Reproduction number of SARS-CoV-2 omicron variants, China, December 2022-January 2023.

China adjusted the zero-COVID strategy in late 2022, triggering an unprecedented Omicron wave. We estimated the time-varying reproduction numbers of 32 provincial-level administrative divisions from December 2022 to January 2023. We found that the pooled estimate of initial reproduction numbers is 4.74 (95% CI: 4.41, 5.07).

Optimizing COVID-19 surveillance using historical electronic health records of influenza infections.

Targeting surveillance resources toward individuals at high risk of early infection can accelerate the detection of emerging outbreaks. However, it is unclear which individuals are at high risk without detailed data on interpersonal and physical contacts. We propose a data-driven COVID-19 surveillance strategy using Electronic Health Record (EHR) data that identifies the most vulnerable individuals who acquired the earliest infections during historical influenza seasons. Our simulations for all three networks demonstrate that the EHR-based strategy performs as well as the most-connected strategy. Compared to the random acquaintance surveillance, our EHR-based strategy detects the early warning signal and peak timing much earlier. On average, the EHR-based strategy has 9.8 days of early warning and 13.5 days of peak timings, respectively, before the whole population. For the urban network, the expected values of our method are better than the random acquaintance strategy (24% for early warning and 14% in-advance for peak time). For a scale-free network, the average performance of the EHR-based method is 75% of the early warning and 109% in-advance when compared with the random acquaintance strategy. If the contact structure is persistent enough, it will be reflected by their history of infection. Our proposed approach suggests that seasonal influenza infection records could be used to monitor new outbreaks of emerging epidemics, including COVID-19. This is a method that exploits the effect of contact structure without considering it explicitly.

Acceptance and attitude towards the traditional chinese medicine among asymptomatic COVID-19 patients in Shanghai Fangcang hospital.

OBJECTIVE: The Coronavirus Disease 2019 (COVID-19) has brought severe damage to global health and socioeconomics. In China, traditional Chinese medicine (TCM) is the most important complementary and alternative medicine (CAM) and it has shown a beneficial role in the prevention and treatment of COVID-19. However, it is unknown whether patients are willing to accept TCM treatment. The objective of our study is to investigate the acceptance, attitude, and independent predictors of TCM among asymptomatic COVID-19 patients admitted to Shanghai fangcang hospital during the outbreak of the COVID-19 pandemic in Shanghai in 2022. METHODS: A cross-sectional study was conducted on asymptomatic COVID-19 patients in the largest fangcang hospital in Shanghai, China, from April 22, 2022, to May 25, 2022. Based on the literature review of previous similar studies, a self-report questionnaire was developed to assess the patients' attitude and acceptance of TCM, and a multivariate logistic regression analysis was conducted to determine the independent predictors of TCM acceptance. RESULTS: A total of 1,121 patients completed the survey, of whom 91.35% were willing to accept CAM treatment whereas 8.65% of participants showed no willingness. Multivariate logistic regression analysis revealed that the patients who have received two doses of COVID-19 vaccine (OR = 2.069, 95%CI: 1.029-4.162, P = 0.041 vs. not received), understood the culture of TCM (OR = 2.293, 95%CI: 1.029-4.162, P = 0.014 vs. not understood), thought the TCM treatment is safe (OR = 2.856, 95%CI: 1.334-6.112, P = 0.007 vs. not thought), thought the TCM treatment is effective (OR = 2.724, 95%CI: 1.249-5.940, P = 0.012 vs. not thought), and those who informed their attending physician if using TCM for treatment (OR = 3.455, 95%CI:1.867-6.392, P < 0.001 vs. not informed) were more likely to accept TCM treatment. However, patients who thought TCM might delay your treatment (OR = 0.256, 95%CI: 0.142-0.462, P < 0.001 not thought) was an independent predictor for unwillingness to accept TCM treatment. CONCLUSION: This study preliminarily investigated the acceptance, attitude, and predictors of intention to receive TCM among asymptomatic COVID-19 patients. It is recommended to increase the publicity of TCM, clarify the impact of TCM and communicate with attending doctors that meet the healthcare needs of asymptomatic COVID-19 patients.

Within-host dynamics of SARS-CoV-2 infection: A systematic review and meta-analysis.

