The daily updated Dutch national database on COVID-19 epidemiology, vaccination and sewage surveillance

The Dutch national open database on COVID-19 has been incrementally expanded since its start on 30 April 2020 and now includes datasets on symptoms, tests performed, individual-level positive cases and deaths, cases and deaths among vulnerable populations, settings of transmission, hospital and ICU admissions, SARS-CoV-2 variants, viral loads in sewage, vaccinations and the effective reproduction number. This data is collected by municipal health services, laboratories, hospitals, sewage treatment plants, vaccination providers and citizens and is cleaned, analysed and published, mostly daily, by the National Institute for Public Health and the Environment (RIVM) in the Netherlands, using automated scripts. Because these datasets cover the key aspects of the pandemic and are available at detailed geographical level, they are essential to gain a thorough understanding of the past and current COVID-19 epidemiology in the Netherlands. Future purposes of these datasets include country-level comparative analysis on the effect of non-pharmaceutical interventions against COVID-19 in different contexts, such as different cultural values or levels of socio-economic disparity, and studies on COVID-19 and weather factors.

Impact analysis of rotavirus vaccination in various geographic regions in Western Europe

BACKGROUND

Universal mass vaccination (UMV) against rotavirus has been implemented in many but not all European countries. This study investigated the impact of UMV on rotavirus incidence trends by comparing European countries with UMV: Belgium, England/Wales and Germany versus countries without UMV: Denmark and the Netherlands.

METHODS

For this observational retrospective cohort study, time series data (2001-2016) on rotavirus detections, meteorological factors and population demographics were collected. For each country, several meteorological and population factors were investigated as possible predictors of rotavirus incidence. The final set of predictors were incorporated in negative binomial models accounting for seasonality and serial autocorrelation, and time-varying incidence rate ratios (IRR) were calculated for each age group and country separately. The overall vaccination impact two years after vaccine implementation was estimated by pooling the results using a random effects meta-analyses. Independent t-tests were used to compare annual epidemics in the pre-vaccination and post-vaccination era to explore any changes in the timing of rotavirus epidemics.

RESULTS

The population size and several meteorological factors were predictors for the rotavirus epidemiology. Overall, we estimated a 42% (95%-CI 23;56%) reduction in rotavirus incidence attributable to UMV. Strongest reductions were observed for age-groups 0-, 1- and 2-years (IRR 0.47, 0.48 and 0.63, respectively). No herd effect induced by UMV in neighbouring countries was observed. In all UMV countries, the start and/or stop and corresponding peak of the rotavirus season was delayed by 4-7 weeks.

CONCLUSIONS

The introduction of rotavirus UMV resulted in an overall reduction of 42% in rotavirus incidence in Western European countries two years after vaccine introduction and caused a change in seasonal pattern. No herd effect induced by UMV neighbouring countries was observed for Denmark and the Netherlands.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Updated cost-effectiveness and risk-benefit analysis of two infant rotavirus vaccination strategies in a high-income, low-endemic setting

BACKGROUND AND OBJECTIVE

Since 2013, a biennial rotavirus pattern has emerged in the Netherlands with alternating high and low endemic years and a nearly 50% reduction in rotavirus hospitalization rates overall, while infant rotavirus vaccination has remained below 1% throughout. As the rotavirus vaccination cost-effectiveness and risk-benefit ratio in high-income settings is highly influenced by the total rotavirus disease burden, we re-evaluated two infant vaccination strategies, taking into account this recent change in rotavirus epidemiology.

METHODS

We used updated rotavirus disease burden estimates derived from (active) surveillance to evaluate (1) a targeted strategy with selective vaccination of infants with medical risk conditions (prematurity, low birth weight, or congenital conditions) and (2) universal vaccination including all infants. In addition, we added herd protection as well as vaccine-induced intussusception risk to our previous cost-effectiveness model. An age- and risk-group structured, discrete-time event, stochastic multi-cohort model of the Dutch pediatric population was used to estimate the costs and effects of each vaccination strategy.

RESULTS

The targeted vaccination was cost-saving under all scenarios tested from both the healthcare payer and societal perspective at rotavirus vaccine market prices (€135/child). The cost-effectiveness ratio for universal vaccination was €51,277 at the assumed vaccine price of €75/child, using a societal perspective and 3% discount rates. Universal vaccination became cost-neutral at €32/child. At an assumed vaccine-induced intussusception rate of 1/50,000, an estimated 1707 hospitalizations and 21 fatal rotavirus cases were averted by targeted vaccination per vaccine-induced intussusception case. Applying universal vaccination, an additional 571 hospitalizations and <  1 additional rotavirus death were averted in healthy children per vaccine-induced intussusception case.

CONCLUSION

While universal infant rotavirus vaccination results in the highest reductions in the population burden of rotavirus, targeted vaccination should be considered as a cost-saving alternative with a favorable risk-benefit ratio for high-income settings where universal implementation is unfeasible because of budget restrictions, low rotavirus endemicity, and/or public acceptance.