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1.
Genome Med ; 14(1): 61, 2022 06 10.
Article in English | MEDLINE | ID: covidwho-1951320

ABSTRACT

BACKGROUND: The continuous emergence of SARS-CoV-2 variants of concern (VOC) with immune escape properties, such as Delta (B.1.617.2) and Omicron (B.1.1.529), questions the extent of the antibody-mediated protection against the virus. Here we investigated the long-term antibody persistence in previously infected subjects and the extent of the antibody-mediated protection against B.1, B.1.617.2 and BA.1 variants in unvaccinated subjects previously infected, vaccinated naïve and vaccinated previously infected subjects. METHODS: Blood samples collected 15 months post-infection from unvaccinated (n=35) and vaccinated (n=41) previously infected subjects (Vo' cohort) were tested for the presence of antibodies against the SARS-CoV-2 spike (S) and nucleocapsid (N) antigens using the Abbott, DiaSorin, and Roche immunoassays. The serum neutralising reactivity was assessed against B.1, B.1.617.2 (Delta), and BA.1 (Omicron) SARS-CoV-2 strains through micro-neutralisation. The antibody titres were compared to those from previous timepoints, performed at 2- and 9-months post-infection on the same individuals. Two groups of naïve subjects were used as controls, one from the same cohort (unvaccinated n=29 and vaccinated n=20) and a group of vaccinated naïve healthcare workers (n=61). RESULTS: We report on the results of the third serosurvey run in the Vo' cohort. With respect to the 9-month time point, antibodies against the S antigen significantly decreased (P=0.0063) among unvaccinated subjects and increased (P<0.0001) in vaccinated individuals, whereas those against the N antigen decreased in the whole cohort. When compared with control groups (naïve Vo' inhabitants and naïve healthcare workers), vaccinated subjects that were previously infected had higher antibody levels (P<0.0001) than vaccinated naïve subjects. Two doses of vaccine elicited stronger anti-S antibody response than natural infection (P<0.0001). Finally, the neutralising reactivity of sera against B.1.617.2 and BA.1 was 4-fold and 16-fold lower than the reactivity observed against the original B.1 strain. CONCLUSIONS: These results confirm that vaccination induces strong antibody response in most individuals, and even stronger in previously infected subjects. Neutralising reactivity elicited by natural infection followed by vaccination is increasingly weakened by the recent emergence of VOCs. While immunity is not completely compromised, a change in vaccine development may be required going forward, to generate cross-protective pan-coronavirus immunity in the global population.


Subject(s)
COVID-19 , Viral Vaccines , Antibodies, Viral , COVID-19/prevention & control , Humans , SARS-CoV-2 , Vaccination
2.
Commun Med (Lond) ; 2: 54, 2022.
Article in English | MEDLINE | ID: covidwho-1947549

ABSTRACT

Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%. Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331841

ABSTRACT

Population testing remains central to COVID-19 control and surveillance, with countries increasingly using antigen tests rather than molecular tests. Here we describe a SARS-CoV-2 variant that escapes N antigen tests due to multiple disruptive amino-acid substitutions in the N protein. By fitting a multistrain compartmental model to genomic and epidemiological data, we show that widespread antigen testing in the Italian region of Veneto favored the undetected spread of the antigen-escape variant compared to the rest of Italy. We highlight novel limitations of widespread antigen testing in the absence of molecular testing for diagnostic or confirmatory purposes. Critically, in the presence of a variant that escapes antigen testing, following up a proportion of negative antigen tests with a molecular test is the optimal testing strategy. Together, these findings highlight the importance of retaining molecular testing for surveillance purposes, also in contexts where the use of antigen tests is widespread.

4.
Clin Infect Dis ; 2022 Feb 17.
Article in English | MEDLINE | ID: covidwho-1692237

ABSTRACT

BACKGROUND: Estimating the transmissibility of infectious diseases is key to inform situational awareness and for response planning. Several methods tend to overestimate the basic (R0) and effective (Rt) reproduction numbers during the initial phases of an epidemic. The reasons driving the observed bias are unknown. In this work we explore the impact of incomplete observations and underreporting of the first generations of infections during the initial epidemic phase. METHODS: We propose a debiasing procedure which utilises a linear exponential growth model to infer unobserved initial generations of infections and apply it to EpiEstim. We assess the performance of our adjustment using simulated data, considering different levels of transmissibility and reporting rates. We also apply the proposed correction to SARS-CoV-2 incidence data reported in Italy, Sweden, the United Kingdom and the United States of America. RESULTS: In all simulation scenarios, our adjustment outperforms the original EpiEstim method. The proposed correction reduces the systematic bias and the quantification of uncertainty is more precise, as better coverage of the true R0 values is achieved with tighter credible intervals. When applied to real world data, the proposed adjustment produces basic reproduction number estimates which closely match the estimates obtained in other studies while making use of a minimal amount of data. CONCLUSIONS: The proposed adjustment refines the reproduction number estimates obtained with the current EpiEstim implementation by producing improved, more precise estimates earlier than with the original method. This has relevant public health implications.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315482

