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1.
Pathogens ; 11(4)2022 Mar 24.
Article in English | MEDLINE | ID: covidwho-1822431

ABSTRACT

BACKGROUND: SARS-CoV-2 enters the body through inhalation or self-inoculation to mucosal surfaces. The kinetics of the ocular and nasal mucosal-specific-immunoglobulin A(IgA) responses remain under-studied. METHODS: Conjunctival fluid (CF, n = 140) and nasal epithelial lining fluid (NELF, n = 424) obtained by paper strips and plasma (n = 153) were collected longitudinally from SARS-CoV-2 paediatric (n = 34) and adult (n = 47) patients. The SARS-CoV-2 spike protein 1(S1)-specific mucosal antibody levels in COVID-19 patients, from hospital admission to six months post-diagnosis, were assessed. RESULTS: The mucosal antibody was IgA-predominant. In the NELF of asymptomatic paediatric patients, S1-specific IgA was induced as early as the first four days post-diagnosis. Their plasma S1-specific IgG levels were higher than in symptomatic patients in the second week after diagnosis. The IgA and IgG levels correlated positively with the surrogate neutralization readout. The detectable NELF "receptor-blocking" S1-specific IgA in the first week after diagnosis correlated with a rapid decline in viral load. CONCLUSIONS: Early and intense nasal S1-specific IgA levels link to a rapid decrease in viral load. Our results provide insights into the role of mucosal immunity in SARS-CoV-2 exposure and protection. There may be a role of NELF IgA in the screening and diagnosis of SARS-CoV-2 infection.

2.
J Theor Biol ; 542: 111105, 2022 Jun 07.
Article in English | MEDLINE | ID: covidwho-1814837

ABSTRACT

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.


Subject(s)
COVID-19 , Epidemics , COVID-19/epidemiology , Humans , Models, Theoretical , Pandemics , SARS-CoV-2/genetics
3.
Journal of theoretical biology ; 2022.
Article in English | EuropePMC | ID: covidwho-1749848

ABSTRACT

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that cannot be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in showing or even containing the growth of the proportion of mutated variants.

4.
J Travel Med ; 2022 Mar 02.
Article in English | MEDLINE | ID: covidwho-1722537

ABSTRACT

Given the heterogeneity in individual transmissibility, we estimated the superspreading potential of SARS-CoV-2 Delta variants. Using case series of Delta variants in Guangdong, China, we found 15% (95%CrI: 12, 19) of cases seeded 80% of offspring cases.

5.
J Glob Health ; 11: 05028, 2021.
Article in English | MEDLINE | ID: covidwho-1687375

ABSTRACT

BACKGROUND: The COVID-19 pandemic poses serious threats to public health globally, and the emerging mutations in SARS-CoV-2 genomes has become one of the major challenges of disease control. In the second epidemic wave in Nigeria, the roles of co-circulating SARS-CoV-2 Alpha (ie, B.1.1.7) and Eta (ie, B.1.525) variants in contributing to the epidemiological outcomes were of public health concerns for investigation. METHODS: We developed a mathematical model to capture the transmission dynamics of different types of strains in Nigeria. By fitting to the national-wide COVID-19 surveillance data, the transmission advantages of SARS-CoV-2 variants were estimated by likelihood-based inference framework. RESULTS: The reproduction numbers were estimated to decrease steadily from 1.5 to 0.8 in the second epidemic wave. In December 2020, when both Alpha and Eta variants were at low prevalent levels, their transmission advantages (against the wild type) were estimated at 1.51 (95% credible intervals (CrI) = 1.48, 1.54), and 1.56 (95% CrI = 1.54, 1.59), respectively. In January 2021, when the original variants almost vanished, we estimated a weak but significant transmission advantage of Eta against Alpha variants with 1.14 (95% CrI = 1.11, 1.16). CONCLUSIONS: Our findings suggested evidence of the transmission advantages for both Alpha and Eta variants, of which Eta appeared slightly more infectious than Alpha. We highlighted the critical importance of COVID-19 control measures in mitigating the outbreak size and relaxing the burdens to health care systems in Nigeria.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/transmission , COVID-19/virology , Humans , Likelihood Functions , Nigeria/epidemiology , Pandemics , Retrospective Studies
6.
J Infect Public Health ; 15(3): 338-342, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1665197

