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1.
China CDC Wkly ; 5(3): 56-62, 2023 Jan 20.
Article in English | MEDLINE | ID: covidwho-2242916

ABSTRACT

What is already known about this topic?: Little is known about the epidemiology, natural history, and transmission patterns of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant. Monitoring the evolution of viral fitness of SARS-CoV-2 in the host population is key for preparedness and response planning. What is added by this report?: We analyzed a successfully contained local outbreak of Delta that took place in Hunan, China, and provided estimates of time-to-key event periods, infectiousness over time, and risk factors for SARS-CoV-2 infection and transmission for a still poorly understood variant. What are the implications for public health practice?: Our findings simultaneously shed light on both the characteristics of the Delta variant, by identifying key age groups, risk factors, and transmission pathways, and planning a future response effort against SARS-CoV-2.

2.
Infect Dis Model ; 8(1): 203-211, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-2179302

ABSTRACT

Since the epidemic of the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), many governments have used reverse transcription polymerase chain reaction (RT-PCR) to detect the virus. However, there are fewer measures of CT values information based on RT-PCR results, and the relationship between CT values and factors from consecutive tests is not clear enough. So in this study, we analyzed the connection between CT values and the factors based on cohort data from Delta variant of SARS-CoV-2 in Hunan Province. Previous studies have showed that the mean age of the cases was 33.34 years (±18.72 years), with a female predominance (55.03%, n = 71), and the greatest proportion of clinical symptoms were of the common type (60.47%, n = 78). There were statistical differences between the N and ORF1ab genes in the CT values for the cases. Based on the analysis of the association between CT values and the factors, the lowest CT values were obtained for the unvaccinated, older and clinically symptomatic group at 3-10 days, the maximum peak of viral load occurred. Therefore, it is recommended to use patient information to focus on older, clinically symptomatic, unvaccinated patients and to intervene promptly upon admission.

3.
Infect Dis Model ; 8(1): 192-202, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-2179301

ABSTRACT

Background: The current outbreak of novel coronavirus disease 2019 has caused a serious disease burden worldwide. Vaccines are an important factor to sustain the epidemic. Although with a relatively high-vaccination worldwide, the decay of vaccine efficacy and the arising of new variants lead us to the challenge of maintaining a sufficient immune barrier to protect the population. Method: A case-contact tracking data in Hunan, China, is used to estimate the contact pattern of cases for scenarios including school, workspace, etc, rather than ordinary susceptible population. Based on the estimated vaccine coverage and efficacy, a multi-group vaccinated-exposed-presymptomatic-symptomatic-asymptomatic-removed model (VEFIAR) with 8 age groups, with each partitioned into 4 vaccination status groups is developed. The optimal dose-wise vaccinating strategy is optimized based on the currently estimated immunity barrier of coverage and efficacy, using the greedy algorithm that minimizes the cumulative cases, population size of hospitalization and fatality respectively in a certain future interval. Parameters of Delta and Omicron variants are used respectively in the optimization. Results: The estimated contact matrices of cases showed a concentration on middle ages, and has compatible magnitudes compared to estimations from contact surveys in other studies. The VEFIAR model is numerically stable. The optimal controled vaccination strategy requires immediate vaccination on the un-vaccinated high-contact population of age 30-39 to reduce the cumulative cases, and is stable with different basic reproduction numbers ( R 0 ). As for minimizing hospitalization and fatality, the optimized strategy requires vaccination on the un-vaccinated of both aged 30-39 of high contact frequency and the vulnerable older. Conclusion: The objective of reducing transmission requires vaccination in age groups of the highest contact frequency, with more priority for un-vaccinated than un-fully or fully vaccinated. The objective of reducing total hospitalization and fatality requires not only to reduce transmission but also to protect the vulnerable older. The priority changes by vaccination progress. For any region, if the local contact pattern is available, then with the vaccination coverage, efficacy, and disease characteristics of relative risks in heterogeneous populations, the optimal dose-wise vaccinating process will be obtained and gives hints for decision-making.

