Transmission risks of Omicron BA.5 following inactivated COVID-19 vaccines among children and adolescents in China.

BACKGROUND: As SARS-CoV-2 Omicron variants circulating globally since 2022, assessing the transmission characteristics, and the protection of vaccines against emerging Omicron variants among children and adolescents are needed for guiding the control and vaccination policies. METHODS: We conducted a retrospective cohort study for SARS-CoV-2 infections and close contacts aged <18 years from an outbreak seeded by Omicron BA.5 variants. The secondary attack rate (SAR) was calculated and the protective effects of two doses of inactivated vaccine (mainly Sinopharm /BBIBP-CorV) within a year versus one dose or two doses above a year after vaccination against the transmission and infection of Omicron BA.5 were estimated. RESULTS: A total of 3442 all-age close contacts of 122 confirmed SARS-CoV-2 infections aged 0-17 years were included. The SAR was higher in the household setting and for individuals who received a one-dose inactivated vaccine or those who received a two-dose for more than one year, with estimates of 28.5% (95% credible interval [CrI]: 21.1, 37.7) and 55.3% (95% CrI: 24.4, 84.8), respectively. The second dose of inactivated vaccine conferred substantial protection against all infection and transmission of Omicron BA.5 variants within a year. CONCLUSIONS: Our findings support the rollout of the second dose of inactivated vaccine for children and adolescents during the Omciron BA.5 predominant epidemic phase. Given the continuous emergence of SARS-CoV-2 variants, monitoring the transmission risk and corresponding vaccine effectiveness against SARS-CoV-2 variants among children and adolescents is important to inform control strategy.

Children and adolescents have reported suffering less severe outcomes from the SARS-CoV-2 Omicron variant. However, the risk of transmission and vaccine effectiveness among this population group is not well studied. Here, we used contact tracing data that was collected during an Omicron BA.5 outbreak from Urumqi, China, before the exit of "zero-COVID" measures, to evaluate the spread of SARS-CoV-2 infection among those age under 18 years, and the effectiveness of inactivated vaccine regimens. Our findings indicate there is a high rate of transmission among children and adolescents in a household setting and receiving two doses of inactivated COVID-19 vaccination within a year was more effective than a single dose or two doses given more than a year apart. These findings highlight the importance of tracking transmission and vaccine effectiveness of novel SARS-CoV-2 variants in younger populations to inform control strategies.

Comparison of diclofenac with tramadol, tizanidine or placebo in the treatment of acute low back pain and sciatica: multi-center randomized controlled trial.

BACKGROUND: Low back pain (LBP) is a leading cause of disability worldwide and has posed numerous health and socioeconomic challenges. This study compared whether nonsteroidal anti-inflammatory drugs (NSAIDs) in combination with tramadol, tizanidine or placebo would be the best treatment regime to improve the Roland Morris Disability Questionnaire (RMDQ) scores at 1 week. METHODS: This was a multi-center, double-blind, randomized, and placebo-controlled trial including adult patients with acute LBP and sciatica in three emergency departments in Hong Kong. Patients were randomized to the receive tramadol 50 mg, tizanidine 2 mg, or placebo every 6 hours for 2 weeks in a 1:1:1 ratio. The RMDQ and other secondary outcomes were measured at baseline, Day 2, 7, 14, 21, and 28. Data were analyzed on an intention to treat basis. Crude and adjusted mean differences in the changes of RMDQ and NRS scores from baseline to Day 7 between tizanidine/tramadol and placebo were determined with 95% confidence intervals. RESULTS: Two hundred and ninety-one patients were analyzed with the mean age of 47.4 years and 57.7% were male. The primary outcome of mean difference in RMDQs on Day 7 (compared with baseline) was non-significant for tizanidine compared with placebo (adjusted mean difference - 0.56, 95% CI -2.48 to 1.37) and tramadol compared with placebo (adjusted mean difference - 0.85, 95% CI -2.80 to 1.10). Only 23.7% were fully compliant to the treatment allocated. Complier Average Causal Effect analysis also showed no difference in the primary outcome for the tizanidine and tramadol versus placebo. CONCLUSION: Among patients with acute LBP and sciatica presenting to the ED, adding tramadol or tizanidine to diclofenac did not improve functional recovery.

