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1.
Proc Natl Acad Sci U S A ; 120(22): e2221887120, 2023 05 30.
Article in English | MEDLINE | ID: covidwho-2325449

ABSTRACT

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection-for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we reanalyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same dataset reported shorter mean observed incubation period (3.2 d vs. 4.4 d) and serial interval (3.5 d vs. 4.1 d) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8 to 4.5 d) for both variants but a shorter mean generation interval for the Omicron variant (3.0 d; 95% CI: 2.7 to 3.2 d) than for the Delta variant (3.8 d; 95% CI: 3.7 to 4.0 d). The differences in estimated generation intervals may be driven by the "network effect"-higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.


Subject(s)
COVID-19 , Epidemics , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , Netherlands/epidemiology
2.
Epidemics ; 2023.
Article in English | EuropePMC | ID: covidwho-2285167

ABSTRACT

Background Children play a key role in the transmission of many infectious diseases. They have many of their close social encounters at home or at school. We hypothesized that most of the transmission of respiratory infections among children occur in these two settings and that transmission patterns can be predicted by a bipartite network of schools and households. Aim and methods To confirm transmission over a school-household network, SARS-CoV-2 transmission pairs in children aged 4-17 years were analyzed by study year and primary/secondary school. Cases with symptom onset between 1 March 2021 and 4 April 2021 identified by source and contact-tracing in the Netherlands were included. In this period, primary schools were open and secondary school students attended class at least once per week. Within pairs, spatial distance between the postcodes was calculated as the Euclidean distance. Results A total of 4,059 transmission pairs were identified;51.9% between primary schoolers;19.6% between primary and secondary schoolers;28.5% between secondary schoolers. Most (68.5%) of the transmission for children in the same study year occurred at school. In contrast, most of the transmission of children from different study years (64.3%) and most primary-secondary transmission (81.7%) occurred at home. The average spatial distance between infections was 1.2 km (median 0.4) for primary school pairs, 1.6 km (median 0) for primary-secondary school pairs and 4.1 km (median 1.2) for secondary school pairs. Conclusion The results provide evidence of transmission on a bipartite school-household network. Schools play an important role in transmission within study years, and households play an important role in transmission between study years and between primary and secondary schools. Spatial distance between infections in a transmission pair reflects the smaller school catchment area of primary schools versus secondary schools. Many of these observed patterns likely hold for other respiratory pathogens.

3.
Epidemics ; 43: 100675, 2023 06.
Article in English | MEDLINE | ID: covidwho-2285166

ABSTRACT

BACKGROUND: Children play a key role in the transmission of many infectious diseases. They have many of their close social encounters at home or at school. We hypothesized that most of the transmission of respiratory infections among children occur in these two settings and that transmission patterns can be predicted by a bipartite network of schools and households. AIM AND METHODS: To confirm transmission over a school-household network, SARS-CoV-2 transmission pairs in children aged 4-17 years were analyzed by study year and primary/secondary school. Cases with symptom onset between 1 March 2021 and 4 April 2021 identified by source and contact-tracing in the Netherlands were included. In this period, primary schools were open and secondary school students attended class at least once per week. Within pairs, spatial distance between the postcodes was calculated as the Euclidean distance. RESULTS: A total of 4059 transmission pairs were identified; 51.9% between primary schoolers; 19.6% between primary and secondary schoolers; 28.5% between secondary schoolers. Most (68.5%) of the transmission for children in the same study year occurred at school. In contrast, most of the transmission of children from different study years (64.3%) and most primary-secondary transmission (81.7%) occurred at home. The average spatial distance between infections was 1.2 km (median 0.4) for primary school pairs, 1.6 km (median 0) for primary-secondary school pairs and 4.1 km (median 1.2) for secondary school pairs. CONCLUSION: The results provide evidence of transmission on a bipartite school-household network. Schools play an important role in transmission within study years, and households play an important role in transmission between study years and between primary and secondary schools. Spatial distance between infections in a transmission pair reflects the smaller school catchment area of primary schools versus secondary schools. Many of these observed patterns likely hold for other respiratory pathogens.