4.
Lancet Microbe ; 3(11): e824-e834, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2031776

ABSTRACT

BACKGROUND: The H3N8 avian influenza virus (AIV) has been circulating in wild birds, with occasional interspecies transmission to mammals. The first human infection of H3N8 subtype occurred in Henan Province, China, in April, 2022. We aimed to investigate clinical, epidemiological, and virological data related to a second case identified soon afterwards in Hunan Province, China. METHODS: We analysed clinical, epidemiological, and virological data for a 5-year-old boy diagnosed with H3N8 AIV infection in May, 2022, during influenza-like illness surveillance in Changsha City, Hunan Province, China. H3N8 virus strains from chicken flocks from January, 2021, to April, 2022, were retrospectively investigated in China. The genomes of the viruses were sequenced for phylogenetic analysis of all the eight gene segments. We evaluated the receptor-binding properties of the H3N8 viruses by using a solid-phase binding assay. We used sequence alignment and homology-modelling methods to study the effect of specific mutations on the human receptor-binding properties. We also conducted serological surveillance to detect the H3N8 infections among poultry workers in the two provinces with H3N8 cases. FINDINGS: The clinical symptoms of the patient were mild, including fever, sore throat, chills, and a runny nose. The patient's fever subsided on the same day of hospitalisation, and these symptoms disappeared 7 days later, presenting mild influenza symptoms, with no pneumonia. An H3N8 virus was isolated from the patient's throat swab specimen. The novel H3N8 virus causing human infection was first detected in a chicken farm in Guangdong Province in December, 2021, and subsequently emerged in several provinces. Sequence analyses revealed the novel H3N8 AIVs originated from multiple reassortment events. The haemagglutinin gene could have originated from H3Ny AIVs of duck origin. The neuraminidase gene belongs to North American lineage, and might have originated in Alaska (USA) and been transferred by migratory birds along the east Asian flyway. The six internal genes had originated from G57 genotype H9N2 AIVs that were endemic in chicken flocks. Reassortment events might have occurred in domestic ducks or chickens in the Pearl River Delta area in southern China. The novel H3N8 viruses possess the ability to bind to both avian-type and human-type sialic acid receptors, which pose a threat to human health. No poultry worker in our study was positive for antibodies against the H3N8 virus. INTERPRETATION: The novel H3N8 virus that caused human infection had originated from chickens, a typical spillover. The virus is a triple reassortment strain with the Eurasian avian H3 gene, North American avian N8 gene, and dynamic internal genes of the H9N2 viruses. The virus already possesses binding ability to human-type receptors, though the risk of the H3N8 virus infection in humans was low, and the cases are rare and sporadic at present. Considering the pandemic potential, comprehensive surveillance of the H3N8 virus in poultry flocks and the environment is imperative, and poultry-to-human transmission should be closely monitored. FUNDING: National Natural Science Foundation of China, National Key Research and Development Program of China, Strategic Priority Research Program of the Chinese Academy of Sciences, Hunan Provincial Innovative Construction Special Fund: Emergency response to COVID-19 outbreak, Scientific Research Fund of Hunan Provincial Health Department, and the Hunan Provincial Health Commission Foundation.


Subject(s)
COVID-19 , Influenza A Virus, H3N8 Subtype , Influenza A Virus, H9N2 Subtype , Influenza in Birds , Influenza, Human , Humans , Animals , Child, Preschool , Influenza in Birds/epidemiology , Influenza A Virus, H3N8 Subtype/genetics , Influenza, Human/epidemiology , Phylogeny , Retrospective Studies , Chickens , Poultry , Ducks , Mammals
5.
Frontiers in public health ; 10, 2022.
Article in English | EuropePMC | ID: covidwho-1749552

