19/imunologia , Reinfecção/imunologia , Adolescente , Adulto , Idoso , COVID-19/epidemiologia , COVID-19/prevenção & controle , Teste de Ácido Nucleico para COVID-19 , Teste Sorológico para COVID-19 , Humanos , Modelos Logísticos , Pessoa de Meia-Idade , Reação em Cadeia da Polimerase , Estudos Prospectivos , Reinfecção/prevenção & controle , SARS-CoV-2/imunologia , Estudos Soroepidemiológicos , Fatores de Tempo , Estados Unidos/epidemiologia , Local de Trabalho/estatística & dados numéricos , Adulto JovemRESUMO
The epidemiological characteristics of SARS-CoV-2 transmission have changed over the pandemic due to emergence of new variants. A decrease in the generation or serial intervals would imply a shortened transmission timescale and, hence, outbreak response measures would need to expand at a faster rate. However, there are challenges in measuring these intervals. Alongside epidemiological changes, factors like varying delays in outbreak response, social contact patterns, dependence on the growth phase of an outbreak, and effects of exposure to multiple infectors can also influence measured generation or serial intervals. To guide real-time interpretation of variant data, we simulated concurrent changes in the aforementioned factors and estimated the statistical power to detect a change in the generation and serial interval. We compared our findings to the reported decrease or lack thereof in the generation and serial intervals of different SARS-CoV-2 variants. Our study helps to clarify contradictory outbreak observations and informs the required sample sizes under certain outbreak conditions to ensure that future studies of generation and serial intervals are adequately powered.
Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , Surtos de Doenças , Pandemias , Previsões , BiologiaRESUMO
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.
Assuntos
Surtos de Doenças , Pandemias , Infecções Respiratórias , Instituições Acadêmicas , COVID-19/prevenção & controle , COVID-19/transmissão , Criança , Simulação por Computador , Surtos de Doenças/prevenção & controle , Humanos , Influenza Humana/prevenção & controle , Influenza Humana/transmissão , Pandemias/prevenção & controle , Infecções Respiratórias/prevenção & controle , Infecções Respiratórias/transmissãoRESUMO
During 2020-2022, players and staff in the English Premier League in the United Kingdom were tested regularly for SARS-CoV-2 with the aim of creating a biosecure bubble for each team. We found that prevalence and reinfection estimates were consistent with those from other studies and with community infection trends.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , COVID-19/epidemiologia , Reino Unido/epidemiologia , Prevalência , Teste para COVID-19/métodos , Reinfecção/epidemiologia , Reinfecção/virologia , Masculino , AdultoRESUMO
To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.
Assuntos
COVID-19 , Viroses , Humanos , COVID-19/epidemiologia , SARS-CoV-2 , Pandemias , Saúde PúblicaRESUMO
BACKGROUND: Recurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models. METHODS: We used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given age-stratified data, and links reported case counts to routinely collected covariates (e.g. test number, vaccine coverage). We assessed the predictive performance of our model up to four weeks ahead using proper scoring rules and compared it to the European COVID-19 Forecast Hub ensemble model. Using simulations, we evaluated the impact of variations in transmission on the forecasts. We developed an open-source RShiny App to visualise the forecasts and scenarios. RESULTS: At a national level, the median relative difference between our median weekly case forecasts and the data up to four weeks ahead was 25% (IQR: 12-50%) over the prediction period. The accuracy decreased as the forecast horizon increased (on average 24% increase in the median ranked probability score per added week), while the accuracy of death forecasts was more stable. Beyond two weeks, the model generated a narrow range of likely transmission dynamics. The median national case forecasts showed similar accuracy to forecasts from the European COVID-19 Forecast Hub ensemble model, but the prediction interval was narrower in our model. Generating forecasts under alternative transmission scenarios was therefore key to capturing the range of possible short-term transmission dynamics. DISCUSSION: Our model captures changes in local COVID-19 outbreak dynamics, and enables quantification of short-term transmission risk at a subnational level. The outputs of the model improve our ability to identify areas where outbreaks are most likely, and are available to a wide range of public health professionals through the Shiny App we developed.
Assuntos
COVID-19 , Humanos , COVID-19/epidemiologia , Incidência , Surtos de Doenças , Saúde Pública , PrevisõesRESUMO
Schools play a central role in the transmission of many respiratory infections. Heterogeneous social contact patterns associated with the social structures of schools (i.e., classes/grades) are likely to influence the within-school transmission dynamics, but data-driven evidence on fine-scale transmission patterns between students has been limited. Using a mathematical model, we analyzed a large-scale dataset of seasonal influenza outbreaks in Matsumoto city, Japan, to infer social interactions within and between classes/grades from observed transmission patterns. While the relative contribution of within-class and within-grade transmissions to the reproduction number varied with the number of classes per grade, the overall within-school reproduction number, which determines the initial growth of cases and the risk of sustained transmission, was only minimally associated with class sizes and the number of classes per grade. This finding suggests that interventions that change the size and number of classes, e.g., splitting classes and staggered attendance, may have a limited effect on the control of school outbreaks. We also found that vaccination and mask-wearing of students were associated with reduced susceptibility (vaccination and mask-wearing) and infectiousness (mask-wearing), and hand washing was associated with increased susceptibility. Our results show how analysis of fine-grained transmission patterns between students can improve understanding of within-school disease dynamics and provide insights into the relative impact of different approaches to outbreak control.
