Modelo bayesiano de series temporales estructurales. Aproximación a la evaluación de impacto de VA-MENGOC-BC®

Introducción: Una nueva intervención de salud pública, como la introducción de una vacuna, implica el monitoreo de indicadores que aseguren una intervención efectiva, y que exista la posibilidad de cuantificar sus beneficios. Obtener estimaciones precisas del impacto de una intervención de salud se considera un desafío importante. Objetivos: Estimar el impacto causal de uno de los productos líderes del Instituto Finlay de La Habana: la vacuna cubana registrada y comercializada VA-MENGOC-BC®. Métodos: Se seleccionaron datos en los anuarios estadísticos de salud desde 2009 hasta 2017. Se usaron como variable de interés, la tasa de incidencia de la enfermedad meningocócica en Cuba ( 100 000 habitantes y un conjunto de covariables que no se afectaron por la intervención: tasas de incidencia de fiebre tifoidea, de incidencia de tuberculosis, de mortalidad por enfermedades infecciosas (parasitarias e intestinales) todas ( 100 000 habitantes. Se consideró 1989 como año de la intervención. Se aplicó el método bayesiano de series temporales estructurales, que evaluó el impacto causal de la vacunación sostenida con VA-MENGOC-BC® desde 1989 hasta el presente. Resultados: Se estimó un impacto causal acumulativo significativo en la reducción de la incidencia de la enfermedad meningocócica. Se verificó que se produjo una disminución de la enfermedad en 97,2 %. Conclusiones: La aplicación del método de series de tiempo estructural bayesina para estimar el impacto de la vacuna VA-MENGOC-BC®, constituyó una herramienta novedosa para evaluar el contrafactual. Se proporcionó una apreciación del impacto de la vacunación con VA-MENGOC-BC®, una vacuna implementada y reconocida a nivel mundial.

Introduction: A new public health intervention, such as the introduction of a vaccine, implies monitoring the indicators that guarantee its effectiveness, and the possibility of quantifying its benefits. Obtaining accurate estimates of the impact of a health intervention is considered a major challenge. Objective: To estimate the causal impact of one of the leading products of the Finlay Institute in Havana: the registered and marketed Cuban vaccine VA-MENGOC-BC®. Methods: Data from the health statistics yearbooks from 2009 to 2017 were selected. The incidence rate of the meningococcal disease in Cuba per 100 000 population and a set of co-variables that were not affected by the intervention, such as incidence rate of typhoid fever, tuberculosis, and fatality cases due to infectious diseases (parasitic or intestinal) per 100 000 population were used as variables of interest. The intervention year was 1989. The Bayesian structural time series model was applied to evaluate the causal impact of the continued vaccination with VA-MENGOC-BC® from 1989 to date. Results: A significant cumulative causal impact in reducing the incidence of meningococcal disease was estimated. A decrease of 97.2% in the disease was verified. Conclusions: The application of the Bayesian structural time series model to estimate the impact of the vaccine VA-MENGOC-BC® was a novel tool to estimate the counterfactual. It was provided an estimate of the impact of the vaccination with VA-MENGOC-BC®, an implemented and globally well-known vaccine.

Effects of the national centralized drug procurement policy on drug availability and the structure of hospital drug use / 中国药房

OBJECTIVE To analyze the effects of the national centralized drug procurement （NCDP） policy on drug availability and the structure of drug use in public hospitals. METHODS Using hypoglycemic， lipid-lowering， antiviral drugs， and psychiatric drugs for the treatment of mental illness and depression as objects， the interrupted time series model was used to quantitatively evaluate the changes in consumption sum of drugs， consumption amount and daily cost of the target drugs in national sample hospitals as well as the changes in per capita medication frequency， outpatient prescription amount， and medical insurance surplus of target drugs in a third grade class A hospital before and after the implementation of NCDP policy. RESULTS After the implementation of the NCDP policy， the volume for the four bid-winning drugs increased significantly （P＜0.01 for the remaining three categories except for hypoglycemic drugs）， but DDDc （P＜0.01） and the amount of related drugs （P＜0.001） decreased significantly. The volume for the non-winning drugs （except for lipid-lowering drugs） decreased significantly （P＜0.05）， and DDDc also decreased significantly （P＜0.05 for other 3 categories except for psychiatric drugs）； the volume （P＜0.01） and DDDc （P＜0.01 only for psychiatric drugs） for alternative drugs all increased except for antiviral drugs. The structure of drug use for different drugs was affected differently by the NCDP policy，and that of hypoglycemic drugs was affected obviously； the proportion of alternative drugs increased after centralized procurement. The outpatient prescription amount of each hospital significantly decreased after centralized procurement，and the decrease in the cost paid by the patients using lipid-lowering and antiviral drugs related to centralized procurement was greater than 0.60； the remaining medical insurance amount for bid-winning drugs was approximately 1.252 5 million yuan. CONCLUSIONS NCDP policy effectively alleviates the burden of medical expenditure and also drives the structure changes of drug use such as the substitution of generic drugs for original drugs， the growth of the volume of alternative drugs.

