There is large potential to increase cycling participation worldwide. Participation in cycling is associated with lower risk of mortality from any cause, and incidence of cardiovascular disease and type 2 diabetes, as well as positive mental health and well-being. The largest potential for health gains likely to come from increasing participation amongst those who do not currently cycle regularly, rather than encouraging those who already cycle regularly to cycle more. Replacing car journeys with cycling can lead to reductions in air pollution emissions and lower pollutant exposure to the general population. Important gaps and uncertainties in the existing evidence base include: the extent to which the health benefits associated with cycling participation are fully causal due to the observational nature of much of the existing evidence base; the real-world economic cost-benefits of pragmatic interventions to increase cycling participation; and the most effective (combination of) approaches to increase cycling participation. To address these uncertainties, large-scale, long-term randomised controlled trials are needed to: evaluate the effectiveness, and cost-effectiveness, of (combinations of) intervention approaches to induce sustained long-term increases in cycling participation in terms of increases in numbers of people cycling regularly and number of cycling journeys undertaken, across a range of population demographic groups; establish the effects of such interventions on relevant outcomes related to health and wellbeing, economic productivity and wider societal impacts; and provide more robust quantification of potential harms of increasing cycling participation, such as collision risks. WhilThis narrative review intends to provide a balanced, evidence-based, overview of the benefits and risks of cycling and the potential scope of consequences of increasing cycling participation for health, wellbeing, the environment, and the economy, as well as providing an overview of the evidence about barriers to cycling, and approaches which have been tried so far to increase cycling participation. Throughout, we aim to summarise what is known on each of these topics and to highlight the key evidence gaps and to outline the next steps needed to address these gaps. In doing so, we provide a clear pathway, outlining the work still needed, to facilitate the goal of a sustained increase in cycling uptake globally.2.For outcomes where relevant systematic reviews and meta-analyses have been published, findings from these analyses have been reported. These have been updated with of evidence from more recent studies published since these reviews reported as appropriate. In areas where a systematic review or meta-analysis has not been published, we have attempted to report a representative overview of the available data. The available evidence on cycling and specific health outcomes is summarised in the sections below.2.1.The available evidence from large prospective cohort studies indicates that regular cycling is associated with a lower risk of mortality. In 2014, Kelly et al. published a comprehensive systematic review and meta-analysis collating evidence from all published studies in healthy adults investigating the association between participation in cycling and risk of mortality . This ancompared with no cycling participation, in analyses adjusted for major confounding variables.All but one study reported that higher levels of cycling were associated with a lower risk of mortality over the follow-up period. When data from all studies were combined, there was a clear, statistically significant lower risk of mortality associated with regular cycling participation. The combined data from all of these studies, illustrated in Levels of cycling beyond this range were associated with a further lowering of mortality risk, but the risk reduction was less steep. Participation in approximately 270 min per week was associated with a 24% lower mortality risk compared with no cycling, however, participation in approximately 570 min per week was associated with a 30% lower risk of mortality compared with no cycling. The clear implication of this is that bigger public health gains will be realised by encouraging individuals who currently do not cycle regularly to do some cycling, rather than getting those who currently cycle regularly to cycle more.Since the publication of the Kelly et al. (2014) systematic review and meta-analysis , furtherKoolhaas et al. examined the association between cycling participation and risk of all-cause mortality amongst 7,225 older adults (mean age 70 years) in living in Rotterdam, who were followed up for a median of 13.1 years . They reTo minimise the potential contribution of reverse causality, Koolhaas et al. undertook sensitivity analyses where they excluded deaths occurring in the first 5 and first 10 years of follow up (those with pre-existing disease are more likely to die within the first few years the measurements), and the findings were essentially unchanged . This isIn a large-scale study of 80,306 UK adults followed up for 9.2 years, Oja et al. found that participation in any compared to no cycling was associated with a 15% lower risk of mortality, after adjustment for confounders . InteresIn the largest study to date of cycling participation and risk of mortality—approximately the size of all previous studies combined—Celis-Morales et al. examined the association between mode of commuting to work and risk of mortality amongst 263,540 participants in the UK Biobank cohort who were followed up for 5 years . CompareFinally, in a large study of the combined effects of physical activity and air pollution amongst 52,061 older Danish adults living in urban environments, Anderson et al. reported that participation in cycling was associated with a 17% lower risk of mortality and this association was not modified by exposure to high levels of traffic-related air pollution .Thus, in summary, a large body of epidemiological evidence, including data from over half a million participants has consistently demonstrated that participation in regular cycling is associated with lower risk of mortality compared with no cycling. The curvilinear nature of the dose response relationship  indicate2.2.There is a large body of robust data from prospective cohort studies  that participation in physical activity is associated lower risk of incidence and mortality from cardiovascular disease (CVD) and coronary heart disease (CHD) –14, withA smaller number of studies have specifically examined the association between cycling participation and incidence or mortality from CVD or CHD –9, 15–23Most studies focused on primary prevention and excluded participants with CVD or CHD at baseline. One study considered both primary prevention and secondary prevention data , reporti2.3.Studies which have considered the association between cycling specifically and cancer incidence and mortality amongst populations who did not have cancer at baseline are summarised in 2.4.A number of cross-sectional studies have indicated that participation in cycling is associated lower prevalence of type 2 diabetes , 27–30, Rasmussen et al.  evaluateAn earlier study of 70,658 Chinese women aged 40–70 years followed up for 14.6 years by Villegas et al.  reportedHu et al.  undertooThe wider body of evidence evaluating the association between overall physical activity and type 2 diabetes risk is also consistent the available data on cycling. In 2015, Aune et al.  performeThus, the available evidence for cycling participation and risk of type 2 diabetes enables broadly similar conclusions to be drawn as the data for cycling and risk of mortality. Cycling is associated with lower risk of type 2 diabetes and substantial differences in risk are seen when comparing individuals who undertake some, compared to those who undertake no regular cycling. Approaches to encourage individuals who currently do not cycle regularly to do some cycling is likely to lead to substantial public health gains.2.5.Cross-sectional studies generally report that individuals who participate in cycling have a lower body mass index (BMI), and a lower prevalence of overweight and obesity, than their non-cycling counterparts , 35–39. 2.6.Physical activities which are weight-bearing and induce substantial skeletal impacts are associated with benefits on bone health, including higher levels of bone mineral density –46 whichOlmedillas et al. published a systematic review of the evidence on cycling and bone health . The majOne study included in the review reported that sprint cyclists had stronger bones than longer-distance cyclists ; anotherThere is an absence of data in the literature on the effects of participation in transport and recreational cycling on aspects of bone health. Such studies are needed but given that high level competitive cycling is associated with neutral or negative effects on bone health, it seems unlikely that recreational or transport cycling would have a substantial positive effect in this domain. Thus, particularly for people at risk of osteoporosis (for example women and older adults), the available evidence suggests that cycling should probably not be the sole form of physical activity undertaken and should ideally be supplemented with other forms of bone-strengthening weight-bearing physical activities to maximise bone health. A time-efficient way to do this might be to perform exercises such as vertical jumps  a few times per week .2.7.A combination of observational and intervention studies is needed to gain a complete picture of how cycling participation affects health outcomes. However, studies evaluating the effects of cycling interventions specifically on health outcomes are limited. In 2011, Oja et al.  undertooany health outcomes are also not known at present. Thus, adequately powered larger, longer-term studies are urgently needed to establish the extent to which feasible large-scale cycling interventions are likely to alter health outcomes in real-world settings.The overall picture is that the evidence-base for cycling interventions and health outcomes is very limited, with the published studies all being small (less than 100 participants) and generally short-term. The available evidence indicates that cycling interventions improve cardiorespiratory fitness. There is no clear evidence which indicates effects on body composition or on biomarkers of chronic disease risk, which is likely due to the studies being too small to have sufficient statistical power on these health outcomes. The long-term effects (>1 year) of cycling interventions on 2.8.There a large body of observational data indicating an association between participation in cycling and favourable health outcomes, with the evidence suggesting the largest potential public health gains are likely be realised by encouraging individuals who currently do not cycle regularly to do some cycling, rather than getting those who currently cycle regularly to cycle more. The evidence also indicates that the benefits of cycling are broadly similar to other forms of physical activity, thus to maximise gains in public health, it would be important to increase participation in cycling amongst individuals who currently undertake little physical activity, rather than encouraging those who are currently active in other pursuits to switch to cycling. However, the evidence from intervention trials is much more limited. Thus, there is a clear need for longer, larger RCTs to evaluate the size of potential health gains which are realistically achievable from pragmatic real-world interventions to promote cycling. 3.A large body of evidence suggests that physical activity in general is associated with a range of positive mental health and wellbeing outcomes, including increased sleep quality, improved executive function and other components of cognition, reduced risk of depression and depressive symptoms, and higher perceived quality of life , 60. HowA consistent body of evidence from cross-sectional studies suggests an association between cycling and aspects of mental health, quality or life and wellbeing outcomes. For example, cross-sectional studies have reported associations between cycling and lower levels of perceived stress , 62, higIntervention trial data are more limited. One non-randomised intervention trial indicated that an intervention increasing commuting cycling led to greater vitality at 6 months, but this was not sustained until 1 year . Thus, tThere is a clear lack of trial data about whether interventions to increase cycling will improve mental health, quality of life and wellbeing. Randomised controlled trials to quantify the effect of pragmatic and feasible cycling interventions on these outcomes are urgently needed. In particular, understanding whether cycling interventions can reduce sickness absence amongst employee could potentially play a key role in encouraging employers to introduce interventions and policies which facilitate active commuting. 