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health threat. This study aims to evaluate the effect of virus mutation activities and policy interventions on COVID-19 transmissibility in Hong Kong. METHODS: In this study, we integrated the genetic activities of multiple proteins, and quantified the effect of government interventions and mutation activities against the time-varying effective reproduction number Rt. FINDINGS: We found a significantly positive relationship between Rt and mutation activities and a significantly negative relationship between Rt and government interventions. The results showed that the mutations that contributed most to the increase of Rt were from the spike, nucleocapsid and ORF1b genes. Policy of prohibition on group gathering was estimated to have the largest impact on mitigating virus transmissibility. The model explained 63.2% of the Rt variability with the R2. CONCLUSION: Our study provided a convenient framework to estimate the effect of genetic contribution and government interventions on pathogen transmissibility. We showed that the S, N and ORF1b protein had significant contribution to the increase of transmissibility of SARS-CoV-2 in Hong Kong, while restrictions of public gathering and suspension of face-to-face class are the most effective government interventions strategies.


Subject(s)
COVID-19 , Pandemics , Government , Humans , Mutation , Pandemics/prevention & control , SARS-CoV-2/genetics
7.
Public Health Genomics ; : 1-4, 2022 Jan 05.
Article in English | MEDLINE | ID: covidwho-1606251

ABSTRACT

During coronavirus disease 2019 (COVID-19) pandemic, the genetic mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred frequently. Some mutations in the spike protein are considered to promote transmissibility of the virus, while the mutation patterns in other proteins are less studied and may also be important in understanding the characteristics of SARS-CoV-2. We used the sequencing data of SARS-CoV-2 strains in California to investigate the time-varying patterns of the evolutionary genetic distance. The accumulative genetic distances were quantified across different time periods and in different viral proteins. The increasing trends of genetic distance were observed in spike protein (S protein), the RNA-dependent RNA polymerase (RdRp) region and nonstructural protein 3 (nsp3) of open reading frame 1 (ORF1), and nucleocapsid protein (N protein). The genetic distances in ORF3a, ORF8, and nsp2 of ORF1 started to diverge from their original variants after September 2020. By contrast, mutations in other proteins appeared transiently, and no evident increasing trend was observed in the genetic distance to the original variants. This study presents distinct patterns of the SARS-CoV-2 mutations across multiple proteins from the aspect of genetic distance. Future investigation shall be conducted to study the effects of accumulative mutations on epidemics characteristics.

8.
Pathog Glob Health ; 116(3): 137-139, 2022 May.
Article in English | MEDLINE | ID: covidwho-1585285

ABSTRACT

The circulation of SARS-CoV-2 Beta (B.1.351) variants challenged the control of COVID-19 pandemic. The numbers of COVID-19 cases and deaths and SARS-CoV-2 sequences in South Africa were collected. We reconstructed the variant-specified reproduction numbers (R t) and delay-adjusted case fatality ratio (CFR) to examine the changes in transmissibility and fatality risk of Beta over non-Beta variants. We estimated that Beta variants were 41% (95%CI: 16, 73) more transmissible and 53% (95%CI: 6, 108) more fatal than non-Beta variants. Higher risks of infection and fatality might lead to increasing volumes of infections and critical patients.