Subject(s)
COVID-19 , SARS-CoV-2 , Child , Humans , COVID-19/epidemiology , COVID-19 Testing , Family Characteristics , Schools
4.
Sci Rep ; 13(1): 5166, 2023 03 30.
Article in English | MEDLINE | ID: covidwho-2250791

ABSTRACT

The COVID-19 pandemic was in 2020 and 2021 for a large part mitigated by reducing contacts in the general population. To monitor how these contacts changed over the course of the pandemic in the Netherlands, a longitudinal survey was conducted where participants reported on their at-risk contacts every two weeks, as part of the European CoMix survey. The survey included 1659 participants from April to August 2020 and 2514 participants from December 2020 to September 2021. We categorized the number of unique contacted persons excluding household members, reported per participant per day into six activity levels, defined as 0, 1, 2, 3-4, 5-9 and 10 or more reported contacts. After correcting for age, vaccination status, risk status for severe outcome of infection, and frequency of participation, activity levels increased over time, coinciding with relaxation of COVID-19 control measures.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Pandemics/prevention & control , SARS-CoV-2 , Netherlands/epidemiology
5.
Euro Surveill ; 27(44)2022 11.
Article in English | MEDLINE | ID: covidwho-2109635

ABSTRACT

BackgroundSince the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination.AimWe present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12-17-year-olds) and children (5-11-year-olds).MethodsWe developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per 100,000 people across vaccination scenarios, before the emergence of the Omicron variant.ResultsOur model projections showed that, on average, upon the release of all non-pharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30-49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups.ConclusionsWhile our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves.


Subject(s)
COVID-19 , SARS-CoV-2 , Child , Adolescent , Humans , Aged , Adult , Middle Aged , Child, Preschool , Netherlands/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Vaccination
6.
Euro Surveill ; 27(6)2022 02.
Article in English | MEDLINE | ID: covidwho-1883863

ABSTRACT

The SARS-CoV-2 Omicron variant has a growth advantage over the Delta variant because of higher transmissibility, immune evasion or shorter serial interval. Using S gene target failure (SGTF) as indication for Omicron BA.1, we identified 908 SGTF and 1,621 non-SGTF serial intervals in the same period. Within households, the mean serial interval for SGTF cases was 0.2-0.6 days shorter than for non-SGTF cases. This suggests that the growth advantage of Omicron is partly due to a shorter serial interval.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Netherlands
7.
Clin Infect Dis ; 73(12): 2318-2321, 2021 12 16.
Article in English | MEDLINE | ID: covidwho-1599037

ABSTRACT

This large, nationwide, population-based, seroepidemiological study provides evidence of the effectiveness of physical distancing (>1.5 m) and indoor group size reductions in reducing severe acute respiratory syndrome coronavirus 2 infection. Additionally, young adults may play an important role in viral spread, contrary to children up until age 12 years with whom close contact is permitted. CLINICAL TRIALS REGISTRATION: NTR8473.


Subject(s)
COVID-19 , SARS-CoV-2 , Child , Humans , Netherlands/epidemiology , Physical Distancing , Research , Young Adult
9.
Euro Surveill ; 26(44)2021 11.
Article in English | MEDLINE | ID: covidwho-1503826

ABSTRACT

We estimated SARS-CoV-2 vaccine effectiveness against onward transmission by comparing secondary attack rates among household members for vaccinated and unvaccinated index cases, based on source and contact tracing data collected when the Delta variant was dominant. Effectiveness of full vaccination of the index case against transmission to unvaccinated and fully vaccinated household contacts, respectively, was 63% (95% confidence interval (CI): 46-75) and 40% (95% CI: 20-54), in addition to the direct protection of vaccination of contacts against infection.


Subject(s)
COVID-19 , Vaccines , COVID-19 Vaccines , Family Characteristics , Humans , Netherlands/epidemiology , SARS-CoV-2
10.
BMC Med ; 19(1): 254, 2021 09 29.
Article in English | MEDLINE | ID: covidwho-1496170

ABSTRACT

BACKGROUND: SARS-CoV-2 dynamics are driven by human behaviour. Social contact data are of utmost importance in the context of transmission models of close-contact infections. METHODS: Using online representative panels of adults reporting on their own behaviour as well as parents reporting on the behaviour of one of their children, we collect contact mixing (CoMix) behaviour in various phases of the COVID-19 pandemic in over 20 European countries. We provide these timely, repeated observations using an online platform: SOCRATES-CoMix. In addition to providing cleaned datasets to researchers, the platform allows users to extract contact matrices that can be stratified by age, type of day, intensity of the contact and gender. These observations provide insights on the relative impact of recommended or imposed social distance measures on contacts and can inform mathematical models on epidemic spread. CONCLUSION: These data provide essential information for policymakers to balance non-pharmaceutical interventions, economic activity, mental health and wellbeing, during vaccine rollout.