4.4.1.Collision rates in cycling can be expressed based on a number of different exposure measures, including collisions per trip, per unit distance, or per unit time, amongst others . The mosMindell et al.  reportedRisks of cycling vary according to route infrastructure with lower probabilities for a crash being evident on protected bike lanes (by ∼30%–90%) than on roads shared with motorised traffic , 74. A rOverall, absolute risk of collisions with cycling are somewhat higher than driving, but still very low in absolute terms, and the health benefits of cycling are more than 21 times greater than any increased risk of collision . In shorModelling the impact of interventions on cycling collision risks is complex and findings are difficult to generalise, but the available evidence indicates that increases in cycling lead to disproportionately smaller increases in collisions and that the negative impact of collisions do not outweigh the benefits of physical activity from cycling , 79.4.2.This section considers the risks of exposure to air pollution to the individual cyclist while they are cycling. Exposure to air pollution tends to be higher when travelling on roads than during most other activities due to proximity to motor vehicles . This is3, P10 in the range 37–62 µg/m3, black carbon in range 3–21 µg/m3   . When th0 µg/m3) , 81.2) exposure  and all-cause mortality associated with cycling were not modified by level of exposure to traffic-related air pollution , the tipping point would only be reached after 7 h per day of cycling and breakeven point would never be reached. For the average European city the tipping point was 2.5 h per day of cycling and breakeven point was 9.25 h of cycling. Even in the most polluted city in the database  the tipping point was 30 min of cycling per day and breakeven point was 45 min of cycling per day. Thus, the evidence indicates that in almost all but the most extreme air pollution conditions worldwide, the benefits of cycling exceed the risks of increased exposure to inhaled air pollution for all reasonable durations of daily cycling.Tainio et al. , extendeA summary of what we know and is not yet know about cycling and risk of collisions and exposure to air pollution is shown in 5.The following section discusses the available evidence and current research gaps on the economic benefits and costs associated with cycling, considering costs to the individual, employers and wider society. We searched the academic and grey literature for reports on the economic benefits and costs of cycling, prioritising reporting data from reviews summarising existing evidence, but also reporting data from individual studies. Thus, this section provides a representative overview of the existing evidence, but does not represent a systematic review of the topic.•To the individual .•To employers .•To wider society .Costs and benefits of cycling at these three levels are described in the sections below.When evaluating the economic costs and benefits of cycling (in comparison to other modes of transport), it is important to consider costs at multiple levels. These include costs and benefits:5.1.www.xe.com). If taxation costs (which can vary considerably by country and vehicle emissions) are excluded, the cost of travel was per km €0.039/km (£0.035) by cycle and €0.16 (£0.14) by car.Evidence from Denmark indicates that choosing to cycle over driving a car is cost saving to the individual . Taking −1 and driving speeds of 50 km.h−1, and costed driving time at €15.19/hour and €22.86/hour for delays  and costing cycling time at €12.10/hour and €18.28/hour for delays, equating to a time cost of €0.672/km for cycling and €0.215/km . It also0.215/km .−1 is optimistic. Furthermore costs associated with insurance, as well as costs associated with the personal valuation of perceptions of safely (which may increase cycling costs) and potential discomfort during travel were not considered in this economic model. Inclusion of such factors is needed to provide a more complete picture of economic costs and benefits to the individual.The Danish reports estimated that cost to the individual of cycling collisions at €0.034/km  and approximately £50/month to the individual employee due to reduced travel costs . FurtherThus, while the available data on cycling and productivity are limited the current evidence suggests a potential net benefit to employers of higher levels of cycling amongst employees. Development of employer-led interventions to increase levels of cycling amongst employees could conceivably result in net economic benefit to employers, even when costs of the intervention are taken into consideration.Further research is needed to more robustly quantify the benefits and costs to employers, as well as employees, of pragmatic, large-scale interventions to increase cycling amongst employees. The first stage in this process would be to gain a better understanding of which type of interventions are most likely to be cost-effective in incentivising employees to increase their cycling participation.5.3.There is a growing body of evidence indicating a net benefit to society of increasing participation in cycling as summarized in the following sections relating to cycling impacts on health, pollution and congestion, duty and taxation and employment and retail.5.3.1.To assess the economic costs and benefits of cycling in relation to health, it is necessary to first obtain an estimate of the epidemiological dose-response relationships between cycling and health benefits and health risks, such as pollution exposure and collisions, as well as potential changes to pollution as a result of changes in cycling and then scale them into an impact model according to level or change in level of population cycling . These hCommonly used models relevant to this report include the World Health Organization's Health Economic Assessment Tool (HEAT) for cycling and walking , 88 and In 2008, Cavill et al. systematically reviewed economic analyses of transport infrastructure and policies which included health effects related to cycling . This reSome reports have attempted to quantify population-level health cost savings associated increasing levels of cycling, or active travel. Jarrett et al.  modelledA report by Fishman and coworkers , used HE5.3.2.The available evidence, albeit limited, quantifying the benefits of cycling on congestion and pollution consistently reports that increased cycling levels would lead to reductions in associated costs. These approaches model the effects of replacing car journeys with cycling journeys and monetary attribute costs to reductions in emissions, noise and congestion. Using this approach it was estimated that, in Copenhagen, replacing car travel by cycling would result in a saving of €0.004/km in air pollution costs, €0.005/km in climate change costs, €0.0062/km in congestion costs , 94.•The CDP plan was projected to result economic benefits in 2025 of £283.5 million in reduced congestion, £10.9 million in reduced greenhouse gas emissions, £2.4 million in decreased noise and £1.5 million in improved air quality. Corresponding economic benefits in 2050 were £956.3 million (reduced congestion), £36.6 million (greenhouse gases), £7.9 million (noise) and £5.2 million .•The more ambitious GBC target was projected to result in economic benefits for congestion, greenhouse gases, noise, and air quality of £1.09 billion, £41.5 million, £9.1 million, and £5.9 million, respectively in 2025; and £7.1 billion, £271.6 million, £59.2 million, and £38.6 million, respectively in 2050.Modelling studies evaluating potential effects of increasing levels of cycling for transport on air pollution , AMED (Allied and Complimentary medicine database), PeDRO (Physiotherapy Evidence Database), Cochrane library]. Although our search was not exhaustive, it is likely that the evidence presented here is representative of the evidence base. There were 10 studies identified; these included one systematic review  and nine6.1.The systematic review, which included 21 observational studies from five countries  focused on the effect of the environment on cycling levels . It repoConversely, the presence of dedicated cycle routes or paths, separation of cycling from other traffic, high population density, short trip distance, and proximity of a cycle path or green space were positively associated with cycling . SimilarRelated to safety, three studies further identified the perceived poor attitude of other road users as a barrier to cycling , 103. ThOne study reported that owning a car was negatively associated with using a bike as a mode of transport , and sugOne study used a modelling approach to predict that increases in numbers of people cycling would lead to greater political will to improve the cycling environment and a “safely in numbers” effect that would increase the perceived and actual safety of cycling, thereby creating a virtuous cycle for growth .Finally, at an environmental level, the presence of dedicated cycle routes or paths, separation of cycling from other traffic, high population density, short trip distance, and proximity of a cycle path or green space appear to be positively associated with cycling .6.2.The studies that were not included in the review also reported on individual-level, barriers to cycling. These included: lack of skills and confidence , 105; phIn contrast to studies undertaken in areas with relatively weak infrastructure –103, in Connell et al. conducted a full exploration of barriers for office workers for the development and optimisation of a workplace cycling intervention . They fiThere were a number of evidence gaps in the peer-reviewed literature, particularly on barriers to cycling in older adults and disabled populations. Most studies specifically examined cycling as a mode of transport , 106 or 6.3.The main barriers to cycling operate on both environmental  and individual  levels.Importantly, women may be more concerned about safety and lack confidence to a greater degree than men, and even where cycling infrastructure is good, individual barriers remain important.In addition, the promotion of cycling as an everyday  activity, rather than a sport will be needed to maximise uptake of cycling. A multi-faceted approach targeting different population groups in different contexts is therefore needed to reduce barriers to cycling and facilitate increased participation.However, more research is needed to understand specific barriers to recreational cycling, and in different population groups . 