Assuntos
Influenza Humana/epidemiologia , Influenza Humana/transmissão , Criança , Pré-Escolar , Cidades/epidemiologia , Surtos de Doenças , Feminino , Humanos , Influenza Humana/virologia , Japão/epidemiologia , Masculino , Infecções Respiratórias/epidemiologia , Infecções Respiratórias/transmissão , Infecções Respiratórias/virologia , Instituições Acadêmicas , Estações do Ano , Estrutura Social , EstudantesRESUMO
To assess changes in SARS-CoV-2 spike binding antibody prevalence in the Dominican Republic and implications for immunologic protection against variants of concern, we prospectively enrolled 2,300 patients with undifferentiated febrile illnesses in a study during March 2021-August 2022. We tested serum samples for spike antibodies and tested nasopharyngeal samples for acute SARS-CoV-2 infection using a reverse transcription PCR nucleic acid amplification test. Geometric mean spike antibody titers increased from 6.6 (95% CI 5.1-8.7) binding antibody units (BAU)/mL during March-June 2021 to 1,332 (95% CI 1,055-1,682) BAU/mL during May-August 2022. Multivariable binomial odds ratios for acute infection were 0.55 (95% CI 0.40-0.74), 0.38 (95% CI 0.27-0.55), and 0.27 (95% CI 0.18-0.40) for the second, third, and fourth versus the first anti-spike quartile; findings were similar by viral strain. Combining serologic and virologic screening might enable monitoring of discrete population immunologic markers and their implications for emergent variant transmission.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , República Dominicana/epidemiologia , COVID-19/epidemiologia , Anticorpos Antivirais , Febre , Glicoproteína da Espícula de Coronavírus/genética , Anticorpos NeutralizantesRESUMO
BACKGROUND: Effective Coronavirus Disease 2019 (COVID-19) response relies on good knowledge of population infection dynamics, but owing to under-ascertainment and delays in symptom-based reporting, obtaining reliable infection data has typically required large dedicated local population studies. Although many countries implemented Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing among travellers, it remains unclear how accurately arrival testing data can capture international patterns of infection, because those arrival testing data were rarely reported systematically, and predeparture testing was often in place as well, leading to nonrepresentative infection status among arrivals. METHODS AND FINDINGS: In French Polynesia, testing data were reported systematically with enforced predeparture testing type and timing, making it possible to adjust for nonrepresentative infection status among arrivals. Combining statistical models of polymerase chain reaction (PCR) positivity with data on international travel protocols, we reconstructed estimates of prevalence at departure using only testing data from arrivals. We then applied this estimation approach to the United States of America and France, using data from over 220,000 tests from travellers arriving into French Polynesia between July 2020 and March 2022. We estimated a peak infection prevalence at departure of 2.1% (95% credible interval: 1.7, 2.6%) in France and 1% (95% CrI: 0.63, 1.4%) in the USA in late 2020/early 2021, with prevalence of 4.6% (95% CrI: 3.9, 5.2%) and 4.3% (95% CrI: 3.6, 5%), respectively, estimated for the Omicron BA.1 waves in early 2022. We found that our infection estimates were a leading indicator of later reported case dynamics, as well as being consistent with subsequent observed changes in seroprevalence over time. We did not have linked data on traveller demography or unbiased domestic infection estimates (e.g., from random community infection surveys) in the USA and France. However, our methodology would allow for the incorporation of prior data from additional sources if available in future. CONCLUSIONS: As well as elucidating previously unmeasured infection dynamics in these countries, our analysis provides a proof-of-concept for scalable and accurate leading indicator of global infections during future pandemics.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , COVID-19/diagnóstico , COVID-19/epidemiologia , Prevalência , Estudos Soroepidemiológicos , França/epidemiologiaRESUMO
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.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , COVID-19/diagnóstico , COVID-19/epidemiologia , COVID-19/prevenção & controle , Busca de Comunicante , Controle de Doenças Transmissíveis , Pandemias/prevenção & controleRESUMO
The COVID-19 pandemic has motivated many open and collaborative analytical research projects with real-world impact. However, despite their value, such activities are generally overlooked by traditional academic metrics. Science is ultimately improved by analytical work, whether ensuring reproducible and well-documented code to accompany papers, developing and maintaining flexible tools, sharing and curating data, or disseminating analysis to wider audiences. To increase the impact and sustainability of modern science, it will be crucial to ensure these analytical activities-and the people who do them-are valued in academia.
