The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis.

Tuberculosis (TB) remains a global leading cause of death, necessitating an investigation into its unequal distribution. Sun exposure, linked to vitamin D (VD) synthesis, has been proposed as a protective factor. This study aimed to analyse TB rates in Spain over time and space and explore their relationship with sunlight exposure. An ecological study examined the associations between rainfall, sunshine hours, and TB incidence in Spain. Data from the National Epidemiological Surveillance Network (RENAVE in Spanish) and the Spanish Meteorological Agency (AEMET in Spanish) from 2012 to 2020 were utilized. Correlation and spatial regression analyses were conducted. Between 2012 and 2020, 43,419 non-imported TB cases were reported. A geographic pattern (north-south) and distinct seasonality (spring peaks and autumn troughs) were observed. Sunshine hours and rainfall displayed a strong negative correlation. Spatial regression and seasonal models identified a negative correlation between TB incidence and sunshine hours, with a four-month lag. A clear spatiotemporal association between TB incidence and sunshine hours emerged in Spain from 2012 to 2020. VD levels likely mediate this relationship, being influenced by sunlight exposure and TB development. Further research is warranted to elucidate the causal pathway and inform public health strategies for improved TB control.

Epidemiology of Q fever in humans in four selected regions, Spain, 2016 to 2022.

BackgroundQ fever is a bacterial zoonosis caused by Coxiella burnetii. Spain has the highest number of notified human cases in Europe. Small ruminants are a key reservoir for the pathogen, transmission from animals to humans is usually airborne.AimWe aimed at exploring temporal and spatial epidemiological patterns of sporadic and outbreak cases of Q fever in four Spanish regions with the highest number of notified cases.MethodsWe extracted data on Q fever cases in the Canary Islands, Basque Country, La Rioja and Navarre between 2016 and 2022 from the Spanish National Epidemiological Surveillance Network. We calculated standardised incidence ratios (SIR), spatial relative risks (sRR) and posterior probabilities (PP) utilising Besag-York-Mollié models.ResultsThere were 1,059 notifications, with a predominance of males aged 30-60 years. In Basque Country, La Rioja and Navarre area, 11 outbreaks were reported, while no in the Canary Islands. A seasonal increase in incidence rates was observed between March and June. In the Canary Islands, elevated sRR was seen in La Palma, Gran Canaria, Lanzarote and Fuerteventura. In Basque Country, La Rioja and Navarre area, the highest sRR was identified in the south of Biscay province.ConclusionGoats were the main source for humans in outbreaks reported in the literature. Seasonal increase may be related to the parturition season of small ruminants and specific environmental conditions. Local variations in sRR within these regions likely result from diverse environmental factors. Future One Health-oriented studies are essential to deepen our understanding of Q fever epidemiology.

Excess mortality in Europe coincides with peaks of COVID-19, influenza and respiratory syncytial virus (RSV), November 2023 to February 2024.

Since the end of November 2023, the European Mortality Monitoring Network (EuroMOMO) has observed excess mortality in Europe. During weeks 48 2023-6 2024, preliminary results show a substantially increased rate of 95.3 (95% CI:  91.7-98.9) excess all-cause deaths per 100,000 person-years for all ages. This excess mortality is seen in adults aged 45 years and older, and coincides with widespread presence of COVID-19, influenza and respiratory syncytial virus (RSV) observed in many European countries during the 2023/24 winter season.

Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data.

When responding to infectious disease outbreaks, rapid and accurate estimation of the epidemic trajectory is critical. However, two common data collection problems affect the reliability of the epidemiological data in real time: missing information on the time of first symptoms, and retrospective revision of historical information, including right censoring. Here, we propose an approach to construct epidemic curves in near real time that addresses these two challenges by 1) imputation of dates of symptom onset for reported cases using a dynamically-estimated "backward" reporting delay conditional distribution, and 2) adjustment for right censoring using the NobBS software package to nowcast cases by date of symptom onset. This process allows us to obtain an approximation of the time-varying reproduction number (Rt) in real time. We apply this approach to characterize the early SARS-CoV-2 outbreak in two Spanish regions between March and April 2020. We evaluate how these real-time estimates compare with more complete epidemiological data that became available later. We explore the impact of the different assumptions on the estimates, and compare our estimates with those obtained from commonly used surveillance approaches. Our framework can help improve accuracy, quantify uncertainty, and evaluate frequently unstated assumptions when recovering the epidemic curves from limited data obtained from public health systems in other locations.

