scholarly journals Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization

2021 ◽  
Vol 17 (12) ◽  
pp. e1009697
Author(s):  
Fuminari Miura ◽  
Ka Yin Leung ◽  
Don Klinkenberg ◽  
Kylie E. C. Ainslie ◽  
Jacco Wallinga
Keyword(s):  
The Netherlands ◽  
Optimal Allocation ◽  
Epidemiological Data ◽  
Data Driven ◽  
Allocation Scheme ◽  
Allocation Strategy ◽  
Force Of Infection ◽  
Routine Surveillance ◽  
Complex Models

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

scholarly journals Optimal vaccine allocation for COVID-19 in the Netherlands: a data-driven prioritization

2021 ◽  
Author(s):  
Fuminari Miura ◽  
Ka Yin Leung ◽  
Don Klinkenberg ◽  
Kylie E.C. Ainslie ◽  
Jacco Wallinga
Keyword(s):  
The Netherlands ◽  
Optimal Allocation ◽  
Epidemiological Data ◽  
Single Individual ◽  
Allocation Scheme ◽  
Allocation Strategy ◽  
Force Of Infection ◽  
Routine Surveillance ◽  
Complex Models

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest, such as new infections, due to vaccination that fully immunizes a single individual. We express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. The principle of allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

scholarly journals Data-driven runoff forecasting for Minjiang River: a case study

2020 ◽  
Vol 20 (6) ◽  
pp. 2284-2295
Author(s):  
Yuqiang Wu ◽  
Qinhui Wang ◽  
Ge Li ◽  
Jidong Li
Keyword(s):  
Optimal Allocation ◽  
Data Driven ◽  
Function Parameter ◽  
Support Vector ◽  
Runoff Forecasting ◽  
Minjiang River ◽  
Svm Model ◽  
Runoff Prediction

Abstract Long-term runoff forecasting has the characteristics of a long forecast period, which can be widely applied in environmental protection, hydropower operation, flood prevention and waterlogging management, water transport management, and optimal allocation of water resources. Many models and methods are currently used for runoff prediction, and data-driven models for runoff prediction are now mainstream methods, but their prediction accuracy cannot meet the needs of production departments. To this end, the present research starts with this method and, based on a support vector machine (SVM), it introduces ant colony optimization (ACO) to optimize its penalty coefficient C, Kernel function parameter g, and insensitivity coefficient p, to construct a data-driven ACO-SVM model. The validity of the method is confirmed by taking the Minjiang River Basin as an example. The results show that the runoff predicted by use of ACO-SVM is more accurate than that of the default parameter SVM and the Bayesian method.

scholarly journals COVID-19: first long-term care facility outbreak in the Netherlands following cross-border introduction from Germany, March 2020

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mitch van Hensbergen ◽  
Casper D. J. den Heijer ◽  
Petra Wolffs ◽  
Volker Hackert ◽  
Henriëtte L. G. ter Waarbeek ◽  
...  
Keyword(s):  
The Netherlands ◽  
Long Term Care ◽  
Care Facility ◽  
Control Measures ◽  
Border Region ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility ◽  
Cross Border

Abstract Background The Dutch province of Limburg borders the German district of Heinsberg, which had a large cluster of COVID-19 cases linked to local carnival activities before any cases were reported in the Netherlands. However, Heinsberg was not included as an area reporting local or community transmission per the national case definition at the time. In early March, two residents from a long-term care facility (LTCF) in Sittard, a Dutch town located in close vicinity to the district of Heinsberg, tested positive for COVID-19. In this study we aimed to determine whether cross-border introduction of the virus took place by analysing the LTCF outbreak in Sittard, both epidemiologically and microbiologically. Methods Surveys and semi-structured oral interviews were conducted with all present LTCF residents by health care workers during regular points of care for information on new or unusual signs and symptoms of disease. Both throat and nasopharyngeal swabs were taken from residents suspect of COVID-19, based on regional criteria, for the detection of SARS-CoV-2 by Real-time Polymerase Chain Reaction. Additionally, whole genome sequencing was performed using a SARS-CoV-2 specific amplicon-based Nanopore sequencing approach. Moreover, twelve random residents were sampled for possible asymptomatic infections. Results Out of 99 residents, 46 got tested for COVID-19. Out of the 46 tested residents, nineteen (41%) tested positive for COVID-19, including 3 asymptomatic residents. CT-values for asymptomatic residents seemed higher compared to symptomatic residents. Eleven samples were sequenced, along with three random samples from COVID-19 patients hospitalized in the regional hospital at the time of the LTCF outbreak. All samples were linked to COVID-19 cases from the cross-border region of Heinsberg, Germany. Conclusions Sequencing combined with epidemiological data was able to virtually prove cross-border transmission at the start of the Dutch COVID-19 epidemic. Our results highlight the need for cross-border collaboration and adjustment of national policy to emerging region-specific needs along borders in order to establish coordinated implementation of infection control measures to limit the spread of COVID-19.