Within-host model specified by viral dynamic parameters is a mainstream tool to understand SARS-CoV-2 replication cycle in infected patients. The parameter uncertainty further affects the output of the model, such as the efficacy of potential antiviral drugs. However, gathering empirical data on these parameters is challenging. Here, we aim to conduct a systematic review of viral dynamic parameters used in within-host models by calibrating the model to the viral load data measured from upper respiratory specimens. We searched the PubMed, Embase and Web of Science databases (between 1 December 2019 and 10 February 2022) for within-host modelling studies. We identified seven independent within-host models from the above nine studies, including Type I interferon, innate response, humoral immune response or cell-mediated immune response. From these models, we extracted and analyse seven widely used viral dynamic parameters including the viral load at the point of infection or symptom onset, the rate of viral particles infecting susceptible cells, the rate of infected cells releasing virus, the rate of virus particles cleared, the rate of infected cells cleared and the rate of cells in the eclipse phase can become productively infected. We identified seven independent within-host models from nine eligible studies. The viral load at symptom onset is 4.78 (95% CI:2.93, 6.62) log(copies/ml), and the viral load at the point of infection is -1.00 (95% CI:-1.94, -0.05) log(copies/ml). The rate of viral particles infecting susceptible cells and the rate of infected cells cleared have the pooled estimates as -6.96 (95% CI:-7.66, -6.25) log([copies/ml]-1 day-1 ) and 0.92 (95% CI:-0.09, 1.93) day-1 , respectively. We found that the rate of infected cells cleared was associated with the reported model in the meta-analysis by including the model type as a categorical variable (p < .01). Joint viral dynamic parameters estimates when parameterizing within-host models have been published for SARS-CoV-2. The reviewed viral dynamic parameters can be used in the same within-host model to understand SARS-CoV-2 replication cycle in infected patients and assess the impact of pharmaceutical interventions.

Cost-effectiveness of fractional doses of COVID-19 vaccine boosters in India

Background Coronavirus disease 2019 (COVID-19) continues to be a major global public health crisis in 2022 that exacts significant human and economic costs. Booster vaccination of individuals can improve waning immunity and reduce the impact of community epidemics. Methods Using an epidemiological model that incorporates population-level SARS-CoV-2 transmission and waning of vaccine-derived immunity, we identify the hypothetical potential of mass vaccination with fractionated vaccine doses specific to ChAdOx1 nCoV-19 (AZD1222 [Covishield];AstraZeneca) as an optimal and cost-effective strategy in India's Omicron outbreak. Findings We find that the optimal strategy is 1/8 fractional dosing under mild (Re ∼ 1.2) and rapid (Re ∼ 5) transmission scenarios, leading to an estimated $6 (95% CI: -13, 26) billion and $2 (95% CI:-26, 30) billion in health-related net monetary benefit over 200 days, respectively. Rapid and broad use of fractional dosing for boosters, together with delivery costs divided by fractionation, could substantially gain more net monetary benefit by $11 (95% CI: -10, 33) and $2 (95% CI: -23, 28) billion, respectively, under the mild and rapid transmission scenarios. Conclusions Mass vaccination with fractional doses of COVID-19 vaccines to boost immunity in a vaccinated population could be a cost effective strategy for mitigating the public health costs of resurgences caused by vaccine-evasive variants and fractional dosing deserves further clinical and regulatory evaluation. Funding Financial support was provided by the AIR@InnoHK Programme from Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region. Graphical This analysis demonstrated that the use of fractional dose could offer greater net monetary benefit in both moderate and rapid transmission scenarios given the epidemiological and socioeconomic conditions in India in 2022. In the face of a vaccine shortage, fractional dosage of vaccinations would have additional beneficial public health benefits.

Characterizing Human Collective Behaviors During COVID-19 - Hong Kong SAR, China, 2020.

What is already known about this topic?: People are likely to engage in collective behaviors online during extreme events, such as the coronavirus disease 2019 (COVID-19) crisis, to express awareness, take action, and work through concerns. What is added by this report?: This study offers a framework for evaluating interactions among individuals' emotions, perceptions, and online behaviors in Hong Kong Special Administrative Region (SAR) during the first two waves of COVID-19 (February to June 2020). Its results indicate a strong correlation between online behaviors, such as Google searches, and the real-time reproduction numbers. To validate the model's output of risk perception, this investigation conducted 10 rounds of cross-sectional telephone surveys on 8,593 local adult residents from February 1 through June 20 in 2020 to quantify risk perception levels over time. What are the implications for public health practice?: Compared to the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people's risk perception (individuals who are worried about being infected) during the studied period. We may need to reinvigorate the public by involving people as part of the solution that reduced the risk to their lives.

The risk of SARS-CoV-2 Omicron variant emergence in low and middle-income countries (LMICs).