ABSTRACT

Background: After COVID-19 early expansion occurred in mainland China, seasonal influenza transmission in Hong Kong, which was growing initially, immediately plateaued, and then abruptly declined a few weeks later. These patterns correspond to the three phases of early COVID-19 spread from Wuhan to Hong Kong, i.e. the ordinary: before the occurrence in Wuhan;the awareness: after the evidence of human-to-human transmission was revealed;and the spreading: after the first local case was confirmed in Hong Kong. The available surveyed data on changes in precautionary behavior during these phases, i.e. face mask wearing and avoiding the crowd, provide an opportunity to estimate the protectiveness of face mask on influenza transmissibility. Methods: We developed a time-series susceptible-infected-recovered (TS-SIR) regression model to estimate the time-varying effective reproduction number Rt based on the weekly reported influenza cases. The reporting rate of influenza was adjusted under the assumption that patients with severe influenza were seeking medical care. After separating the effect from herd immunity, the percent reduction in Rt from each behavior was calculated as an indication of the protectiveness. Findings: The average Rt of winter influenza season in 2019/20 was estimated in the three phases: 1.29 (95%CI, 1.27 to 1.32) in the ordinary, 1.00 (95%CI, 0.99 to 1.00) in the awareness, and 0.73 (95%CI, 0.73 to 0.74) in the spreading. Our results showed that face mask wearing protected 22% from being transmitted, which was nearly half of the effect of avoiding the crowd (42%). If more than 79% of the people adopted both precautionary behaviors, the initial Rt reduced to less than one. Interpretation: The results suggested that mandatory face mask wearing along with social distancing practices could be effective in suppressing the transmission of influenza, which may also give hints on preventing COVID-19 infection.Funding Information: We declare no competing interests.Declaration of Interests: We acknowledge the support from grants funded by Health and Medical Research Fund [COVID190329415], City University of Hong Kong [7200573], andWellcome Trust and The Royal Society [213494/Z/18/3Z95].

6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-306829

ABSTRACT

Background:  As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide. Methods: : We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: : Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries. Conclusions: : Our analysis shows that a large number of COVID-19 cases remain undetected across the world. These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-305031

ABSTRACT

Background : The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods : Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results : Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.

8.
Viruses ; 14(2)2022 02 15.
Article in English | MEDLINE | ID: covidwho-1687058

ABSTRACT

In February 2020, the municipality of Vo', a small town near Padua (Italy) was quarantined due to the first coronavirus disease 19 (COVID-19)-related death detected in Italy. To investigate the viral prevalence and clinical features, the entire population was swab tested in two sequential surveys. Here we report the analysis of 87 viral genomes, which revealed that the unique ancestor haplotype introduced in Vo' belongs to lineage B, carrying the mutations G11083T and G26144T. The viral sequences allowed us to investigate the viral evolution while being transmitted within and across households and the effectiveness of the non-pharmaceutical interventions implemented in Vo'. We report, for the first time, evidence that novel viral haplotypes can naturally arise intra-host within an interval as short as two weeks, in approximately 30% of the infected individuals, regardless of symptom severity or immune system deficiencies. Moreover, both phylogenetic and minimum spanning network analyses converge on the hypothesis that the viral sequences evolved from a unique common ancestor haplotype that was carried by an index case. The lockdown extinguished both the viral spread and the emergence of new variants.


Subject(s)
Family Characteristics , Genome, Viral , Haplotypes , Host Microbial Interactions/genetics , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Communicable Disease Control/methods , Evolution, Molecular , Humans , Italy/epidemiology , Mutation , Phylogeny , SARS-CoV-2/classification
9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296548

ABSTRACT

Background:  As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries. Conclusions:  Our analysis shows that a large number of COVID-19 cases remain undetected across the world.   These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

10.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296035

ABSTRACT

Previous work has shown that environment affects SARS-CoV-2 transmission, but it is unclear whether emerging strains show similar responses. Here we show that, like other SARS-CoV-2 strains, lineage B.1.1.7 spread with greater transmission in colder and more densely populated parts of England. However, we also find evidence of B.1.1.7 having a transmission advantage at warmer temperatures compared to other strains. This implies that spring and summer conditions are unlikely to slow B.1.1.7’s invasion in Europe and across the Northern hemisphere - an important consideration for public health interventions.