Impacts The circulation of SARS-CoV-2 Beta (B.1.351) variants, which were firstly reported in South Africa, challenged the control of COVID-19 pandemic.Using the national-wide COVID-19 cases and SARS-CoV-2 sequences data, Beta variants were estimated 41% more transmissible and 53% more fatal than non-Beta variants in South Africa.Higher risks of infection and fatality might lead to increasing volumes of infections and critical patients.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Pandemics , SARS-CoV-2/genetics , South Africa/epidemiology
9.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296125

ABSTRACT

Background Investigations of the natural viral interference effect between rhinovirus (RV) and influenza virus (IV) were conducted in temperate regions. We conducted an epidemiological study in Hong Kong, a major epicentre of influenza virus in the sub-tropical region. RV is the most prevalent respiratory virus year-round and causes asymptomatic to mild symptoms while IV infection exerts a great burden of public health. We aimed to examine the correlation of RV prevalence against IV activity. Methods Nasopharyngeal aspirates (NPA) collected from patients hospitalized in the regional hospitals from 2015 to 2019 were examined for the presence of respiratory viruses. The correlation of the monthly prevalence between all pairs of virus infection, the co-infection rate and the temporal interference of RV and IV were tested. The viral interference was validated in vitro by conducting sequential RV and IV infection in the well-differentiated primary human airway epithelial cells. Findings A total of 112,926 NPA were evaluated, and the Enterovirus/RV was the most prevalent respiratory virus detected. The negative correlation between EV/RV and IVs prevalence was independent of age and meteorological factors. Co-infection of EV/RV and IV was significantly less when compared with other virus pairs. Prior exposure to RV inhibited the replication of influenza A, B and oseltamivir-resistance stain in vitro and the inhibition is replication dependent. Interpretation Epidemiological surveillance and the sequential infection in vitro suggested viral interference between EV/RV and IV operated at the population, individual and cellular levels. Funding This study was supported by the General Research Fund (Ref: 24107017 and 14103119 to RWYC), Health and Medical Research Fund (Ref: COVID190112 to RWYC) and the Chinese University Direct Grant for Research (Ref: 2019.073 to RWYC).

10.
Infect Genet Evol ; 97: 105162, 2022 01.
Article in English | MEDLINE | ID: covidwho-1540856

ABSTRACT

The circulation of SARS-CoV-2 Delta (i.e., B.1.617.2) variants challenges the pandemic control. Our analysis showed that in the United Kingdom (UK), the reported case fatality ratio (CFR) decreased from May to July 2021 for non-Delta variant, whereas the decreasing trends of the CFR of Delta variant appeared weak and insignificant. The association between vaccine coverage and CFR might be stratified by different circulating variants. Due to the limitation of ecological study design, the interpretation of our results should be treated with caution.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2/pathogenicity , Vaccination Coverage/statistics & numerical data , COVID-19/mortality , COVID-19/transmission , Epidemiological Monitoring , Humans , Mortality/trends , SARS-CoV-2/growth & development , SARS-CoV-2/immunology , Time Factors , United Kingdom/epidemiology
11.
BMC Infect Dis ; 21(1): 1039, 2021 Oct 07.
Article in English | MEDLINE | ID: covidwho-1455943

ABSTRACT

BACKGROUND: The COVID-19 pandemic poses serious threats to global health, and the emerging mutation in SARS-CoV-2 genomes, e.g., the D614G substitution, is one of the major challenges of disease control. Characterizing the role of the mutation activities is of importance to understand how the evolution of pathogen shapes the epidemiological outcomes at population scale. METHODS: We developed a statistical framework to reconstruct variant-specific reproduction numbers and estimate transmission advantage associated with the mutation activities marked by single substitution empirically. Using likelihood-based approach, the model is exemplified with the COVID-19 surveillance data from January 1 to June 30, 2020 in California, USA. We explore the potential of this framework to generate early warning signals for detecting transmission advantage on a real-time basis. RESULTS: The modelling framework in this study links together the mutation activity at molecular scale and COVID-19 transmissibility at population scale. We find a significant transmission advantage of COVID-19 associated with the D614G substitution, which increases the infectivity by 54% (95%CI: 36, 72). For the early alarming potentials, the analytical framework is demonstrated to detect this transmission advantage, before the mutation reaches dominance, on a real-time basis. CONCLUSIONS: We reported an evidence of transmission advantage associated with D614G substitution, and highlighted the real-time estimating potentials of modelling framework.