7.individual level ; the social level ; interventions at the physical environment level (could include facilities and infrastructure); and the policy level .When implementing and evaluating potential solutions to increase the number of people cycling, it can be helpful to think about the “level” of the intervention. A useful and previously used  model is7.1.The evidence for the promotion of cycling draws from different study types; observational studies examining factors which influence cycling; experimental studies, empirical studies such as natural experiments, and evaluations of public health policies. In the past two decades there have been numerous attempts to synthesise this evidence. individual , conducting workplace challenges, and having workplace cycling champions.At this level, the evidence base is still early in its development. Again, it is often difficult to identify actions that would be considered purely at the social level; there is often overlap with individual level actions or they contribute to a multi-component, community wide project also including changes to the physical environment. Currently, there is insufficient evidence to support the promotion of several potential solutions at this level by themselves in promoting cycling. Such actions include: workplace Again there are instances where such programmes have been effective, and others where they have not. Whilst such solutions by themselves may not produce behaviour change, they may be useful for the purposes of reinforcing and reminding people about their behaviour, enhancing social support and contributing to the creation of a cycling culture within a community or organisation.7.1.3.The strongest and largest body of evidence exists at this level. Early reviews found inconsistent findings in associations between the physical environment and cycling, potentially due to a lack of studies and low methodological quality. More recent reviews reflect the increased research focus on the physical environment as an important determinant of physical activity behaviours such as cycling.connectivity of streets, distance and access to destinations, and perceived safety are associated with levels of cycling. There is also emerging evidence that changes to these characteristics are associated with changes in cycling. Most recently, there has been an increase in more robust evaluations of cycling infrastructure projects—both in improvements to existing infrastructure and the creation of new infrastructure.Observational evidence consistently demonstrates that several characteristics related to the design of the physical environment including the The evidence is becoming increasingly strong that introducing actions such as appropriate signage, local facilities , dedicated and high-quality cycle paths, comprehensive networks, and traffic calming measures leads to an increase in cycling. It should be noted that such infrastructure improvements may work best when combined with actions at other levels of the socio-ecological model. There is also a substantial body of evidence emerging, demonstrating the consistently positive effects of bicycle hire and sharing schemes within organisations and at wider community and city levels. However, it is important to recognise, as Fell and Kivenen state, that “Infrastructure is generally regarded as necessary but not sufficient to boost cycling” .7.1.4.The evidence on the impact of interventions at the policy level is the least developed. Much of the evidence appraised by the key reviews in 7.2.Cycling is a complex, multi-faceted behaviour, with barriers and facilitators operating at multiple levels for different individuals and sub-groups of the population. Accordingly, in order to address these barriers, multiple solutions will be required. What is clearly evident from this overview of the evidence base is that no single intervention, programme or policy will be sufficient to produce long-lasting, population-wide increases in cycling.place” through improving cycling infrastructure at the physical environmental level, and also the “person” through individual and social level support. Whilst intervening at the level of the physical environment and improving the infrastructure for cycling is possible and undoubtedly necessary, doing so in isolation is unlikely to be sufficient to prompt behaviour change for many individuals. Thus, what will be needed to best promote cycling has been described as “a coordinated package of complementary infrastructure measures, programs and policies” . In short, not all things get evaluated, and not all things that get evaluated make it into journals and reports. The outcome is that the “accepted” evidence base can give a very limited picture of the full scope of approaches.Second, there are some novel and fast changing approaches, for which the effectiveness is not yet fully understood. These include potential strategies such as; the introduction of e-Bikes (electric assisted bicycles) , the useThere is a need to understand how to increase cycling through interventions that can be delivered effectively, cost-effectively and at scale to benefit population health. For the reasons given above, it is important to look beyond what is already evaluated and deemed effective. It is clear that a critical next step is to build the evidence base in terms of possible approaches to promote cycling. An efficient way to do this would be to undertake a scoping review of all existing approaches utilising traditional electronic record searching, and importantly the databases of key cycling promotion organisations, and expert stakeholder consultation. This would generate a more comprehensive evidence base, identifying interventions which have been rigorously evaluated and published and also interventions which have not been evaluated but may provide alternative and potentially novel solutions to promote cycling. This would facilitate mapping of the actions and functions of the different intervention approaches (the active ingredients) as well as specified intervention characteristics including; duration (how long the intervention lasts for), scale , setting , and target population .A conceptual version of this is presented in 7.3.In recognition of the need to address barriers at different levels of the socio-ecologial model, the Cycle Nation Project (CNP) aimed to develop, test the feasibility of, and optimise a multi-component workplace-based intervention to increase cycling among office staff at a multinational bank . To ensuThe CNP pilot intervention was delivered across three sites with 68 participants. It was completed in two sites (the third site was stopped due to COVID-19) and was feasible and acceptable to both women and men and across different ethnicities. In addition, the CNP intervention was successful (at least in the short term) in increasing cycling by 3 rides/week on average, and improving perceptions of safety, vitality, confidence, and motivation to cycle . This ca8.Given the potential positive impact sustained uptake in cycling can have on public health, wellbeing, the economy, and the environment, it is important to invest in effective solutions to improve cycling behaviour. Although still in its infancy, research insights into behaviour change strategies show potential to foster increased cycling levels when applied to target populations. From reviewing the available literature, we observed that programme design for interventions to increase cycling may be most effective when a multi-component approach is utilised. Therefore, there is further need to develop and evaluate multi-component cycling interventions for successful large-scale application to maximise cycling uptake.


Community-based physical activity promotion (c-PAP) with a systems perspective has the potential to address health inequity. To achieve a public health impact, such approaches need to be scaled up. For a successful scale up, a concept is needed that is also scientifically grounded and considers practice-based evidence from various stakeholders at different levels and sectors. Therefore, the aims of this study are to assess what kind of external support communities need for implementation and to identify facilitators and barriers for scaling up c-PAP.Two digital workshops were conducted in Germany in March and April 2021. Stakeholders at the community level (n = 163) were involved in the first workshop to identify, what kind of external support communities need and what they can accomplish themselves to implement c-PAP. In the second workshop, stakeholders at the federal and state levels from the sport, health, and social sector as well as scientists (n = 92) discussed facilitators and barriers for scaling up c-PAP interventions. Protocols were compiled and coded using qualitative content analysis.During the first workshop, we identified 14 themes. They represent external support needs, e.g., guidance and assistance by intermediary organization as well as internal efforts that communities can accomplish themselves, e.g., building local networks. In the second workshop, 11 facilitators and barriers for scaling up c-PAP, e.g., political support or an intermediary organization, were identified.The identified results provide practice-based evidence on support needed for scaling up, facilitators that promote scaling up and barriers that might hinder scaling up c-PAP in Germany. Various stakeholders emphasized the need for collaboration and partnerships across several sectors as well as changes in current political and legal conditions. In a next step, this practice-based evidence needs to be systematically integrated with scientific-based evidence on key components for scaling up such approaches for the development of an effective scaling up concept.This research was funded by the Federal Centre of Health Education (BZgA) on behalf of and with funds from the statutory health insurances according to § 20a SGB V in the context of the GKV Alliance for Health.


Hypersensitivity reactions to heparin are uncommon conditions but pose a serious clinical problem for patients requiring cardiopulmonary bypass. Bivalirudin is a reversible direct thrombin inhibitor that can be used instead of heparin.A 49-year-old male patient was admitted to our hospital for coronary artery bypass graft operation with mitral insufficiency and tricuspid valve insufficiency. Heparin allergy was confirmed by skin biopsy and skin tests. Due to this allergy, we used bivalirudin  during the surgery. A loading dose of 1.0 mg/kg (100 mg) bivalirudin was administered through the central line and a continuous infusion of 2.5 mg/kg/h of the anticoagulant was initiated following the approved protocol. Serial ACTs were obtained at 15-minute intervals during the procedure and the measurements were 330s, 320s, 350s, 360s, and 340s consecutively. Additional boluses of 0.5 mg/kg (50 mg) were administered for each measurement. Left anterior descending, obtuse marginal arteries and the right coronary artery were grafted with the left internal mammary and saphenous veins. Also, mitral valve replacement with St Jude mechanical heart valve and tricuspid ring annuloplasty was performed with Medtronic Duran ring. After the surgery, the patient had an uneventful period in the postoperative intensive care unit with a total of 600ml and 300ml chest tube drainage for two days and was discharged on the 7th day.Alternative anticoagulation strategies are needed for cardiopulmonary bypass in patients unable to use heparin. Bivalirudin may be recommended as a viable alternative anticoagulant in patients with heparin allergy during cardiopulmonary bypass. However, each patient should be evaluated individually and it should not be forgotten that more than recommended doses may be needed. Hypersensitivity reactions to heparin and heparin-like compounds are rare . ManagemBivalirudin is a small oligopeptide analog of hirudin acting on thrombin through direct inhibition. It has a half-life of 25 min in the presence of normal renal function and is mostly cleared from the circulation by proteolytic enzymes. The minority of bivalirudin is cleared by the renal system. Bivalirudin level has been shown to correspond to activated clotting time (ACT) .We report a case of coronary artery bypass surgery, mitral valve replacement and tricuspid ring annuloplasty using bivalirudin for anticoagulation during CPB in a patient with hypersensitivity to heparin.