The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale.

Virus evolution is a common process of pathogen adaption to host population and environment. Frequently, a small but important fraction of virus mutations are reported to contribute to higher risks of host infection, which is one of the major determinants of infectious diseases outbreaks at population scale. The key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation rapidly. Based on classic epidemiology theories of disease transmission, we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population. The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness. The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England. The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

Excess deaths from Alzheimer's disease and Parkinson's disease during the COVID-19 pandemic in the USA.

BACKGROUND: COVID-19 pandemic has indirect impacts on patients with chronic medical conditions, which may increase mortality risks for various non-COVID-19 causes. This study updates excess death statistics for Alzheimer's disease (AD) and Parkinson's disease (PD) up to 2022 and evaluates their demographic and spatial disparities in the USA. METHODS: This is an ecological time-series analysis of AD and PD mortality in the USA from January 2018 to March 2022. Poisson log-linear regressions were utilised to fit the weekly death data. Excess deaths were calculated with the difference between the observed and expected deaths under a counterfactual scenario of pandemic absence. RESULTS: From March 2020 to March 2022, we observed 41,115 and 10,328 excess deaths for AD and PD, respectively. The largest percentage increases in excess AD and PD deaths were found in the initial pandemic wave. For people aged ≥85 years, excess mortalities of AD and PD (per million persons) were 3946.0 (95% confidence interval [CI]: 2954.3, 4892.3) and 624.3 (95% CI: 369.4, 862.5), which were about 23 and 9 times higher than those aged 55-84 years, respectively. Females had a three-time higher excess mortality of AD than males (182.6 vs. 67.7 per million persons). The non-Hispanic Black people experienced larger increases in AD or PD deaths (excess percentage: 31.8% for AD and 34.6% for PD) than the non-Hispanic White population (17.1% for AD and 14.7% for PD). CONCLUSION: Under the continuing threats of COVID-19, efforts should be made to optimise health care capacity for patients with AD and PD.

Suppression of influenza virus infection by rhinovirus interference - at the population, individual and cellular levels.

Background: Influenza virus (IV) and the rhinovirus (RV) are the two most common circulating respiratory viruses circulating. Natural viral interference has been suggested between them. The effect of such at the population level has been described in temperate region, while its effect at the individual and cellular levels warrants further validation. In this study, we described the respiratory virus epidemiology and the co-infection landscape in the hospitalized population and investigated the distinct molecular pathways involved in the inhibition of virus replication. Methods: Nasopharyngeal aspirates (NPAs) collected from patients during 2015 to 2019 were examined for the presence of respiratory viruses. The correlation of the monthly prevalence between all the tested respiratory viruses, 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 infections in the well-differentiated primary human airway epithelial cells. The contributing molecular pathways were determined by transcriptome analysis. Findings: A total of 112,926 NPAs 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. Compare with other viruses, EV/RV had a significantly lower incidence of co-infection with IVs. Prior exposure to RV inhibited the replication of IV species A, B and oseltamivir-resistance stain in vitro. RV uniquely downregulated genes related to processing of viral mRNA, ribosomal proteins, translation and influenza infection. Interpretation: Epidemiological surveillance and the sequential infection in vitro suggested viral interference between EV/RV and IV operates at the population, individual and cellular levels. Funding: This study was supported by the General Research Fund (Ref: 24107017 and 14103119 to RWYC) and the Chinese University Direct Grant for Research (Ref: 2019·073 to RWYC).

Enabling Factors, Barriers, and Perceptions of Pneumococcal Vaccination Strategy Implementation: A Qualitative Study.

Invasive pneumococcal disease (IPD) is a leading cause of disability and mortality worldwide, particularly in the elderly population. With the implementation of the Government Vaccination Programme (GVP) and the Vaccination Subsidy Scheme (VSS), enabling factors and barriers in service provider scheme participation and vaccination uptake were examined in 32 interviews with doctors and 16 interviews with vaccine recipients. Interview data were analysed in NVivo 11.0 with reference to the Consolidated Framework for Implementation Research (CFIR) and the REAIM Framework to develop codes and themes. Barriers to pneumococcal vaccination uptake included concerns on vaccine efficacy and poor understanding of the disease and vaccine schemes, whilst service provider participation was hindered by ill-defined parameters for patient eligibility and time, location, and logistical constraints. Enabling factors to improve intervention implementation were involvement of the government and physicians to encourage participation, clarifying eligibility criteria, and improving individual knowledge of IPD and vaccination schemes. As participation rates in the GVP and VSS remains low in Hong Kong, efforts concentrating on health promotion strategies encouraging pneumococcal vaccination amongst the elderly population are recommended.