scholarly journals The Impact of Function Focused Care From Acute Care to Home Care and Nursing Homes

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 629-629
Author(s):  
Silke Metzelthin ◽  
Sandra Zwakhalen ◽  
Barbara Resnick
Keyword(s):  
Older Adults ◽  
The Netherlands ◽  
Home Care ◽  
Acute Care ◽  
Long Term Care ◽  
Functional Decline ◽  
Term Care ◽  
The Us ◽  
The Impact

Abstract Functional decline in older adults often lead towards acute or long-term care. In practice, caregivers often focus on completion of care tasks and of prevention of injuries from falls. This task based, safety approach inadvertently results in fewer opportunities for older adults to be actively involved in activities. Further deconditioning and functional decline are common consequences of this inactivity. To prevent or postpone these consequences Function Focused Care (FFC) was developed meaning that caregivers adapt their level of assistance to the capabilities of older adults and stimulate them to do as much as possible by themselves. FFC was first implemented in institutionalized long-term care in the US, but has spread rapidly to other settings (e.g. acute care), target groups (e.g. people with dementia) and countries (e.g. the Netherlands). During this symposium, four presenters from the US and the Netherlands talk about the impact of FFC. The first presentation is about the results of a stepped wedge cluster trial showing a tendency to improve activities of daily living and mobility. The second presentation is about a FFC training program. FFC was feasible to implement in home care and professionals experienced positive changes in knowledge, attitude, skills and support. The next presenter reports about significant improvements regarding time spent in physical activity and a decrease in resistiveness to care in a cluster randomized controlled trial among nursing home residents with dementia. The fourth speaker presents the content and first results of a training program to implement FFC in nursing homes. Nursing Care of Older Adults Interest Group Sponsored Symposium

scholarly journals Financial losses for Dutch stakeholders during the 2013 aflatoxin incident in Maize in Europe

2021 ◽  
Author(s):  
M. Focker ◽  
H. J. van der Fels-Klerx ◽  
A. G. J. M. Oude Lansink
Keyword(s):  
The Netherlands ◽  
Uncertain Data ◽  
Feed Industry ◽  
Sequence Of Events ◽  
Bulk Milk ◽  
High Concentrations ◽  
Aflatoxin B ◽  
Financial Losses

AbstractEarly 2013, high concentrations of aflatoxin M1 were found in the bulk milk of a few dairy farms in the Netherlands. These high concentrations were caused by aflatoxin B1 contaminated maize from Eastern Europe that was processed into compound feed, which was fed to dairy cows. Since the contamination was discovered in the downstream stages of the supply chain, multiple countries and parties were involved and recalls of the feed were necessary, resulting into financial losses. The aim of this study was to estimate the direct short-term financial losses related to the 2013 aflatoxin incident for the maize traders, the feed industry, and the dairy sector in the Netherlands. First, the sequence of events of the incident was retrieved. Then, a Monte Carlo simulation model was built to combine the scarce and uncertain data to estimate the direct financial losses for each stakeholder. The estimated total direct financial losses of this incident were estimated to be between 12 and 25 million euros. The largest share, about 60%, of the total losses was endured by the maize traders. About 39% of the total losses were for the feed industry, and less than 1% of the total losses were for the dairy sector. The financial losses estimated in this study should be interpreted cautiously due to limitations associated with the quality of the data used. Furthermore, this incident led to indirect long-term financial effects, identified but not estimated in this study.

KAMEDO Report No. 82 Explosion at the Fireworks Warehouse in the Netherlands in 2000

2006 ◽  
Vol 21 (2) ◽  
pp. 123-125 ◽  
Author(s):  
Viveka Björnhagen ◽  
Torbjörn Messner ◽  
Helge Brändström
Keyword(s):  
The Netherlands ◽  
Communication Networks ◽  
Psychosocial Support ◽  
Public Information ◽  
Short Term ◽  
Disaster Plan ◽  
Counselling Center

AbstractA fire and subsequent explosions occurred in a fireworks warehouse on 13 May 2000. A total of 947 persons were injured and 21 persons died, including four firefighters and one reporter. Communication networks became overloaded and impaired notification chains. The hospital disaster plan was followed, but was proved inadequate. Public information was a high priority. A counselling center was established early and was planned to continue operation for five years. The command function did not perform to expectations. Hospital triage was impaired as many responsible left the triage area. Short-term psychosocial support evolved to long-term programs. Liability issues were examined.

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