Risk-based cost-benefit analysis of alternative vaccines against COVID-19 in Brazil: Coronavac vs. Astrazeneca vs. Pfizer

We propose a probabilistic model to quantify the cost-benefit of mass Vaccination Scenarios (VSs) against COVID-19. Through this approach, we conduct a six-month simulation, from August 31st, 2021 to March 3rd, 2022, of nine VSs, i.e., the three primary vaccine brands in Brazil (CoronaVac, AstraZeneca and Pfizer), each with three different vaccination rates (2nd doses per week). Since each vaccine has different individual-level effectiveness, we measure the population-level benefit as the probability of reaching herd immunity (HI). We quantify and categorize the cost-benefit of VSs through risk graphs that show: (i) monetary cost vs. probability of reaching HI; and (ii) number of new deaths vs. probability of reaching HI. Results show that AstraZeneca has the best cost-benefit when prioritizing acquisition costs, while Pfizer is the most cost-beneficial when prioritizing the number of deaths. This work provides helpful information that can aid public health authorities in Brazil to better plan VSs. Furthermore, our approach is not restricted to Brazil, the COVID-19 pandemic, or the mentioned vaccine brands. Indeed, the method is flexible so that this study can be a valuable reference for future cost-benefit analyses in other countries and pandemics, especially in the early stages of vaccination, when data is scarce and uncertainty is high.     

Diabetes prevalence in England, 2001--estimates from an epidemiological model.

AIMS: To estimate the total prevalence of diabetes mellitus (diagnosed and undiagnosed) at national, regional and local level in England to support health-care planning and delivery. METHODS: An epidemiological model was constructed by applying age-sex-ethnic-specific reference prevalence rates from epidemiological studies to resident populations (2001 census) of England at national, regional, and local authority/Primary Care Trust levels. RESULTS: Estimated prevalence of total diabetes for all persons in England was 4.41% in 2001, equating to 2 168 000 persons. Type 2 diabetes was estimated to affect 2 002 000 persons (92.3%) and Type 1 diabetes 166 000 persons (7.7%). Diabetes prevalence was estimated to be higher in women (5.17%) than men (3.61%). People from ethnic minority groups had higher crude prevalence than White Europeans (4.29, 5.69, 6.63 and 2.13% among White Europeans, Black African/Caribbeans, South Asians and 'other' groups, respectively). Prevalence increased sharply with age (0.33, 3.37 and 13.92%, respectively, in those aged 0-29, 30-59 and 60+ years). The model allows use of user-defined population denominator estimates to derive numbers and prevalence of people with diabetes for a given local population group, such as at ward or general practice level. CONCLUSIONS: Self-reported diabetes prevalence estimates from community surveys underestimate the true burden of diabetes. The model can be used to derive the expected total prevalence of diabetes in health areas that lack reliable data to facilitate the implementation of the National Service Framework for diabetes. It will also allow estimates of future diabetes prevalence to be derived, and can potentially be used for prevalence estimates in all of the UK.     

Statistical characterisation of bacterial wild-type MIC value distributions and the determination of epidemiological cut-off values

MIC distribution data were obtained from a variety of international sources, and pooled after selection by a defined criterion. Sixty-seven of these datasets were subjected to a range of statistical goodness-of-fit tests. The log-normal distribution was selected for subsequent modelling. Cumulative counts of MIC distribution data were fitted to the cumulative log-normal distribution using non-linear least squares regression for a range of data subsets from each antibiotic-bacterium combination. Estimated parameters in the regression were the number of isolates in the subset, and (the log(2) values of) the mean and standard deviation. Optimum fits for the cumulative log-normal curve were then used to determine the wild-type MIC range, determined by calculating the MICs associated with the lower and upper 0.1% of the distribution, rounding to the nearest two-fold dilution, and calculating the probabilities of values higher and lower than these values. When plotted logarithmically, histograms of MIC frequencies appeared normal (Gaussian), but standard goodness-of-fit tests showed that the two-fold dilution grouping of MICs fits poorly to a log-normal distribution, whereas non-linear regression gave good fits to population (histogram) log-normal distributions of log(2) MIC frequencies, and even better fits to log-normal cumulative distributions. Optimum fits were found when the difference between the estimated and true number of isolates in the fitted subset was minimal. Sixteen antibiotic-bacterium datasets were fitted using this technique, and the log(2) values of the means and standard deviations were used to determine the 0.1% and 99.9% wild-type cut-off values. When rounded to the nearest two-fold dilution, > or = 98.5% of MIC values fall within the cut-off value range. Non-linear regression fitting to a cumulative log-normal distribution is a novel and effective method for modelling MIC distributions and quantifying wild-type MIC ranges.     

