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1.
Euro Surveill ; 29(10)2024 Mar.
Article in English | MEDLINE | ID: mdl-38456214

ABSTRACT

BackgroundModel projections of coronavirus disease 2019 (COVID-19) incidence help policymakers about decisions to implement or lift control measures. During the pandemic, policymakers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions.AimWe aimed at developing a model on ICU admissions and updating a procedure for informing policymakers.MethodThe projections were produced using an age-structured transmission model. A consistent, incremental update procedure integrating all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a changepoint analysis guided by Akaike's Information Criterion.ResultsThe model and update procedure allowed us to make weekly projections. Most 3-week prediction intervals were accurate in covering the later observed numbers of ICU admissions. When projections were too high in March and August 2020 or too low in November 2020, the estimated effectiveness of the policy changes was adequately adapted in the changepoint analysis based on the natural accumulation of incoming data.ConclusionThe model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation with the rise of new variants and the start of vaccination.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , Netherlands/epidemiology , Critical Care , Policy
2.
PLoS One ; 19(2): e0298218, 2024.
Article in English | MEDLINE | ID: mdl-38349925

ABSTRACT

Measuring the severity of the disease of SARS-CoV-2 is complicated by the lack of valid estimations for the prevalence of infection. Self-administered rapid antigen diagnostic tests (Ag-RDTs) were available in the Netherlands since March 2021, requiring confirmation by reverse-transcription polymerase chain reaction (RT-PCR) for positive results. We explored the possibility of utilizing the positive predictive value (PPV) of Ag-RDTs to estimate SARS-CoV-2 prevalence. We used data from all Public Health service testing facilities between 3 May 2021 and 10 April 2022. The PPV was calculated by dividing the number of positive RT-PCR results by the total number of confirmation tests performed, and used to estimate the prevalence and compared with the number of COVID-19 hospital admissions. In total 3,599,894 cases were included. The overall PPV was 91.8% and 88.8% were symptomatic. During our study period, the estimated prevalence ranged between 2-22% in symptomatic individuals and 2-14% in asymptomatic individuals, with a correlation between the estimated prevalence and hospital admissions two weeks later (r = 0.68 (p<0.01) and r = 0.60 (p<0.01) for symptomatic/asymptomatic individuals). The PPV of Ag-RDTs can help estimate changes in SARS-CoV-2 prevalence, especially when used in conjunction with other surveillance systems. However, the used method probably overestimated the true prevalence because of unmonitored differences in test propensity between individuals.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Netherlands/epidemiology , COVID-19/diagnosis , COVID-19/epidemiology , Predictive Value of Tests , Prevalence , Sensitivity and Specificity
3.
BMC Med ; 22(1): 69, 2024 Feb 16.
Article in English | MEDLINE | ID: mdl-38360645

ABSTRACT

BACKGROUND: New 15- and 20-valent pneumococcal vaccines (PCV15, PCV20) are available for both children and adults, while PCV21 for adults is in development. However, their cost-effectiveness for older adults, taking into account indirect protection and serotype replacement from a switch to PCV15 and PCV20 in childhood vaccination, remains unexamined. METHODS: We used a static model for the Netherlands to assess the cost-effectiveness of different strategies with 23-valent pneumococcal polysaccharide vaccine (PPV23), PCV15, PCV20, and PCV21 for a 65-year-old cohort from a societal perspective, over a 15-year time horizon. Childhood vaccination was varied from PCV10 to PCV13, PCV15, and PCV20. Indirect protection was assumed to reduce the incidence of vaccine serotypes in older adults by 80% (except for serotype 3, no effect), completely offset by an increase in non-vaccine serotype incidence due to serotype replacement. RESULTS: Indirect effects from childhood vaccination reduced the cost-effectiveness of vaccination of older adults, depending on the serotype overlap between the vaccines. With PCV10, PCV13, or PCV15 in children, PCV20 was more effective and less costly for older adults than PPV23 and PCV15. PCV20 costs approximately €10,000 per quality-adjusted life year (QALY) gained compared to no pneumococcal vaccination, which falls below the conventional Dutch €20,000/QALY gained threshold. However, with PCV20 in children, PCV20 was no longer considered cost-effective for older adults, costing €22,550/QALY gained. As indirect effects progressed over time, the cost-effectiveness of PCV20 for older adults further diminished for newly vaccinated cohorts. PPV23 was more cost-effective than PCV20 for cohorts vaccinated 3 years after the switch to PCV20 in children. PCV21 offered the most QALY gains, and its cost-effectiveness was minimally affected by indirect effects due to its coverage of 11 different serotypes compared to PCV20. CONCLUSIONS: For long-term cost-effectiveness in the Netherlands, the pneumococcal vaccine for older adults should either include invasive serotypes not covered by childhood vaccination or become more affordable than its current pricing for individual use.