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility.

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19.

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.

Temporal Patterns in the Evolutionary Genetic Distance of SARS-CoV-2 during the COVID-19 Pandemic.

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.

Real-time quantification of the transmission advantage associated with a single mutation in pathogen genomes: a case study on the D614G substitution of SARS-CoV-2.

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.

A Bayesian method for synthesizing multiple diagnostic outcomes of COVID-19 tests.

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.

How Transportation Restriction Shapes the Relationship Between Ambient Nitrogen Dioxide and COVID-19 Transmissibility: An Exploratory Analysis.

Background: Several recent studies reported a positive (statistical) association between ambient nitrogen dioxide (NO2) and COVID-19 transmissibility. However, considering the intensive transportation restriction due to lockdown measures that would lead to declines in both ambient NO2 concentration and COVID-19 spread, the crude or insufficiently adjusted associations between NO2 and COVID-19 transmissibility might be confounded. This study aimed to investigate whether transportation restriction confounded, mediated, or modified the association between ambient NO2 and COVID-19 transmissibility. Methods: The time-varying reproduction number (Rt ) was calculated to quantify the instantaneous COVID-19 transmissibility in 31 Chinese cities from January 1, 2020, to February 29, 2020. For each city, we evaluated the relationships between ambient NO2, transportation restriction, and COVID-19 transmission under three scenarios, including simple linear regression, mediation analysis, and adjusting transportation restriction as a confounder. The statistical significance (p-value < 0.05) of the three scenarios in 31 cities was summarized. Results: We repeated the crude correlational analysis, and also found the significantly positive association between NO2 and COVID-19 transmissibility. We found that little evidence supported NO2 as a mediator between transportation restriction and COVID-19 transmissibility. The association between NO2 and COVID-19 transmissibility appears less likely after adjusting the effects of transportation restriction. Conclusions: Our findings suggest that the crude association between NO2 and COVID-19 transmissibility is likely confounded by the transportation restriction in the early COVID-19 outbreak. After adjusting the confounders, the association between NO2 and COVID-19 transmissibility appears unlikely. Further studies are warranted to validate the findings in other regions.

Shrinkage in serial intervals across transmission generations of COVID-19.

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.

Evaluation of a package of risk-based pharmaceutical and lifestyle interventions in patients with hypertension and/or diabetes in rural China: A pragmatic cluster randomised controlled trial.