Estimates of mpox effective reproduction number in Spain, April-August 2022.

We analysed the transmission of the human mpox virus in Spain by estimating the effective reproduction number of the disease from official surveillance data. Our computations show that this decreased steadily after an initial burst phase, dropping below 1 on July 12, and thus the outbreak was expected to reduce in the following weeks. Differences in trends were found across geographical regions of the country and across MSM and heterosexual populations.

Meteorological conditions and Legionnaires' disease sporadic cases-a systematic review.

A number of studies suggest that meteorological conditions are related to the risk of Legionnaires' disease (LD) but the findings are not consistent. A systematic review was conducted to investigate the association of weather with sporadic LD and highlight the key meteorological conditions related to this outcome. PubMed, EMBASE, The Cochrane Library and OpenGrey were searched on 26-27 March 2020 without date, language or location restrictions. Key words included "legionellosis", "legionnaires' disease", combined with "meteorological conditions", "weather", "temperature", "humidity", "rain", "ultraviolet rays", "wind speed", etc. Studies were excluded if they did not examine the exposure of interest, the outcome of interest and their association or if they only reported LD outbreak cases. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and it was registered in PROSPERO (#CRD42020168869). There were 811 articles, of which 17 were included in the review. The studies investigated different meteorological variables and most of them examined the combined effect of several variables. The most commonly examined factors were precipitation and temperature, followed by relative humidity. The studies suggested that increased precipitation, temperature and relative humidity were positively associated with the incidence of LD. There was limited evidence that higher wind speed, pressure, visibility, UV radiation and longer sunshine duration were inversely linked with the occurrence of LD. A period of increased but not very high temperatures, followed by a period of increased precipitation, favour the occurrence of LD. Increased awareness of the association of temperature and precipitation and LD occurrence among clinicians and public health professionals can improve differential diagnosis for cases of sporadic community-acquired pneumonia and at the same time contribute to improving LD surveillance.

Socioeconomic differences in COVID-19 infection, hospitalisation and mortality in urban areas in a region in the South of Europe.

BACKGROUND: To analyse differences in confirmed cases, hospitalisations and deaths due to COVID-19 related to census section socioeconomic variables.  METHODS: Ecological study in the 12 largest municipalities in Andalusia (Spain) during the first three epidemic waves of the COVID-19 (02/26/20-03/31/21), covering 2,246 census sections (unit of analysis) and 3,027,000 inhabitants. Incidence was calculated, standardised by age and sex, for infection, hospitalisation and deaths based on average gross income per household (AGI) for the census tracts in each urban area. Association studied using a Poisson Bayesian regression model with random effects for spatial smoothing. RESULTS: There were 140,743 cases of COVID-19, of which 12,585 were hospitalised and 2,255 died. 95.2% of cases were attributed to the second and third waves, which were jointly analysed. We observed a protective effect of income for infection in 3/12 cities. Almeria had the largest protective effect (smoothed relative risk (SRR) = 0.84 (0.75-0.94 CI 95%). This relationship reappeared with greater magnitude in 10/12 cities for hospitalisation, lowest risk in Algeciras SRR = 0.41 (0.29-0.56). The pattern was repeated for deaths in all urban areas and reached statistical significance in 8 cities. Lowest risk in Dos Hermanas SRR = 0.35 (0.15-0.81). CONCLUSIONS: Income inequalities by geographical area were found in the incidence of COVID-19. The strengths of the association increased when analysing the severe outcomes of hospitalisations and, above all, deaths.

