Monte Carlo simulations can quantify various types of DNA damage to evaluate the biological effects of ionizing radiation at the nanometer scale. This work presents a study simulating the DNA target response after proton irradiation. A chromatin fiber model and new physics constructors with the ELastic Scattering of Electrons and Positrons by neutral Atoms (ELSEPA) model were used to describe the DNA geometry and the physical stage of water radiolysis with the Geant4-DNA toolkit, respectively. Three key parameters  of scoring DNA damage were studied to investigate the impact on the uncertainties of DNA damage. On the basis of comparison of our results with experimental data and published findings, we were able to accurately predict the yield of various types of DNA damage. Our results indicated that the difference in physics constructor can cause up to 56.4% in the DNA double-strand break (DSB) yields. The DSB yields were quite sensitive to the energy threshold for strand breaks (SB) and the maximum distance to classify the DSB clusters, which were even more than 100 times and four times than the default configurations, respectively. Proton therapy has the benefits of providing a therapeutic dose to tumors with significantly lower dose delivery to normal tissues . This th−15 s) to microseconds (10−6 s). Many studies have focused on DNA single-strand breaks (SSBs) and double-strand breaks (DSBs), the latter of which are the most common lesions caused by irradiation ,4,5. ExpSeveral MCTS codes have been developed for radiobiological research, such as KURBUC ,14,15,16Indeed, the distance between neighboring ionizations in the track of a heavily ionizing particle is in the order of nanometers, which is the same order of magnitude as the size of the many molecules that make up DNA. Hence, a realistic geometrical model of DNA targets is an important aspect in MCTS simulations for DNA damage evaluation. The DNA, nucleosome, and chromatin fiber were originally depicted as cylinders with a specific diameter . SubsequTo accurately evaluate the DNA damage with Monte Carlo methods, investigating the uncertainty of DNA damage simulation is an important scientific problem. A relevant aspect of MCTS simulations is the precision of physical processes at a scale suitable for DNA models. Indeed, creating the currently available cross-sections of the liquid water medium presumed in clinical radiotherapy for charged particle track simulation was an enormous task, and the cross-sections were only recently made widely available to the broader scientific community via the Geant4-DNA toolkit . In GeanIn this work, the Geant4-DNA simulation toolkit was used to investigate the DNA response after proton irradiation. A solenoid chromatin fiber model was implemented in Geant4-DNA for early DNA damage simulation. The ELSEPA model substituted the default elastic scattering model of three recommended physics constructors available in Geant4-DNA, denoted option2 with ELSEPA, option4 with ELSEPA and option6 with ELSEPA. The “option2and4” was also included in Geant4-DNA.We compared them with three recommended Geant4-DNA physics constructors, using dedicated Geant4 examples. The yields of SSBs and DSBs were calculated with these physics constructors through comparison with data from published simulations and experimental measurements. Furthermore, the impact of the physics constructors, the energy threshold model for SSBs and the clustering distance for DSBs on the yield of DSBs and the ratio of SSBs to DSBs induced by monoenergetic protons was studied to estimate the uncertainties of DNA damage calculation.D by various physics constructors from 10 eV to 10 keV at different scales. As shown in the D than those of the other options. Clearly, the values obtained for other options were as close to each other as their inelastic cross-sections; notably, those for option2and4 and option4 were nearly identical. For the different scales of scoring volume , the DSB yields, the SSB yields and the ratio of DSB to SSB induced by monoenergetic protons with other published results in Dependencies of the ratio of DSB yields to SSB yields and DSB yields on the physics constructors are shown in The influence of the ET model for the breaks in D. It was found that from D than the other options, owing to the larger inelastic cross-sections of the CPA100 model. Overall, due to the major contribution of elastic scattering, MFP, track length, and yD are all affected by elastic scattering at energies below 100 eV.This study aims to calculate the proton-induced DNA damage and understand how the parameters of scoring the DNA damage model in MCTS simulation in a physical stage affect the DNA SSB and DSB yields. In the physical stage of water radiolysis, most of the DNA damage is caused by secondary electrons. We first verified the establishment of the extended physics constructors and studied its influence on the fundamental MCTS simulation quantities and the microdosimetry spectra y−6, 0.015, and 0.012 bp/nm3, respectively. Thus, the DSB yields simulated in this work match well with the data measured by Frankenberg et al.,  and impinged with random directions.Chromatin fiber had a density of 4.2 nucleosomes per 11 nm, which corresponded to a loose fiber. Because liquid water makes up more than 70% of the biological medium in the human body, the total volume material was G4_WATER with a density of 1 g/cmThe energy deposition of primary and secondary particles, primarily the latter, causes direct DNA damage. Geant4-DNA provides three sets of alternative physics model for the simulation of electron interactions with liquid water, which have been described in detail in the previous publications ,53,54. AOption4 used models based on the Emfietzouglou parameterization of the dielectric response function of liquid water to provide larger and more realistic excitation cross-section data than data in the gas phase as well as more accurate low-energy corrections, particularly for exchange and correlation in electron–electron interactions, than option2. Option6 is a complete port of the well-known CPA100 track structure code, which employs the relativistic Binary-Encounter-Bethe technique for ionization modeling and the Dingfelder model of liquid water dielectric response for excitation. Option4 employs an improved screened Rutherford model with a screening factor derived from vapor water data, whereas option6 employs the traditional Independent Atom Method. In general, option4 has a more accurate W-value (the mean energy required to generate an ion pair) and dose point kernels.The ELSEPA model developed by Shin et al., to improve the accuracy of electron elastic scattering in Geant4-DNA, which used the Dirac partial wave approach including relativistic corrections and the optical parameters included in the correlation–polarization and in the absorption potentials . In thisAs shown in As explained by Emfietzoglou et al. , the “mfIn the “range” example, three spectra were calculated: “track length”, which represented the path length of particle trajectories; “penetration,” which was the distance between the initial and final states; and “projected range”, which represented the projection along the incident direction. To verify the simulations, the track length and the penetration were estimated with various options listed in Fy defined as:y. The linear energy y is defined as the energy transfer in a single event in the target of the mean chord length: The “microyz” example  simulatey theory  if the tDy, was calculated as:Another type is the dose-mean lineal energy, 5 to minimize the simulation time for energy ≥ 5 keV and 106 for other energy. The targets simulated were spheres with diameters of 2.3 nm, 10 nm and 30 nm, representing the diameters of the B-DNA helix, nucleosome, and chromatin fiber, respectively, according to homogeneity. Moreover, the simulation parameters of previous study [The incident particle in this study was an electron with energies of 50 eV, 100 eV, 200 eV, 300 eV, 400 eV, 500 eV, 700 eV, 1 keV, 3 keV, 5 keV, 7 keV and 10 keV, with option4 limited to 10 keV. The number of incident particles was set to 10us study  were appWe examined the physical damage parameters only, not chemical damage, to see how this model performed when the physical damage parameters were changed. In the physical stage of water radiolysis, radiation interacted with DNA molecules and a medium (water). Direct DNA damage was induced from physical interactions between primary and secondary particles within the DNA target. To connect energy deposition close to DNA molecules with DNA damage, mechanistic DNA simulations relied on a DNA damage model. In this work, a single energy threshold (ET) model with 8.22 eV, 12.6 eV, 17.5 eV or 21.25 eV and a linear proportional model between 5 and 37.5 eV were used to predict the damage. The minimum excitation energy of water molecules was 8.22 eV; 12.6 eV was the first ionization energy of water molecules; and 17.5 eV was the energy threshold in KURBUC  accordinThe proportional model, which was also used in PARTRAC  and TOPAWe also investigated the impact of different physics models on physically induced DNA damage, using three recommended physics constructors listed in The DNA damage classification for the complexity of SSBs and DSBs is shown in DNA damage by 0.5–100 MeV monoenergetic protons irradiation was studied by simulating the yield of DSB and SSB lesions in a chromatin fiber model with the Geant4-DNA toolkit. The default physics constructors in Geant4-DNA including the ELSEPA model and the “option2and4” physics list have been built in our work and were verified with respect to reference data. Our results for the yields of DSBs and SSBs and the ratio of DSBs to SSBs were consistent with other simulations. On the basis of calculated sensitivities, we further estimated the uncertainties of calculated DSB yields and ratio of DSB to SSB due to the uncertainties in the physics constructors, the ET damage model and the clustering distance in the physical stage.The differences in physics constructors have less influence on the SSB yield and more influence on the DSB yields. Our simulations show that G4EmDNAPhysics_option6 results in the highest DSB yields, whereas the G4EmDNAPhysics_option2 has the lowest DSB yields. The elastic scattering model has little effect on SSB yields, whereas the recommended physics constructors in Geant4-DNA that cause less diffusive distribution result in larger DSB yields due to more concentrated deposited energy.Differences in the ET damage model can largely affect the DSB yields and the ratio of DSBs to SSBs. For the constant ET model, the DSB yields and the ratio of DSBs to SSBs can decrease up to many times with the ET value from 8.22 to 17.5 eV, whereas the little change for that from 17.5 to 21.25 eV was found in our simulations. The DNA damage for the linear proportional model was consistent with the constant ET model with values between 12.6 and 17.5 eV. Differences in the clustering distance can cause differences up to five times in predicted DSB yields, especially for the clustering algorithm.However, the pre-chemical and chemical stage and the uncertainly due to the parameters in these stages, such as the reaction radius to search for damage and the temporal length of the chemical stage, were not considered in this work. In addition, the DNA geometry for the human fibroblast was not constructed, and the direct and indirect damage were not distinguished in our simulations. Unfortunately, because of the limitation of the energy for the proton in the Geant4-DNA toolkit (only up to 100 MeV), the energy of proton therapy range from 100 to 230 MeV cannot be simulated. The effect of histone scavenging and base damage will also be investigated in the future.


