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Objectives: To study the spatio-temporal distribution of cases of invasive pneumococcal disease (IPD) due to serotypes resistant to erythromycin and its relationship with community consumption of macrolides and childhood vaccination coverage., Methods: We selected IPD cases in adults over 59 years old, residents in the Community of Madrid (MC), notified in the period 2007-2016. The variables studied were obtained from the Vaccination Information Systems and the Pharmaceutical Service. The cut-off point (minimum inhibitory erythromycin concentration > 0.5 mg/L) of the EUCAST classification was used to define erythromycin resistant serotypes. We used JointPoint to estimate the incidence trends by erythromycin resistant serotypes included in the 13-valent vaccine (STPCV13) and not included in it (STnoPCV13). The association of these incidences with the community consumption of macrolides and vaccination coverage was made using Poisson models. Statistical scanning was used for the detection of temporal-spaces clusters of cases., Results: 1936 cases were identified, of which 427 erythromycin resistant serotypes were identified. The incidence of all cases due to resistant serotypes was decreasing (AAPC: -5,40%). During the period studied, the incidence of cases due to erythromycin resistant STPCV13 was decreasing with an annual percentage change (APC): -13.8 and was inversely associated with childhood vaccination coverage (IRR 0.641), while that of cases due to erythromycin resistant STnoPCV13 was ascending (APC): 4.5; and was not associated with coverage. 1 cluster was detected by STnoPCV13 and none by STPCV13 after the date of inclusion of the 13-valent in the childhood vaccination calendar., Conclusions: The decrease in IPD due to resistant STPCV13 was associated with an increase in childhood vaccination coverage. The presence of clusters due to STnoPCV13 after the date of inclusion of the 13-valent vaccine in the childhood vaccination calendar indicates serotypes replacement. The increase in cases of resistant STnoPCV13 could be related to the replacement of vaccine serotypes in nasopharyngeal colonization, facilitated by the consumption of macrolides still at high levels in MC., (Copyright © 2021 Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. Publicado por Elsevier España, S.L.U. All rights reserved.)

Introduction and Objective: Zika virus disease is a challenge for public health due to its rapid spread and potential foetal complications. Although it is imported in Spain, there is a risk of autochthonous transmission due to Aedes albopictus presence. Zika disease and congenital cases have been under surveillance since 2016. The objective of this study is to explore the epidemiology of disease and pregnancies result., Material and Methods: A descriptive study was carried out into cases reported to the National Surveillance Network (RENAVE) during the 30/11/2015 to 31/12/2017 period. The case definition and the survey are included in the RENAVE protocol. The variables were: date; notifying region (Autonomous Community (AC)); pregnancy and its evolution; case classification; mode of transmission; country or region of infection; socio-demographical, clinical and microbiological data. A descriptive analysis of the cases and their distribution according to the other variables was carried out., Results: A total of 512 cases were reported by 17 ACs. 507 were non-congenital, of which 327 (64.5%) were women (52.5% of childbearing age). 403 cases (79.5%) corresponded to 2016 and 193 (38.1%) resided in regions with A. albopictus presence between May and October. 96.1% of imported cases were infected in America (51.7% while visiting relatives). Three cases (3.9%) of congenital Zika virus infection were detected among 77 pregnant women., Conclusions: The evolution of reported cases was in accordance with that of the epidemic in America. The largest group of travellers was young women who travelled to Latin America on family visits. Pregnancy monitoring resulted in the identification of Zika related foetal complications., (Copyright © 2019 Elsevier España, S.L.U. All rights reserved.)

Objective: To estimate the areas of greatest density of road traffic accidents with fatalities at 24 hours per km(2)/year in Spain from 2008 to 2011, using a geographic information system., Methods: Accidents were geocodified using the road and kilometer points where they occurred. The average nearest neighbor was calculated to detect possible clusters and to obtain the bandwidth for kernel density estimation., Results: A total of 4775 accidents were analyzed, of which 73.3% occurred on conventional roads. The estimated average distance between accidents was 1,242 meters, and the average expected distance was 10,738 meters. The nearest neighbor index was 0.11, indicating that there were aggregations of accidents in space. A map showing the kernel density was obtained with a resolution of 1 km(2), which identified the areas of highest density., Conclusions: This methodology allowed a better approximation to locating accident risks by taking into account kilometer points. The map shows areas where there was a greater density of accidents. This could be an advantage in decision-making by the relevant authorities., (Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.)