Assessing the effect of non-pharmaceutical interventions on COVID-19 transmission in Spain, 30 August 2020 to 31 January 2021.

BackgroundAfter a national lockdown during the first wave of the COVID-19 pandemic in Spain, regional governments implemented different non-pharmaceutical interventions (NPIs) during the second wave.AimTo analyse which implemented NPIs significantly impacted effective reproduction number (Rt) in seven Spanish provinces during 30 August 2020-31 January 2021.MethodsWe coded each NPI and levels of stringency with a 'severity index' (SI) and computed a global SI (mean of SIs per six included interventions). We performed a Bayesian change point analysis on the Rt curve of each province to identify possible associations with global SI variations. We fitted and compared several generalised additive models using multimodel inference, to quantify the statistical effect on Rt of the global SI (stringency) and the individual SIs (separate effect of NPIs).ResultsThe global SI had a significant lowering effect on the Rt (mean: 0.16 ± 0.05 units for full stringency). Mandatory closing times for non-essential businesses, limited gatherings, and restricted outdoors seating capacities (negative) as well as curfews (positive) were the only NPIs with a significant effect. Regional mobility restrictions and limited indoors seating capacity showed no effect. Our results were consistent with a 1- to 3-week-delayed Rt as a response variable.ConclusionWhile response measures implemented during the second COVID-19 wave contributed substantially to a decreased reproduction number, the effectiveness of measures varied considerably. Our findings should be considered for future interventions, as social and economic consequences could be minimised by considering only measures proven effective.

Real time surveillance of COVID-19 space and time clusters during the summer 2020 in Spain.

BACKGROUND: On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. AIM: To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. METHODS: A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf's prospective space-time scan statistic (STSS) to detect daily emerging active clusters. RESULTS: Analyses were performed daily during the summer 2020 (June 21st - August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. CONCLUSION: STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.

Evaluating the impact of the weather conditions on the influenza propagation.

BACKGROUND: Predicting the details of how an epidemic evolves is highly valuable as health institutions need to better plan towards limiting the infection propagation effects and optimizing their prediction and response capabilities. Simulation is a cost- and time-effective way of predicting the evolution of the infection as the joint influence of many different factors: interaction patterns, personal characteristics, travel patterns, meteorological conditions, previous vaccination, etc. The work presented in this paper extends EpiGraph, our influenza epidemic simulator, by introducing a meteorological model as a modular component that interacts with the rest of EpiGraph's modules to refine our previous simulation results. Our goal is to estimate the effects of changes in temperature and relative humidity on the patterns of epidemic influenza based on data provided by the Spanish Influenza Sentinel Surveillance System (SISSS) and the Spanish Meteorological Agency (AEMET). METHODS: Our meteorological model is based on the regression model developed by AB and JS, and it is tuned with influenza surveillance data obtained from SISSS. After pre-processing this data to clean it and reconstruct missing samples, we obtain new values for the reproduction number of each urban region in Spain, every 10 minutes during 2011. We simulate the propagation of the influenza by setting the date of the epidemic onset and the initial influenza-illness rates for each urban region. RESULTS: We show that the simulation results have the same propagation shape as the weekly influenza rates as recorded by SISSS. We perform experiments for a realistic scenario based on actual meteorological data from 2010-2011, and for synthetic values assumed under simplified predicted climate change conditions. Results show that a diminishing relative humidity of 10% produces an increment of about 1.6% in the final infection rate. The effect of temperature changes on the infection spread is also noticeable, with a decrease of 1.1% per extra degree. CONCLUSIONS: Using a tool like ours could help predict the shape of developing epidemics and its peaks, and would permit to quickly run scenarios to determine the evolution of the epidemic under different conditions. We make EpiGraph source code and epidemic data publicly available.

Environmental drivers, climate change and emergent diseases transmitted by mosquitoes and their vectors in southern Europe: A systematic review.