® Celite Activated Clotting Time (CeliteACT) test cartridges and i-STAT®1 blood analyzer  in our clinic.A 49-year- old man was admitted to our hospital for coronary artery bypass graft operation (CABG) with concomitant ischemic mitral insufficiency and moderate tricuspid valve insufficiency. Patient characteristics and laboratory parameters are shown in Table 0 C while on CPB.A Sorin Inspire oxygenator  was set up on a Jostra HL20 heart-lung machine . The circuit was primed with 1500ml ringer lactate solution, 100ml mannitol 20%, and 50 mg bivalirudin. Non-coated CPB circuits are used and no cell-saver is used. After standard monitoring, a right radial artery catheter and a jugular central venous pressure catheter were inserted and normal saline was used for flushing. Routine intravenous general anesthesia with propofol, fentanyl, and pancuronium bromide was performed. Baseline ACT was measured as 138s. After the harvesting of the mammary artery was completed, a loading dose of 1.0 mg/kg (100 mg) bivalirudin was administered through the central line for the 97 kg patient and a continuous infusion of 2.5 mg/kg/h of the anticoagulant was initiated as in the CHOOSE ON study [0 C. Because proteolytic activity is responsible for the elimination of bivalirudin, we wanted to reduce the proteolytic activity with this extra cooling and increase the infusion rate at the same time [0 C and stopped the infusion and waited 25 min before termination of CPB because bivalirudin has a half-life of about 25 min [After clamping of the aorta, cold blood cardioplegia was administered through the aortic root cannula. We gave close attention to maintaining blood volume in the cardiotomy reservoir below 600ml to avoid possible stagnation. ACT measurement was obtained and ACT was found to be 390s. An additional bolus of 0.5 mg/kg (50 mg) was administered for increasing ACT above 400s which is a generally accepted time for proceeding CPB [After discontinuation of CPB, ACT was measured as 320s. Two packs of fresh frozen plasma and 3 packs of platelet suspension were transfused to the patient. Despite an abnormal ACT (245s) 15 min after that, satisfactory hemostasis in the surgical field was obtained after a deliberate bleeding control, and the chest was closed 30 min after terminating CPB. Measured ACT values were 160s and 129s respectively after 3 and 6 h of operation .Hirudin is a natural anti-thrombin and is now produced as recombinant (lepirudin). Several studies and cases are reporting successful use of lepirudin use during CPB. Koster et al. reported that 95% of 57 patients were discharged uneventfully . In addiArgatroban is a synthetic, nonpeptide L-arginine derivative that reversibly inhibits thrombin. It undergoes hepatic elimination with a half-life of 40-50 m but this can be prolonged with hepatic dysfunction. There is very limited data for its use during CPB in the literature. Martin et al. reported six patients with CPB and three had severe coagulopathy that needed threefold use of blood products and clot in the pump was observed in one patient despite elevated ACT . Smith eBivalirudin is a small peptide that inhibits thrombin reversibly. Bivalirudin is cleared by proteases including thrombin with approximately 80% elimination by enzymatic cleavage and the other 20% is renally eliminated. The elimination half-life of bivalirudin is 20–30 min in the presence of normal renal function. Bivalirudin is currently approved in many countries for patients with unstable angina undergoing percutaneous coronary intervention with provisional use of glycoprotein IIb/IIIa inhibitor and in patients at risk of HIT undergoing percutaneous coronary intervention. According to current American College of Clinical Pharmacology guidelines, it is the preferred agent for patients with HIT requiring urgent cardiac surgery . There aGiven that there is no reversal agent or antidote specifically for bivalirudin, there are some suggested precautions to be taken to maintain a reliable operation while using bivalirudin. In addition, in the study of Koster et al., it is reported that zero-balance modified hemodiafiltration without the addition of vacuum aspiration is effective in improving bivalirudin elimination after CPB . HeparinIn this report, we needed to use more frequent and more amounts of bolus doses to get above 400s ACT levels and reach the safe range with this regimen. We had to increase the infusion rate. Although we initially planned the operation under mild hypothermia, we needed to cool the patient further to reduce bivalirudin elimination. After stopping the infusion, we waited for about 55 min, but ACT levels did not decrease to the desired level and we had to complete the operation while ACT levels were high. This may be the result of both greater hypothermia and the additional use of bivalirudin. ACT level returned to normal after 6 h.As a result, our experience with bivalirudin for anticoagulation during CPB in this patient was very convenient. This patient had neither thrombotic nor excessive bleeding complications. However, we can suggest that every patient has to be evaluated individually and dosages can be increased more than planned if needed. Bivalirudin may be suggested as a viable alternative anticoagulant in patients with heparin allergy during CPB.


In response to the traditional Dempster–Shafer (D-S) combination rule that cannot handle highly conflicting evidence, an evidence combination method based on the stochastic approach for link-structure analysis (SALSA) algorithm combined with Lance-Williams distance is proposed. Firstly, the degree of conflict between evidences is calculated based on the number of correlation coefficients between evidences. Then, the evidences with a number of correlation coefficients greater than the average number of correlation coefficients of evidence are connected to construct an evidence association network. The authority weight of the evidence is calculated based on the number of citations in the concept of SALSA algorithm combined with the support of the evidence. Subsequently, the Lance-Williams distance between the evidences is calculated and transformed into support of the evidence. Next, the authority weight and support of evidence are combined to jointly construct a novel correction coefficient to correct the evidence. Finally, the corrected evidence is fused using the D-S combination rule to obtain the final fusion result. The numerical results verify that the method proposed in this paper can effectively solve the problem of the traditional D-S combination rule being unable to handle highly conflicting evidence. The Dempster–Shafer (D-S) theory of evidence  was firsIn practical applications, the D-S combination rule is incomplete and unable to handle highly conflicting evidence to the extent that it produces results that are contrary to the facts. Several scholars in China and abroad have studied and improved this deficiency, and their methods are mainly divided into two categories. The first category is the revision of evidence sources. This approach considers that the traditional D-S combination rule is not problematic in itself, but requires processing of the original evidence. An example is the weighted average method proposed by In this paper, based on the improved method of modifying the evidence source, we propose to combine the stochastic approach for link-structure analysis (SALSA) algorithm  with theThe SALSA algorithm is a new link analysis algorithm proposed by This paper focuses on solving the problem that the D-S evidence theory cannot deal with highly conflicting evidence by correcting the evidence sources. Firstly, we construct an evidence association network based on the correlation coefficients between the evidences, use the SALSA algorithm and combine the support of the evidence to jointly determine the correction coefficients of the evidence. Finally, we use the D-S combination rule to fuse the corrected evidence to obtain the final fusion results.i.e., the power set of Θ is 2Θ; m is a function of 2Θ on to Θ is a complete set of mutually incompatible fundamental propositions. The entire set of its subsets,  1.i.e., m(∅) = 0;the basic probability of an improbable event is 0,  2.Θ is 1, i.e., ∀A ∈ 2Θ, m(A) ≥ 0 and ∑A∈Θm(A) = 1.The basic probability sum of all subsets in 2m(A) is called the basic probability assignment (BPA) on Θ, also known as mass function. If m(A) ≠ 0, A is called a focal element. In reasoning, Θ is usually called frame of discernment, which represents a finite set of basic propositions of all possible conclusions under condition E. A subset of Θ, i.e., the elements in 2Θ, can be understood as a proposition.m is defined as follows: The belief function is the minimum value of the total trust that supports A. In the frame of discernment Θ, the trust function based on BPA m is defined as follows: Plausibility function means that it does not deny A ’s trust in you, and it is the maximum of the total trust that supports A. At the frame of discernment, the likelihood function based on BPA In evidence theory, for a certain hypothesis A of frame of discernment m1, m2, …, mn on the ∀A⊆Θ frame of discernment Θ are as follows: The D-S combination rule for a limited number of mass functions and K is called the conflict factor, K → 1, the conflict between evidences is large; when K → 0, the conflict between evidences is small. If K = 1, there is complete conflict between evidences, and K = 0 indicates that there is no conflict between evidences.where Due to the diversity and complexity of data, evidence fusion using the D-S evidence theory may lead to situations contrary to the facts, which are mainly divided into the following four categories.A, B and evidence E1, E2 are: The basic probability distribution functions of frame of discernment Θ = m(A) = m(B) > 0. The conflict factor K = 1, and E1, E2 are calculated by In this example, according to common sense, the combination result is 1 > A, B, C} and evidence E1, E2, E3 are: The basic probability distribution functions of the frame of discernment Θ = {m(A) > m(C) > m(B) > 0,  and the final result obtained by using the traditional D-S evidence theory is m(A) = m(C) = 0, m(B) = 1. The recognition target does not point to focal elements A and C with generally high basic probability assignment but points to focal element B with generally low basic probability assignment. The result is contrary to the fact, and this type of conflict is called the 0 trust paradox.In this example, the basic probability assignment of focal element A is generally high, followed by focal element C; finally, the basic probability assignment of focal element B is generally low. According to common sense, the combination result is 1 > A, B, C, D} andevidence E1, E2, E3are: The basic probability distribution functions of frame of discernment Θ = {E1, E2, E3 to focal element B is low, and there is a high degree of trust in focal elements A, C and D, respectively, i.e., all of them are 0.99. According to common sense, the combination result is 1 > m(A) = m(C) = m(D) > m(B) > 0,  and using the traditional D-S evidence theory, the final result is m(A) = m(C) = m(D) = 0, m(B) = 1. This type of conflict is called 1 trust paradox.In this example, the basic probability assignment of evidence A, B, C, D} and evidence E1, E2, E3 are: The basic probability distribution functions of frame of discernment Θ = {E2, E3 basic probability distribution function is the same; E1, E2 and E3 of the focal element are not the same and m2(B) = m3(B) > m1(C∪D) > m1(C). Therefore, according to common sense, the combination result should be 1 > m(B) > m(C∪D) > m(C) > 0, where m(B) < m2(B) = m1(B), m(C∪D) < m1(C∪D), m(C) < m1(C). The probability of pointing to the focal element B should be greater after adding evidence E3 again; then, m(B) increases, and the result obtained by synthesizing evidence E1, E2 using the traditional D-S evidence theory m(C) = 0.35, m(C∪D) = 0.65 is the same as E1. The final result obtained by synthesizing evidence E1, E2, E3 is still m(C) = 0.35, m(C∪D) = 0.65 (same as E1), evidence E3 fails, and the result is contrary to common sense. This type of conflict is called the evidence failure paradox.In this example, the evidence Considering that the traditional D-S evidence theory cannot deal with highly conflicting evidence and produces contradiction with facts in practical applications. This paper uses the SALSA algorithm combined with Lance-Williams distance to jointly construct a novel correction coefficient to correct the evidence and use the D-S combination rule to fuse the corrected evidence in the following process. The flow chart of specific steps is shown in The evidence association network is a network that can indicate the correlation between evidences. The lower the conflict between two pieces of evidence, the stronger the correlation between evidences and the higher the similarity between the two pieces of evidence. Conversely, the higher the conflict between two pieces of evidence, the weaker the relevance of the evidence and the lower the similarity between evidences. The current methods to measure the degree of conflict between evidences include the amount of evidence agreement and conflict, conflict coefficient, evidence distance, information entropy, and correlation coefficient. Through analysis and comparison, the conflict coefficient and amount of consistency and conflict