ABSTRACT

Introduction Modeling on infectious diseases is significant to facilitate public health policymaking. There are two main mathematical methods that can be used for the simulation of the epidemic and prediction of optimal early warning timing: the logistic differential equation (LDE) model and the more complex generalized logistic differential equation (GLDE) model. This study aimed to compare and analyze these two models. Methods We collected data on (coronavirus disease 2019) COVID-19 and four other infectious diseases and classified the data into four categories: different transmission routes, different epidemic intensities, different time scales, and different regions, using R2 to compare and analyze the goodness-of-fit of LDE and GLDE models. Results Both models fitted the epidemic curves well, and all results were statistically significant. The R2 test value of COVID-19 was 0.924 (p < 0.001) fitted by the GLDE model and 0.916 (p < 0.001) fitted by the LDE model. The R2 test value varied between 0.793 and 0.966 fitted by the GLDE model and varied between 0.594 and 0.922 fitted by the LDE model for diseases with different transmission routes. The R2 test values varied between 0.853 and 0.939 fitted by the GLDE model and varied from 0.687 to 0.769 fitted by the LDE model for diseases with different prevalence intensities. The R2 test value varied between 0.706 and 0.917 fitted by the GLDE model and varied between 0.410 and 0.898 fitted by the LDE model for diseases with different time scales. The GLDE model also performed better with nation-level data with the R2 test values between 0.897 and 0.970 vs. 0.731 and 0.953 that fitted by the LDE model. Both models could characterize the patterns of the epidemics well and calculate the acceleration weeks. Conclusion The GLDE model provides more accurate goodness-of-fit to the data than the LDE model. The GLDE model is able to handle asymmetric data by introducing shape parameters that allow it to fit data with various distributions. The LDE model provides an earlier epidemic acceleration week than the GLDE model. We conclude that the GLDE model is more advantageous in asymmetric infectious disease data simulation.

6.
J Hazard Mater ; 425: 128051, 2022 03 05.
Article in English | MEDLINE | ID: covidwho-1561920

ABSTRACT

The number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to increase worldwide, but despite extensive research, there remains significant uncertainty about the predominant routes of SARS-CoV-2 transmission. We conducted a mechanistic modeling and calculated the exposure dose and infection risk of each passenger in a two-bus COVID-19 outbreak in Hunan province, China. This outbreak originated from a single pre-symptomatic index case. Some human behavioral data related to exposure including boarding and alighting time of some passengers and seating position and mask wearing of all passengers were obtained from the available closed-circuit television images/clips and/or questionnaire survey. Least-squares fitting was performed to explore the effect of effective viral load on transmission risk, and the most likely quanta generation rate was also estimated. This study reveals the leading role of airborne SARS-CoV-2 transmission and negligible role of fomite transmission in a poorly ventilated indoor environment, highlighting the need for more targeted interventions in such environments. The quanta generation rate of the index case differed by a factor of 1.8 on the two buses and transmission occurred in the afternoon of the same day, indicating a time-varying effective viral load within a short period of five hours.


Subject(s)
Air Microbiology , COVID-19 , Fomites/virology , Motor Vehicles , SARS-CoV-2 , COVID-19/transmission , Disease Outbreaks , Humans
7.
Build Environ ; 207: 108414, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1446479

ABSTRACT

Uncertainty remains on the threshold of ventilation rate in airborne transmission of SARS-CoV-2. We analyzed a COVID-19 outbreak in January 2020 in Hunan Province, China, involving an infected 24-year-old man, Mr. X, taking two subsequent buses, B1 and B2, in the same afternoon. We investigated the possibility of airborne transmission and the ventilation conditions for its occurrence. The ventilation rates on the buses were measured using a tracer-concentration decay method with the original driver on the original route. We measured and calculated the spread of the exhaled virus-laden droplet tracer from the suspected index case. Ten additional passengers were found to be infected, with seven of them (including one asymptomatic) on B1 and two on B2 when Mr. X was present, and one passenger infected on the subsequent B1 trip. B1 and B2 had time-averaged ventilation rates of approximately 1.7 and 3.2 L/s per person, respectively. The difference in ventilation rates and exposure time could explain why B1 had a higher attack rate than B2. Airborne transmission due to poor ventilation below 3.2 L/s played a role in this two-bus outbreak of COVID-19.