Mosquito borne diseases are a group of infections that affect humans. Emerging or reemerging diseases are those that (re)occur in regions, groups or hosts that were previously free from these diseases: dengue virus; chikungunya virus; Zika virus; West Nile fever and malaria. In Europe, these infections are mostly imported; however, due to the presence of competent mosquitoes and the number of trips both to and from endemic areas, these pathogens are potentially emergent or re-emergent. Present and future climatic conditions, as well as meteorological, environmental and demographic aspects are risk factors for the distribution of different vectors and/or diseases. This review aimed to identify and analyze the existing literature on the transmission of mosquito borne diseases and those factors potentially affecting their transmission risk of them in six southern European countries with similar environmental conditions: Croatia, France, Greece, Italy, Portugal and Spain. In addition, we would identify those factors potentially affecting the (re)introduction or spread of mosquito vectors. This task has been undertaken with a focus on the environmental and climatic factors, including the effects of climate change. We undertook a systematic review of the vectors, diseases and their associations with climactic and environmental factors in European countries of the Mediterranean region. We followed the PRISMA guidelines and used explicit and systematic methods to identify, select and critically evaluate the studies which were relevant to the topic. We identified 1302 articles in the first search of the databases. Of those, 160 were selected for full-text review. The final data set included 61 articles published between 2000 and 2017.39.3% of the papers were related with dengue, chikungunya and Zika virus or their vectors. Temperature, precipitation and population density were key factors among others. 32.8% studied West Nile virus and its vectors, being temperature, precipitation and NDVI the most frequently used variables. Malaria have been studied in 23% of the articles, with temperature, precipitation and presence of water indexes as the most used variables. The number of publications focused on mosquito borne diseases is increasing in recent years, reflecting the increased interest in that diseases in southern European countries. Climatic and environmental variables are key factors on mosquitoes' distribution and to show the risk of emergence and/or spread of emergent diseases and to study the spatial changes in that distributions.

Imported cases of malaria in Spain: observational study using nationally reported statistics and surveillance data, 2002-2015.

BACKGROUND: Malaria was eliminated in Spain in 1964. Since then, more than 10,000 cases of malaria have been reported, mostly in travellers and migrants, making it the most frequently imported disease into this country. In order to improve knowledge on imported malaria cases characteristics, the two main malaria data sources were assessed: the national surveillance system and the hospital discharge database (CMBD). METHODS: Observational study using prospectively gathered surveillance data and CMBD records between 2002 and 2015. The average number of hospitalizations per year was calculated to assess temporal patterns. Socio-demographic, clinical and travel background information were analysed. Bivariate and multivariable statistical methods were employed to evaluate hospitalization risk, fatal outcome, continent of infection and chemoprophylaxis failure and their association with different factors. RESULTS: A total of 9513 malaria hospital discharges and 7421 reported malaria cases were identified. The number of reported cases was below the number of hospitalizations during the whole study period, with a steady increase trend in both databases since 2008. Males aged 25-44 were the most represented in both data sources. Most frequent related co-diagnoses were anaemia (20.2%) and thrombocytopaenia (15.4%). The risks of fatal outcome increased with age and were associated with the parasite species (Plasmodium falciparum). The main place of infection was Africa (88.9%), particularly Equatorial Guinea (33.2%). Most reported cases were visiting friends and relatives (VFRs) and immigrants (70.2%). A significant increased likelihood of hospitalization was observed for children under 10 years (aOR:2.7; 95% CI 1.9-3.9), those infected by Plasmodium vivax (4.3; 95% CI 2.1-8.7) and travellers VFRs (1.4; 95% CI 1.1-1.7). Only 4% of cases reported a correct regime of chemoprophylaxis. Being male, over 15 years, VFRs, migrant and born in an endemic country were associated to increased risk of failure in preventive chemotherapy. CONCLUSIONS: The joint analysis of two data sources allowed for better characterization of imported malaria profile in Spain. Despite the availability of highly effective preventive measures, the preventable burden from malaria is high in Spain. Pre-travel advice and appropriately delivered preventive messages needs to be improved, particularly in migrants and VFRs.