BACKGROUND: Primary prevention of cardiovascular disease (CVD) requires adequate control of hypertension and diabetes. We designed and implemented pharmaceutical and healthy lifestyle interventions for patients with diabetes and/or hypertension in rural primary care, and assessed their effectiveness at reducing severe CVD events. METHODS AND FINDINGS: We used a pragmatic, parallel group, 2-arm, controlled, superiority, cluster trial design. We randomised 67 township hospitals in Zhejiang Province, China, to intervention (34) or control (33). A total of 31,326 participants were recruited, with 15,380 in the intervention arm and 15,946 in the control arm. Participants had no known CVD and were either patients with hypertension and a 10-year CVD risk of 20% or higher, or patients with type 2 diabetes regardless of their CVD risk. The intervention included prescription of a standardised package of medicines, individual advice on lifestyle change, and adherence support. Control was usual hypertension and diabetes care. In both arms, as usual in China, most outpatient drug costs were out of pocket. The primary outcome was severe CVD events, including coronary heart disease and stroke, during 36 months of follow-up, as recorded by the CVD surveillance system. The study was implemented between December 2013 and May 2017. A total of 13,385 (87%) and 14,745 (92%) participated in the intervention and control arms, respectively. Their mean age was 64 years, 51% were women, and 90% were farmers. Of all participants, 64% were diagnosed with hypertension with or without diabetes, and 36% were diagnosed with diabetes only. All township hospitals and participants completed the 36-month follow-up. At 36 months, there were 762 and 874 severe CVD events in the intervention and control arms, respectively, yielding a non-significant effect on CVD incidence rate (1.92 and 2.01 per 100 person-years, respectively; crude incidence rate ratio = 0.90 [95% CI: 0.74, 1.08; P = 0.259]). We observed significant, but small, differences in the change from baseline to follow-up for systolic blood pressure (-1.44 mm Hg [95% CI: -2.26, -0.62; P < 0.001]) and diastolic blood pressure (-1.29 mm Hg [95% CI: -1.77, -0.80; P < 0.001]) in the intervention arm compared to the control arm. Self-reported adherence to recommended medicines was significantly higher in the intervention arm compared with the control arm at 36 months. No safety concerns were identified. Main study limitations include all participants being informed about their high CVD risk at baseline, non-blinding of participants, and the relatively short follow-up period available for judging potential changes in rates of CVD events. CONCLUSIONS: The comprehensive package of pharmaceutical and healthy lifestyle interventions did not reduce severe CVD events over 36 months. Improving health system factors such as universal coverage for the cost of essential medicines is required for successful risk-based CVD prevention programmes. TRIAL REGISTRATION: ISRCTN registry ISRCTN58988083.

Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2.

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.

Attach importance of the bootstrap t test against Student's t test in clinical epidemiology: a demonstrative comparison using COVID-19 as an example.

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.

Differential Influence of Age on the Relationship between Genetic Mismatch and A(H1N1)pdm09 Vaccine Effectiveness.

Assessment of influenza vaccine effectiveness (VE) and identification of relevant influencing factors are the current priorities for optimizing vaccines to reduce the impacts of influenza. To date, how the difference between epidemic strains and vaccine strains at genetic scale affects age-specific vaccine performance remains ambiguous. This study investigated the association between genetic mismatch on hemagglutinin and neuraminidase genes and A(H1N1)pdm09 VE in different age groups with a novel computational approach. We found significant linear relationships between VE and genetic mismatch in children, young adults, and middle-aged adults. In the children's group, each 3-key amino acid mutation was associated with an average of 10% decrease in vaccine effectiveness in a given epidemic season, and genetic mismatch exerted no influence on VE for the elderly group. We demonstrated that present vaccines were most effective for children, while protection for the elderly was reduced and indifferent to vaccine component updates. Modeling such relationships is practical to inform timely evaluation of VE in different groups of populations during mass vaccination and may inform age-specific vaccination regimens.

Modelling the association between COVID-19 transmissibility and D614G substitution in SARS-CoV-2 spike protein: using the surveillance data in California as an example.

BACKGROUND: The COVID-19 pandemic poses a serious threat to global health, and pathogenic mutations are a major challenge to disease control. We developed a statistical framework to explore the association between molecular-level mutation activity of SARS-CoV-2 and population-level disease transmissibility of COVID-19. METHODS: We estimated the instantaneous transmissibility of COVID-19 by using the time-varying reproduction number (Rt). The mutation activity in SARS-CoV-2 is quantified empirically depending on (i) the prevalence of emerged amino acid substitutions and (ii) the frequency of these substitutions in the whole sequence. Using the likelihood-based approach, a statistical framework is developed to examine the association between mutation activity and Rt. We adopted the COVID-19 surveillance data in California as an example for demonstration. RESULTS: We found a significant positive association between population-level COVID-19 transmissibility and the D614G substitution on the SARS-CoV-2 spike protein. We estimate that a per 0.01 increase in the prevalence of glycine (G) on codon 614 is positively associated with a 0.49% (95% CI: 0.39 to 0.59) increase in Rt, which explains 61% of the Rt variation after accounting for the control measures. We remark that the modeling framework can be extended to study other infectious pathogens. CONCLUSIONS: Our findings show a link between the molecular-level mutation activity of SARS-CoV-2 and population-level transmission of COVID-19 to provide further evidence for a positive association between the D614G substitution and Rt. Future studies exploring the mechanism between SARS-CoV-2 mutations and COVID-19 infectivity are warranted.