10.
Nat Commun ; 12(1): 1533, 2021 03 09.
Article in English | MEDLINE | ID: covidwho-1125484

ABSTRACT

Several mechanisms driving SARS-CoV-2 transmission remain unclear. Based on individual records of 1178 potential SARS-CoV-2 infectors and their 15,648 contacts in Hunan, China, we estimated key transmission parameters. The mean generation time was estimated to be 5.7 (median: 5.5, IQR: 4.5, 6.8) days, with infectiousness peaking 1.8 days before symptom onset, with 95% of transmission events occurring between 8.8 days before and 9.5 days after symptom onset. Most transmission events occurred during the pre-symptomatic phase (59.2%). SARS-CoV-2 susceptibility to infection increases with age, while transmissibility is not significantly different between age groups and between symptomatic and asymptomatic individuals. Contacts in households and exposure to first-generation cases are associated with higher odds of transmission. Our findings support the hypothesis that children can effectively transmit SARS-CoV-2 and highlight how pre-symptomatic and asymptomatic transmission can hinder control efforts.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Contact Tracing , SARS-CoV-2/pathogenicity , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/prevention & control , Child , Child, Preschool , China/epidemiology , Disease Susceptibility , Family Characteristics , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Risk Factors , SARS-CoV-2/isolation & purification , Young Adult
11.
Science ; 371(6526)2021 01 15.
Article in English | MEDLINE | ID: covidwho-944842

ABSTRACT

A long-standing question in infectious disease dynamics concerns the role of transmission heterogeneities, which are driven by demography, behavior, and interventions. On the basis of detailed patient and contact-tracing data in Hunan, China, we find that 80% of secondary infections traced back to 15% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primary infections, which indicates substantial transmission heterogeneities. Transmission risk scales positively with the duration of exposure and the closeness of social interactions and is modulated by demographic and clinical factors. The lockdown period increases transmission risk in the family and households, whereas isolation and quarantine reduce risks across all types of contacts. The reconstructed infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom presentation. Modeling indicates that SARS-CoV-2 control requires the synergistic efforts of case isolation, contact quarantine, and population-level interventions because of the specific transmission kinetics of this virus.


Subject(s)
Asymptomatic Infections , COVID-19/prevention & control , COVID-19/transmission , Chain of Infection/prevention & control , SARS-CoV-2 , Adolescent , Adult , Aged , Child , Child, Preschool , China/epidemiology , Contact Tracing , Family Characteristics , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Quarantine , Social Interaction , Virus Shedding , Young Adult
12.
Open Forum Infect Dis ; 7(10): ofaa430, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-756946

ABSTRACT

Here we report a case study of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak event during bus trips of an index patient in Hunan Province, China. This retrospective investigation suggests potential airborne transmission of SARS-CoV-2 and the possibility of superspreading events in certain close contact and closed space settings, which should be taken into account when control strategies are planned.

13.
medRxiv ; 2020 Nov 03.
Article in English | MEDLINE | ID: covidwho-721054

ABSTRACT

Several mechanisms driving SARS-CoV-2 transmission remain unclear. Based on individual records of 1,178 SARS-CoV-2 infectors and their 15,648 contacts in Hunan, China, we estimated key transmission parameters. The mean generation time was estimated to be 5.7 (median: 5.5, IQR: 4.5, 6.8) days, with infectiousness peaking 1.8 days before symptom onset, with 95% of transmission events occurring between 8.8 days before and 9.5 days after symptom onset. Most of transmission events occurred during the pre-symptomatic phase (59.2%). SARS-CoV-2 susceptibility to infection increases with age, while transmissibility is not significantly different between age groups and between symptomatic and asymptomatic individuals. Contacts in households and exposure to first-generation cases are associated with higher odds of transmission. Our findings support the hypothesis that children can effectively transmit SARS-CoV-2 and highlight how pre-symptomatic and asymptomatic transmission can hinder control efforts.

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