Methodological approaches to the study of cancer risk in the vicinity of pollution sources: the experience of a population-based case-control study of childhood cancer.

BACKGROUND: Environmental exposures are related to the risk of some types of cancer, and children are the most vulnerable group of people. This study seeks to present the methodological approaches used in the papers of our group about risk of childhood cancers in the vicinity of pollution sources (industrial and urban sites). A population-based case-control study of incident childhood cancers in Spain and their relationship with residential proximity to industrial and urban areas was designed. Two methodological approaches using mixed multiple unconditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) were developed: (a) "near vs. far" analysis, where possible excess risks of cancers in children living near ("near") versus those living far ("far") from industrial and urban areas were assessed; and (b) "risk gradient" analysis, where the risk gradient in the vicinity of industries was assessed. For each one of the two approaches, three strategies of analysis were implemented: "joint", "stratified", and "individualized" analysis. Incident cases were obtained from the Spanish Registry of Childhood Cancer (between 1996 and 2011). RESULTS: Applying this methodology, associations between proximity (≤ 2 km) to specific industrial and urban zones and risk (OR; 95% CI) of leukemias (1.31; 1.04-1.65 for industrial areas, and 1.28; 1.00-1.53 for urban areas), neuroblastoma (2.12; 1.18-3.83 for both industrial and urban areas), and renal (2.02; 1.16-3.52 for industrial areas) and bone (4.02; 1.73-9.34 for urban areas) tumors have been suggested. CONCLUSIONS: The two methodological approaches were used as a very useful and flexible tool to analyze the excess risk of childhood cancers in the vicinity of industrial and urban areas, which can be extrapolated and generalized to other cancers and chronic diseases, and adapted to other types of pollution sources.

Non-imported malaria in non-endemic countries: a review of cases in Spain.

Spain declared the elimination of malaria in 1964. In non-endemic areas, the overwhelming majority of malaria cases are acquired abroad, and locally acquired infections are rare events. In Spain, malaria is a statutorily notifiable disease. During these fifty years more than ten thousand malaria cases have been reported, and about 0.8% of them did not have a history of recent travel. In this report, it was carried out a review of the ways in which malaria can be transmitted in non-endemic areas and a short description of the Spanish cases, aggregated by their transmission mechanisms. Four cases contracted malaria by mosquito bites; there were two autochthonous cases and two of "airport malaria". The other 28 cases were: congenital malaria cases, transfusion-transmitted malaria, post-transplant cases, nosocomial transmission and cases in intravenous drug users. In addition, in 1971 there was an outbreak of 54 cases due to exposure to blood or blood products. So, while malaria usually is an imported disease in non-endemic areas, it should not be excluded in the differential diagnosis of persons who have fever of unknown origin, regardless of their travel history.

Spatial clustering and risk factors of malaria infections in Bata district, Equatorial Guinea.