We estimated the probability of undetected emergence of the SARS-CoV-2 Omicron variant in 25 low and middle-income countries (LMICs) prior to December 5, 2021. In nine countries, the risk exceeds 50 %; in Turkey, Pakistan and the Philippines, it exceeds 99 %. Risks are generally lower in the Americas than Europe or Asia.

Cost effectiveness of fractional doses of COVID-19 vaccine boosters in India.

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to be a major global public health crisis that exacts significant human and economic costs. Booster vaccination of individuals can improve waning immunity and reduce the impact of community epidemics. METHODS: Using an epidemiological model that incorporates population-level severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and waning of vaccine-derived immunity, we identify the hypothetical potential of mass vaccination with fractionated vaccine doses specific to ChAdOx1 nCoV-19 (AZD1222 [Covishield]; AstraZeneca) as an optimal and cost-effective strategy in India's Omicron outbreak. FINDINGS: We find that the optimal strategy is 1/8 fractional dosing under mild (Re ∼ 1.2) and rapid (Re ∼ 5) transmission scenarios, leading to an estimated $6 (95% confidence interval [CI]: -13, 26) billion and $2 (95% CI: -26, 30) billion in health-related net monetary benefit over 200 days, respectively. Rapid and broad use of fractional dosing for boosters, together with delivery costs divided by fractionation, could substantially gain more net monetary benefit by $11 (95% CI: -10, 33) and $2 (95% CI: -23, 28) billion, respectively, under the mild and rapid transmission scenarios. CONCLUSIONS: Mass vaccination with fractional doses of COVID-19 vaccines to boost immunity in a vaccinated population could be a cost-effective strategy for mitigating the public health costs of resurgences caused by vaccine-evasive variants, and fractional dosing deserves further clinical and regulatory evaluation. FUNDING: Financial support was provided by the AIR@InnoHK Program from Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region.

The Structural Identifiability of a Humidity-Driven Epidemiological Model of Influenza Transmission.

Influenza epidemics cause considerable morbidity and mortality every year worldwide. Climate-driven epidemiological models are mainstream tools to understand seasonal transmission dynamics and predict future trends of influenza activity, especially in temperate regions. Testing the structural identifiability of these models is a fundamental prerequisite for the model to be applied in practice, by assessing whether the unknown model parameters can be uniquely determined from epidemic data. In this study, we applied a scaling method to analyse the structural identifiability of four types of commonly used humidity-driven epidemiological models. Specifically, we investigated whether the key epidemiological parameters (i.e., infectious period, the average duration of immunity, the average latency period, and the maximum and minimum daily basic reproductive number) can be uniquely determined simultaneously when prevalence data is observable. We found that each model is identifiable when the prevalence of infection is observable. The structural identifiability of these models will lay the foundation for testing practical identifiability in the future using synthetic prevalence data when considering observation noise. In practice, epidemiological models should be examined with caution before using them to estimate model parameters from epidemic data.

Epidemic Surveillance of Influenza Infections: A Network-Free Strategy - Hong Kong Special Administrative Region, China, 2008-2011.

Introduction: The ease of coronavirus disease 2019 (COVID-19) non-pharmacological interventions and the increased susceptibility during the past COVID-19 pandemic could be a precursor for the resurgence of influenza, potentially leading to a severe outbreak in the winter of 2022 and future seasons. The recent increased availability of data on Electronic Health Records (EHR) in public health systems, offers new opportunities to monitor individuals to mitigate outbreaks. Methods: We introduced a new methodology to rank individuals for surveillance in temporal networks, which was more practical than the static networks. By targeting previously infected nodes, this method used readily available EHR data instead of the contact-network structure. Results: We validated this method qualitatively in a real-world cohort study and evaluated our approach quantitatively by comparing it to other surveillance methods on three temporal and empirical networks. We found that, despite not explicitly exploiting the contacts' network structure, it remained the best or close to the best strategy. We related the performance of the method to the public health goals, the reproduction number of the disease, and the underlying temporal-network structure (e.g., burstiness). Discussion: The proposed strategy of using historical records for sentinel surveillance selection can be taken as a practical and robust alternative without the knowledge of individual contact behaviors for public health policymakers.

Antiviral activity and mechanism of the antifungal drug, anidulafungin, suggesting its potential to promote treatment of viral diseases.