Subject(s)
Pneumococcal Infections , Child , Humans , Aged , Pneumococcal Infections/epidemiology , Pneumococcal Infections/prevention & control , Cost-Benefit Analysis , Netherlands/epidemiology , Pneumococcal Vaccines , Vaccination , Quality-Adjusted Life Years , Vaccines, Conjugate
4.
Euro Surveill ; 29(8)2024 Feb.
Article in English | MEDLINE | ID: mdl-38390648

ABSTRACT

BackgroundWastewater surveillance has expanded globally as a means to monitor spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data because of the sampling and quantification process, limiting the applicability of wastewater surveillance as a monitoring tool.AimTo present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.MethodsWe developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan during 2021-22 as an example.ResultsObserved notified cases were matched with the range of cases estimated by our approach with wastewater data only, across different study areas and virus quantification methods, especially when the disease prevalence was high. Estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10-20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.ConclusionOur study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.


Subject(s)
COVID-19 , Humans , Basic Reproduction Number , COVID-19/epidemiology , Japan/epidemiology , SARS-CoV-2 , Wastewater , Wastewater-Based Epidemiological Monitoring
5.
J Infect Dis ; 229(3): 800-804, 2024 Mar 14.
Article in English | MEDLINE | ID: mdl-37014716

ABSTRACT

Mpox has spread rapidly to many countries in nonendemic regions. After reviewing detailed exposure histories of 109 pairs of mpox cases in the Netherlands, we identified 34 pairs where transmission was likely and the infectee reported a single potential infector with a mean serial interval of 10.1 days (95% credible interval, 6.6-14.7 days). Further investigation into pairs from 1 regional public health service revealed that presymptomatic transmission may have occurred in 5 of 18 pairs. These findings emphasize that precaution remains key, regardless of the presence of recognizable symptoms of mpox.


Subject(s)
Mpox (monkeypox) , Humans , Netherlands
6.
Epidemics ; 46: 100735, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38128242

ABSTRACT

During the COVID-19 pandemic, contact tracing was used to identify individuals who had been in contact with a confirmed case so that these contacted individuals could be tested and quarantined to prevent further spread of the SARS-CoV-2 virus. Many countries developed mobile apps to find these contacted individuals faster. We evaluate the epidemiological effectiveness of the Dutch app CoronaMelder, where we measure effectiveness as the reduction of the reproduction number R. To this end, we use a simulation model of SARS-CoV-2 spread and contact tracing, informed by data collected during the study period (December 2020 - March 2021) in the Netherlands. We show that the tracing app caused a clear but small reduction of the reproduction number, and the magnitude of the effect was found to be robust in sensitivity analyses. The app could have been more effective if more people had used it, and if notification of contacts could have been done directly by the user and thus reducing the time intervals between symptom onset and reporting of contacts. The model has two innovative aspects: i) it accounts for the clustered nature of social networks and ii) cases can alert their contacts informally without involvement of health authorities or the tracing app.