Epidemiological characteristics and trend prediction of pulmonary tuberculosis in Ankang City, Shaanxi Province from 2011 to 2021 / 中国热带医学

@#Abstract: Objective To analyze the epidemiological characteristics of pulmonary tuberculosis (PTB) in Ankang City from 2011 to 2021, so as to provide a scientific basis for the formulation of PTB prevention and control strategy. Methods Descriptive statistics were used to analyze the epidemiological characteristics of PTB in Ankang City from 2011 to 2021, and a time series model was established to quantitatively predict the incidence of pulmonary tuberculosis in 2023. Results The incidence rate in Ankang City showed a significant upward trend from 2011 to 2017, and a more obvious downward trend in 2017-2021 (P<0.05), and the decrease rate in 2021 was 40.36% compared with that in 2017. The proportion of etiological positivity increased from 12.5% in 2014 to over 50.00% after 2019. The incidence season was mainly concentrated in the first quarter, accounting for 28.39% of the annual incidence. High incidence areas were concentrated in the south of Ankang: Langao County, Ziyang County and Zhenping County, with 128.32/100 000, 117.07/100 000 and 110.44/100 000, respectively. Low incidence areas were located in the north of Ankang: Ningshan County, with 60.62/100 000. Farmers and students were the high incidence groups, accounting for 81.80% and 4.97% of the total cases respectively. The incidence of young children was relatively low, but cases were reported every year. The incidence rate of male was 2.39 times that of female. The age of onset increased significantly from 15 years old, and the peak incidence was in the age group of 60-<80 years old, followed by the age group of 45-<60 years old, the average annual incidence was 136.44/100 000 and 104.47/100 000, respectively. The model ARIMA(0,1,1)(0,1,1)12 predicted that the incidence of the disease generally increased from October 2022 to March 2023, then steadily decreased, and increased again in December. Conclusions The incidence of tuberculosis varies in different areas of Ankang City, and males, farmers, students and the elderly are all factors of high incidence of tuberculosis. Therefore, different prevention and control strategies should be adopted according to the characteristics of population in different areas. The number of cases in Ankang City in 2023 showed an overall downward trend, which can provide a reference for the prevention and control of PTB.

Spatial and temporal characteristics of reported schistosomiasis cases in China based on a Bayesian interrupted time-series model / 中国血吸虫病防治杂志

Objective To investigate the spatial-temporal characteristics of reported schistosomiasis cases in China from 2004 to 2017, so as to provide insights into the development of different schistosomiasis control strategies at various stages. Methods The monthly data of reported schistosomiasis cases at a provincial level of China from 2004 to 2017 were collected from the Public Health Science Data Center, and the spatial-temporal distribution of reported schistosomiasis cases was preliminarily identified using a descriptive statistical method. According to the goals at different stages proposed by the National Mid- and Long-term Program for Schistosomiasis Prevention and Control in China (2004—2015), a Bayesian interrupted time-series model was established to analyze the provincial reported incidence, time trend and seasonal variations of schistosomiasis in China at different stages. Results The reported schistosomiasis cases were mainly concentrated in 5 provinces of Anhui, Jiangsu, Jiangxi, Hubei and Hunan and 2 provinces of Sichuan and Yunnan in China from 2004 to 2017, and the number of reported cases in endemic areas decreased gradually. The incidence of reported schistosomiasis cases predominantly peaked during the period from May to September in the marshland and lake regions, while no regular seasonality was seen in hilly regions. Bayesian interrupted time-series analysis showed the peak incidence of reported schistosomiasis cases in 4 provinces of Anhui, Hubei, Hunan and Jiangxi between May and September and in Jiangsu Province from July to November; however, no regular seasonal cycle was identified in hilly regions. The number of reported schistosomiasis cases showed a tendency towards an increase in 2 provinces of Hubei and Hunan from 2008 to 2014, with a minor peak during the period between March and April, and since 2015, the seasonality was not remarkable any longer in 3 provinces of Anhui, Jiangsu and Jiangxi with a decline in the incidence of reported schistosomiasis cases, while the seasonality remained in Hubei Province. Conclusions The spatial-temporal characteristics of schistosomiasis in China, notably seasonality, vary at different control stages. Bayesian interrupted time-series model is effective to identify the spatial-temporal changes of schistosomiasis, and the schistosomiasis control strategy may be adjusted according to the spatial-temporal changes to improve the schistosomiasis control efficiency.

Forecast analysis on export of Chinese materia medica based on time series model / 中草药

To forecast the export trend of Chinese materia medica (CMM) in China in the next few years by using the export data of CMM from 1994 to 2016, and analyze the current situation of CMM export. Based on time series ARIMA model, the optimal model was established by sequence leveling test, model identification, verification, and prediction. The ARIMA (3, 2, 3) model is the optimal model to forecast the export trend of CMM. We use this model to conclude that the forecast of CMM exports in China from 2017 to 2020 is 3.687, 4.363, 4.850, and 4.965 billions, respectively. Finally, we put forward the problem of the share of CMM export supply and its structural problems. The supply of CMM in China does not have a correct understanding of the demand in the international market. China’s exports of CMM should seize the opportunity of the “Comprehensive Health” environment and the “Belt and Road” Initiative.

Evaluating cerebral endothelial dysfunction induced by amyloid based on the time series model / 中国药科大学学报

@#Time series model was developed to investigate the effect and contributions of related biomarkers on the cerebral endothelial dysfunction induced by beta amyloid(Aβ). HCMEC/D3 was incubated with 2. 5 μmol/L Aβ for 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 and 24 h, and biomarkers including cytosolic calcium ion, mitochondrial membrane potential(MMP), endothelial nitric oxide synthase(eNOS)and cell viability were determined. Time series model was established to assess the dynamic relationship between the related biomarkers and cell viability and the contribution of different biomarkers to cell damage. Impulse response analysis indicated that after a positive impact on cytosolic calcium ion, cell viability decreased and this impact continued to decline; after a positive impact on endothelial nitric oxide synthase and mitochondrial membrane potential, cell viability increases, which increased rapidly in the early stage, and the rate decreased in later stage. The result of variance decomposition showed that the cytosolic calcium ion played a major role in cerebral endothelial dysfunction induced by Aβ. Combined with the model study, it is concluded that the intervention on the level of cytosolic calcium ion at the early stage may be the possible way to slow the disease progression.