Objective: An excess of mortality was detected in Spain in February and March 2012 by the Spanish daily mortality surveillance system and the «European monitoring of excess mortality for public health action» program. The objective of this article was to determine whether this excess could be attributed to influenza in this period., Methods: Excess mortality from all causes from 2006 to 2012 were studied using time series in the Spanish daily mortality surveillance system, and Poisson regression in the European mortality surveillance system, as well as the FluMOMO model, which estimates the mortality attributable to influenza. Excess mortality due to influenza and pneumonia attributable to influenza were studied by a modification of the Serfling model. To detect the periods of excess, we compared observed and expected mortality., Results: In February and March 2012, both the Spanish daily mortality surveillance system and the European mortality surveillance system detected a mortality excess of 8,110 and 10,872 deaths (mortality ratio (MR): 1.22 (95% CI:1.21-1.23) and 1.32 (95% CI: 1.29-1.31), respectively). In the 2011-12 season, the FluMOMO model identified the maximum percentage (97%) of deaths attributable to influenza in people older than 64 years with respect to the mortality total associated with influenza (13,822 deaths). The rate of excess mortality due to influenza and pneumonia and respiratory causes in people older than 64 years, obtained by the Serfling model, also reached a peak in the 2011-2012 season: 18.07 and 77.20, deaths per 100,000 inhabitants, respectively., Conclusion: A significant increase in mortality in elderly people in Spain was detected by the Spanish daily mortality surveillance system and by the European mortality surveillance system in the winter of 2012, coinciding with a late influenza season, with a predominance of the A(H3N2) virus, and a cold wave in Spain. This study suggests that influenza could have been one of the main factors contributing to the mortality excess observed in the winter of 2012 in Spain., (Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background: Cardiovascular disease is the leading cause of death worldwide, but its spatial distribution is not homogeneous. The objective of this study is to analyze the spatial pattern of mortality from these diseases for men and women, in the populated urban area (AUP) of the municipality of Madrid, and to identify spatial aggregations., Methods: An ecological study was carried out by census tract, for men and women in 2010. Standardized Mortality Ratio (SMR), Relative Risk Smoothing (RRS) and Posterior Probability (PP) were calculated to consider the spatial pattern of the disease. To identify spatial clusters the Moran index (Moran I) and the Local Index of Spatial Autocorrelation (LISA) were used. The results were mapped., Results: SMR higher than 1.1 was observed mainly in central areas among men and in peripheral areas among women. The PP that RRS was higher than 1 surpassed 0.8 in the center and in the periphery, in both men and women. Moran's I was 0.04 for men and 0.03 for women (p <0.05 in both cases)., Conclusions: Sex differences were observed in the spatial distribution of mortality cases. RME RRS and PP maps showed a heterogeneous pattern in men, whereas in women a clearer pattern was detected, with a relatively higher risk in peripheral areas of the AUP. The LISA method showed similar patterns to those previously observed.

Objectives: To analyze the spatial pattern of legionellosis in Spain for men and women during the period 2003-2007 and to identify spatial clustering of risk., Methods: We identified the spatial pattern of the distribution of legionellosis rates based on calculation of rates by municipality through the direct method. Smoothing of these rates was performed by the Empirical Bayes method for studying the spatial pattern of disease for both sexes. We used Morańs index to analyze spatial autocorrelation rates globally. To calculate local rates, the Local Moran's Index [known as local indicators of spatial association (LISA)], was used to analyze the clusters of municipalities with the highest risk., Results: After smoothing the risk, the highest rates (over 50 per 100,000 inhabitants) were grouped in the eastern Mediterranean coastal areas and the north of the mainland, as well as in the Mediterranean islands. Moran's index smoothed rates were 0.15 for men and 0.23 for women. The spatial clusters of statistically significant higher rates calculated by the LISA index were distributed in the north and east for both sexes., Conclusions: These methods of spatial analysis allow patterns of disease distribution to be identified. All the methods used yielded similar results. These techniques are a complementary tool for epidemiological surveillance of infectious diseases., (Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.)

Background: Tuberculosis incidence has been associated with many factors, both epidemiological and social. In Spain, tuberculosis is a statutorily notifiable disease requiring individualised reporting. During the last few years rates of respiratory tuberculosis show a steady decline. This study sought to assess respiratory tuberculosis morbidity and mortality in association to socio-economic and epidemiological covariates and estimate its spatial distribution across the country, using geo-statistical methods., Methods: Respiratory tuberculosis incidence rates were standardised by age and sex with the data of the National Epidemiological Surveillance Network (RENAVE, Red Nacional de Vigilancia Epidemiológica) for 2006. The following socio-economic variables were included in the study: socio-economic status, educational level, overcrowding rate, population density, standardised immigration rate by sex, unemployment rate and average spending per person in euros. The epidemiological variables included were, such as, AIDS rate and the influenza incidence rate. To assess the association of covariables a multivariate analysis was performed using a Generalised Linear Model assuming Poisson distribution. The goestatistical method co-kriging was adjusted with the significant variables to built the spatial distribution of risk., Results: The statistically significant covariates were overcrowding rate, standardised immigration rate by sex, educational level, unemployment rate, average spending per person in euros, AIDS rate and the influenza incidence rate. The geostatistical method shows spatial variability of the risk with higher risks in the northwest and southeast of the peninsula., Conclusion: Results prove that the co-kriging method is a useful tool to show the spatial distribution of risk. Alternatively, tuberculosis is associated with both social and epidemiological covariates.