Subject(s)
COVID-19 , Mobile Applications , Humans , COVID-19/epidemiology , Contact Tracing , SARS-CoV-2 , Pandemics/prevention & control
7.
Health Aff (Millwood) ; 42(12): 1630-1636, 2023 Dec.
Article in English | MEDLINE | ID: mdl-38048502

ABSTRACT

We reflect on epidemiological modeling conducted throughout the COVID-19 pandemic in Western Europe, specifically in Belgium, France, Italy, the Netherlands, Portugal, Switzerland, and the United Kingdom. Western Europe was initially one of the worst-hit regions during the COVID-19 pandemic. Western European countries deployed a range of policy responses to the pandemic, which were often informed by mathematical, computational, and statistical models. Models differed in terms of temporal scope, pandemic stage, interventions modeled, and analytical form. This diversity was modulated by differences in data availability and quality, government interventions, societal responses, and technical capacity. Many of these models were decisive to policy making at key junctures, such as during the introduction of vaccination and the emergence of the Alpha, Delta, and Omicron variants. However, models also faced intense criticism from the press, other scientists, and politicians around their accuracy and appropriateness for decision making. Hence, evaluating the success of models in terms of accuracy and influence is an essential task. Modeling needs to be supported by infrastructure for systems to collect and share data, model development, and collaboration between groups, as well as two-way engagement between modelers and both policy makers and the public.


Subject(s)
COVID-19 , Pandemics , Humans , Pandemics/prevention & control , SARS-CoV-2 , Europe/epidemiology , Policy
8.
R Soc Open Sci ; 10(11): 230966, 2023 Nov.
Article in English | MEDLINE | ID: mdl-38034127

ABSTRACT

BACKGROUND: We describe how rates of two frequently occurring notifiable diseases-diphtheria and scarlet fever-varied between regions of The Netherlands in the early twentieth century, and identify potential factors underlying this variation. METHODS: Digitized weekly mandatory notification data for 1905-1925, municipality level, were aggregated into 27 'spatial units' defined by unique combinations of province and population density category (high: more than 4500; mid : 1250-4500; low: less than 1250 inhabitants km-2). Generalized additive regression models were fitted to estimate the associations between notification rates and population density, infant mortality rate and household income, while adjusting for temporal trends per spatial unit. RESULTS: Annual per capita notification rates for both diphtheria and scarlet fever tended to rise from the beginning of the period 1905-1925 until peaking around 1918/1919. Adjusted diphtheria notification rates were higher for high- and mid- compared with low-density municipalities (by 71.6 cases per 100 000, 95% confidence interval (CI) : 52.7-90.5; 39.0/100 k, 95% CI : 24.7-53.3, respectively). Scarlet fever showed similar associations with population density (35.7 cases per 100 000, 95% CI : 9.4-62.0; 21.4/100 k, 95% CI: 1.5-41.3). CONCLUSIONS: There was considerable spatial variation in notification rates for both diseases in early twentieth century Netherlands, which could partly be explained by factors capturing variation in living conditions and socio-economic circumstances. These findings aid understanding of contemporary respiratory infection transmission.

9.
J Infect Dis ; 2023 Sep 22.
Article in English | MEDLINE | ID: mdl-37740556

ABSTRACT

BACKGROUND: In the Netherlands, the number of mpox cases started declining before mpox vaccination was initiated. Most cases were men who have sex with men (MSM). We investigated whether the decline in mpox could be attributed to infection-induced immunity or behavioural adaptations. METHODS: We developed a transmission model and accounted for possible behavioural adaptations: less casual partners and shorter time until MSM with mpox refrain from sexual contacts. RESULTS: Without behavioural adaptations, the peak in modelled cases matched observations, but the decline was less steep than observed. With behavioural adaptations in the model, we found a decline of 16-18% in numbers of casual partners in June and 13-22% in July 2022. Model results showed a halving of the time before refraining from sex. When mpox vaccination started, 57% of MSM with very high sexual activity in the model had been infected. Model scenarios revealed that the outbreak could have waned by November 2022 even without vaccination. CONCLUSIONS: The limited duration of the mpox outbreak in the Netherlands can be ascribed primarily to infection-induced immunity among MSM with high sexual activity levels. The decline was accelerated by behavioural adaptations. Immunity among those most sexually active is essential to impede mpox resurgence.