During 2021–2022 many countries in the European region of the World Health Organization (WHO) adopted mandatory and incentive-based vaccination measures to stimulate immunization against COVID-19. The measures ranged from positive incentive-based programs  to introducing COVID-19 certificates and enforcing the universal mandatory vaccination with fines. We assessed the effect of such interventions on COVID-19 vaccine uptake in the population of eight countries within the region. An interrupted time series (ITS) analysis was performed using an autoregressive integrated moving average (ARIMA) approach to account for autocorrelation and seasonality. The results showed the immediate positive impact of vaccination incentives on vaccine uptake in most cases, with the highest impact being cash incentives for the population (1197 per million population per day). Discount incentives did not show any significant impact. The introduction of COVID-19 certificates was associated with a significant immediate or gradual increase in daily administered vaccine doses in all the countries included in the study, up to 117,617 doses gained per million per month. The effect of mandatory vaccination for all or some groups of the population varied from a continuous decrease in daily administered doses (332 per million capita per day), no significant effect, or a delayed or temporary increase (1489 per million capita per day). The COVID-19 pandemic showed that the significance of the topic of vaccines and vaccination policies extends beyond the public health domain . The choAs the pandemic persists, vaccination policies will continue to play an important part in mitigating the potential waves of COVID-19. Therefore, more evidence is needed on the effectiveness and impact of past and current vaccination policies in addition to updated vaccines . Not onlThere is a lack of comprehensive and systematic data regarding the effectiveness of mandatory and incentive-based vaccination schemes; even when available, data are often not adequately utilized or examined. During the COVID-19 pandemic, some countries adopted unprecedented measures to increase vaccine uptake, such as lockdowns and limited access to businesses for the unvaccinated. Despite some studies that explored the impact of the implementation of country-level measures during the 2021 time period, such as the introduction of COVID-19 vaccine certificates, more evidence is needed to understand the impact of the whole range of interventions aimed at increasing vaccine uptake . Focus dDuring 2021–2022, many countries in the European region of the WHO, which comprises 53 countries, adopted mandatory and incentive-based vaccination measures to stimulate the immunization against COVID-19. The measures introduced in the countries of the region range from positive incentive-based approaches  to introducing COVID-19 certificates or enforcing the universal mandatory vaccination with fines.This article addresses one of the most pressing social challenges of mandatory vaccination. The aim of the study is to assess the effect of mandatory and incentive-based vaccination measures on vaccine uptake for COVID-19 in the population of the countries within the WHO European region. The study focuses on eight countries  that introduced one or more of such measures at a specific point during the 2021/2022 time period, and where data were available pre- and post-intervention. The included countries have varied levels of COVID-19 vaccine acceptance, from high  to low (Poland and Russia) ,14,15.The interventions introduced between June 2021 and January 2022 in eight countries of the WHO European region  were analyzed. The list of the analyzed policy interventions in each country is presented in Data on daily administered COVID-19 vaccine doses were sourced from Our World in Data, which utilized governmental reports to inform their database . AdditioThe study focuses on the population of eight countries of the WHO European region that introduced one or more of mandatory or incentive-based measures at a specific point in time, and where sufficient data were available before and after the introduction of the measures and on exact dates of introduction of the interventions, necessary for an ITS analysis with daily data. The rationale for our choice was to include countries that represent different levels of the COVID-19 vaccine acceptance. The included countries had the following levels of acceptance of the COVID-19 vaccine: high , medium , and low  ,14,15. WThe primary outcome of this analysis was the change in the number of daily administered doses following the interventions. Outcomes could be broken down into categories. An instantaneous impact is defined as an impact that occurs in the same period in which the policy is introduced, and the impact in the days following the introduction of the policy, that is, the dynamic effect of the impact. We also report the change in the number of administered vaccine doses per million capita, to facilitate the comparison between the interventions and countries. Through conducting a counterfactual analysis, we report the values of daily administered doses in the absence of interventions, and number of doses gained (or missed) due to the implementation of interventions. An Interrupted Time Series, a quasi-experimental method, was used to carry out this analysis. ITS analyses have increasingly been applied to evaluate the impact of large-scale health interventions. The choice of this method was based on its suitability for the dataset, which satisfied the following conditions: clear differentiation of the pre-intervention period and the post-intervention period and sufficient number of datapoints. In their ITS regression tutorial Bernal et al. argue that ITS works best with short-term outcomes that are expected to change either relatively quickly after an intervention is implemented or after a clearly defined lag . AccordiFurthermore, we conducted a counterfactual analysis to obtain the values predicted by the ARIMA model in absence of the intervention compared with the observed values. To do this, we built additional ARIMA models for the periods up to the time before the intervention, with the forecasts representing what would happen if no intervention had been put into place.To develop the models, the general to particular approach was applied. This consisted of starting from a dynamic model with a large lag structure , and then eliminating the non-significant lags until a nested model with all significant variables was identified. The intervention variables were entered as predictors into the model, and if statistically significant, this induced a positive or negative change in the intercept of the model.Stationarity was tested by Dickey–Fuller test, and autocorrelation by the Ljung–Box test. Autocorrelation, nonstationarity, and seasonality were handled through differencing in the ARIMA model. To check the stability of the models, the calculation of the inverse values of the roots of the autoregressive polynomial was performed. To conduct the statistical analysis, Eviews  and SPSS software  were utilized. The data were analysed by country and type of implemented measure.The sample consisted of 161 observations for the period 1 September 2021–8 February 2022. The mean number of daily doses in the sample was 44,984, while 50 percent of the observations were below 32,736 doses. The maximum number of doses was 112,599, and the minimum number of doses was 12,932.The purpose of the ARIMA model was to determine the impact of the following intervention variables: announcement of the employee vaccine mandate (am1), enforcement of the employee vaccine mandate (m1force), introduction of lockdown for the unvaccinated (m2) and announcement of the universal vaccine mandate with fines (am3). p-value < 0.000). The announcement of the universal vaccine mandate (am3) acted as a leading indicator, that is, it impacted doses administered one day after the announcement. This announcement on 19 November 2021 had a negative impact on doses and was associated with a reduction from on intervention period to the next by 3010 doses (95% CI: −3592–2428). The introduction of mandatory vaccination for the employees (am1) did not produce an immediate effect but likely produced an anticipatory and/or delayed effect. This is in line with the data on vaccine coverage among different age groups (17). The observed effect can also be linked to the data reporting issues for Austria. In order to produce a complete series of daily figures and account for missing data Our World in Data, the data source utilized, used a rolling 7-day average window, possibly hiding some of the significant effects of the assessed interventions [The ARIMA model shows that the only intervention variable affecting the doses variable was am3, the universal vaccine mandate with fines, which was statistically significant at any significance level , a 5.52% drop and a 3.98% drop in doses, respectively. These dummies correct for atypical behaviors in the dose variable. The October increase is associated with the entry into force of the employee vaccine mandate on 1 November 2021, whereas the December outliers are related to the holiday season. The sample included 273 observations covering the period 1 June 2021–28 February 2022. The mean number of daily doses was 53,884, with 50 percent of the observations below 45,991 doses. The maximum number of doses was 109,105 and the minimum number of doses was 18,105.The purpose of the ARIMA model was to determine the impact of the following intervention variables: introduction of “freedom pass” (m1force), introduction of financial incentives for pharmacists and doctors (m2), introduction of COVID-19 certificates (m3), entry into force of the vaccine mandate for adults aged 60 and older (m4force), announcement of entry into force of “freedom pass” (am1), and announcement of entry into force of the vaccine mandate for adults aged 60 and older (am4). The intervention variables m1force and am4 were not significant. According to the estimated model, the announcement of the entry into force of the “freedom pass” (am1) on 28 June 2021, had an immediate and delayed impact. Meaning in the current period it increased the number of interperiod doses by 12,354 ; however, one period