BACKGROUND: The severe fever with thrombocytopenia syndrome disease (SFTS), caused by the novel tick-borne SFTS virus (SFTSV), was listed among the top 10 priority infectious disease by World Health Organization due to the high fatality rate of 5-30% and the lack of effective antiviral drugs and vaccines and therefore raised the urgent need to develop effective anti-SFTSV drugs to improve disease treatment. METHODS: The antiviral drugs to inhibit SFTSV infection were identified by screening the library containing 1340 FDA-approved drugs using the SFTSV infection assays in vitro. The inhibitory effect on virus entry and the process of clathrin-mediated endocytosis under different drug doses was evaluated based on infection assays by qRT-PCR to determine intracellular viral copies, by Western blot to characterize viral protein expression in cells, and by immunofluorescence assays (IFAs) to determine virus infection efficiencies. The therapeutic effect was investigated in type I interferon receptor defective A129 mice in vivo with SFTSV infection, from which lesions and infection in tissues caused by SFTSV infection were assessed by H&E staining and immunohistochemical analysis. RESULTS: Six drugs were identified as exerting inhibitory effects against SFTSV infection, of which anidulafungin, an antifungal drug of the echinocandin family, has a strong inhibitory effect on SFTSV entry. It suppresses SFTSV internalization by impairing the late endosome maturation and decreasing virus fusion with the membrane. SFTSV-infected A129 mice had relieving symptoms, reduced tissue lesions, and improved disease outcomes following anidulafungin treatment. Moreover, anidulafungin exerts an antiviral effect in inhibiting the entry of other viruses including SARS-CoV-2, SFTSV-related Guertu virus and Heartland virus, Crimean-Congo hemorrhagic fever virus, Zika virus, and Herpes simplex virus 1. CONCLUSIONS: The results demonstrated that the antifungal drug, anidulafungin, could effectively inhibit virus infection by interfering with virus entry, suggesting it may be utilized for the clinical treatment of infectious viral diseases, in addition to its FDA-approved use as an antifungal. The findings also suggested to further evaluate the anti-viral effects of echinocandins and their clinical importance for patients with infection of viruses, which may promote therapeutic strategies as well as treatments and improve outcomes pertaining to various viral and fungal diseases.

Impact of mass rapid antigen testing for SARS-CoV-2 to mitigate Omicron outbreaks in China.

We analysed the effectiveness of various non-pharmaceutical interventions in containing the 2022 Omicron outbreak in China. The results show that the Rapid Antigen Test contributed to containing the outbreak, reducing the reproduction number by 0.788 (95% CI:-0.306, 1.880) in studied cities.

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022.

Introduction: Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the "Dynamic COVID-zero" strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods: Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks. Results: Under the transmission scenario (R0 =5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days. Conclusions: Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 - especially when new variants emerge.

Neuropilin-1 Facilitates Pseudorabies Virus Replication and Viral Glycoprotein B Promotes Its Degradation in a Furin-Dependent Manner.

Pseudorabies virus (PRV), which is extremely infectious and can infect numerous mammals, has a risk of spillover into humans. Virus-host interactions determine viral entry and spreading. Here, we showed that neuropilin-1 (NRP1) significantly potentiates PRV infection. Mechanistically, NRP1 promoted PRV attachment and entry, and enhanced cell-to-cell fusion mediated by viral glycoprotein B (gB), gD, gH, and gL. Furthermore, through in vitro coimmunoprecipitation (Co-IP) and bimolecular fluorescence complementation (BiFC) assays, NRP1 was found to physically interact with gB, gD, and gH, and these interactions were C-end Rule (CendR) motif independent, in contrast to currently known viruses. Remarkably, we illustrated that the viral protein gB promotes NRP1 degradation via a lysosome-dependent pathway. We further demonstrate that gB promotes NRP1 degradation in a furin-cleavage-dependent manner. Interestingly, in this study, we generated gB furin cleavage site (FCS)-knockout PRV (Δfurin PRV) and evaluated its pathogenesis; in vivo, we found that Δfurin PRV virulence was significantly attenuated in mice. Together, our findings demonstrated that NRP1 is an important host factor for PRV and that NRP1 may be a potential target for antiviral intervention. IMPORTANCE Recent studies have shown accelerated PRV cross-species spillover and that PRV poses a potential threat to humans. PRV infection in humans always manifests as a high fever, tonic-clonic seizures, and encephalitis. Therefore, understanding the interaction between PRV and host factors may contribute to the development of new antiviral strategies against PRV. NRP1 has been demonstrated to be a receptor for several viruses that harbor CendR, including SARS-CoV-2. However, the relationships between NRP1 and PRV are poorly understood. Here, we found that NRP1 significantly potentiated PRV infection by promoting PRV attachment and enhanced cell-to-cell fusion. For the first time, we demonstrated that gB promotes NRP1 degradation via a lysosome-dependent pathway. Last, in vivo, Δfurin PRV virulence was significantly attenuated in mice. Therefore, NRP1 is an important host factor for PRV, and NRP1 may be a potential target for antiviral drug development.

