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Background: Social restrictions and vaccination seem to have shaped the pandemic development in Europe, but the influence of geographical position is still debated. This study aims to verify whether the pandemic spread through Europe following a particular direction, during the period between the start of the pandemic and November 2021. The existence of a spatial gradient for epidemic intensity is also hypothesized., Methods: Daily COVID-19 epidemiological data were extracted from Our World in Data COVID-19 database, which also included vaccination and non-pharmacological interventions data. Latitude and longitude of each country's centroid were used as geographic variables. Epidemic periods were delimited from epidemic surge data. Multivariable linear and Cox's regression models were performed for each epidemic period to test if geographical variables influenced surge dates. Generalized additive models (GAM) were used to test the spatial gradient hypothesis with three epidemic intensity measures., Results: Linear models suggest a possible west-east shift in the first epidemic period and features a significant association of NPIs with epidemic surge delay. Neither latitude nor longitude had significant associations with epidemic surge timing in both second and third periods. Latitude displays strong negative associations with all epidemic intensity measures in GAM models. Vaccination was also negatively associated with intensity., Conclusions: A longitudinal spread of the pandemic in Europe seems plausible, particularly concerning the first wave. However, a recurrent trend was not observed. Southern Europe countries may have experienced increased transmissibility and incidence, despite climatic conditions apparently unfavourable to the virus., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Martínez-Portillo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: I have read the journal’s policy and some of the co-authors of this manuscript have the following competing interests: ML discloses honoraria/consulting from Merck, Affinivax, Sanofi-Pasteur, Bristol Myers-Squibb, and Antigen Discovery; research funding (institutional) from Pfizer, and an unpaid scientific advice to Janssen, Astra-Zeneca, One Day Sooner, and Covaxx (United Biomedical). MS discloses having received institutional research support from Johnson and Johnson.The rest of co-authors declare no competing interest.

Introduction: Scabies is a neglected disease stablished worldwide with a fairy well determined incidence. In high-income countries, it often causes outbreaks affecting the residents and staff of institutions and long-term facilities, usually hard to detect and control due to the difficult diagnosis and notification delay. This study aim at characterizing the affected population, geographical distribution, and evolution of scabies in Spain from 1997-2019 as well as to describe the main environments of transmission using different data sources., Methods: We carried out a nationwide retrospective study using four databases, which record data from different perspectives: hospital admissions, patients attended at primary healthcare services, outbreaks, and occupational diseases. We described the main characteristics from each database and calculated annual incidences in order to evaluate temporal and geographical patterns. We also analyzed outbreaks and occupational settings to characterize the main transmission foci and applied Joinpoint regression models to detect trend changes., Results: The elderly was the most frequent collective among the hospital admitted patients and notified cases in outbreaks, while children and young adults were the most affected according to primary care databases. The majority of the outbreaks occurred in homes and nursing homes; however, the facilities with more cases per outbreak were military barracks, healthcare settings and nursing homes. Most occupational cases occurred also in healthcare and social services settings, being healthcare workers the most common affected professional group. We detected a decreasing trend in scabies admissions from 1997 to 2014 (annual percentage change -APC- = -11.2%) and an increasing trend from 2014 to 2017 (APC = 23.6%). Wide geographical differences were observed depending on the database explored., Discussion: An increasing trend in scabies admissions was observed in Spain since 2014, probably due to cutbacks in social services and healthcare in addition to worsen of living conditions as a result of the 2008 economic crisis, among other reasons. The main transmission foci were healthcare and social settings. Measures including enhancing epidemic studies and national registries, reinforcing clinical diagnosis and early detection of cases, hygiene improvements and training of the staff and wide implementation of scabies treatment (considering mass drug administration in institutions outbreaks) should be considered to reduce the impact of scabies among most vulnerable groups in Spain., Competing Interests: The authors have declared that no competing interests exist.