An epidemiological study of methicillin-resistant Staphylococcus aureus (MRSA) isolated from medical staff, inpatients, and hospital environment in one ward at our hospital.

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most important causative microorganisms for nosocomial infections. Recently, the incidence of isolation of MRSA has been increasing every year in Japan and is, notably, much more frequently found in inpatients than in outpatients. Therefore, we have done epidemiological studies of MRSA isolated from medical staff, inpatients, and the hospital environment in one ward of our hospital. Thereafter, we examined the antibiotic susceptibility (ABPC, DMPPC, CET, CMZ, IPM, GM, MINO, OFLX, EM, CLDM, VCM), phage typing, and coagulase typing of these MRSA. MRSA were isolated more frequently from anterior nares of inpatients than from doctors and nurses. MRSA were isolated more frequently from the environment near carriers of MRSA. Coagulase type II and phage type N.T. (not typable) were the dominant types of MRSA in our hospital (69% and 61%). MRSA strains were resistant to most antibiotics with a few exceptions (VCM, IPM, CMZ, CET). The high isolation frequency of MRSA in our hospital seems to suggest that inpatients who are carrying MRSA spread MRSA throughout the hospital environment and that the anterior nares of inpatients are the major MRSA harbor.     

HBV血清学标记携带者家庭内传染性多因素分析

HBV血清学标记携带者的传染受许多因素的影响。本研究采用多因素分析方法,定量描述了各种类型HBV血清学标记携带者家庭内传染性及有关因素影响的大小。家中上次HBsAg携带与易感者HBsAg和HBeAg阳转呈正相关。家中上次抗-HBc携带与易感者抗-HBc阳转呈正相关,OR=5.98;但与抗-HBc滴度变化无显著联系。而家中上次抗-HBc携带,HBsAg与抗-HBc同时携带与易感者HBsAg和HBeAg阳转呈负相关。年龄与HBsAg阳转呈负相关;文化水平与易感者抗-HBs阳转亦呈负相关;手术史、注射史与乙肝续发感染正相关。多因素分析对阐明人群中大量HBV血清学标记携带者的动态变化有一定意义。     

四川省绵阳市2019—2021年流行性感冒流行病学特征分析

目的 了解绵阳市2019—2021年流行性感冒流行病学特征,为绵阳市流感防控工作提供重要依据。方法 收集绵阳市2019—2021年流感监测相关数据,采用描述性流行病学方法进行统计学分析。结果 绵阳市2019—2021年流感共报告发病55 970例,年均报告发病率388.08/10万。报告流感样病例（influenza-like illness cases, ILI） 103 723例,年平均ILI%为3.58%。2019年流感报告发病率、ILI%、阳性检出率均远超过历年同期水平。人群分类构成以15岁以下学生为主。报告发病数居前三位的地区分别为涪城区20 118例（占35.94%）、游仙区6 394例（占11.42%）、江油市5 800例（占10.36%）。2019—2021年共收到并检测ILI标本10 126份,阳性率19.53%;标本阳性检出率以15岁以下学生为主。历年流感病毒优势毒株呈现出交替流行的趋势,2019年以A（H3）型为主,2020年受新冠疫情影响,全年阳性检出率均较低,2021年除检出2份A（H9）型外,其余均为BV型。2019—2021年共报告ILI暴发疫情43起,发生时间主要集中在冬季,场所以小学居多。结论 2019—2021年绵阳市流感病例、ILI、病原学监测、暴发疫情的特征基本一致,15岁以下的学生及学校仍为重点关注人群及场所。而新型冠状病毒肺炎疫情大流行下,流感的低发水平进一步印证非药物干预措施对流感防控工作的重要性。     