Reproduction Numbers of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants: A Systematic Review and Meta-analysis.

The coronavirus disease 2019 (COVID-19) pandemic continues to pose substantial risks to public health, worsened by the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that may have a higher transmissibility and reduce vaccine effectiveness. We conducted a systematic review and meta-analysis on reproduction numbers of SARS-CoV-2 variants and provided pooled estimates for each variant.

Systematic review and meta-analyses of superspreading of SARS-CoV-2 infections.

Superspreading, or overdispersion in transmission, is a feature of SARS-CoV-2 transmission which results in surging epidemics and large clusters of infection. The dispersion parameter is a statistical parameter used to characterize and quantify heterogeneity. In the context of measuring transmissibility, it is analogous to measures of superspreading potential among populations by assuming that collective offspring distribution follows a negative-binomial distribution. We conducted a systematic review and meta-analysis on globally reported dispersion parameters of SARS-CoV-2 infection. All searches were carried out on 10 September 2021 in PubMed for articles published from 1 January 2020 to 10 September 2021. Multiple estimates of the dispersion parameter have been published for 17 studies, which could be related to where and when the data were obtained, in 8 countries (e.g. China, the United States, India, Indonesia, Israel, Japan, New Zealand and Singapore). High heterogeneity was reported among the included studies. The mean estimates of dispersion parameters range from 0.06 to 2.97 over eight countries, the pooled estimate was 0.55 (95% CI: 0.30, 0.79), with changing means over countries and decreasing slightly with the increasing reproduction number. The expected proportion of cases accounting for 80% of all transmissions is 19% (95% CrI: 7, 34) globally. The study location and method were found to be important drivers for diversity in estimates of dispersion parameters. While under high potential of superspreading, larger outbreaks could still occur with the import of the COVID-19 virus by traveling even when an epidemic seems to be under control.

Optimizing COVID-19 surveillance using historical electronic health records of influenza infections

Targeting surveillance resources toward individuals at high risk of early infection can accelerate the detection of emerging outbreaks. However, it is unclear which individuals are at high risk without detailed data on interpersonal and physical contacts. We propose a data-driven COVID-19 surveillance strategy using Electronic Health Record (EHR) data that identifies the most vulnerable individuals who acquired the earliest infections during historical influenza seasons. Our simulations for all three networks demonstrate that the EHR-based strategy performs as well as the most-connected strategy. Compared to the random acquaintance surveillance, our EHR-based strategy detects the early warning signal and peak timing much earlier. On average, the EHR-based strategy has 9.8 days of early warning and 13.5 days of peak timings, respectively, before the whole population. For the urban network, the expected values of our method are better than the random acquaintance strategy (24% for early warning and 14% in-advance for peak time). For a scale-free network, the average performance of the EHR-based method is 75% of the early warning and 109% in-advance when compared with the random acquaintance strategy. If the contact structure is persistent enough, it will be reflected by their history of infection. Our proposed approach suggests that seasonal influenza infection records could be used to monitor new outbreaks of emerging epidemics, including COVID-19. This is a method that exploits the effect of contact structure without considering it explicitly.

Reproduction Number of the Omicron Variant Triples That of the Delta Variant.

COVID-19 remains a persistent threat, especially with the predominant Omicron variant emerging in early 2022, presenting with high transmissibility, immune escape, and waning. There is a need to rapidly ramp up global vaccine coverage while enhancing public health and social measures. Timely and reliable estimation of the reproduction number throughout a pandemic is critical for assessing the impact of mitigation efforts and the potential need to adjust for control measures. We conducted a systematic review on the reproduction numbers of the Omicron variant and gave the pooled estimates. We identified six studies by searching PubMed, Embase, Web of Science, and Google Scholar for articles published between 1 January 2020 and 6 March 2022. We estimate that the effective reproduction number ranges from 2.43 to 5.11, with a pooled estimate of 4.20 (95% CI: 2.05, 6.35). The Omicron variant has an effective reproduction number which is triple (2.71 (95% CI: 1.86, 3.56)) that of the Delta variant.