10.
BMC Public Health ; 23(1): 1829, 2023 09 20.
Article in English | MEDLINE | ID: mdl-37730628

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, social distancing measures were imposed to protect the population from exposure, especially older adults and people with frailty, who have the highest risk for severe outcomes. These restrictions greatly reduced contacts in the general population, but little was known about behaviour changes among older adults and people with frailty themselves. Our aim was to quantify how COVID-19 measures affected the contact behaviour of older adults and how this differed between older adults with and without frailty. METHODS: In 2021, a contact survey was carried out among people aged 70 years and older in the Netherlands. A random sample of persons per age group (70-74, 75-79, 80-84, 85-89, and 90 +) and gender was invited to participate, either during a period with stringent (April 2021) or moderate (October 2021) measures. Participants provided general information on themselves, including their frailty, and they reported characteristics of all persons with whom they had face-to-face contact on a given day over the course of a full week. RESULTS: In total, 720 community-dwelling older adults were included (overall response rate of 15%), who reported 16,505 contacts. During the survey period with moderate measures, participants without frailty had significantly more contacts outside their household than participants with frailty. Especially for females, frailty was a more informative predictor of the number of contacts than age. During the survey period with stringent measures, participants with and without frailty had significantly lower numbers of contacts compared to the survey period with moderate measures. The reduction of the number of contacts was largest for the eldest participants without frailty. As they interact mostly with adults of a similar high age who are likely frail, this reduction of the number of contacts indirectly protects older adults with frailty from SARS-CoV-2 exposure. CONCLUSIONS: The results of this study reveal that social distancing measures during the COVID-19 pandemic differentially affected the contact patterns of older adults with and without frailty. The reduction of contacts may have led to the direct protection of older adults in general but also to the indirect protection of older adults with frailty.


Subject(s)
COVID-19 , Frailty , Female , Humans , Aged , Aged, 80 and over , COVID-19/epidemiology , SARS-CoV-2 , Frailty/epidemiology , Netherlands/epidemiology , Pandemics
11.
Influenza Other Respir Viruses ; 17(8): e13174, 2023 08.
Article in English | MEDLINE | ID: mdl-37621921

ABSTRACT

Background: The severity of Severe Acute Respiratory Syndrome Coronavirus 2 infection varies with age and time. Here, we quantify how age-specific risks of hospitalization, intensive care unit (ICU) admission, and death upon infection changed from February 2020 to June 2021 in the Netherlands. Methods: A series of large representative serology surveys allowed us to estimate age-specific numbers of infections in three epidemic periods (late-February 2020 to mid-June 2020, mid-June 2020 to mid-February 2021, and mid-February 2021 to late-June 2021). We accounted for reinfections and breakthrough infections. Severity measures were obtained by combining infection numbers with age-specific numbers of hospitalization, ICU admission, and excess all-cause deaths. Results: There was an accelerating, almost exponential, increase in severity with age in each period. The rate of increase with age was the highest for death and the lowest for hospitalization. In late-February 2020 to mid-June 2020, the overall risk of hospitalization upon infection was 1.5% (95% confidence interval [CI] 1.3-1.8%), the risk of ICU admission was 0.36% (95% CI: 0.31-0.42%), and the risk of death was 1.2% (95% CI: 1.0-1.4%). The risk of hospitalization was significantly increased in mid-June 2020 to mid-February 2021, while the risk of ICU admission remained stable over time. The risk of death decreased over time, with a significant drop among ≥70-years-olds in mid-February 2021 to late-June 2021; COVID-19 vaccination started early January 2021. Conclusion: Whereas the increase in severity of Severe Acute Respiratory Syndrome Coronavirus 2 with age remained stable, the risk of death upon infection decreased over time. A significant drop in risk of death among elderly coincided with the introduction of COVID-19 vaccination.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged , Humans , COVID-19/epidemiology , Netherlands/epidemiology , COVID-19 Vaccines , Age Factors
12.
Euro Surveill ; 28(27)2023 07.
Article in English | MEDLINE | ID: mdl-37410383