Influence of epidemiological factors on blood transfusion

The prevalence, incidence and risk factors of infectious diseases observed in the general population have been described to directly influence transfusion medicine, especially the blood selection. The objective is to ensure the blood safety. The characterization of modes of transmission influences the donor selection: the risk factors of the main blood‐borne infections have permitted to adapt the pre‐donation questionnaire in order to exclude at‐risk donors. The prevalence of infections also has an impact on the blood screening strategy. For example, anti‐HBc antibody (Ab) screening is currently performed only in countries where the HBV prevalence is compatible with a reasonable number of donor exclusions. HTLV Ab screening is implemented in countries in which the rate of donors originating from endemic areas could represent a risk for blood components. Measurement of incidence which contributes to the residual risk has led to the introduction of nucleic acid testing (NAT) for HIV, HCV and in some cases for HBV in viral screening strategy in many countries worldwide. The observed NAT yield differs according to the incidence of the infection and according to the country. Finally, the putative blood transmission of new and emerging pathogens has led to implement specific and non‐specific measures in order to enhance blood safety. Conversely, although the blood donor population is selected, the data observed in this population have also contributed to better understand epidemiology and pathogenesis of infection. Moreover, owing to the recent progress in developing modelling approaches for estimating risk, we are able to anticipate a transfusion transmission threat by introducing, when necessary, specific measures intended for reduce this risk.     

Psychotropic drug utilization patterns in a metropolitan population

Summary Psychotropic drug intake by a random sample of citizens of the city of Munich aged 30–69 years has been assessed. A 1-week prevalence of 9.3% for all psychotropic drug users was found, benzodiazepines accounting for approximately two-thirds (6.6%) of the users. Two-thirds of drug users were women. Drug use in both sexes increased with age. The doses of benzodiazepines prescribed in most cases were less than 10 mg diazepam equivalent per day. Intake of benzodiazepines in combination with analgesics or alcohol (40 g/day) did not appear to represent a major problem. Multiple logistic regression analysis showed that the number of chronic diseases was the strongest predictor of benzodiazepine intake in men, whereas stress and age determined intake in women. Long-term use seemed to be relatively rare at 11% of all benzodiazepine users, so it was not considered to be a severe public health problem.     

2015—2020年四川省手足口病流行病学特征分析

目的 分析2015—2020年四川省手足口病流行病学及病原学特征,为手足口病的防控提供科学依据。 方法 利用描述流行病学方法对2015—2020年四川省手足口病监测资料进行统计分析。 结果 2015—2020年四川省累计报告手足口病520 147例,重症1 759例,死亡38例,2015—2020年四川省手足口病发病率呈波动状,年均发病率为104.82/10万,2015—2017和2019年呈现明显的双峰(4—7月和10—12月),2018、2020年呈单峰,发病高峰分别在7—11月和10—12月;年龄以 5 岁及以下儿童为主,男女性别比为1.38∶1;发病率居前五位的地区是成都市(221.25/10万)、眉山市(145.51/10万)、德阳市(115.52/10万)、雅安市(108.02/10万)和遂宁市(100.56/10);共报告实验室确诊病例44 410例,其中其他肠道病毒、CoxA16、EV71分别占65.53%、22.35%、12.12% 。 结论 2015—2020年四川省手足口病发病水平呈上升趋势,防控压力逐渐加大。四川省手足口病发病以5岁以下儿童为主,成都及周边,川东北发病率较高,优势病原分型构成发生变化,其他肠道病毒比重逐渐提高,病原学监测工作需要调整。     

2010—2020年云南省学校食源性疾病暴发事件流行病学分析

目的 了解云南省学校食源性疾病暴发事件流行病学特征和趋势。 方法 收集2010—2020年云南省各地报告的学校食源性疾病暴发资料,并进行描述性流行病学分析。 结果 2010—2020年共发生学校食源性疾病暴发260起,发病6 600人,死亡2人,总体呈下降趋势。学校食源性疾病暴发高峰期为第二、四季度,占总起数的66.54%(173/260);暴发场所多发生在小学,占总起数的58.08%(151/260)。报告明确或可疑致病因子的185起事件中由微生物或可疑微生物引起的占40.00%(74/185),毒素引起的占46.49%(86/185);明确致病因子的118起暴发事件中,60.17%(71/118)是由4种致病因子引起的,其中蓖麻毒素导致的最多,达22起(18.64%),发病人数428人,其次是蜡样芽孢杆菌20起(16.95%),原因食品被归因为一类食品植物类,主要是大米、三明治、面包。导致暴发污染环节最多的是生产加工环节(50.77%,132/260)。 结论 关注学校食源性疾病暴发事件流行特征,在学生开学季时,加强对小学食堂植物类食品的生产加工环节管理和监督。微生物、毒素感染是学校食源性疾病主要的致病因素,且原因查明率低,进一步强化医疗机构食源性疾病微生物、毒素检测能力,提高原因查明率,最大限度地降低学校食源性疾病的发病率。