after the announcement it indicated a drop of 14,715  doses period to period. Further, the announcement of the entry into force of the “freedom pass” (am1) led to a drop of 2361 doses interperiod. This is in line with data on vaccine coverage in the age group targeted by the introduction of the “freedom pass” . RegardiThe sample of 181 observations covered the period 1 September 2021–28 February 2022. The average number of daily doses in the sample was 312,657, while 50 percent of the observations were under the daily dose level of 248,011. The maximum number of doses was 665,777, while the minimum number was 114,725.The main reason for estimating the model was to determine the impact of intervention variables, specifically, the entry into force of the “Green pass” mandate for employees (m1) and the entry into force of the vaccine mandate for adults aged 50 and older (m2). According to the estimated model, only the vaccine mandate for adults aged 50 and older (m2) had a significant impact on the number of administered vaccine doses. This is in line with the data on vaccine coverage among different age groups (17). The model shows that m2 impacted with lags. In fact, once m2 came into effect on 5 January 2022, the impact on the number of doses took place from the following period, inducing an interperiod drop of 43,357  doses, to two periods beyond the effective date where there was a change in the trend. This change resulted in an increase of 89,728  doses from period to period. The direction of the trend was maintained for one more period, but with a smaller interperiod growth of 17,919  doses. Four periods after the entry into force of m2, the measure’s previous trend was reversed, implying an interperiod drop of 76,621  doses. Further, the impact of m2 on daily dose-behavior was negative, indicating an interperiod decrease of 12,330 doses on the fifth period. A substantial increase in the number of administered doses in the period between the end of November and Christmas holidays can be attributed to the mass administration of the third dose of the vaccine, as well as the start of the vaccination of 5–11-year-old children ,26.Several published studies have analyzed COVID-19 vaccination mandates in Italy ,27,28. HThe sample of 182 observations spanned the period 2 June 2021–30 November 2021. The mean number of daily doses was 32,630, and the number of doses in which 50 percent of the observations fell below was 35,443. The maximum number of doses was 69,114, while the minimum was 4762.As the attempted ARIMA models did not appropriately fit the data, we estimated an autoregressive distributed lagged model, where the dependent variable entered as a significant lagged explanatory variable until period 7. It was necessary to introduce four dummy variables during the sample period  to pick up outlier effects. These dummy variables were associated with a decrease in doses of 7.11%, 3.55%, 9.01%, and 12.05%, respectively. The outliers are related to summer holidays and COVID-19 vaccination calendar in Norway. The vaccination calendar is important to note during the period of our sample as it coincides with the earlier stages of the mass vaccination campaign in Norway, where the numbers of daily doses were dependent on vaccination appointments offered to people of certain age groups .The purpose of the ARDL model was to determine the impact of a single intervention variable, which was entry into force of the COVID-19 certificates (m1). The entry into force of COVID-19 certificates was on 20 June 2021 and remained in force until 25 September 2021. According to the estimated ARDL model, once the measure came into effect it had a positive impact after four days, with an approximate increase of 1308 doses from one period to the next, and a negative impact of 1399 doses on the fifth day after coming into effect. Further, the effect is negative, with a drop from one period to another of 90 doses (1308.2 + (−1398.64)). This period overlaps with the availability of vaccinations for the 45–54 age group, according to the vaccination calendar. From August 2021 COVID-19 vaccine became available for everybody over 18 years old in Norway, and the summer holidays in ended the same month, which is reflected in the spike of the vaccine uptake curve . TherefoThe sample comprised 122 observations for the period 1 June 2021–30 September 2021. An average number of 145,891 daily doses were observed in the dataset, while 50 percent of the data fell below 99,022 daily doses. The strong discrepancy between the mean and median suggests the existence of outliers in this dataset. The highest dose level observed was 341,329, while the lowest dose level was 19,980.An ARIMA GARCH model was developed to determine the impact of the intervention variable “introduction of national lottery and municipality competitions” (m1). When the measure came into force on 1 July 2021, it had a positive impact with an interperiod increase of 25,196 doses. One period after the measure’s entry into force, the trend shifted and resulted in a decrease of 24,368 doses from period to period. Further, the measure produces an interperiod increase of 827 doses ).It was necessary to introduce dummy variables on the dates 24 June 2021, 26 June 2021, 3 July 2021 and 11 July 2021 to pick up irregularities in the dependent variable. These irregularities were a drop of 12.47%, an increase of 8.46%, a fall of 10.65% and an increase of 5.61%, respectively. The variations can be explained by the vaccination schedule and logistical reasons, such as closure of vaccination points .The intervention had an immediate temporary positive effect on the number of daily administered vaccine doses. To our knowledge, there are no published studies evaluating this initiative specific to Poland; however, there are studies that examined the effect of incentives on vaccine coverage in other countries such as the USA. Our findings are in line with the conclusion derived by these researchers, reporting an increase in COVID-19 vaccinated rates after the implementation of conditional cash lotteries in Ohio . DespiteThe sample consisted of 255 observations for the period 1 June 2021–10 February 2022. The average number of daily doses was 502,514, with a median of 484,198 daily doses. The maximum number of doses was 1,020,075 and the minimum number of doses was 66,419.The purpose of the ARIMA model was to determine the impact of intervention variables, namely: introduction of employee vaccine mandates (m1), launch of the lottery for the vaccinated (m2), announcement of the introduction of COVID-19 certificates (am3) and entry into force of COVID-19 certificates (m3force). According to the estimated ARIMA model, the intervention associated with the entry into force of COVID-19 certificates (m3force) was not significant. The entry into force of employee vaccine mandate (m1) on 1 July 2021 had an immediate but negative impact on the number of doses; stimulating a drop from one period to another by 43,429 doses. On the other hand, the launch of the lottery program (m2) in the period 1 September 2021 had an immediate positive impact, increasing the number of doses interperiod by 9766 doses. The announcement of the entry into force of COVID-19 certificates (am3) on 22 October 2021 had an immediate and lagged impact on the behavior of doses. The immediate impact was negative, with a fall from one period to another in the order of 42,718 doses. In the period after the announcement, the impact was positive with an interperiod increase of 43,775 doses. Further, am3 implied an interperiod increase of 1056 doses.Even though the analysis showed an immediate negative effect of the introduction of the employee vaccine mandate, the intervention produced a positive delayed effect. Russia’s vaccination curve reflects the regulation implemented in many regions of the country, according to which the employers must vaccinate with the first dose 60% of the employees by the middle of July 2021 and with the second dose by the middle of August 2021 ,34. ThisAn increase in the number of administered doses in the middle of October and the beginning of November 2021 coincides with the introduction of mandatory vaccination for adults aged 60 and older in a subset of regions throughout the country ,37. FinaFinally, the increase in the vaccination in December 2021 fell at the time of when many Russians were preparing for the two-week long winter holiday at the end of December. Many travelled during that period, and were required to have a COVID-19 certificate to access resorts and other facilities within the country. As a result, this increase can be considered a delayed effect of the introduction of COVID-19 certificates .The sample consisted of 163 observations for the period 1 September 2021–10 February 2022. There were no missing values during this time period. The average number of daily doses was 157,899, and the number of doses below which 50 percent of the observations were found was 146,011. The minimum number of doses observed was 2724, while the maximum number of doses was 670,109.The main purpose in estimating the ARIMA model was to determine the impact of the predictor variables: announcement of the introduction of COVID-19 certificates (m1) and entry into force of COVID-19 certificates (m2). Regarding the impact of the variable m1, on the date when the announcement of the future entry into force of the regulation was made in most of the regions that applied COVID-19 certificates (22 November 2021), the impact was positive, producing an increase of about 24,902 doses. However, in the three days following that initial increase, the positive effect vanishes. The first day resulted in a decrease of 19,015, followed by a decrease in the order of 32,626 doses three days after the initial spike. In the three days following the announcement, and positive spike, there was a cumulative decrease in the number of doses of 51,641 on average. Enforcement of the COVID-19 certificates (m2) had a negative impact on the date the regulation came into effect, inducing a decrease of 61,287 doses on average. However, in the three days following the introduction the impact of the measure became positive. An increase of 49,711, 58,830, and 103,764 doses were seen on the three days following its introduction, respectively. This