between evidence cannot accurately measure the degree of conflict between evidence in some cases. Additionally, the evidence distance mainly describes the degree of difference between evidences, which is not equivalent to describing the degree of conflict between evidences. In this paper, we use the correlation coefficient to measure whether there is a conflict between two pieces of evidence. Its specific definition can be found in the study presented in The distributions of the random variables X and Y are as follows: The bias entropy of the random variable X with respect to Y is defined as follows: The entropy of association between the random variables X and Y is defined as follows: The partial correlation coefficients and correlation coefficients of the random variables are defined as follows:epk− can not completely change the number of 0-1 in a wide range, which needs to add a coefficient on top of epk− into the form of epk−5, this coefficient is closer to the log result based on the check calculation.The formula uses a similar idea to that of entropy, and the proposed concept of entropy-like is to vary the number of 0-1 over a wide range, because e and log are related by an inverse function, so the function e is used instead of log. But the simple r = 1; this indicates that the two pieces of evidence are consistent, there is no conflict, and the calculation is consistent with the facts.When the number of correlation coefficients between two pieces of evidence is large, it indicates that the evidence is highly correlated and less conflicting. If the correlation coefficient between two pieces of evidence is small, it indicates that the evidence is less correlated and more conflicting. The calculation of the full conflict paradox example using the correlation coefficient method yields The evidence involved in the combination is calculated by the above method to calculate the number of correlation links; the evidence with the number of correlation links greater than the average of the number of correlation links of that evidence is connected to build the evidence correlation network. The main idea of the evidence association network is that a high quality evidence is pointed towards by many high quality evidences, and points to many high quality evidences as well.Ei are calculated as follows: The SALSA algorithm is one of the link analysis algorithms which combines the main features of PageRank and HITS algorithms. According to the concept of SALSA algorithm, the evidence association network is transformed into an undirected bipartite graph, and the weights of the evidence are calculated using the formula of authority weights in SALSA algorithm. Then, the weights of the ith evidence i, j =1 , 2, …, N,  N is the number of evidence, Ai is the number of evidence in the connected graph, A is the number of evidence in the authority subset, Bj is the total number of incoming chains in the connected graph.where Ei in the connectivity graph, the higher number of evidence associated with that evidence, and the higher its importance. The greater the ratio Ei, the greater the importance of this evidence in the evidence associated with it and the greater the corresponding weight.The number of evidences in the authority subset is Lance-Williams distance is a quantity that is both dimensionless and unitless. Thus, its numerical magnitude is independent of the chosen unit, overcoming the drawback that Ming’s distance is related to the magnitude of each indicator, while the dimensionless quantity is more suitable for expressing the distance between evidence. The Lance-Williams distance formula is introduced to calculate the distance between individual pieces of evidence, and the distance is transformed into the support of evidence. The specific steps of the method are described as follows.A1, A2, …, An}, Lance-Williams distance between evidence mi and mj is as follows: After defining the identification frame Θ = {The distance between individual pieces of evidence can be expressed as a distance matrix: The similarity between individual pieces of evidence can be expressed in terms of the distance between the evidences: sij is larger, the similarity between the evidence is higher; the smaller the sij, the lower the similarity between evidences. The degree of similarity of the evidence can be expressed by a similarity matrix as follows: When SUPi; if two pieces of evidence are similar, the two pieces of evidence support each other. The higher the degree of similarity, the greater the degree of support. The degree of support of evidence is defined as follows:The support of the evidence is calculated as ωi for the ith evidence is defined as follows: To avoid that a single discount factor is not accurate enough to correct the evidence, this paper adopts a compound discount factor, and combines the SALSA algorithm concept with the support of evidence to jointly construct a new type of correction coefficient to correct the evidence. The correction factor Normalizing the correction factor is defined as follows: The correction of the underlying probability assignment for each piece of evidence is defined as follows: The corrected evidence was fused using the D-S combination rule to obtain the final fusion results.To verify that the method proposed in this paper can deal better with highly conflicting evidence and solve the main problems existing in the traditional D-S evidence theory, this chapter cites single conflict and multi-conflict arithmetics to verify it. Additionally, the proposed method is used to synthesize several typical conflicting evidences to compare and analyze them with other combination methods. The purpose is to show that the proposed method can effectively solve the existing problems in the combination of highly conflicting evidence as well as the traditional D-S evidence theory.A, B, C}, a sensor collects five mutually independent evidences whose corresponding basic probability assignments are as follows: For the frame of discernment Θ = {Data source from literature .The evidence association network is constructed according to the method described in section 3.1, as shown in We convert the evidence association network into an undirected bipartite graph, as shown in The authority weight of the evidence is calculated according to The support of the evidence can be calculated according to The correction factor for the evidence is calculated from From Finally, the amended evidence was fused using the D-S combination rule to obtain the final fusion results as follows: The following fusion method of this paper is compared with other evidence fusion methods in Observing the above five evidences, it can be seen that the probability that evidences E1, E3, E4 and E5 point to the focal element A is not less than 0.5. However, the probability that evidence E2 points to B is not less than 0.5, which conflicts with the other four evidences.m(A) = 0.8483, the results are more similar to the methods of The analysis of the fusion results obtained by different methods in The following will use several types of typical combination methods to synthesize the four types of typical conflict problems introduced in section 2.2 to compare with the methods in this paper, and the specific combination results are shown in m(A) = m(B) > 0, the traditional D-S combination rule cannot be fused, the open-framework-based improvement method is inconsistent with this criterion, and the above two methods cannot deal with the full conflict paradox. For example 2, the reasonable fusion result is 1 > m(A) > m(C) > m(B) > 0; according to this criterion, it can be seen that the traditional D-S combination rule, absorption method, weighted average method, and weighted distribution conflict method are obviously inconsistent with this criterion, and the above methods cannot deal with the 0 trust paradox. For example 3, the reasonable fusion result is 1 > m(A) = m(C) = m(D) > m(B) > 0. According to this criterion, only the method proposed in this paper, weighted average method, and conflicting evidence combination method based on the similarity coefficient between evidences can deal with the 1 trust paradox in m(B) > m(C∪D) > m(C) > 0 and m(B) < m2(B) = m1(B), m(C∪D) < m1(C∪D), m(C) < m1(C). According to this criterion the traditional D-S combination rule, absorption method, weighted allocation conflict method, and open frame of discernment combination rule based on evidence distance in After analyzing A, B, C, D a sensor collects seven mutually independent evidences whose corresponding basic probability assignments are as follows: For the frame of discernment Θ = Data source from literature .The combination results obtained using the proposed method in this paper and conflicting evidence combination method based on the similarity coefficients between evidences were synthesized separately as shown in m(X) isinfluenced by two aspects. The first is the overall support of the individual evidence for the focal element, which can be quantified by the concept of basic confidence number, i.e.,N is the number of evidences. The second is the number of pieces of evidence supporting the focal element X.For the focal element X, the size of its synthetic basic probability assignment E2, E3, E4, E5, E6 all point to element B with a high probability. The basic probability assignment of evidence E2, E3 to focal element A is the same as that of evidence E6, E7 to focal element C. However, the synthesis result of m1(A) > m4(C)is m(A) > m(C) according to common sense. The evidences E4, E6, E7 support 0.4, 0.5, and 0.1 for focal element C, respectively, and evidences E5, E7 support 0.1, 0.9, and 0.9 for focal element D, respectively. The average basic credible number of both of them is the same, but the number of evidence supporting focal element C is greater than the number of evidence supporting focal element D. Then, according to common sense, its synthetic result is m(C) > m(D). In summary, its synthetic result is the reasonable standard m(B) > m(A) > m(C) > m(D). The analysis of Observing the above seven pieces of evidence, we can see that p1, p2, p3, p4, p5. In one of the tests in 2020, if it appears that the actual measured value of a test parameter is outside the standard threshold range, the health status of the device is directly determined to be a fault state. Taking one of the missiles as an example, the actual value of the current test, the non-faulty value of the last test, the average value of the historical test, and the standard threshold value for the five test parameters are shown in To show the effectiveness of the method proposed in this paper in practical applications, an example of missile health status assessment in literature  was usedp1, p2, p3, p4, p5 corresponds to a BPA of m1, m2, m3, m4, m5, and the specific values are shown in Assuming that the quality levels corresponding to excellent, very good, good and proposed failure are A, B, C and D, respectively, the BPA is constructed according to the method proposed in the literature . The tesThe method proposed in this paper is combined with other conflict evidence synthesis methods respectively, and the results are shown in p1 for this test is 0. 69, i.e., outside the threshold range, there is a certain degree of conflict in the test message. The data in Since the value of The traditional D-S combination rule cannot handle highly conflicting evidence and produces contradiction with facts in practical applications. To address this shortcoming, this paper proposes an evidence combination method based on SALSA algorithm and Lance-Williams distance. The verification simulation shows that the proposed method can effectively deal with highly conflicting evidence compared with the traditional D-S combination rule, with faster recognition speed, while reducing the uncertainty of recognition results. The shortcomings of the proposed method in this paper is that it only considers the relationship between the evidence and does not take into the influence of internal evidence on evidence preprocessing methods, The next step in the research plan is to consider addressing this shortcoming.10.7717/peerj-cs.1307/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj-cs.1307/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj-cs.1307/supp-3Supplemental Information 3Click here for additional data file.