Subject(s)
COVID-19 , Genome, Viral , SARS-CoV-2 , COVID-19/virology , Humans , Likelihood Functions , Mutation , Pandemics , SARS-CoV-2/genetics
12.
J Theor Biol ; 529: 110861, 2021 11 21.
Article in English | MEDLINE | ID: covidwho-1437518

ABSTRACT

One of the key epidemiological characteristics that shape the transmission of coronavirus disease 2019 (COVID-19) is the serial interval (SI). Although SI is commonly considered following a probability distribution at a population scale, recent studies reported a slight shrinkage (or contraction) of the mean of effective SI across transmission generations or over time. Here, we develop a likelihood-based statistical inference framework with truncation to explore the change in SI across transmission generations after adjusting the impacts of case isolation. The COVID-19 contact tracing surveillance data in Hong Kong are used for exemplification. We find that for COVID-19, the mean of individual SI is likely to shrink with a factor at 0.72 per generation (95%CI: 0.54, 0.96) as the transmission generation increases, where a threshold may exist as the lower boundary of this shrinking process. We speculate that one of the probable explanations for the shrinkage in SI might be an outcome due to the competition among multiple candidate infectors within the same case cluster. Thus, the nonpharmaceutical interventive strategies are crucially important to block the transmission chains, and mitigate the COVID-19 epidemic.


Subject(s)
COVID-19 , Contact Tracing , Hong Kong , Humans , Likelihood Functions , SARS-CoV-2
13.
R Soc Open Sci ; 8(9): 201867, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1429382

ABSTRACT

The novel coronavirus disease 2019 (COVID-19) has spread worldwide and threatened human life. Diagnosis is crucial to contain the spread of SARS-CoV-2 infections and save lives. Diagnostic tests for COVID-19 have varying sensitivity and specificity, and the false-negative results would have substantial consequences to patient treatment and pandemic control. To detect all suspected infections, multiple testing is widely used. However, it may be challenging to build an assertion when the testing results are inconsistent. Considering the situation where there is more than one diagnostic outcome for each subject, we proposed a Bayesian probabilistic framework based on the sensitivity and specificity of each diagnostic method to synthesize a posterior probability of being infected by SARS-CoV-2. We demonstrated that the synthesized posterior outcome outperformed each individual testing outcome. A user-friendly web application was developed to implement our analytic framework with free access via http://www2.ccrb.cuhk.edu.hk/statgene/COVID_19/. The web application enables the real-time display of the integrated outcome incorporating two or more tests and calculated based on Bayesian posterior probability. A simulation-based assessment demonstrated higher accuracy and precision of the Bayesian probabilistic model compared with a single-test outcome. The online tool developed in this study can assist physicians in making clinical evaluations by effectively integrating multiple COVID-19 tests.

15.
Epidemics ; 36: 100482, 2021 09.
Article in English | MEDLINE | ID: covidwho-1281413

ABSTRACT

The coronavirus disease 2019 (COVID-19) emerged by end of 2019, and became a serious public health threat globally in less than half a year. The generation interval and latent period, though both are of importance in understanding the features of COVID-19 transmission, are difficult to observe, and thus they can rarely be learnt from surveillance data empirically. In this study, we develop a likelihood framework to estimate the generation interval and incubation period simultaneously by using the contact tracing data of COVID-19 cases, and infer the pre-symptomatic transmission proportion and latent period thereafter. We estimate the mean of incubation period at 6.8 days (95 %CI: 6.2, 7.5) and SD at 4.1 days (95 %CI: 3.7, 4.8), and the mean of generation interval at 6.7 days (95 %CI: 5.4, 7.6) and SD at 1.8 days (95 %CI: 0.3, 3.8). The basic reproduction number is estimated ranging from 1.9 to 3.6, and there are 49.8 % (95 %CI: 33.3, 71.5) of the secondary COVID-19 infections likely due to pre-symptomatic transmission. Using the best estimates of model parameters, we further infer the mean latent period at 3.3 days (95 %CI: 0.2, 7.9). Our findings highlight the importance of both isolation for symptomatic cases, and for the pre-symptomatic and asymptomatic cases.