can also be interpreted as a cumulative increase of about 212,306 doses over this three-day period. Estimates show that the positive impact of the regulation’s entry into force was greater than its announcement; however, the positive impact of the implemented regulation acted as a leading indicator. Two additive outliers were found on 12 October 2021 and 26 December 2021 that negatively impacted the dose variable, causing decreases of 16,295 and 14,139 doses, respectively. These outliers coincide with holidays in Spain. A transitory outlier was also identified on 16 December 2021 causing a positive impact, increasing the number of doses by 41,090. This increase corresponds to the start of the vaccination of 5–11 year old children; the estimated decay factor was 0.445 .The positive effect of the introduction of COVID-19 certificates on the number of administered doses in Spain is evident. The regulation was introduced in the context of the preparation for Christmas holidays and the spread of Omicron variant. Furthermore, to facilitate the vaccination, the authorities set up additional vaccination points in this period . COVID-1The sample consisted of 92 observations for the period 1 July 2021–30 September 2021. The mean number of daily doses in the sample was 180,283, with 50 percent of the observations falling below 200,182. The maximum number of doses in the sample was 327,284, while the minimum number was 63,283 doses.An ARIMA ARCH model was developed to determine the impact of the intervention variable “introduction of discounts and vouchers for the vaccinated” (m1) on the number of doses administered. p = 0.1345), which is higher than the standard significance levels of 1%, 5% or 10%. Regardless, the effect on the number of doses is negative, inducing a fall of 2558 doses period to period.According to the ARIMA ARCH model, the intervention variable impacts the number of doses one period after its entry into force on 1 August 2021. However, this impact was not statistically significant . Discounts incentives did not show any significant impact. The introduction of COVID-19 certificates was associated with a significant immediate (Spain) or gradual increase (Greece) in daily administered vaccine doses in all the countries included in the study, up to 117,617 doses gained per million per month seen in Russia. The effect of mandatory vaccination for all or some groups of the population varied from a continuous decrease in daily administered doses (Austria—332 per million capita per day), no significant effect, delayed or temporary increase . Our study provides new insights on the effectiveness of vaccine interventions that had not previously been assessed. The impact of both incentive and mandate interventions are of great interest to various stakeholders including researchers, policy makers, and the general population. The study has several limitations: it does not account for changes in the required vaccine doses over time, differences in the countries’ information campaigns aimed at increasing the vaccine uptake and differences in the degree of ethical concerns regarding mandatory vaccination, which was beyond the scope of this study. It is important to note that these findings should be applied with caution, especially in policy making. Interventions producing a significant effect on the vaccine uptake may come at a cost, both direct financial and indirect. Further research is needed in many additional areas and disciplines to have a complete understanding of the impact of mandates, other than its direct impact on doses. This includes evaluating the costs of implementation of vaccine incentives and mandates, assessing individuals’ willingness to trust authorities or vaccines, as well as the effect on civil liberties and collateral effects such as forging the evidence of immunization status. The COVID-19 pandemic has highlighted many inadequacies in public health response, but has also been a demonstration of ingenuity. It is obvious that high level of vaccine hesitancy is reflected in lower vaccine uptake. At the same time, we did not find clear difference in the effectiveness of the interventions among the countries with different levels of the vaccine acceptance. Yet, vaccination policies have varied impact depending on context and setting. This in itself is an important outcome because it gives countries the tools to learn from their own policies, as well as the policies of like nations. Moving forward, long-term programs such as scientific outreach activities should be ongoing to provide people with objective and transparent information and education regarding vaccinations in order to improve the outcomes of emergency public health initiatives in the future.


The comparative study performed for the transport of 4–nitrophenol (NP) showed that the module based on spheres (Ms) was more performant than the one with phase dispersion under the form of droplets (Md). The sphere material influenced the transport of 4–nitrophenol (NP). The transport module with glass spheres (Gl) was superior to the one using copper spheres (Cu), but especially with the one with steel spheres (St). In all the studied cases, the sphere-based module (Ms) had superior transport results compared to the module with droplets (Md). The extraction efficiency (EE) and the transport of 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP), studied in the module with glass spheres, showed that the two phenolic derivatives could be separated by adjusting the pH of the source phase. At the acidic pH of the source phase (pH = 2), the two derivatives were extracted with good results (EE > 90%), while for pH values ranging from 4 to 6, they could be separated, with DCP having doubled separation efficiency compared to DNP. At a pH of 8 in the source phase, the extraction efficiency halved for both phenolic compounds.Regardless of the type of liquid membrane (LM) (Bulk Liquid Membranes (BLM), Supported Liquid Membranes (SLM) or Emulsion Liquid Membranes (ELM)), transport and separation of chemical species are conditioned by the operational (OP) and constructive design parameters (DP) of the permeation module. In the present study, the pH of the aqueous source phase (SP) and receiving phase (RP) of the proposed membrane system were selected as operational parameters. The mode of contacting the phases was chosen as the convective transport generator. The experiments used BLM-type membranes with spheres in free rotation as film contact elements of the aqueous phases with the membrane. The target chemical species were selected in the range of phenol derivatives (PD), 4–nitrophenol (NP), 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP), all being substances of technical-economic and environmental interest. Due to their acid character, they allow the evaluation of the influence of pH as a determining operational parameter of transport and separation through a membrane consisting of  The solvent containing the chemical species of interest is introduced in a stripping apparatus, where it is contacted with a receiving aqueous phase  in order to recover and concentrate the target chemical species ,10. HoweThe development of separation, concentration and purification through liquid membranes did not exclude, over time, any of the presented operating variants , as eachIf we focus on BLM, the technical problems to be solved are: the large volume of solvent used (V), the small mass transfer area (σ), the almost unit ratio between the volume of the source phase, the volume of the receiving phase (r) and the volume of the membrane organic solvent (OS or M) and therefore, implicitly, the long operating time (t) ,19,20.Bulk liquid membranes (BLM) are constituted as a stage of laboratory study of the transfer and/or separation of some chemical species of interest. BLMs allow, in a relatively short time, the determination of the individual competitive influence of the operating parameters: pH, concentration of chemical species, ionic strength, concentration of some complexes or carriers, working temperature and the nature of the membrane solvent ,22,23,246–C12 [Recently, a BLM system with dispersed phases has been studied, in which the aqueous phases of the separation system disperse in/through the membranes. The membrane is a nanodispersed system of magnetic nanoparticles that has the role of ensuring both convection and transport for ionic chemical species in membranes based on saturated alcohols C6–C12 ,28,29,30The BLM system with dispersed phases is close to the performances of liquid membranes on hollow fiber support or emulsion-type liquid membranes, but has several limitations that restrict its applicability: stability of the membrane nanodispersion, control of the size of droplets in recirculating aqueous phases, losses of membrane material (solvent or nanoparticles) .n–octanol or n–decanol (n–AlcM).In the present paper, a BLM system is approached, starting from the design of the one presented above, in which the recirculation of aqueous phases is performed by flowing on spheres in free rotation. To test the new design of the permeation module, three phenolic derivatives of technical interest and environmental protection were chosen: 4–nitrophenol (NP), 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP). All of these allow the evaluation of pH as an operational parameter for transport and separation through a membrane consisting of n–octanol, n–decanol, 4–nitrophenol (or p–nitrophenol), 2,4–dichlorophenol and 2,4–dinitrophenol : hydrochloric acid, sodium chloride, sodium hydroxide, rophenol .