The decarboxylative pathways are activated for two main physiological reasons. Decarboxylation is one of the responses of cells to acid stress and it has been demonstrated that the transcription of many decarboxylase genes is induced by low pH and improves cell performances in acid conditions. Moreover, these pathways can bring supplementary energy to the cells by energizing the proton motive force associated with the membrane.Biogenic amines (BAs) are non-volatile low-molecular-weight nitrogenous organic bases that can be found in nearly all types of foods in a wide and variable range of concentrations. The most significant BAs occurring in food are histamine, tyramine, putrescine, cadaverine, tryptamine, 2-phenylethylamine, spermine, spermidine, and agmatine. BAs are produced by microorganisms, mainly bacteria, through the action of decarboxylases, which act selectively on precursor amino acids in which they remove the carboxyl group with the formation of the correspondent biogenic amine and COBAs can be produced both by Gram-positive and Gram-negative bacteria which occur naturally in food products, are introduced by contamination, or are added as a starter culture. Among Gram-negative bacteria, spoilage microorganisms belonging to Enterobacteriaceae and Pseudomonas are known as the major producers of cadaverine, histamine, and putrescine. The ability to produce BAs is widespread also among Gram-positive bacteria. The decarboxylase activity has been found in strains belonging to the genera Bacillus and Staphylococcus. However, attention has been mainly focused on lactic acid bacteria (LAB), which are commonly present or intentionally used in fermented food.Ingestion of food containing BAs represents a considerable toxicological risk for consumer health since these compounds can cause headaches, heart palpitations, vomiting, diarrhea, and hypertensive crisis. However, their toxic effect depends on the type of BAs, individual sensitivity or health status, and on the consumption of ethanol or monoamine oxidase inhibitory drugs, which interact with amino oxidase enzymatic systems responsible for the detoxification process of exogenous BAs.Microorganisms  that are able to produce biogenic amines in models or real systems may be evaluated. Furthermore, such subjects could include descriptions of novel knowledge and strategies for aminogenesis control: use of bioprotective cultures producing bacteriocins or other antimicrobial substances, technological additives, effects of packaging, other non-thermal treatments, and use of microbial cultures able to degrade BAs and detoxifying them through the action of amino oxidases.The Aminobiogenic Potential of Fermented Food Microbiota”. The topic collected four research articles from international researchers. This Research Topic is focused on the aminobiogenic potential of fermented food microbiota, taking into consideration the conditions affecting biogenic amine accumulation and the enzymes and genes involved in the biosynthetic mechanisms.In this context, we organized this Research Topic on “Sang et al. aimed to evaluate the ability to produce BAs of halophilic bacteria isolated from grasshopper sub shrimp paste. The authors analyzed and discussed the bacterial and fungal diversities and BAs contents in grasshopper sub shrimp paste at different fermentation times. They concluded that the actual production of BA by a particular strain was closely related to other species present in the complex fermentation system. The experiment carried out provided important insights into the microbiota and BAs content of grasshopper sub shrimp paste.The study of Yang et al. evaluated the amine production abilities of strains of enteric bacteria screened from Chinese traditional fermented fish. The genotypic diversity of amino acid decarboxylase and the effect of pH were explored on strains of high-yield BAs. They reported that all tested strains carried the corresponding amino acid decarboxylase genes of putrescine and cadaverine. In addition, almost half of the strains carried the histidine decarboxylase gene. The research demonstrates that acid stress causes growth delay but can increase the contents of putrescine, histamine, and cadaverine.Yu et al. presented a study on the change in BA content and microbes involved in BA formation during mustard fermentation. They showed that diverse bacterial species harbored genes associated with the production of various BAs. Four BAs  were generated during mustard fermentation. According to the metagenome sequencing, the predominant genus was Bacillus followed by Lactobacillus, Weissella, and Leuconostoc in the initial fermentation stage, while Lactobacillus became the most dominant genus in the late stage.Hernández-Macias et al. investigated whether the use of cava lees can help to control biogenic amine formation in bread and fermented sausages. The authors showed that cava lees and their phenolic extract are an effective strategy to control the undesirable accumulation of high levels of biogenic amines during the production of fermented products. However, the effect of reducing the high levels of biogenic amines was not as effective as the use of starter cultures.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


An estimated 85% of research resources are wasted worldwide, while there is growing demand for context-based evidence-informed health policymaking. In low- and middle-income countries (LMICs), research uptake for health policymaking and practice is even lower, while little is known about the barriers to the translation of health evidence to policy and local implementation. We aimed to compile the current evidence on barriers to uptake of research in health policy and practice in LMICs using scoping review.The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses-extension for Scoping Reviews (PRISMA-ScR) and the Arksey and O'Malley framework. Both published evidence and grey literature on research uptake were systematically searched from major databases , Global Health (Ovid)) and direct Google Scholar. Literature exploring barriers to uptake of research evidence in health policy and practice in LMICs were included and their key findings were synthesized using thematic areas to address the review question.A total of 4291 publications were retrieved in the initial search, of which 142 were included meeting the eligibility criteria. Overall, research uptake for policymaking and practice in LMICs was very low. The challenges to research uptake were related to lack of understanding of the local contexts, low political priority, poor stakeholder engagement and partnership, resource and capacity constraints, low system response for accountability and lack of communication and dissemination platforms.Important barriers to research uptake, mainly limited contextual understanding and low participation of key stakeholders and ownership, have been identified. Understanding the local research and policy context and participatory evidence production and dissemination may promote research uptake for policy and practice. Institutions that bridge the chasm between knowledge formation, evidence synthesis and translation may play critical role in the translation process.The online version contains supplementary material available at 10.1186/s12961-023-01084-5. Globally, an estimated 85% of research resources are wasted due to errors, exaggeration and inefficiency , 2. ContAbout 42% of research resource waste is avoidable through simple and inexpensive intervention . HoweverAbout 40–90% of research published from trials is not replicable –17, and Research evidence is vital for policymaking, and the role of researchers in translating research evidence into policymaking is crucial . Power rWhat is the available evidence on barriers to uptake of research for policymaking in LMICs?What are the challenges to research uptake for policymaking process in LMICs?What recommendations might strengthen evidence uptake for policymaking in LMICs?The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses-extension for Scoping Reviews (PRISMA-ScR) –33 and tRelevant publications on research uptake for policymaking were identified from major databases , Global Health (Ovid), and direct search of Google Scholar and other sources, including sharing of high-quality evidence via email from authors and senior researchers. Only publications since 2000 were considered due to the growing interest in evidence-informed policy making over the last two decades . LiteratDocuments written in EnglishPublished and relevant grey literature on evidence uptake to policy strategiesEvidence related to research uptake challenges and opportunities in LMICs. The LMICs were selected based on the World Bank’s country classification .Editorials, commentaries, fact sheets, conference abstracts and case-studies.Publications were retrieved from selected databases, recorded using citation manager (EndNote), and duplicates were removed. Two authors (AS & EG) independently screened the title and abstracts of retrieved publications against the eligibility criteria, and based on review questions. Further appraisal assessed the methodological quality and findings before any article was included into the scoping review. Any disagreement between the two independent reviewers was resolved through consensus. If consensus was not reached, two of the senior authors (AF & TM) made a final decision based on the predetermined eligibility criteria. The screening and selection process of the scoping review was guided by the PRISMA flow diagram  Fig. 1)1).Fig. 1Basic descriptions of the included studies, including authors, date, aim of the article, type of study, key findings and recommendation for action, were abstracted and recorded in a Microsoft Word table The challenges of research uptake for policymaking are presented thematically. Eight main themes emerged: understanding context, stakeholder engagement and partnership, building trust and ownership, research capacity, resource constraints and misuse of resources, platform for evidence production and translation, investment in research infrastructure development, and research uptake framework and accountability Fig. . ThematiWe found over 30 papers on the importance of understanding the research uptake context , 145. ThPolitical dimension: Mapping the political dimensions and policy demand [y demand , 135–138y demand , 147, poy demand , 130, any demand , 91, 131y demand , 135–137y demand , 138 incy demand , lack ofy demand , 140, wey demand , 143–145y demand , 147. Siy demand , bureaucy demand , leadersy demand , 105, aly demand , and noty demand , 150 arePriority setting: Priority setting [ setting , 29–156  setting , 156 and setting , 153, an setting –154, 156 setting , 156, an setting , 106. Pr setting , 146 mus setting , 153. Ne setting , 115, sc setting , 158 and setting , 155 are setting , 115. St setting , 159. Po setting .Leadership: Willingness and/or commitment of political leaders influence health research translation in LMICs [. Evidence-informed health policymaking relies on good leadership [in LMICs , 163. Evadership , 157, leadership , 163, deadership , 71. Lacadership , 81, pooadership , 121, anadership , 139 areadership  will heladership , 160. Laadership , 49, 125Engagement of key stakeholders is a crucial strategy in translation of evidence to policy , 159–166Concerns about the quality of evidence have limited research uptake for policymaking , 156–158Limited research capacity is a major challenge to research uptake for policymaking in LMICs , 162–165The lack of skill that researchers have in research and translation , 146, anResource constraints are a major barrier to uptake of research for policy and practice in LMICs. , 165. UnResearch uptake for health policy and practice requires an enabling platform for research priority setting and dissemination of findings , 163, caResearch infrastructure development , 164, in. In addition, addressing bottle necks related to legal frameworks, policy, and system responses are critical to guide evidence use for policy [Developing a testable evidence uptake framework , 163 thar policy , 139. Enr policy , 139 is r policy , 113. Thr policy , 