Subject(s)
COVID-19 , Contact Tracing , Basic Reproduction Number , Humans , SARS-CoV-2 , Time Factors
17.
Epidemiol Infect ; 149: e107, 2021 04 30.
Article in English | MEDLINE | ID: covidwho-1220258

ABSTRACT

Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research. We aim to demonstrate that the bootstrap t test outperforms Student's t test under normality in data. Using random data samples from normal distributions, we evaluated the testing performance, in terms of true-positive rate (TPR) and false-positive rate and diagnostic abilities, in terms of the area under the curve (AUC), of the bootstrap t test and Student's t test. We explore the AUC of both tests with varying sample size and coefficient of variation. We compare the testing outcomes using the COVID-19 serial interval (SI) data in Shenzhen and Hong Kong, China, for demonstration. With fixed TPR, the bootstrap t test maintained the equivalent accuracy in TPR, but significantly improved the true-negative rate from the Student's t test. With varying TPR, the diagnostic ability of bootstrap t test outperformed or equivalently performed as Student's t test in terms of the AUC. The equivalent performances are possible but rarely occur in practice. We find that the bootstrap t test outperforms by successfully detecting the difference in COVID-19 SI, which is defined as the time interval between consecutive transmission generations, due to sex and non-pharmaceutical interventions against the Student's t test. We demonstrated that the bootstrap t test outperforms Student's t test, and it is recommended to replace Student's t test in medical data analysis regardless of sample size.


Subject(s)
COVID-19/epidemiology , Models, Statistical , Analysis of Variance , Area Under Curve , COVID-19/transmission , China/epidemiology , Female , Humans , Male , ROC Curve , SARS-CoV-2 , Sample Size
18.
Viruses ; 13(4)2021 04 08.
Article in English | MEDLINE | ID: covidwho-1178428

ABSTRACT

As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS-CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the pandemic. Characterizing the relationship between mutation activities and the risk of severe clinical outcomes is of public health importance for informing the healthcare decision-making process. Using a likelihood-based approach, we developed a statistical framework to reconstruct a time-varying and variant-specific case fatality ratio (CFR), and to estimate changes in CFR associated with a single mutation empirically. For illustration, the statistical framework is implemented to the COVID-19 surveillance data in the United Kingdom (UK). The reconstructed instantaneous CFR gradually increased from 1.0% in September to 2.2% in November 2020 and stabilized at this level thereafter, which monitors the mortality risk of COVID-19 on a real-time basis. We identified a link between the SARS-CoV-2 mutation activity at molecular scale and COVID-19 mortality risk at population scale, and found that the 501Y variants may slightly but not significantly increase 18% of fatality risk than the preceding 501N variants. We found no statistically significant evidence of change in COVID-19 mortality risk associated with 501Y variants, and highlighted the real-time estimating potentials of the modelling framework.


Subject(s)
COVID-19/mortality , COVID-19/virology , Mutation , SARS-CoV-2/genetics , Humans , Likelihood Functions , Models, Biological , Pandemics , Public Health , United Kingdom/epidemiology
19.
One Health ; 12: 100201, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1147320

ABSTRACT

Nationwide mass social unrest has emerged in the US since May 25 and raised broad concerns about its impacts on the local COVID-19 epidemics. We compared the COVID-19 transmissibility between May 19-May 25 and May 29-June 4 for each state of the US. We found that social unrest is likely associated with the rebound of the COVID-19 transmissibility, which might raise difficulties in the pandemic control.

20.
Alexandria Engineering Journal ; 2021.
Article in English | ScienceDirect | ID: covidwho-1135227

ABSTRACT

Estimating the number of cases under-ascertained by inconsistencies is an essential concept in epidemiology. The aim of this study is to estimate the number of COVID-19 under- ascertained (η), and the basic reproduction number (R0) in Kano, Nigeria during the early epidemic period. We adopt a simple exponential growth model to capture the COVID-19 epidemic curve in Kano. Our findings indicate that the early epidemic growth mimics an exponential growth pattern. We find that the number of COVID-19 cases under-ascertained likely occurred during the fourth week of April 2020, and should be considered for future epidemiological investigations and mitigation plan.

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