® Direct 8 RO Water Purification System, Merck, Darmstadt, Germany).The purified water characterized by 18.2 μS/cm conductivity was obtained with an RO Millipore system , in the present experiments, spheres in free rotation were interposed in the direction of the drops towards the membrane  of 30 mm, and the receiving phase distribution sphere had a diameter (D) of 50 mm.The four source phase distribution spheres had a diameter  and sodium hydroxide (for basic pH).The ionic strength of the source phase was adjusted by the addition of sodium chloride in a gravimetric concentration of 1–5%.M being the permeate mass (g or mol), S being the effective surface of the membrane (m2) and Δt the time interval (s).The flows of the phenol derivatives from the source phase were determined at specific time intervals, using Equation (1) ,33:(1)J=EE %) for the phenol derivatives was calculated as follows [fc being the final concentration of the solute (phenol derivatives) and c0 the initial concentration of the solute (phenol derivatives).The extraction efficiency  ,35, as iThe analysis of the content of the studied phenolic compounds was performed at the wavelength characteristic of each form of phenolic derivatives (phenol or phenolate)  using CaFurthermore, the UV–Vis validation analysis of the phenol derivative solutions was performed on a dual-beam UV equipment–Varian Cary 50  at a resolution of 1 nm, spectral bandwidth of 1.5 nm and a scan rate of 300 nm/s. The UV–Vis spectra of the samples were recorded for a wavelength ranging from 200 to 800 nm, at room temperature, using 10 mm quartz cells.All determinations were performed on the same day, for each scheduled experiment, by two experienced analysts from different laboratories, based on 3 specimens taken for each sample, and to ensure the quality of chemical measurements, the specific EURACHEM guide was followed. .The phenolic derivative content of the membrane was determined on the basis of the mass balance of the three phases of the membrane system .Determination and monitoring of pH were achieved using a conductance cell or combined selective electrode  and a multi-parameter system  .The surface characteristics of the spheres were determined with a scanning electron microscope (SEM) equipped with a probe for energy dispersive spectroscopy analysis (EDX). Hitachi S4500 system  was used .Contact angle measurements for the considered sphere materials (with distilled water or phenol derivative solution)  were carThe molecules of the organic substances were transported through an organic liquid membrane by means of a series of solubilization–diffusion equilibria that take place at the two interfaces of the membrane. In the case studied in this paper, the phenolic derivatives considered were organic compounds with a weak acidic character . In the Phenolic derivatives were distributed between the source phase and the membrane according to the equilibrium in Equation (4):and (7)) :(ArOH)SPThese equilibria could be used, by adjusting the pH of the aqueous phases, for the separation of the three phenolic derivatives considered . Thus, tc being the degree of formation of species cA(n−c)−H, and HnAC the total concentration of the phenolic derivative in aqueous solution.The degree of formation of one of the chemical species can be defined by a general relation of the form :(8)αc=[HC, as a result of equilibrium (9) in solution, we have the chemical species ArOH (phenol) and ArO– (phenolate) [For the phenolic acid derivative, ArOH, of total concentration enolate) :ArOH + HThe degree of formation of these chemical species is :(11)α1=[Using the mass balance equation of the chemical species present in solution , for theTheoretical considerations and previous experimental results ,49,50 han–pure alkyl alcohols (n–AlcM) [The transport experiments were performed in the installation presented in (n–AlcM) .p–nitrophenol (approximately 2 g/L) had a pH of 2 or 5. The flow rate of the source phase was 80 mL/min (20 mL/min for each nozzle), and the flow rate of the receiving phase was 20 mL/min. The results obtained . Thus, in these experiments , as well as by interposing the spheres in the path of the droplets through the membrane (Ms)  for a 2 g/L ane (Ms) .p–nitrophenol in the source phase for the n–octanol membrane  than for the module using droplet dispersion (Md), for –decanol b, but es–octanol a. It is –octanol . This ob–octanol .Because the morphological appearance of the surfaces was slightly different (SEM), and the elemental analysis (EDX) showed that on each surface, in addition to the specific elements, oxygen was identified a–c, it wThe contact angles of pure water with the sphere material showed that all three types were hydrophilic, with a contact angle (θ) of less than 90°. The most hydrophilic sphere was the glass one, with the smallest contact angle and the highest oxygen content (oxides). At the opposite pole was the steel, which had the largest contact angle.p–nitrophenol was more visible in the case of the n–decanol membrane  and surface (dS), we can write Equation (14):dd) = 4 ± 2 mm [Thus, if we refer to the surface offered by the drip module, for a drop of diameter  and (17):At the same time, it is possible to calculate the surface offered by the transformation of the volume of a drop (15), into a surface film of imposed thickness, on the spheres considered with diameters However, the calculation of the effective mass transfer area, according to Equations (1) and (14)–(17), is affected by the hypothesis of a film of the aqueous phase, of imposed thickness and a degree of coverage of the sphere is difficult to determine experimentally.The apparent flows of the aromatic derivatives considered in the studied membrane system are presented in Comparative data show that drop-by-drop and free-rotating sphere systems have flows 10 to 100 times higher than previously obtained data for bulk or supported liquid membranes . Becausep–nitrophenol in the source phase can be achieved by adding salts [p–nitrophenol extraction is presented in The reduction of the membrane solvent losses but also the decrease of the solubility of ng salts . In ordeThe choice of less aggressive pH conditions was imposed by the need to reduce the consumption of hydrochloric acid and sodium hydroxide, but also to be able to observe the influence of ionic strength, because at more aggressive pH values (pH = 1 for source phase and pH = 13 for receiving phase) extraction efficiency was nearly quantitative.The values obtained in 2,4–dinitrophenol (DNP) and 1 g/L 2,4–dichlorophenol (DCP) are phenolic derivatives of high toxicity , relativThe transport experiments for a duration of 120 min, to evaluate the influence of the pH of the source phase, were performed in the installation according to n–octanol.The volume of the phases was set at 5000 mL for the source phase, 500 mL for the receiving phase of pH = 13 and 500 mL for the membrane based on In order for the source aqueous solutions to contain 2,4–dinitrophenol (DNP) and 1g/L 2,4–dichlorophenol (DCP) in a molecular  form favorable to extraction, from Equations (9)–(19), it follows that a strong acid pH must be used.The experimental results  obtaineda 2,4–dinitrophenol (DNP), led to a half-attenuation of the decrease in the concentration of this compound  (At a pH = 8 of the source phase close to pKol (DCP) , the redol (DCP) d.The efficiency of the extraction of phenolic derivatives in the installation with spheres in free rotation is strongly influenced by the pH of the source phase see .Membrane transport can be amplified by permeation module design parameters, which can improve convection, but being a solubilization–diffusion process, the solubility of phenolic derivatives is very important , especiaAr-OHS, is dependent on pH, according to Equation (18), which shows the available pH range dependencies (before or after pKa of the considered aromatic derivatives):Ka,Ar-OH being the acidity constant of the corresponding phenolate form.The solubility of the phenolic derivative, SAr-OH being the solubility of the aromatic derivative at a given pH, and S0,Ar-OH the solubility in pure water at a considered pH.Thus, the pH dependence is of the general form presented in Equation (19):0 in pure water) to the limit solubility of the phenolic form at pH = 0 (0 in pure water (pH = 7), the solubility of the aromatic derivative increased with increasing pH to the limit solubility of the phenolate form at pH = 14  and the receiving phase of high pH aqueous solution.Starting from the obtained results for the separation and transport of the chemical species in a permeation module with the dispersion of aqueous phases in the form of droplets, this paper studied the effect of interposing spheres in free rotation between the droplets and the membrane phase. These spheres determine the contact, in the form of a film, between the aqueous phases and the membrane phase of the organic solvent. The study was performed in a membrane system in which the variable pH source phase consists of phenolic derivatives (PD) of technical-economic and environmental interest (4–nitrophenol (NP), 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP)), a membrane of n–alkyl alcohols (n–octanol and n–decanol) and the receiving phase of high pH aqueous solution.Starting from the obtained results for the separation and transport of the chemical species in a permeation module with the dispersion of aqueous phases in the form of droplets, in this paper, we studied the effect of interposing spheres in free rotation between the droplets and the membrane phase. These spheres determine the contact of aqueous phases in the form of a film with the membrane phase of the organic solvent. The study was performed in a membrane system in which the variable pH source phase consists of phenolic derivatives of technical-economic and environmental interest (4–nitrophenol (NP), 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP)), a membrane of The transport of 4-nitrophenol was determined by the difference in pH between the aqueous phases, the nature of the membrane solvent and the nature of the spherical material. Thus, the transport in which the module has glass spheres (Gl) is superior to that using copper spheres (Cu), but especially to those made of steel (St). In all the studied cases, the module with spheres (Ms) had superior transport results to the module with drops (Md).The extraction efficiency (EE) and the transport of 2,4–dichlorophenol (DCP) and 2,4–dinitrophenol (DNP), studied in the module with glass spheres, showed that the two phenolic derivatives could be separated by adjusting the pH of the source phase. At a source phase with a strong acid character (pH = 2), the two derivatives are extracted with good results (EE > 90%), while at a pH in the range , they caThe influence of the material of the spheres in the extraction module suggests possibilities to control the performance of the membrane process by chemically modifying the surface of the spheres, especially those made of glass.


