Search

The aim of study was to evaluate completeness and estimate sensitivity of the measles surveillance using the new electronic version of the national notification system of infectious diseases (ISIN) in order to assess its performance.The completeness of measles reporting in the ISIN for demographic characteristics (week and region of reporting, age and gender), date of onset, complications, hospitalisations, vaccination status, used laboratory methods and country of import from January 2018 to June 2019 was assessed. The register from National Reference Laboratory (NRL) and the ISIN were compared using the capture-recapture method (CRM). Cases were matched using unique personal identifier. The total number of measles cases in the population was assessed using the Chapmans formula. Sensitivity of reporting was calculated by dividing the number of reported cases by the CRM estimated true number of cases.In the ISIN, 765 measles cases were registered within specified time period. For many variables 100% completeness was found. The data were missing mainly for vaccination status (20%), serology results (55%) and used laboratory methods (8%). The NRL confirmed 653 patient samples in respected period. Within both registries (ISIN and NRL) the total 612 cases were matched. Estimated real number of measles cases using the CRM was 816 (95% CI: 809-823) compared to 806 reported cases. The estimated surveillance system sensitivity was 98.8%. Five percent (n = 41) of cases tested positively in the NRL were not reported to the ISIN.We found high level of reported measles data completeness in the ISIN for most variables. Estimated real and reported number of cases was in a good correlation and calculated sensitivity of the ISIN was on very high level. Though, the data sources used in the study were not independent on each other, therefore results may not be fully accurate. The technical changes (more mandatory fields and more logical syntax to check data) in the ISIN to improve data completeness are being recommended. Data providers should report all measles cases to the ISIN with maximum precision in entering individual variables and investigating laboratories should send samples for confirmation to the NRL in required cases.

The primary objective of the SAVIAH, a multi-centre study funded by European Union, was to assess new methodology for study of small area health statistics and to implement it in epidemiological health statistics and geography. In Prague, the study has been conducted in two city districts with large variation in air pollution. Data at individual level (health symptoms and socio-economic circumstances of the family) were collected by questionnaires completed by parents of 3680 children aged 7-10 both resident and attending schools within the area (response rate 88%). Aggregated data for geographical areas were available from census and urban planning sources for 692 enumeration districts in the study area which were aggregated into 75 medium sized areas. Outdoor concentrations of nitrogen dioxide (NO2) were monitored by passive samplers. All these data were integrated into a geographic information system (GIS). Spatial distribution of air pollution was estimated by kriging and multiple regression modelling. These models explained about 80% of the variation in air pollution measured by passive samplers. GIS was then used to assign to individuals an exposure based on place of residence and school in order to conduct individual based analyses. Association between NO2 and life-time prevalence of wheezing and/or whistling, and wheezing/whistling in the last 12 months was studied by logistic regression. For both outcomes, school levels of NO2 were positively related to symptoms but home levels of NO2 showed a negative association. Logistic regression at individual level gives similar results as ecological analysis and multilevel modelling. Hierarchical model yielded somewhat wider confidence limits. Adjustment for parental behavioural and socio-economic factors did not affect these estimates substantially. This study demonstrated the power of the GIS methodology in studying the effects of complex environmental factors on respiratory health of children.