Assuntos
Pesquisa Biomédica , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Acesso à Informação , Disciplinas das Ciências Biológicas/estatística & dados numéricos , Pesquisa Biomédica/estatística & dados numéricos , COVID-19 , Pandemias , Editoração , Recompensa , Software , UniversidadesRESUMO
Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24-60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.
Assuntos
Influenza Humana , Anticorpos Antivirais , Teorema de Bayes , Criança , Pré-Escolar , Estudos Transversais , Humanos , Incidência , Vírus da Influenza A Subtipo H3N2 , Influenza Humana/epidemiologia , Estações do AnoRESUMO
BACKGROUND: Subnational heterogeneity in immunity to measles can create pockets of susceptibility and result in long-lasting outbreaks despite high levels of national vaccine coverage. The elimination status defined by the World Health Organization aims to identify countries where the virus is no longer circulating and can be verified after 36 months of interrupted transmission. However, since 2018, numerous countries have lost their elimination status soon after reaching it, showing that the indicators defining elimination may not be associated with lower risks of outbreaks. METHODS: We quantified the impact of local vaccine coverage and recent levels of incidence on the dynamics of measles in each French department between 2009 and 2018, using mathematical models based on the "Endemic-Epidemic" regression framework. After fitting the models using daily case counts, we simulated the effect of variations in the vaccine coverage and recent incidence on future transmission. RESULTS: High values of local vaccine coverage were associated with fewer imported cases and lower risks of local transmissions, but regions that had recently reported high levels of incidence were also at a lower risk of local transmission. This may be due to additional immunity accumulated during recent outbreaks. Therefore, the risk of local transmission was not lower in areas fulfilling the elimination criteria. A decrease of 3% in the 3-year average vaccine uptake led to a fivefold increase in the average annual number of cases in simulated outbreaks. CONCLUSIONS: Local vaccine uptake was a reliable indicator of the intensity of transmission in France, even if it only describes yearly coverage in a given age group, and ignores population movements. Therefore, spatiotemporal variations in vaccine coverage, caused by disruptions in routine immunisation programmes, or lower trust in vaccines, can lead to large increases in both local and cross-regional transmission. The incidence indicator used to define the elimination status was not associated with a lower number of local transmissions in France, and may not illustrate the risks of imminent outbreaks. More detailed models of local immunity levels or subnational seroprevalence studies may yield better estimates of local risk of measles outbreaks.
Assuntos
Vacina contra Sarampo , Sarampo , Surtos de Doenças/prevenção & controle , Humanos , Incidência , Lactente , Sarampo/epidemiologia , Sarampo/prevenção & controle , Estudos Soroepidemiológicos , VacinaçãoRESUMO
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.
Assuntos
COVID-19 , Controle de Doenças Transmissíveis/estatística & dados numéricos , Viagem/estatística & dados numéricos , Algoritmos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Biologia Computacional , Atividades Humanas/estatística & dados numéricos , Humanos , SARS-CoV-2 , Mídias Sociais/estatística & dados numéricos , Reino UnidoRESUMO
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.
Assuntos
COVID-19 , Europa (Continente)/epidemiologia , Hospitalização , Humanos , SARS-CoV-2 , VacinaçãoRESUMO
Contact between wild animals and farmed livestock may result in disease transmission with huge financial, welfare and ethical consequences. Conflicts between people and wildlife can also arise when species such as wild boar (Sus scrofa) consume crops or dig up pasture. This is a relatively recent problem in England where wild boar populations have become re-established in the last 20 years following a 500-year absence. The aim of this pilot study was to determine if and how often free-living wild boar visited two commercial pig farms near the Forest of Dean in southwest England. We placed 20 motion-sensitive camera traps at potential entry points to, and trails surrounding, the perimeter of two farmyards housing domestic pigs between August 2019 and February 2021, covering a total of 6030 trap nights. Forty wild boar detections were recorded on one farm spread across 27 nights, with a median (range) of 1 (0 to 7) night of wild boar activity per calendar month. Most of these wild boar detections occurred between ten and twenty metres of housed domestic pigs. No wild boar was detected at the other farm. These results confirm wild boar do visit commercial pig farms, and therefore, there is potential for contact and pathogen exchange between wild boar and domestic pigs. The visitation rates derived from this study could be used to parameterise disease transmission models of pathogens common to domestic pigs and wild boars, such as the African swine fever virus, and subsequently to develop mitigation strategies to reduce unwanted contacts.
RESUMO
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.