155, otr policy , 90, 155r policy , 88, 155We have identified several pieces of evidence that forward key recommendations , 160. WeEvidence-to-policy platform: Establishing knowledge translation platforms [latforms , 151, stlatforms , 81, andlatforms , 155 arelatforms , 157, anlatforms , 149 areRecognize context: Understanding political dimension and contexts [contexts , 160 andcontexts , 131 placontexts , addresscontexts , and idecontexts  are alsocontexts .Collaboration and stakeholders engagements: Engagement of stakeholders is a critical step in establishing strong multisectoral collaborations and partnerships and has a key role in improving evidence uptake for policymaking [cymaking , 162. Stcymaking , 112, focymaking , 153, stcymaking , 122, incymaking , 157, ancymaking  are robucymaking , 101, ancymaking , 164. Stcymaking , 158.Advocacy and ownership: Building a sense of ownership through co-production of evidence [evidence –159, 164evidence  are esseevidence , 152, glevidence , 120 andevidence , 91, 120evidence , 76, 87 evidence , 163, stevidence , 159, anevidence , 92, 155evidence .Invest in research: Investments in research infrastructure to strengthen and sustain institutional research capacity [capacity , 158 wilcapacity , mobilizcapacity , 91, 130capacity , supportcapacity , 87, 138capacity , are sugcapacity  and engacapacity , 147 maycapacity , 163 is capacity , 130, stcapacity , and undcapacity . Establicapacity , 157, crcapacity , 158, anEndogenous capacity building: establishing a contextual model for capacity development will help to drive evidence uptake for policymaking [cymaking , 163. Recymaking , 164 andcymaking , 83 playcymaking , 157 is Considerable amount of evidence relevant to translation of evidence into policymaking in LMICs was identified. We found that the common barriers to research uptake are lack of understanding political dimension, low government priority, poor engagement of stakeholders, low investment in research, capacity and resource constraints, lack of ownership and trust in domestic research products, lack of a guiding research uptake framework, and lack of platform to bridge the research uptake gap in LMICs. Mapping to identify the most common forms of research use involves the direct application of research to policymaking and practice , and priWe have identified common barriers limiting research uptake for health policymaking in low resource setting. Enhancing capacity for evidence-informed policy improves priority setting, filtration and amplification of evidence for policy-making and practice . InstituWe identified key recommendations to improve research uptake for health policymaking in LMICs. Establishing evidence translation platforms, improving health policy research literacy and understanding the political dimension and context –174 are Research uptake for health policymaking requires strategies to contextualize and balance global and local health research findings, to understand the complexity of producing high-quality research  and to aStakeholder involvement will improve policy-maker confidence , 66, resThis scoping review has mainly focused on the translation of research evidence into policy. Evidence-informed practice was considered to be a manifestation of uptake; however, the evidence-to-policymaking process is far greater than evidence-informed practice or implementation.This scoping review identified challenges to evidence uptake and possible strategies through which this might be strengthened. A range of studies were identified, including primary studies, trials, and syntheses. Mapping the availability of quality evidence and recognizing challenges to evidence translation will enhance policymaking and practice. Dedicated centers or platforms appear likely to facilitate evidence uptake in real settings. Stakeholders in the research production and translation ecosystem should use pragmatic approaches to assess the political context and priorities, enhance collaboration, invest in research infrastructure development and adapt contextual pathways for evidence uptake. These finding will guide the focus of a Unit for Health Evidence and Policy (UHEP) which is being established to serve as a platform for evidence translation in Ethiopia and beyond. Establishing a platform to bridge the gap between researchers and policy makers is crucial to utilize available evidence for health policymaking and practice.We found substantial evidence on challenges to health research uptake for policymaking and practice in LMICs. Understanding of the national and international context and priorities, involving key stakeholders, resource and establishing a coordinating platform to facilitate capacity building, quality evidence production, communication and a framework for accountability are crucial to facilitate evidence uptake for policymaking. Barriers to poor evidence uptake for health policymaking have to be addressed through investing in research capacity building, partnership and stakeholder participation, co-mobilize resources, building trust and ownership on evidence production. This must be guided by a well-grounded theory of change framework to address barriers in LMICs. A platform for interaction and capacity building of key actors, including politicians, policy makers, academics, public health researchers and medical practitioners is essential to improve insight and establish a network for evidence sharing in LMICs.Additional file1. Completed- Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist.Additional file 2. Literature search strategies.Additional file 3. Data charting.


In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon, (ii) constructing its generalized initial value (GIV), (iii) identifying its analogs based on the GIV, and (iv) assembling typhoon disasters of the analogs. Typhoon track, intensity, and landfall date are introduced in GIV at this early development stage. The pre-assessment results show that the mean threat scores of two important damage levels of LTDs reach 0.48 and 0.55, respectively. Of significance is that most of the damage occurs near the typhoon centers around the time of landfall. These results indicate the promising performance of the model in capturing the main damage characteristics of typhoon disasters, which would help coastal community mitigate damage from destructive typhoons. One example of costly TCs is Typhoon Rammasun (2014) that produced a direct economic loss of over ¥40 billion with more damage over coastal regions in Guangdong, Guangxi, and Hainan provinces3. Super-Typhoon Lekima (2019) was also one of the most serious typhoons to cause damage in China in recent years. In China, 11 provinces were affected, with a total of 14.02 million people affected and direct economic losses of ¥51.53 billion4. Because of the potential for more typhoon hazards under the current global warming trend7, and more rapid economic developments and population growth9, the typhoon-related disaster risk with more economic losses over coastal regions will likely continue to increase in the future12. Thus, it is highly desirable to improve our capability of disaster prevention and mitigation.Typhoons, also referred to as tropical cyclones (TC) herein, are among the deadliest and costliest natural hazards with considerable economic loss every year in East Asia13. After reviewing typhoon disaster pre-assessment models, Wu et al.14 categorized them into statistical, dynamical, and statistical–dynamical models. For the statistical models, many scholars paid attention to establishing mathematical relationships such as regression or exponent functions to pre-assess disaster risks and damage19. Some studies have integrated recent advances in fuzzy mathematics, grey theory and information spread technique in order to assess typhoon disaster risks21. With the rapid development of artificial intelligence, some neural network and support vector machine models have been developed24. This type of models, based on historical disaster information, makes direct connections between typhoon disaster and impact factors. Thus, these models are usually limited to regional applications, data accuracy, and oversimplified physical mechanisms of typhoon disaster.Skillful typhoon disaster pre-assessment, in which the property damage, potential casualties, and economic losses of a typhoon event that may occur can be evaluated, is of extreme importance for disaster prevention and mitigation25 and the Florida Public Hurricane Loss Model (FPHLM) developed by Hamid et al.26, which can be considered as dynamical models, focus more on simulating and analyzing the dynamical processes of typhoon disasters with clear physical mechanisms. However, the complexity of typhoon disasters and the limitation of human’s knowledge on the disaster physical mechanism restrict the construction of typhoon disaster pre-assessment models at each phase, such as the description of the associated hazard scenarios, thereby making relatively large spreads of pre-assessment results.The HAZUS Hurricane Model developed by Vickery et al.29. Currently, the idea is gradually used in the establishment of disaster pre-assessment model and appears to be promising for improving our capability of disaster prevention and mitigation31. These models make disaster pre-assessments directly by selecting historically similar typhoons that satisfy certain parameter threshold criteria for variables with physical characteristics. Nevertheless, we have not seen a well-recognized dynamical-statistical pre-assessment model in the literature.Combining statistical methods to extract information from historical data to improve the forecasting skill of dynamical model forecasts has proven to be effective33 developed the Dynamical-Statistical Analog Ensemble Forecast (DSAEF) theory that is based on relatively solid physical mechanisms for similarity forecast, and they also developed a technique to achieve the forecast, i.e., through the ensemble algorithms. A specific forecast model for a certain factor of prediction based on this theory can be built by taking into account the physical formation characteristics of the factor, combining with corresponding historical data, etc. The theory has been successfully applied to the precipitation forecast for landfalling typhoons, leading to the construction of the Dynamical Statistical Analog Ensemble Forecast Model for landfalling typhoon precipitation (DSAEF_LTP) with many encouraging results35. That is, three large sample-sized numerical experiments for precipitation forecasts of landfalling typhoons occurring in China38 using the most recent version of the model show better performance for ≥ 100 mm accumulated precipitation than the existing objective methods that are based on the current numerical weather prediction (NWP) models. Thus, the major objective of this study is to extend the encouraging results by applying the DSAEF theory to the pre-assessment for landfalling typhoon disasters (LTD) in an attempt to develop a DSAEF_LTD model. This will be done in conjunction with a complete typhoon disaster dataset at the county-level resolution from 1980 to 2018 over coastal China.Recently, Ren et al.The next section introduces the DSAEF_LTD model. "(i)0, which is determined by parameter P1 0, but also, if necessary, the subsequent temporal evolution of the main variables that may impact disaster occurrences in the dynamical and statistical sense. So, the GIV is distinguished from what is usually referred to as the initial value.Constructing the generalized initial value (GIV) that includes not only the initial conditions at T(iii)m top analogs according to the GIV. It consists of three substeps: identifying analogs for each variable, finding GIV’s analogs, and determining the m best analogs. The Track Similarity Area Index (TSAI) 39 is applied to the calculated area between the target typhoon track and a historical typhoon  track in an established similarity region (P2). The threshold m (P7) historical typhoons.Assemble disasters of the analogs. The pre-assessment of potential disasters for the target typhoon is obtained by applying the best ensemble pre-assessment scheme P8 Table  to the cThe DASEF_LTD model is developed