BACKGROUND: The transmission of malaria is intense in the majority of the countries of sub-Saharan Africa, particularly in those that are located along the Equatorial strip. The present study aimed to describe the current distribution of malaria prevalence among children and its environment-related factors as well as to detect malaria spatial clusters in the district of Bata, in Equatorial Guinea. METHODS: From June to August 2013 a representative cross-sectional survey using a multistage, stratified, cluster-selected sample was carried out of children in urban and rural areas of Bata District. All children were tested for malaria using rapid diagnostic tests (RDTs). Results were linked to each household by global position system data. Two cluster analysis methods were used: hot spot analysis using the Getis-Ord Gi statistic, and the SaTScan™ spatial statistic estimates, based on the assumption of a Poisson distribution to detect spatial clusters. In addition, univariate associations and Poisson regression model were used to explore the association between malaria prevalence at household level with different environmental factors. RESULTS: A total of 1416 children aged 2 months to 15 years living in 417 households were included in this study. Malaria prevalence by RDTs was 47.53%, being highest in the age group 6-15 years (63.24%, p < 0.001). Those children living in rural areas were there malaria risk is greater (65.81%) (p < 0.001). Malaria prevalence was higher in those houses located <1 km from a river and <3 km to a forest (IRR: 1.31; 95% CI 1.13-1.51 and IRR: 1.44; 95% CI 1.25-1.66, respectively). Poisson regression analysis also showed a decrease in malaria prevalence with altitude (IRR: 0.73; 95% CI 0.62-0.86). A significant cluster inland of the district, in rural areas has been found. CONCLUSIONS: This study reveals a high prevalence of RDT-based malaria among children in Bata district. Those households situated in inland rural areas, near to a river, a green area and/or at low altitude were a risk factor for malaria. Spatial tools can help policy makers to promote new recommendations for malaria control.

Association between residential proximity to environmental pollution sources and childhood renal tumors.

BACKGROUND: Few risk factors for childhood renal tumors are well established. While a small fraction of cases might be attributable to susceptibility genes and congenital anomalies, the role of environmental factors needs to be assessed. OBJECTIVES: To explore the possible association between residential proximity to environmental pollution sources (industrial and urban areas, and agricultural crops) and childhood renal cancer, taking into account industrial groups and toxic substances released. METHODS: We conducted a population-based case-control study of childhood renal cancer in Spain, including 213 incident cases gathered from the Spanish Registry of Childhood Tumors (period 1996-2011), and 1278 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the respective subject's residences to the 1271 industries, the 30 urban areas with ≥75,000 inhabitants, and the agricultural crops located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders. RESULTS: Excess risk (OR; 95%CI) of childhood renal tumors was observed for children living near (≤2.5km) industrial installations as a whole (1.97; 1.13-3.42) - particularly glass and mineral fibers (2.69; 1.19-6.08), galvanization (2.66; 1.14-6.22), hazardous waste (2.59; 1.25-5.37), ceramic (2.35; 1.06-5.21), surface treatment of metals (2.25; 1.24-4.08), organic chemical industry (2.22; 1.15-4.26), food and beverage sector (2.19; 1.18-4.07), urban and waste-water treatment plants (2.14; 1.07-4.30), and production and processing of metals (1.98; 1.03-3.82) -, and in the proximity of agricultural crops (3.16; 1.54-8.89 for children with percentage of crop surface ≥24.35% in a 1-km buffer around their residences). CONCLUSIONS: Our study provides some epidemiological evidence that living near certain industrial areas and agricultural crops may be a risk factor for childhood renal cancer.

Residential proximity to environmental pollution sources and risk of rare tumors in children.

BACKGROUND: Few epidemiologic studies have explored risk factors for rare tumors in children, and the role of environmental factors needs to be assessed. OBJECTIVES: To ascertain the effect of residential proximity to both industrial and urban areas on childhood cancer risk, taking industrial groups into account. METHODS: We conducted a population-based case-control study of five childhood cancers in Spain (retinoblastoma, hepatic tumors, soft tissue sarcomas, germ cell tumors, and other epithelial neoplasms/melanomas), including 557 incident cases from the Spanish Registry of Childhood Tumors (period 1996-2011), and 3342 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the residences to the 1271 industries and the 30 urban areas with ≥75,000 inhabitants located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to industrial and urban pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders. RESULTS: Children living near industrial and urban areas as a whole showed no excess risk for any of the tumors analyzed. However, isolated statistical associations (OR; 95%CI) were found between retinoblastoma and proximity to industries involved in glass and mineral fibers (2.49; 1.01-6.12 at 3km) and organic chemical industries (2.54; 1.10-5.90 at 2km). Moreover, soft tissue sarcomas registered the lower risks in the environs of industries as a whole (0.59; 0.38-0.93 at 4km). CONCLUSIONS: We have found isolated statistical associations between retinoblastoma and proximity to industries involved in glass and mineral fibers and organic chemical industries.