Subject(s)
COVID-19 , Pandemics , Adult , Child , Europe/epidemiology , Humans , Models, Theoretical , SARS-CoV-2
11.
Euro Surveill ; 26(8)2021 02.
Article in English | MEDLINE | ID: covidwho-1150673

ABSTRACT

BackgroundDuring the COVID-19 pandemic, many countries have implemented physical distancing measures to reduce transmission of SARS-CoV-2.AimTo measure the actual reduction of contacts when physical distancing measures are implemented.MethodsA cross-sectional survey was carried out in the Netherlands in 2016-17, in which participants reported the number and age of their contacts the previous day. The survey was repeated among a subsample of the participants in April 2020, after strict physical distancing measures were implemented, and in an extended sample in June 2020, after some measures were relaxed.ResultsThe average number of community contacts per day was reduced from 14.9 (interquartile range (IQR): 4-20) in the 2016-17 survey to 3.5 (IQR: 0-4) after strict physical distancing measures were implemented, and rebounded to 8.8 (IQR: 1-10) after some measures were relaxed. All age groups restricted their community contacts to at most 5, on average, after strict physical distancing measures were implemented. In children, the number of community contacts reverted to baseline levels after measures were eased, while individuals aged 70 years and older had less than half their baseline levels.ConclusionStrict physical distancing measures greatly reduced overall contact numbers, which likely contributed to curbing the first wave of the COVID-19 epidemic in the Netherlands. However, age groups reacted differently when measures were relaxed, with children reverting to normal contact numbers and elderly individuals maintaining restricted contact numbers. These findings offer guidance for age-targeted measures in future waves of the pandemic.


Subject(s)
COVID-19/prevention & control , Pandemics , Physical Distancing , Social Interaction , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Netherlands/epidemiology , Young Adult
12.
Eurosurveillance ; 26(8):1, 2021.
Article in English | ProQuest Central | ID: covidwho-1124144

ABSTRACT

Background: During the COVID-19 pandemic, many countries have implemented physical distancing measures to reduce transmission of SARS-CoV-2. Aim: To measure the actual reduction of contacts when physical distancing measures are implemented. Methods: A cross-sectional survey was carried out in the Netherlands in 2016–17, in which participants reported the number and age of their contacts the previous day. The survey was repeated among a subsample of the participants in April 2020, after strict physical distancing measures were implemented, and in an extended sample in June 2020, after some measures were relaxed. Results: The average number of community contacts per day was reduced from 14.9 (interquartile range (IQR): 4–20) in the 2016–17 survey to 3.5 (IQR: 0–4) after strict physical distancing measures were implemented, and rebounded to 8.8 (IQR: 1–10) after some measures were relaxed. All age groups restricted their community contacts to at most 5, on average, after strict physical distancing measures were implemented. In children, the number of community contacts reverted to baseline levels after measures were eased, while individuals aged 70 years and older had less than half their baseline levels. Conclusion: Strict physical distancing measures greatly reduced overall contact numbers, which likely contributed to curbing the first wave of the COVID-19 epidemic in the Netherlands. However, age groups reacted differently when measures were relaxed, with children reverting to normal contact numbers and elderly individuals maintaining restricted contact numbers. These findings offer guidance for age-targeted measures in future waves of the pandemic.

13.
Euro Surveill ; 25(5)2020 02.
Article in English | MEDLINE | ID: covidwho-668

ABSTRACT

A novel coronavirus (2019-nCoV) is causing an outbreak of viral pneumonia that started in Wuhan, China. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan in the early outbreak phase, we estimate the mean incubation period to be 6.4 days (95% credible interval: 5.6-7.7), ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values should help inform 2019-nCoV case definitions and appropriate quarantine durations.


Subject(s)
Betacoronavirus/pathogenicity , Coronavirus Infections , Infectious Disease Incubation Period , Pneumonia, Viral , Travel , COVID-19 , China/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Humans , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , SARS-CoV-2 , Severe Acute Respiratory Syndrome/diagnosis , Severe Acute Respiratory Syndrome/transmission , Virus Latency
14.
Non-conventional in 0 | WHO COVID | ID: covidwho-707434

ABSTRACT

OBJECTIVE: To determine whether children play a role in the transmission of SARS-CoV-2 to other children and adults, and to gain insight into symptomatic and asymptomatic infections in children. DESIGN: Analysis of national COVID-19 notifications and prospective observational study in families with children. METHOD: Information about COVID-19 patients and their contacts was obtained from the registration systems used by the public health services. In an ongoing study, patients with COVID-19 were asked to participate if they have a family with children. On two occasions nose-throat swabs and blood were collected for PCR analysis and determination of antibodies against SARS-CoV-2. RESULTS: The notifications suggest that transmission finds place mainly between adults and to a lesser extent between parents and children. For the family study, data were available from 54 households with a total of 227 participants. In families of a confirmed COVID-19 patient, children between 1 and 11 years were less often positive in PCR and serology than older children and adults. CONCLUSION: The study gives no indications that children play an important role in the transmission of SARS-CoV-2. Children can indeed become infected, but transmission mainly takes place between adult peers and from adult family members to children. Transmission among children or from children to adults, as is known in influenza, appears to be less common. Ongoing studies should provide important information for further decision-making on control measures, such as closure of schools.

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