in accordance with the DSAEF theory. This model consists of the following four elements:P1).In addition, the third column in Table (i)Ideally, the GIV of DSAEF_LTD model involves typical four dimensions and may contain all possible variables associated with LTDs. It can be meteorological variables that related to heavy precipitation and high wind over land associated with typhoon disasters, e.g., typhoon movement, structure, and some environmental factors such as monsoonal flows, vertical wind shear, and subtropical high. It can also be some factors such as socioeconomic vulnerability, exposure to population and wealth, and disaster prevention and mitigation capability see Fig. . In this44 that contribute to the typhoon disasters can be progressively incorporated into the model.With the gradual introduction of typhoon hazard-related variables, the characteristics of the disaster-bearing bodies and artificial influences(ii)46.The model uses the typhoon track forecasts from operational NWP models to determine the influences of target typhoons, given the revolutionary improvements in the operational track forecasts during the past few decades(iii)The typhoon hazard pre-assessment is achieved by using historically similar physical processes. Although the model itself does not include a specific physical expression of disaster processes, the associated disaster information of the most similar typhoons should be close to that of the target typhoons. This reflects the significance of historical observations in determining target typhoon disasters.Based on the above description, one can see the following three unique characteristics of the DSAEF_LTD model.To apply effectively the DSAEF_LTD model, it is essential to obtain a long historical record of meteorological observations , typhoon disaster information, and operationally available typhoon track forecasts.47.In this study, an integrated multi-source disaster dataset from 505 stations in China’s eight coastal provinces see Fig.  is used,In addition, damage in terms of direct economic losses associated with each typhoon at individual stations was classified into the following five categories: mild, medium, heavy, severe, and extremely severe, which are denoted as C1–C5 in Table https://tcdata.typhoon.org.cn/)49. This dataset includes the center location, maximum surface wind, and minimum sea-level pressure of each typhoon at 6-h intervals.The best track data are obtained from the Shanghai Typhoon Institute of CMA  The same landfalling typhoon sample size from the eastern China and the southern China should be used for both the simulation and pre-assessment experiments in order to balance the influences of different large-scale flows on experiment results. (iii) All landfalling typhoon samples have forecast tracks. (iv) The training sample size should be larger than the independent sample size, and typhoons in the former should be relatively long-lived in order to ensure that the results are universally applicable. Meanwhile, considering the actual records for the period from 2004 to 201347, as a result, 3 at C5, 16 at C4 and 11 at C3 damage category landfalling typhoons from 2004 to 2011 are selected as training samples  The typhoon damage reaches the C3 category and above because the pre-assessment accuracy for relatively heavy damage is of more concern to the publicAs listed in Table The procedures for determining the best pre-assessment scheme are given as follows: obtaining the common schemes from the simulation experiments that are suitable for all the 30 training samples, and then the best common scheme is identified from these schemes by some criteria. Due to the short track of some target typhoons that may limit the selection of similarity regions, or the small sample size of historically similar typhoons in the similarity region, some typhoons cannot take all the pre-assessment schemes. Thus, the common schemes of the 30 training samples are often less than 3,240,000.TS indicates the general pre-assessment ability ranging within ; the closer to 1 is the higher pre-assessment ability; hits denotes the number of stations with correct forecasts whose observed and pre-assessed damage both reach a certain magnitude; misses refers to the number of stations whose observed damage reaches a certain magnitude but the pre-assessed damage does not; and falsealarms is the number of stations whose pre-assessed damage reaches a certain magnitude but the observed damage does not.The threat score (TS) is an important verification metric to evaluate the merits and demerits of the station-based damage pre-assessment ability of the DSAEF_LTD model. It is defined byThe bias score is another indicator to test the station-based damage pre-assessment performance of the model, and to evaluate the tendency of false alarms or misses. It is defined byBS = 1 when the area of false alarms is equal to the area of misses. The value is > 1 (< 1) if the area of false alarms is greater than (less than) the area of misses.It is evident that In this paper, TS scoring criteria are used to evaluate the simulation performance of each disaster distribution. In the simulation experiments, TSs of ≥ C3 and ≥ C2, which reflect the main damage characteristics of a typhoon disaster case and its overall disaster distribution, are selected to evaluate the simulation performance. TS_sum  is used to determine the best common scheme as the pre-assessment scheme.Then, the pre-assessment experiments are conducted by applying the best common scheme to the 21 independent samples obtained during the years of 2012–2015. Like the calculation of TS_sum, BS_sum is obtained as BS of ≥ C3 plus BS of ≥ C2. TS_sum and BS_sum are both used to evaluate the performance of the DSAEF_LTD model in terms of pre-assessment ability.Based on the above discussion, 15,802 common schemes are found from the 30 training samples and then used for simulation experiments. Figure The parameter values of the best common scheme are as follows. The time of 0000 UTC on the first day that typhoon precipitation and wind occurred simultaneously over land is defined as the initial time of typhoon track forecast. A rectangle-shaped region, defined by typhoon locations at the initial time and 6 h before the maximum lead time, is used to determine the tracks of historically similar typhoons. The landfall times of the historically similar typhoons are limited to the months of July to September. In this study, the criterion for typhoon intensities could not be too strict, because the number of historically similar typhoons may be otherwise reduced, making the intensity parameter less effective for pre-assessment. Thus, selecting similar typhoons is less limited by typhoon intensity but more by typhoon track. For the damage of each station among these similar typhoons, the maximum damage value encountered is taken as a better ensemble pre-assessment scheme.During the pre-assessment experiments, three independent samples are found to fail in applying the best scheme due to their short tracks; so, they are excluded from the analysis that follows. Figure Figure To help gain insight into the pre-assessment capability of the DSAEF_LTD model, three typhoons with the highest TS_sum and three typhoons with the lowest TS_sum in the independent samples are compared in Fig. P8 in Table Analysis of the different physical characteristics of the above two groups revealed that typhoon intensities had a greater impact on the pre-assessment results and the stronger the average intensity and maximum intensity of the typhoon during the impacted period, the better performance is the pre-assessment Fig. c. This h52. Despite the presence of these errors, this case analysis indicates that the DSAEF_LTD model could be an important tool for pre-assessing the overall disaster distribution of a typhoon disaster case, especially for the heavy damage occurring in the core region of a typhoon prior to and after landfall.Typhoon Kalmaegi (2014), which has the highest TS_sum value in the pre-assessment experiments, is used to demonstrate how well the observed spatial damage distribution could be pre-assessed. The observed damage distribution, given in Fig. (i)The DSAEF theory can be successfully applied to pre-assessing landfalling typhoon disasters in coastal China. The DSAEF_LTD model consists of the following four elements: obtaining the forecast track of a target landfalling typhoon; constructing the generalized initial value (GIV); identifying analogs based on the GIV, and assemble typhoon disasters of the analogs. In this early stage of model development, typhoon track, landfall date, and intensity are considered into GIV. In addition, in the fourth elements of the model composition, an integrated multi-source disaster dataset from 505 stations in China’s eight coastal provinces is used for the model establishment.(ii)The DSAEF_LTD model is tested with 15,802 common schemes through the simulation experiments. The best common scheme is then identified in accordance with the highest threat score from all the training samples. The best scheme, containing 8 parameters, uses the initial time at 0000 UTC on the first day that typhoon precipitation and maximum surface wind simultaneously occur on land, and the maximum damage value as the damage pre-assessment scheme.(iii)An application of the best common scheme through the pre-assessment experiments shows that threat scores of the heavy damage and above, and the medium damage and above for the independent samples reach 0.48 and 0.55, respectively. This indicates the ability of the DSAEF_LTD model in capturing the main damage characteristics of typhoon disasters, especially for more destructive ones. In addition, the model could reproduce the general distribution of damage, namely, from the core region over coastal regions laterally outward to inland around the landfall of a typhoon.In this paper, we present the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (DSAEF_LTD) in order to improve our capability of disaster prevention and mitigation. Disaster-damage simulation experiments using this model are then conducted with 30 landfalling typhoons occurring during 2004–2011 as training samples, followed by disaster-damage pre-assessment experiments with 18 landfalling typhoons occurring during 2012–2015 as independent samples. Major findings are summarized as follows:56. In addition, considering the complexity of disaster formation, the factors related to environmental vulnerability, economical, agricultural and industrial developments should also be considered. How to express these physical factors objectively is worth exploring. The impact of each factor incorporation on model pre-assessment performance also needs to carry out a large number of sample experiments in the future. Meanwhile, more tests need be conducted in the future to determine whether the existing parameters selected herein are suitable for other regions during the landfall of TCs. Clearly, all these improvements will help communities make an informed decision for mitigating damage and casualties from destructive TCs.Despite the encouraging application of the DSAEF_LTD model, some pre-assessment errors are noted, suggesting that more improvements of the model are much needed. New variables in meteorology, such as landfalling typhoon structures, monsoonal surge, cloud physical properties and other factors should be considered in GIV. Many research indicated that the disaster-related typhoon wind and rainfall characteristics are related to these factors14, so the pre-assessment results were only compared with observations in this study. Meanwhile, the model has shown good performances for the typhoons at C5 damage category, such as Typhoon Haikui (2012) and Typhoon Fitow (2013). However, for other typhoons at C5 category, the simulation or pre-assessment capabilities of the model need to be further tested in the future with the update and expanstion of the typhoon disaster dataset.Nowadays, the pre-assessment results of previous models concentrated more on damage of one particular province or the total damage of a typhoon, no models could give the county-level resolution damage of enough provinces for comparison