Agricultural crop exposure and risk of childhood cancer: new findings from a case-control study in Spain.

BACKGROUND: Childhood cancer is the main cause of disease-related death in children in Spain. Although little is known about the etiology, environmental factors are potential explanations for a fraction of the cases. Previous studies have shown pesticides to be associated with childhood cancer. The difficulty of collecting personal environmental exposure data is an important limitation; this lack of information about pesticides motivates the development of new methods to subrogate this exposure. We developed a crop exposure index based on geographic information to study the relationship between exposure to different types of crops and risk of childhood tumors. METHODS: We conducted a population-based case-control study of childhood cancer covering 3350 cases and 20,365 controls in two Spanish regions. We used CORINE Land Cover to obtain data about agricultural land use. We created a 1 km buffer around every child and calculated the percentage of crop surface within the buffer (Global Crop Index) for total crops and for individual types of crops. We fitted mixed multiple unconditional logistic regression models by diagnostic group. RESULTS: We found excess of risk among children living in the proximity of crops. For total crops our results showed excesses of risk for almost all diagnostic groups and increasing risk with increasing crop index value. Analyses by region and individual type of crop also showed excess of risk. CONCLUSION: The results suggest that living in the proximity of cultivated land could be a risk factor for several types of cancer in children.

Childhood leukemia and residential proximity to industrial and urban sites.

BACKGROUND: Few risk factors for the childhood leukemia are well established. While a small fraction of cases of childhood leukemia might be partially attributable to some diseases or ionizing radiation exposure, the role of industrial and urban pollution also needs to be assessed. OBJECTIVES: To ascertain the possible effect of residential proximity to both industrial and urban areas on childhood leukemia, taking into account industrial groups and toxic substances released. METHODS: We conducted a population-based case-control study of childhood leukemia in Spain, covering 638 incident cases gathered from the Spanish Registry of Childhood Tumors and for those Autonomous Regions with 100% coverage (period 1990-2011), and 13,188 controls, individually matched by year of birth, sex, and autonomous region of residence. Distances were computed from the respective subject's residences to the 1068 industries and the 157 urban areas with ≥10,000 inhabitants, located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance to industrial and urban pollution sources were calculated, with adjustment for matching variables. RESULTS: Excess risk of childhood leukemia was observed for children living near (≤2.5 km) industries (OR=1.31; 95%CI=1.03-1.67) - particularly glass and mineral fibers (OR=2.42; 95%CI=1.49-3.92), surface treatment using organic solvents (OR=1.87; 95%CI=1.24-2.83), galvanization (OR=1.86; 95%CI=1.07-3.21), production and processing of metals (OR=1.69; 95%CI=1.22-2.34), and surface treatment of metals (OR=1.62; 95%CI=1.22-2.15) - , and urban areas (OR=1.36; 95%CI=1.02-1.80). CONCLUSIONS: Our study furnishes some evidence that living in the proximity of industrial and urban sites may be a risk factor for childhood leukemia.

Trends in infectious disease mortality rates, Spain, 1980-2011.

Using mortality data from National Institute of Statistics in Spain, we analyzed trends of infectious disease mortality rates in Spain during 1980-2011 to provide information on surveillance and control of infectious diseases. During the study period, 628,673 infectious disease-related deaths occurred, the annual change in the mortality rate was -1.6%, and the average infectious disease mortality rate was 48.5 deaths/100,000 population. Although the beginning of HIV/AIDS epidemic led to an increased mortality rate, a decreased rate was observed by the end of the twentieth century. By codes from the International Classification of Diseases, 9th revision, the most frequent underlying cause of death was pneumonia. Emergence and reemergence of infectious diseases continue to be public health problems despite reduced mortality rates produced by various interventions. Therefore, surveillance and control systems should be reinforced with a goal of providing reliable data for useful decision making.