13.
Nat Commun ; 12(1): 4383, 2021 07 19.
Article in English | MEDLINE | ID: covidwho-1317806

ABSTRACT

In February and March 2020, two mass swab testing campaigns were conducted in Vo', Italy. In May 2020, we tested 86% of the Vo' population with three immuno-assays detecting antibodies against the spike and nucleocapsid antigens, a neutralisation assay and Polymerase Chain Reaction (PCR). Subjects testing positive to PCR in February/March or a serological assay in May were tested again in November. Here we report on the results of the analysis of the May and November surveys. We estimate a seroprevalence of 3.5% (95% Credible Interval (CrI): 2.8-4.3%) in May. In November, 98.8% (95% Confidence Interval (CI): 93.7-100.0%) of sera which tested positive in May still reacted against at least one antigen; 18.6% (95% CI: 11.0-28.5%) showed an increase of antibody or neutralisation reactivity from May. Analysis of the serostatus of the members of 1,118 households indicates a 26.0% (95% CrI: 17.2-36.9%) Susceptible-Infectious Transmission Probability. Contact tracing had limited impact on epidemic suppression.


Subject(s)
Antibodies, Viral/immunology , COVID-19 Testing/methods , COVID-19/immunology , COVID-19/transmission , SARS-CoV-2/immunology , Serologic Tests/methods , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Nucleic Acid Testing , Contact Tracing , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Italy/epidemiology , Male , Nucleocapsid , Seroepidemiologic Studies , Spike Glycoprotein, Coronavirus/immunology
14.
Clin Infect Dis ; 73(1): e215-e223, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1291317

ABSTRACT

BACKGROUND: As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding the pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the basic reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. METHODS: Using simulated epidemic data, we assess the performance of 7 commonly used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario: fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. RESULTS: We find that most methods considered here frequently overestimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. CONCLUSIONS: We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision in the early stages of epidemic growth, particularly for data with significant over-dispersion. As localized epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.


Subject(s)
COVID-19 , Epidemics , Zika Virus Infection , Zika Virus , Basic Reproduction Number , Caribbean Region , Humans , Pandemics , Reproduction , SARS-CoV-2
15.
Proc Natl Acad Sci U S A ; 118(25)2021 06 22.
Article in English | MEDLINE | ID: covidwho-1262033

ABSTRACT

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


Subject(s)
COVID-19/transmission , Cold Temperature , Population Density , Basic Reproduction Number , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/legislation & jurisprudence , Forecasting , Humans , Movement , SARS-CoV-2 , Seasons , United States/epidemiology
17.
Nat Commun ; 12(1): 1090, 2021 02 17.
Article in English | MEDLINE | ID: covidwho-1087445

ABSTRACT

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


Subject(s)
COVID-19/transmission , Communicable Disease Control/methods , Pandemics/prevention & control , SARS-CoV-2/isolation & purification , Algorithms , COVID-19/epidemiology , COVID-19/virology , Communicable Disease Control/statistics & numerical data , Global Health , Humans , Models, Theoretical , Physical Distancing , Quarantine/methods , SARS-CoV-2/physiology
18.
Clin Infect Dis ; 73(1): e215-e223, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1066278

ABSTRACT

BACKGROUND: As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding the pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the basic reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. METHODS: Using simulated epidemic data, we assess the performance of 7 commonly used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario: fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. RESULTS: We find that most methods considered here frequently overestimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. CONCLUSIONS: We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision in the early stages of epidemic growth, particularly for data with significant over-dispersion. As localized epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.


Subject(s)
COVID-19 , Epidemics , Zika Virus Infection , Zika Virus , Basic Reproduction Number , Caribbean Region , Humans , Pandemics , Reproduction , SARS-CoV-2
19.
Int J Infect Dis ; 105: 161-171, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1062393

ABSTRACT

OBJECTIVE: The COVID-19 pandemic demonstrates the need for understanding pathways to healthcare demand, morbidity, and mortality of pandemic patients. We estimate H1N1 (1) hospitalization rates, (2) severity rates (length of stay, ventilation, pneumonia, and death) of those hospitalized, (3) mortality rates, and (4) time lags between infections and hospitalizations during the pandemic (June 2009 to March 2010) and post-pandemic influenza season (November 2010 to February 2011) in England. METHODS: Estimates of H1N1 infections from a dynamic transmission model are combined with hospitalizations and severity using time series econometric analyses of administrative patient-level hospital data. RESULTS: Hospitalization rates were 34% higher and severity rates of those hospitalized were 20%-90% higher in the post-pandemic period than the pandemic. Adults (45-64-years-old) had the highest ventilation and pneumonia hospitalization rates. Hospitalizations did not lag infection during the pandemic for the young (<24-years-old) but lagged by one or more weeks for all ages in the post-pandemic period. DISCUSSION: The post-pandemic flu season exhibited heightened H1N1 severity, long after the pandemic was declared over. Policymakers should remain vigilant even after pandemics seem to have subsided. Analysis of administrative hospital data and epidemiological modelling estimates can provide valuable insights to inform responses to COVID-19 and future influenza and other disease pandemics.


Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza, Human/epidemiology , Pandemics , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , England/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Influenza, Human/mortality , Male , Middle Aged , Severity of Illness Index , Time Factors , Young Adult
20.
J Travel Med ; 27(8)2020 12 23.
Article in English | MEDLINE | ID: covidwho-1059308
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