ABSTRACT
Safety on vaccine issues has been under greater concern.Epidemiologically,classical study designs on investigating the association between a rare adverse event and vaccine inoculation usually confronted with lower feasibility in practice.Self-controlled case series (SCCS) method was derived from cohort studies.The key advantage of this method is that it only uses data related to cases and trying to find relative incidence of events in the ‘ at risk' periods relative to the ‘ controlled' periods.A further benefit of this method is that all the fixed confounders are controlled implicitly,by self-control,thus provides high statistic powers.With these advantages,SCCS is suitable for the causality assessment on rare but severe adverse events caused by immunization,which has been widely used,abroad.However,the methodology of SCCS is still being developed,and the areas in use have been expanded to the studies related to the safety and effectiveness of drugs,efficacy of vaccines as well as risk factors of disease.
ABSTRACT
<p><b>OBJECTIVE</b>forecast the epidemic trend and to evaluate the effect of outbreak control measures by investigation of a varicella outbreak event with a discrete time delay SEIR model.</p><p><b>METHODS</b>A discrete time delay model was formulated by discretization method based on a continuous SEIR model with the consideration of the time delay effect on latent period and communicable period. The epidemic trend forecast was carried out based on the number of expected cases. The theoretical effect evaluation was assessed by comparing the results from different emergency control measures.</p><p><b>RESULTS</b>Without any control measures, the theoretical attack rate was 30.16% (504/1671). The course of the epidemic lasted for 4 months and the peak epidemic time was 78 days after the onset of the first case. 'Generation' phenomenon had been observed in the course of the epidemic with the interval of two weeks. The actual number of cases was decreased by 89.48% (451/504) compared with the number of expected cases under no control measure scenario. With the rigorous quarantine measure for all cases on their onset day, when the measure was conducted on 0, 14, 28, 42 days after the onset of the first case, the total numbers of expected cases were 22, 59, 127 and 220 respectively. With the quarantine measure conducted on 14 days after the onset of the first case, when the proportion of quarantine was 30%, 50%, 70%, 90%, the total number of expected cases were 485, 457, 386 and 169, respectively. With the emergent vaccination for all persons, when the measure was conducted on 0, 14, 28, 42 days after the onset of the first case, the total numbers of expected cases were 7, 26, 81 and 202 respectively. With the emergent vaccination conducted on 14 days after the onset of the first case, when the immunization coverage rate was 30%, 50%, 70%, 90%, the total numbers of expected cases were 354, 246, 127 and 40, respectively.</p><p><b>CONCLUSION</b>The number of expected cases can be regarded as the reference to evaluate the effect of control measures. The simulation results suggest that it will get more benefits to conduct control measures earlier in varicella outbreak events, and the effect of emergent vaccination is better than that of quarantine measure under the same conditions.</p>
Subject(s)
Humans , Chickenpox , Epidemiology , Communicable Disease Control , Methods , Disease Outbreaks , Incidence , Models, TheoreticalABSTRACT
For most variety of vaccines, two types of effects-direct and indirect, can result from immunization programs. Unimmunized individuals in the population that receive immunization program can benefit from the vaccines in addition to the protection from immunization.The classical vaccine trails allocate individuals into study and control arms with individual randomization, so the programs' cost-benefit is underestimated due to the impossible measurement on indirect effect. The objectives of the present work are to introduce the conceptual framework,developed by Halloran et al, for four types of study designs that differentiate and account for direct,indirect, total and overall effects of intervention programs, and to explain the relationships of these effects as well. With the examples of field trails of oral cholera vaccines in Bangladesh and Vi typhoid vaccine in India, further issues refer to the identification of indirect effect. The application in practice is also discussed.
ABSTRACT
Interaction assessment is an important step in epidemiological analysis. When etiological study is carried out, the logarithmic models such as logistic model or Cox proportional hazard model are commonly used to estimate the independent effects of the risk factors. However,estimating interaction between risk factors by the regression coefficient of the product term is on multiplicative scale, and for public-health purposes, it is supposed to be on additive scale or departure from additivity. This paper illustrates with a example of cohort study by fitting Cox proportional hazard model to estimate three measures for additive interaction which presented by Rothman.Adopting the S-Plus application with a built-in Bootstrap function, it is convenient to estimate the confidence interval for additive interaction. Furthermore, this method can avoid the exaggerated estimation by using ORs in a cohort study to gain better precision. When using the complex combination models between additive interaction and multiplicative interaction, it is reasonable to choose the former one when the result is inconsistent.