Background: The aim of this study is to explore whether transmission of M. leprae has ceased in Spain, based upon the patterns and trends of notified cases., Methodology: Data on new cases reported to the National Leprosy Registry between the years 2003-2018 were extracted. In absence of detailed travel history, cases were considered "autochthonous" or "imported" based on whether they were born within or outside of Spain. These data were analyzed by age, sex, clinical type, country of origin, and location of residence at time of notification., Principal Findings: Data were available on 61 autochthonous and 199 imported cases since 2003. There were clear declines in incidence in both groups, and more imported than autochthonous cases every year since 2006. Autochthonous cases were more frequently multibacillary and had older age at diagnosis compared to imported cases. All the autochthonous cases had been born before 1985 and were more than 25 years old at diagnosis. Male-to-female ratio increased with time for autochthonous cases (except for the last time period). The imported cases originated from 25 countries, half of them from Brasil and Paraguay. Autochthonous cases were mainly distributed in the traditionally endemic regions, especially Andalucía and the eastern Mediterranean coast., Conclusions: Autochthonous and imported cases have different epidemiologic patterns in Spain. There was a clear decline in incidence rates of autochthonous disease, and patterns consistent with those reported from other regions where transmission has ceased. Autochthonous transmission of M. leprae is likely to have now effectively stopped in Spain., Competing Interests: The authors have declared that no competing interests exist.

Background: Central nervous system tumors (CNS) are the most frequent solid tumor in children. Causes of CNS tumors are mainly unknown and only 5% of the cases can be explained by genetic predisposition. We studied the effects of environmental exposure on the incidence of CNS tumors in children by subtype, according to exposure to industrial and/or urban environment, exposure to crops and according to socio-economic status of the child., Methods: We carried out a population-based case-control study of CNS tumors in Spain, covering 714 incident cases collected from the Spanish Registry of Childhood Tumors (period 1996-2011) and 4284 controls, individually matched by year of birth, sex, and autonomous region of residence. We built a covariate to approximate the exposure to industrial and/or urban environment and a covariate for the exposure to crops (GCI) using the coordinates of the home addresses of the children. We used the 2001 Census to obtain information about socio-economic status (SES). We fitted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs)., Results: The results for all CNS tumors showed an excess risk (OR = 1.37; 95%CI = 1.09-1.73) for SES, i.e., children living in the least deprived areas had 37% more risk of CNS tumor than children living in the most deprived areas. For GCI, an increase of 10% in crop surface in the 1-km buffer around the residence implied an increase of 22% in the OR (OR = 1.22; 95%CI = 1.15-1.29). Children living in the intersection of industrial and urban areas could have a greater risk of CNS tumors than children who live outside these areas (OR = 1.20; 95%CI = 0.82-1.77). Living in urban areas (OR = 0.90; 95%CI = 0.65-1.24) or industrial areas (OR = 0.96; 95%CI = 0.81-1.77) did not seem to increase the risk for all CNS tumors together. By subtype, Astrocytomas, Intracranial and intraspinal embryonal tumors, and other gliomas showed similar results., Conclusion: Our results suggest that higher socioeconomic status and exposure to crops could increase the risk of CNS tumors in children.

Background: Childhood cancer was the leading cause of death among children aged 1-14 years for 2012 in Spain. Leukemia has the highest incidence, followed by tumors of the central nervous system (CNS) and lymphomas (Hodgkin lymphoma, HL, and Non-Hodgkin's lymphoma, NHL). Spatial distribution of childhood cancer cases has been under concern with the aim of identifying potential risk factors., Objective: The two objectives are to study overall spatial clustering and cluster detection of cases of the three main childhood cancer causes, looking to increase etiological knowledge., Methods: We ran a case-control study. The cases were children aged 0 to 14 diagnosed with leukemia, lymphomas (HL and NHL) or CNS neoplasm in five Spanish regions for the period 1996-2011. As a control group, we used a sample from the Birth Registry matching every case by year of birth, autonomous region of residence and sex with six controls. We geocoded and validated the address of the cases and controls. For our two objectives we used two different methodologies. For the first, for overall spatial clustering detection, we used the differences of K functions from the spatial point patterns perspective proposed by Diggle and Chetwynd and the second, for cluster detection, we used the spatial scan statistic proposed by Kulldorff with a level for statistical significance of 0.05., Results: We had 1062 cases of leukemia, 714 cases of CNS, 92 of HL and 246 of NHL. Accordingly we had 6 times the number of controls, 6372 controls for leukemia, 4284 controls for CNS, 552 controls for HL and 1476 controls for NHL. We found variations in the estimated empirical D(s) for the different regions and cancers, including some overall spatial clustering for specific regions and distances. We did not find statistically significant clusters., Conclusions: The variations in the estimated empirical D(s) for the different regions and cancers could be partially explained by the differences in the spatial distribution of the population; however, according to the literature, we cannot discard environmental hazards or infections agents in the etiology of these cancers.