From the perspective of economics, this study discusses the value of establishing a standardized clinical nutrition diagnosis and treatment pathway in the diagnosis and treatment of pulmonary infection and provides a reference for optimizing the diagnosis and treatment pathway of pulmonary infection.  The patients who received the nutrition diagnosis and treatment pathway intervention in 2017 were counted as the routine group and were subdivided into the conventional intervention group (C1) and conventional control group (C2) according to whether the standardized nutrition therapy was applied or not. The patients who received the nutrition diagnosis and treatment pathway intervention in 2020 were counted as the experimental group and were subdivided into the experimental intervention group (T1) and the experimental control group (T2) according to whether standardized intervention was applied or not. The total hospitalization expenses, average daily hospitalization cost, nutrition support expenses, plasma albumin before and after nutrition support, readmission, and other indicators of all patients were recorded and compared. The cost-effectiveness ratio (CER), incremental cost-effectiveness ratio (ICER), and cost-effectiveness threshold for cost-effectiveness analysis were adopted. P < 0.001). Compared with the T2 group, the T1 group had higher total hospitalization cost, average daily hospitalization expenses, nutritional support expenses, and plasma albumin improvement rate and lower readmission rate (P < 0.001). Taking the improvement rate of plasma albumin as the effect index, compared with the C1 group, the T1 group has less investment cost and better effect, and the ICER is negative (below the cost-effect threshold). And taking the readmission rate as the effective index, compared with the C1 group, the T1 group invested less cost and had a better effect, and the ICER was negative (below the cost-effect threshold).  Compared with the C2 group, the C1 group had higher total hospitalization expenses, average daily hospitalization expenses, nutritional support expenses, and plasma albumin improvement rate and lower readmission rate ( For the patients with pulmonary infection, whether the improvement rate of plasma albumin or the readmission rate is used as the impact index, the standardized nutrition diagnosis and treatment pathway in 2020 is more economical than the nonstandardized nutrition diagnosis and treatment pathway. Disease-associated malnutrition  refers to malnutrition caused by feeding and metabolic changes because of the disease . The proPulmonary infection is a reaction caused by lung damage caused by viruses, bacteria, or physical and chemical factors in the lungs of patients. Most patients are in a state of high decomposition and high metabolism and often develop malnutrition. Patients with respiratory diseases can experience prolonged hospitalization, prolonged ventilator use, aggravated myasthenia gravis, increased infection, increased hospitalization cost, poor treatment effects, and so on . The earThe essence of health economic evaluation is to compare the “cost-effectiveness analysis (CEA)” of different health intervention programs. The purpose of CEA is to analyze the treatment program with the lowest cost when seeking a certain treatment. In clinical treatment, the most expensive program is not necessarily the best, and the low-cost program is not necessarily the best. Therefore, it is necessary to evaluate the ratio of the cost of an intervention program to its possible effect through CEA. The results of CEA are expressed as “cost-effectiveness ratio (CER)” and “incremental cost-effectiveness ratio (ICER).” CER directly links healthcare costs to clinical outcomes. The lower the CER, that is, the lower the input cost, the better the effect. Although CER can directly compare the resource utilization efficiency of different programs, it cannot fully reflect the cost to be paid and the health output obtained, nor the pursuit of better health outcomes. ICER represents the “difference in average cost” of the different options divided by the “difference in average effect.” The smaller the ICER value, the less the cost per unit of health outcome gained, and the more likely the option is to be economical. At the same time, the concept of threshold is also introduced in ICER's judgment; that is, considering the level of social willingness to pay for health output, it has richer decision-making information. The cost-effectiveness threshold refers to the level of cost and effectiveness that an intervention should achieve in a given health care system to be acceptable. And the ICER indicator for decision support must also specify a judgment threshold to judge which one is better than the increased health output and the increased cost .Although the safety and efficacy of the main technologies for the treatment of diseases vary, the medical resources of any country are limited, and it is very meaningful to increase the economic evaluation for clinicians to choose the treatment of patients. Currently, pharmacoeconomic evaluation research is currently quite successful, but there are few economic evaluations related to medical nutrition therapy, which have problems such as a single existing evaluation index and a relatively immature evaluation method system. It is necessary to select appropriate nutrition intervention projects and adopt more targeted intervention tools and economic evaluation methods according to the actual domestic situation . Our stuWe retrospectively collected 100 pulmonary infection patients who underwent nutritional support at West China Hospital of Sichuan University in 2017 and collected 100 pulmonary infection patients who underwent nutritional support at the same hospital in 2020. This study was approved by the Ethics Committee of West China Hospital of Sichuan University; all patients were informed and consented.The inclusion criteria were as follows: (1) patients admitted to West China Hospital of Sichuan University, aged 18 to 90 years old; (2) lung infection patients; and (3) patients with nutritional support after consultation.Exclusion criteria were as follows: (1) patients under the age of 18 or over 90, (2) patients undergoing daytime surgery or staying in the hospital overnight and patients undergoing surgery before 8 o'clock the next day, (3) patients with advanced malignant tumors, (4) end-stage patients such as brain death, (5) patients with severe liver and renal function, and (6) participating in other nutritional interventions.The grouping standard is as follows: before the implementation of the standardized clinical nutrition diagnosis and treatment pathway in 2017, the patients receiving nutritional support were in the routine group. Then, the patients were divided into a conventional intervention (C1) group and a conventional control (C2) group according to whether they received standardized nutritional treatment. The C1 group was the nutritional intervention group treated with standardized nutrition therapy, and the C2 group was the nutrition intervention group after the doctor directly consulted without a standardized nutrition treatment process. Patients after the implementation of the standardized clinical nutrition diagnosis and treatment pathway in 2020 were used as the trial group. Moreover, they were divided into the trial intervention (T1) group and trial control (T2) group according to whether they received standardized nutritional treatment. The T1 group was the nutritional intervention group treated with standardized nutrition therapy, and the T2 group was the nutrition intervention group after the doctor directly consulted without a standardized nutrition treatment process.Conventional nutrition support pathways include a single nutritional risk screening, physician assessment of nutritional status, and clinical dietitian development of nutrition treatment plans in a scattered form, without a unified pathway. The standardized clinical nutrition diagnosis and treatment pathway referred to the nutritional risk screening-nutritional status evaluation-nutrition support (intervention) action plan. Specifically, nutritional risk screening was routinely performed by the ward head nurse with an NRS 2002 nutritional risk screening scale within 24 h of admission, Grade < 3 points for patients a week after rescreening, Grade ≥ 3 points of patient HIS system for risk warning, and nutrition status evaluated by a clinical dietitian, and nutritional diagnosis was performed based on the evaluation results. Moreover, we consulted with the physician in charge to formulate an individualized nutrition intervention plan that included enteral nutritional therapy and parenteral nutrition therapy. Then, the implementation was assisted by a competent nurse, joint monitoring, and effect evaluation .According to the guidelines of their Chinese Society for Parenteral and Enteral Nutrition, standardized nutritional support was defined as 25 kcal/kg/d-30 kcal/kg/d, nonprotein energy (as carbohydrate and fat), and 0.93 g/kg/d-1.25 g/kg/d protein for patients.According to the reference range of the WS/T404 common clinical biochemical test project of the health industry standard of China, the normal range of albumin was 40-55 g/L, so albumin < 40 g/L was judged as malnutrition.The most important health economic analysis method used in this study was the cost-effectiveness ratio (CER), which directly linked medical costs to clinical treatment effects. The lower the input cost is, the better the effect. Although it could straightforwardly compare the resource use efficiency of different programs, it could not fully reflect the cost to be paid and the health output obtained, nor can it reflect the pursuit of better health effects.Incremental cost-effectiveness ratio evaluation is the incremental input cost of marginal health improvement, which reflects the pursuit of better health output and the consideration of resource utilization efficiency. At the same time, the threshold is also introduced in the ICER judgment, which includes the consideration of the social payment willingness level of health output, with richer decision-making information. The cost-effectiveness threshold refers to the level of cost and effect that an intervention should achieve if it can be accepted under a given health care system. Also, the ICER indicator for decision support must also specify a judgment threshold to judge which is better than the increased health output and the increased cost .CER and ICER were used in this study, which were used to analyze the problem from the perspective of the patient. Considering the difference in the number of hospitalization days, the