ABSTRACT

BackgroundSince May 2022, an mpox outbreak affecting primarily men who have sex with men (MSM) has occurred in numerous non-endemic countries worldwide. As MSM frequently reported multiple sexual encounters in this outbreak, reliably determining the time of infection is difficult; consequently, estimation of the incubation period is challenging.AimWe aimed to provide valid and precise estimates of the incubation period distribution of mpox by using cases associated with early outbreak settings where infection likely occurred.MethodsColleagues in European countries were invited to provide information on exposure intervals and date of symptom onset for mpox cases who attended a fetish festival in Antwerp, Belgium, a gay pride festival in Gran Canaria, Spain or a particular club in Berlin, Germany, where early mpox outbreaks occurred. Cases of these outbreaks were pooled; doubly censored models using the log-normal, Weibull and Gamma distributions were fitted to estimate the incubation period distribution.ResultsWe included data on 122 laboratory-confirmed cases from 10 European countries. Depending on the distribution used, the median incubation period ranged between 8 and 9 days, with 5th and 95th percentiles ranging from 2 to 3 and from 20 to 23 days, respectively. The shortest interval that included 50% of incubation periods spanned 8 days (4-11 days).ConclusionCurrent public health management of close contacts should consider that in approximately 5% of cases, the incubation period exceeds the commonly used monitoring period of 21 days.


Subject(s)
Homosexuality, Male , Mpox (monkeypox) , Humans , Male , Berlin/epidemiology , Disease Outbreaks , Holidays , Infectious Disease Incubation Period , Mpox (monkeypox)/epidemiology , Sexual and Gender Minorities
13.
Influenza Other Respir Viruses ; 17(6): e13146, 2023 Jun.
Article in English | MEDLINE | ID: mdl-37346096

ABSTRACT

Background: Despite the known relatively high disease burden of influenza, data are lacking regarding a critical epidemiological indicator, the case-fatality ratio. Our objective was to infer age-group and influenza (sub)type specific values by combining modelled estimates of symptomatic incidence and influenza-attributable mortality. Methods: The setting was the Netherlands, 2011/2012 through 2019/2020 seasons. Sentinel surveillance data from general practitioners and laboratory testing were synthesised to supply age-group specific estimates of incidence of symptomatic infection, and ecological additive modelling was used to estimate influenza-attributable deaths. These were combined in an Bayesian inferential framework to estimate case-fatality ratios for influenza A(H3N2), A(H1N1)pdm09 and influenza B, per 5-year age-group. Results: Case-fatality estimates were highest for influenza A(H3N2) followed by influenza B and then A(H1N1)pdm09 and were highest for the 85+ years age-group, at 4.76% (95% credible interval [CrI]: 4.52-5.01%) for A(H3N2), followed by influenza B at 4.08% (95% CrI: 3.77-4.39%) and A(H1N1)pdm09 at 2.51% (95% CrI: 2.09-2.94%). For 55-59 through 85+ years, the case-fatality risk was estimated to double with every 3.7 years of age. Conclusions: These estimated case-fatality ratios, per influenza sub(type) and per age-group, constitute valuable information for public health decision-making, for assessing the retrospective and prospective value of preventative interventions such as vaccination and for health economic evaluations.


Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza Vaccines , Influenza, Human , Humans , Influenza A Virus, H3N2 Subtype , Seasons , Netherlands/epidemiology , Retrospective Studies , Bayes Theorem , Prospective Studies
14.
Proc Natl Acad Sci U S A ; 120(22): e2221887120, 2023 05 30.
Article in English | MEDLINE | ID: mdl-37216529

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
15.
Epidemics ; 43: 100675, 2023 06.
Article in English | MEDLINE | ID: mdl-36889158

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
16.
Sci Rep ; 13(1): 5166, 2023 03 30.
Article in English | MEDLINE | ID: mdl-36997550

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
17.
Euro Surveill ; 28(12)2023 03.
Article in English | MEDLINE | ID: mdl-36951783

ABSTRACT

In early May 2022, a global outbreak of mpox started among persons without travel history to regions known to be enzootic for monkeypox virus (MPXV). On 8 August 2022, the Netherlands reported its 1,000th mpox case, representing a cumulative incidence of 55 per million population, one of the highest cumulative incidences worldwide. We describe characteristics of the first 1,000 mpox cases in the Netherlands, reported between 20 May and 8 August 2022, within the context of the public health response. These cases were predominantly men who have sex with men aged 31-45 years. The vast majority of infections were acquired through sexual contact with casual partners in private or recreational settings including LGBTQIA+ venues in the Netherlands. This indicates that, although some larger upsurges occurred from point-source and/or travel-related events, the outbreak was mainly characterised by sustained transmission within the Netherlands. In addition, we estimated the protective effect of first-generation smallpox vaccine against moderate/severe mpox and found a vaccine effectiveness of 58% (95% CI: 17-78%), suggesting moderate protection against moderate/severe mpox symptoms on top of any possible protection by this vaccine against MPXV infection and disease. Communication with and supporting the at-risk population in following mitigation measures remains essential.


Subject(s)
Mpox (monkeypox) , Sexual and Gender Minorities , Smallpox Vaccine , Male , Humans , Female , Public Health , Netherlands/epidemiology , Homosexuality, Male , Mpox (monkeypox)/diagnosis , Mpox (monkeypox)/epidemiology , Mpox (monkeypox)/prevention & control , Travel , Travel-Related Illness , Disease Outbreaks/prevention & control , Antigens, Viral , Monkeypox virus
19.
Nat Commun ; 13(1): 7727, 2022 12 13.
Article in English | MEDLINE | ID: mdl-36513688

ABSTRACT

The generation time distribution, reflecting the time between successive infections in transmission chains, is a key epidemiological parameter for describing COVID-19 transmission dynamics. However, because exact infection times are rarely known, it is often approximated by the serial interval distribution. This approximation holds under the assumption that infectors and infectees share the same incubation period distribution, which may not always be true. We estimated incubation period and serial interval distributions using 629 transmission pairs reconstructed by investigating 2989 confirmed cases in China in January-February 2020, and developed an inferential framework to estimate the generation time distribution that accounts for variation over time due to changes in epidemiology, sampling biases and public health and social measures. We identified substantial reductions over time in the serial interval and generation time distributions. Our proposed method provides more reliable estimation of the temporal variation in the generation time distribution, improving assessment of transmission dynamics.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , Infectious Disease Incubation Period , Time Factors , China/epidemiology
20.
R Soc Open Sci ; 9(11): 220030, 2022 Nov.
Article in English | MEDLINE | ID: mdl-36397968

ABSTRACT

Background. Scarlet fever, an infectious disease caused by Streptococcus pyogenes, largely disappeared in developed countries during the twentieth century. In recent years, scarlet fever is on the rise again, and there is a need for a better understanding of possible factors driving transmission. Methods. Using historical case notification data from the three largest cities in The Netherlands (Amsterdam, Rotterdam and The Hague) from 1906 to 1920, we inferred the transmission rate for scarlet fever using time-series susceptible-infected-recovered (TSIR) methods. Through additive regression modelling, we investigated the contributions of meteorological variables and school term times to transmission rates. Results. Estimated transmission rates varied by city, and were highest overall for Rotterdam, the most densely populated city at that time. High temperature, seasonal precipitation levels and school term timing were associated with transmission rates, but the roles of these factors were limited and not consistent over all three cities. Conclusions. While weather factors alone can only explain a small portion of the variability in transmission rates, these results help understand the historical dynamics of scarlet fever infection in an era with less advanced sanitation and no antibiotic treatment and may offer insights into the driving factors associated with its recent resurgence.

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