cost adopted the total hospitalization cost and average (daily) hospitalization cost, and the effect was the improvement rate of plasma albumin and nonreadmission. The ICER was used for each increase in hospitalization cost, improvement in plasma albumin, and reduction in readmission rate.C)/effects (E)CER = cost  hospitalization expenses, and nutritional support expenses were collected, and the Wilcoxon signed rank-sum test was performed for each pair of groups.Z = −5.936 (P < 0.001) and compared with the C1 group and C2 group, Z = −6.391 (P < 0.001), and the difference was statistically significant. However, the costs of the T1 group were higher than those of the T2 group; the C1 group was higher than the C2 group. The T1 group was compared with the C1 group, Z = −1.868 (P > 0.05). Although the T1 group was lower than the C1 group in terms of cost, the difference was not statistically significant , and the C1 group was compared with the C2 group, Z = −4.833 (P < 0.001), The difference is statistically significant, but the cost of the T1 group was higher than that of the T2 group, and the C1 group was higher than the C2 group. Compared with the C1 group, the T1 group was lower in cost, Z = −1.820 (P > 0.05), but the difference was not statistically significant, as shown in the details in Due to the difference in the number of hospitalization days, comparing the average (daily) hospitalization expenses, the T1 group was compared with the T2 group, Both the comparative total hospitalization cost and average (daily) hospitalization expenses were significantly higher in the intervention group than in the control group.Z = −5.515 (P < 0.001), and the C1 group was compared with the C2 group, Z = −5.667 (P < 0.001); the difference was statistically significant. The cost of the T1 group was higher than that of the T2 group, and the C1 group was higher than the C2 group. Compared with the C1 group, the T1 group was lower, Z = −1.096 (P > 0.05), and the proportion of nutritional support expenses was higher , but the difference was not statistically significant . The difference between the T1 group and the T2 group was also statistically significant (P < 0.05); the difference between the C1 group and the C2 group was not statistically significant (P > 0.05) . This shows that nutrition support treatment under the “standardized clinical nutrition diagnosis and treatment pathway” can effectively reduce the readmission rate.First, the chi-square test was performed on the readmission rate of the four groups of inpatients, and it was found that the difference in the readmission rate of the four groups of inpatients was statistically significant  hospitalization expenses of each group of patients as the cost and taking the percentage of improvement in plasma albumin before and after nutritional support and the rate of nonreadmission for each group as the effect, the cost-effectiveness ratio and incremental cost-effectiveness ratio were calculated according to the formula. The discount rate recommended by my country's pharmaceutical economics was used for the cost of different years, and it was generally 3% to 5% in my country. The World Health Organization recommends a cost–benefit discount rate of 3%. Comprehensively, the cost and effect of this article were both at a discount rate of 3% .If the improvement rate of plasma albumin was used as an effect indicator, from the perspective of the cost-effectiveness ratio, the T1 group costs more than the T2 group, and the C1 group costs more than the C2 group, but the effect was better. Moreover, when the T1 group costs less than the C1 group, the effect is better, but the effect of the T1 group is higher than that of the T2 group, and the effect of the C1 group is higher than that of the C2 group. From the perspective of the incremental cost-effectiveness ratio, for every one percentage point improvement in plasma albumin, the T1 group needed an additional investment of RMB 179,800, and the C1 group needed an additional investment of RMB 262,100. Compared with the C1 group, the T1 group invested less cost and obtained better results, and the ICER was a negative value. That is, it was an advantageous plan to follow a standardized clinical nutrition diagnosis, and the treatment pathway was the superior plan.If the rate of nonreadmission was the effect index, from the perspective of the cost-effectiveness ratio, the T1 group and C1 group cost more than the T2 group and C2 group, but the effect was higher. The T1 group was less costly than the C1 group, and the effect was better. From the perspective of the incremental cost-effectiveness ratio, to reduce the readmission rate by one percentage point, the T1 group required an additional investment of RMB 111,300, and the C1 group required an additional investment of RMB 786,400. However, the effect of the T1 group was higher than that of the T2 group, and the effect of the C1 group was higher than that of the C2 group. Compared with the C1 group, the T1 group had a negative ICER value  as a comparison and convert it to RMB according to the USD exchange rate of the year (GDP of 190 yuan/day in 2017 and 160 yuan/day in 2020). The results are as follows.If the rate of plasma albumin improvement before and after nutritional support was an effect, the incremental cost-effect ratio of the T1 group and T2 group and the incremental cost-effect ratio of the C1group and C2 group were below the threshold, suggesting that the economy of the T1 group was better than that of the T2 group and the C1 group was better than the C2 group.If the rate of nonreadmission is an effect, the incremental cost-effect ratio of the T1 group over the T2 group is below the threshold, suggesting that the T1 group was better than the T2 group. With the C1 group incremental cost effect greater than the threshold, the C2 group was more economical  hospitalization expenses are considered costs. Considering that nutritional support expenses account for a relatively small proportion, the cost of nutritional support was compared to the cost, and the improvement rate of patients' plasma albumin and the rate of nonreadmission were used as the effects and then analyzed.This study found that before the implementation of standardized clinical nutrition diagnosis and treatment pathway, a clinical dietitian performed nutritional risk screening for some inpatients for nutritional support. Compared with nutrition support without nutritional screening, each patient's every one percentage point improvement in plasma albumin requires an additional investment of RMB 77.7 per day, of which there is an additional RMB 3 per day (accounting for 3.9%). To reduce the readmission rate by one percentage point for a patient, an additional RMB 233.2 is required per day, of which an additional RMB 5 per day is spent on nutrition support (accounting for 2.1%).Similarly, after the implementation of the standardized clinical nutrition diagnosis and treatment pathway in 2020, it was found that patients who implement nutrition support through standardized nutrition diagnosis and treatment pathway, compared with patients undergoing nutrition support through direct consultation, require an additional investment of RMB 73.8 per day for each improvement in plasma albumin by one percentage point, and nutrient support costs invested RMB 3 more per day (accounting for 4.1%). Every 1% reduction in the readmission rate requires an additional investment of RMB 45.7 per day, and nutrient support costs invested RMB 2 more per day (accounting for 4.4%).This is inconsistent with most of the studies. Herbert et al.  found thλ  needs to be introduced [λ, the treatment plan is considered acceptable. In this study, 1 times GDP is selected as λ [Think deeply about this issue. Compared with the original nutritional support model, standardized nutritional therapy has improved the plasma albumin of more patients and reduced the readmission rate, but it costs more. Whether it should be selected and whether it is recognized by society need further verification. Since research evaluation is a comparison of two treatment options, usually, a treatment option may increase health output while also increasing costs. However, deciding whether to adopt this treatment option requires incremental analysis, that is, judging whether to adopt this treatment option. After the treatment plan, the cost of increasing a unit of health output is worthwhile. At this time, an external reference value troduced , that isted as λ .If plasma albumin improvement was taken as the effective index, the ICER in the 2017 routine groups and 2020 test groups were below the cost-effect threshold we set, suggesting that the standardized nutrition support program is more economical than the doctor directly asking for nutrition support in the same year. This shows that standardized nutritional support can detect patients with malnutrition earlier and conduct a timely nutritional intervention. Although the cost is higher, the effect is better, and the price is within the acceptable range . If the Comparing the implementation of nutritional therapy through the standardized nutritional diagnosis and treatment pathway in 2020 with the standardized nutritional therapy before 2017, the comparison result of the discount rate conversion shows that the cost of the standardized nutritional treatment pathway is lower and the economic effect is better. This shows that it is also a standardized nutrition therapy. After the functions of each role are improved in 2020, the division of labor in each process is clear, and multidisciplinary cooperation is involved, which is more conducive to the early start of nutrition therapy and improves the effectiveness of diagnosis and treatment. This is consistent with most studies and shows that the establishment of a standardized clinical nutrition diagnosis and treatment pathway is the key to achieving reasonable nutrition support treatment, which can improve the nutritional status of patients, improve clinical outcomes, and save medical expenses for patients and the country , 27.In summary, although the application of a standardized diagnosis and treatment pathway for nutrition requires higher costs, it can improve the nutritional status and treatment effective of patients and has cost-effect advantages and high economic value, which is worth being recommended and applied in clinical treatment. Through the analysis of health economics, the standardized nutrition diagnosis and treatment pathway can be accepted. We hope that people's views of the standardized clinical nutrition diagnosis and treatment pathway can be changed in the future to encourage everyone to accept this path and better serve clinical practice.


The oxide layers were produced on the EN AW-5251 aluminum alloy by means of a direct current anodizing in a three-component electrolyte. The input variables (current density and electrolyte temperature) were selected based on the overall design of the experiment. The current density was 1, 2, 3 A/dm2, and the electrolyte temperature was 283, 293, 303 K. The surface morphology was examined using a scanning electron microscope (SEM), and then the microscopic images were analyzed using a graphics program. The micromechanical and sclerometric properties were examined by determining the ITH hardness and three critical loads: Lc1 , Lc2  and Lc3 (load at which the layers were completely damaged). Sclerometric tests with the use of scratch tests were supplemented with pictures from a scanning microscope, showing the scratches. The produced layers are characterized by a hardness above 3 GPa and a porosity of 4.9–10.3%. Such a range of porosity of the produced layers allows their wide application, both for sliding associations with polymers and for their modification.The article presents the dependence of the morphology as well as micromechanical and sclerometric properties of Al The tests were carried out in accordance with the guidelines of ISO 20502  and ASTMLc1 , Lc2  and Lc3 (load at which the layer was completely damaged).Photos of the surface show three critical loads: 2O3 layers at a magnification of 50,000×.With the use of scanning electron microscopy (SEM), it is possible to observe the porosity of the oxide layers, which is the basic property of aluminum oxides. The surface morphology images show the nanoporosity characteristic of oxide layers, which is a channel for the migration of oxygen ions connecting with the anode material in the electrical and chemical processes.2O3 layer, the values from the table were converted for the area of 100 µm2. All image analysis calculations were made on the basis of three images of the layer from different locations.Based on the image analysis, the results of the stereological parameters were obtained , which w2 and an electrolyte temperature of 293 K is characterized by the highest porosity and the highest average nanopore area. The lowest porosity was determined for the anodized oxide layer at the lowest production parameters: current density 1 A/dm2 and electrolyte temperature 283 K (Sample A). The Al2O3 layer of sample C produced at a current density of 1 A/dm2 and a temperature of 303 K is characterized by the smallest average nanopore field and the highest nanopore density per µm2.The layer of sample E produced at a current density of 1 A/dm2O3 layers, resulting from the applied conditions of the anodizing process, were observed. The increase in the current density at an electrolyte temperature of 283 K causes a linear increase in both the porosity and the average surface area of the nanopores. The histograms also show an increase in the proportion of pores with a larger surface area. The layers produced in the electrolyte with a temperature above 283 K at a constant current density of 1 A/dm2 showed an approximately two-fold increase in porosity. The layer produced at a current density of 1 A/dm2 with an electrolyte temperature of 303 K is characterized by a very high pore density of up to 98 pores/µm2; however, these are pores with very small areas (up to 2000 nm2). The histograms also show a high proportion of pores with large surfaces for samples E and B; the vast majority of pores have an area of 2000–3000 nm2, and a significant number of pores with an area of over 3000 nm2 is also noticeable.Significant changes in the surface morphology of Al2O3 layers in a constant process time , is a layer produced at a current density of 3 A/dm2 in an electrolyte at a temperature of 283 K. The smallest layer thickness (5.1 μm) was shown for Sample C, on which a layer was produced at the density current of 1 A/dm2 in the electrolyte at a temperature of 303 K.As a result of the thickness measurements carried out, it can be concluded that the parameters of the electrochemical process (anodizing current density) have a significant impact on the thickness of Aless time . A signiITH oxide layers produced with various parameters according to the overall plan, with standard deviations. The maximum penetration depth h is also included, which facilitates the interpretation of microhardness changes.The undoubted advantage of anodic oxide layers produced in the electrochemical process is the ability to control their operational properties by changing their porosity , thickneThe oxide layers produced in order to improve the abrasion resistance of the surface of aluminum alloys (reducing the friction coefficient and the wear intensity of triboelements) are produced by the so-called hard anodizing method. Hard anodizing is considered to be the process of anodic production of oxide layers on aluminum and its alloys by an electrochemical method, as a result of which the oxide layer obtains a microhardness of at least 3 GPa. As a result of the research analysis, it can be concluded that the electrochemical process is a hard anodizing process, because all the produced layers are characterized by a hardness above 3 GPa. The oxide layers obtained on the EN AW-5251 alloy with the electrochemical method are mainly characterized by an increase in hardness compared with the parent metal see .2  and for sample I produced at a current density of 2 A/dm2 in an electrolyte at a temperature of 293 K. A current density of 1 A/dm2 resulted in obtaining layers with lower microhardness . In the case of changes in the electrolyte temperature’s tested ranges, the greatest changes in the microhardness occur for the current density of 2 A/dm2 , whereas in the case of changes in the current density, the greatest changes in the microhardness occur for the temperature of 283 K . The layers produced at 283 and 303 K show lower microhardness values, whereas the layer produced at 293 K shows high microhardness. To sum up, in order to increase the microhardness of oxide coatings obtained on aluminum alloys, the anodizing process should be carried out at a current density of 3 A/dm2 or at a temperature of 293 K.The highest values of microhardness were demonstrated for layers produced at a current density of 3 A/dm2 and the electrolyte temperature of 293 (sample E), with which were produced a high microhardness of 5.077 GPa and very high porosity—as much as 10.3%.In many scientific works, oxide layers produced on aluminum alloys are modified with solid lubricants in the form of e.g., graphite, molybdenum disulphide or tungsten disulphide, or are used for anti-corrosion protection, improving aesthetics (colored layers) or electrical insulation. The increase in the content of the composite component in the structure of the oxide layer is very often influenced by high porosity or large diameters of nanopores. For this reason, it is advantageous to optimize the conditions for producing the oxide layer so as to obtain high porosity while maintaining high microhardness. The conducted research shows that the best parameters for the production of oxide layers in order to obtain a matrix for composite layers are the current density of 1 A/dmThe advantages of oxide layers produced on aluminum alloys also include their excellent adhesion to the substrate. The most common method of testing the adhesion forces of a layer to the substrate is the scratch test. As a result of such a test, scratches on the surface of the layer are obtained, which may have the character of Hertz cracks occurring usually at the beginning of loading the layer (cohesive damage), and adhesive cracks, which completely damage layers. Cohesive cracks result from the action of forces inside the torn layer and appear as cracks in a direction perpendicular to the direction of movement of the indenter. Adhesive cracks result from the action of significant compressive stresses arising in the layer and are revealed by the crushing and tearing of the layer in front of the indenter.Lc1, Lc2 and Lc3 are presented in The following phenomena are visible on the samples subjected to the scratch tests: plastic deformation, circular Hertz cracks, forward V-shaped cracks (at the edges inside and outside of the scratch), deformed coform cracks and cohesive chipping along the scratch marks. The places where the Hertz-type cracks occurred, as well as the cohesive and adhesive cracks, are shown in The analysis of the adhesion test results showed that the scratch resistance of the layers largely depends on the current density ; therefo2, whose thicknesses are the largest , show the highest mechanical strength . On the other hand, the layers produced at a current density of 1 A/dm2, the thicknesses of which are the smallest , have the lowest mechanical strength . The lowest scratch resistance was demonstrated by the layer produced at the current density of 1 A/dm2 in the electrolyte at 283 K. For this layer, the first damage was observed at the load of Lc1 = 1.43 N. The layer was completely broken at the load of Lc3 = 3.87 N. The layer produced at a current density of 3 A/dm2 in an electrolyte at a temperature of 303 K showed the highest mechanical strength. Load Lc3 is equal to 8.71 N (which is more than a double increase compared with the layer with the lowest strength). The layer produced at the current density of 3 A/dm2 in the electrolyte at the temperature of 293 K also showed significant mechanical strength. For this layer, the highest load values were observed for the Hertz cracks of 2.42 N and for cohesive cracks of 4.29, and the complete tear of the layer occurred at a load of 8.12, which is slightly less than that for the layer produced at the same current density but in an electrolyte with a temperature of 303 K.The layers, produced at a current density of 3 A/dm2 or H2SO4, which significantly reduces costs of the conducted process. The highest values of microhardness were demonstrated for layers produced at a current density of 3 A/dm2 in the electrolyte at 283 and 303 K and at a current density of 2 A/dm2 in the electrolyte at 293 K. The scratch resistance of the layers correlates more closely with their thickness than with their hardness. As a result of strength tests, cracks are obtained on the surface of the layer, which may be elastic Hertzian cracks inside the layer (Lc1), cohesive cracks (Lc2) or adhesive cracks (Lc3). As a result of the action, cohesive cracks are formed by forces inside the broken layer and appear in the form of cracks in the direction perpendicular to the direction of movement of the indenter. Adhesive cracks result from the action of significant compressive stresses arising in the layer and revealing themselves as a result of crushing and tearing beyond the layer before the indenter. The layers produced at a current density of 3 A/dm2, the thicknesses of which are the highest, show the highest mechanical strength. All the produced layers are characterized by a hardness above 3 GPa, and thus they can be used in sliding kinematic nodes. The anodizing parameters used in the research make it possible to obtain layers with a porosity of 4.9–10.3%. Such a range of porosity of the produced layers allows their wide application, both for sliding associations with polymers and for their modification. The highest values of porosity were demonstrated for the layer produced at the current density of 1 A/dm2 in the electrolyte at the temperature of 293 K. The greatest correlations were shown for the dependence of layer thickness and mechanical strength on the current density.The research results and their analysis presented in the article confirm the sense of modifying the surface of the EN AW-5251 aluminum alloy in the electrochemical process in order to increase the hardness and strength of its surface. The three-component electrolyte used in the tests enables the formation of hard oxide layers at room temperature (283–303 K) without the need for intensive cooling, as is the case with anodizing in acid solutions (COOH)