Switzerland Population: Agglomerations: Geneva data was reported at 592.060 Person th in 2017. This records an increase from the previous number of 585.400 Person th for 2016. Switzerland Population: Agglomerations: Geneva data is updated yearly, averaging 504.265 Person th from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 592.060 Person th in 2017 and a record low of 442.106 Person th in 1991. Switzerland Population: Agglomerations: Geneva data remains active status in CEIC and is reported by Swiss Federal Statistical Office. The data is categorized under Global Database’s Switzerland – Table CH.G001: Population.

IntroductionGlobally, cancer cases are expected to significantly increase due to population growth and aging, reaching 29.9 million by 2040 (+49.5% since 2022) and 32.6 million by 2045 (+63%), with countries like Switzerland forecasting a 36.5% increase. Rare cancers, defined as less than six cases/100,000 individuals/year, account for 15-24% for recent nationwide studies but they have fewer treatment options and lower survival rates. Using the Geneva Cancer Registry, we analyzed rare cancer incidence and survival rates in adults from the canton of Geneva, Switzerland (2011–2020), with the aim of informing future research at local and national levels.MethodsWe analyzed adult patients diagnosed with invasive cancers (2011–2020) in Geneva using Geneva Cancer Registry data, which were annually updated. Rare cancers were defined according to RARECAREnet criteria (incidence less than six cases/100,000 individuals/year) and categorized into Tier 1 and Tier 2 entities based on clinical features. Crude and standardized incidence rates were calculated for both sexes using the 1976 European reference population, as well as age-specific rates for rare and common cancers. Five-year survival rates were estimated using the Kaplan–Meier method. Survival differences between rare and common cancers were assessed using log-rank tests and Cox proportional hazards models adjusted for age and gender. Statistical analyses were performed using STATA software.ResultsBetween 2011 and 2020, 31,233 invasive cancers were diagnosed in adults in Geneva, of which 4,296 cases (13.75%) were classified as rare based on aforementioned thresholds. While some rare Tier 1 cancers included common subtypes, most Tier 2 cancers (141 in total) were classified as rare, with significant gender disparities. Men had higher rare cancer rates such as epithelial hypopharynx, larynx, and liver tumors, while women had higher rates of squamous cell carcinoma of the anus. Rare neuroendocrine tumors, central nervous system tumors, and hematological malignancies, such as follicular B lymphoma and acute myeloid leukemia, were also prevalent among rare cancers. Rare cancers increase with age, but less so than common cancers. The 5-year survival rate for rare cancers was 58.4% when compared with 62.3% for common cancers, indicating a 15.7% higher risk of death for patients with these cancers.DiscussionThese findings highlight the critical challenges and requirements of targeted research and improving care strategies for rare cancers. Efforts combatting such cancers include European Reference Networks and the Swiss Sarcoma Network, which have improved access to care via collaborative efforts. In Switzerland, Molecular Tumor Boards have leveraged genomic knowledge to refine treatments and allow patient participation in clinical trials. Early referral to such boards for aggressive or treatment-limited cancers can streamline care and facilitate patient access to specialist centers. However, Switzerland requires more comprehensive data on the distribution of rare cancers in terms of age, gender, and region to improve management strategies at national levels.

BackgroundSARS-CoV-2 infection and its health consequences have disproportionally affected disadvantaged socio-economic groups globally. This study aimed to analyze the association between socio-economic conditions and having developed antibodies for-SARS-CoV-2 in a population-based sample in the canton of Geneva, Switzerland.MethodsData was obtained from a population-based serosurvey of adults in Geneva and their household members, between November and December, 2020, toward the end of the second pandemic wave in the canton. Participants were tested for antibodies for-SARS-CoV-2. Socio-economic conditions representing different dimensions were self-reported. Mixed effects logistic regressions were conducted for each predictor to test its association with seropositive status as the main outcome.ResultsTwo thousand eight hundred and eighty-nine adults completed the study questionnaire and were included in the final analysis. Retired participants and those living in suburban areas had lower odds of a seropositive result when compared to employed participants (OR: 0.42, 95% CI: 0.20–0.87) and those living in urban areas (OR: 0.67, 95% CI: 0.46–0.97), respectively. People facing financial hardship for less than a year had higher odds of a seropositive result compared to those who had never faced them (OR: 2.23, 95% CI: 1.01–4.95). Educational level, occupational position, and household income were not associated with being seropositive, nor were ethnicity or country of birth.DiscussionWhile conventional measures of socio-economic position did not seem to be related to the risk of being infected in this sample, this study sheds lights on the importance of examining the broader social determinants of health when evaluating the differential impact of the pandemic within the population.

人口：结块：日内瓦在12-01-2017达592.060千人，相较于12-01-2016的585.400千人有所增长。人口：结块：日内瓦数据按年更新，12-01-1991至12-01-2017期间平均值为504.265千人，共27份观测结果。该数据的历史最高值出现于12-01-2017，达592.060千人，而历史最低值则出现于12-01-1991，为442.106千人。CEIC提供的人口：结块：日内瓦数据处于定期更新的状态，数据来源于Office Fédéral de la Statistique，数据归类于Global Database的瑞士 – 表 CH.G001：人口。

Abstract (en): These data are a collection of demographic statistics for the populations of 125 countries or areas throughout the world, prepared by the Statistical Office of the United Nations. The units of analysis are both country and data year. The primary source of data is a set of questionnaires sent monthly and annually to national statistical services and other appropriate government offices. Data include statistics on approximately 50 types of causes of death for the years 1966 through 1974 for males, females, and total populations. Causes of death in 125 countries or areas throughout the world between the years 1966 and 1974. 2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions. The causes of death are classified according to the 6th, 7th, and 8th versions of an abbreviated list of the World Health Organization's INTERNATIONAL STATISTICAL CLASSIFICATION OF DISEASES, INJURIES, AND CAUSES OF DEATH. Therefore, data for causes of death are not necessarily comparable across countries or data years. Users should refer to Variable 5 in the Variable List for full discussion of this problem. Users interested in comparing deaths for countries or years that use different versions of the Abbreviated list should consult two publications: A. Joan Klebba, and Alice B. Dolman. COMPARABILITY OF MORTALITY STATISTICS FOR THE SEVENTH AND EIGHTH REVISIONS OF THE INTERNATIONAL CLASSIFICATION OF DISEASES, UNITED STATES. Rockville, MD: United States Department of Health, Education, and Welfare. Public Health Service. Health Services and Mental Health Administration. National Center for Health Statistics, 1975, and World Health Organization. MANUAL OF THE INTERNATIONAL STATISTICAL CLASSIFICATION OF DISEASES, INJURIES, AND CAUSES OF DEATH. Geneva, Switzerland: World Health Organization, 1967.The user should note that countries have data covering a variety of time spans (the maximum span being 1965-1973), and the data have not been padded to supply missing data codes for those years for which a country does not have data. Thus, Egypt has data for years 1965 through 1972, while Kenya has data for only 1970. (See Appendix D in the codebook to determine the years for which a country has data.)It is important that any user of these data consult the United Nations' DEMOGRAPHIC YEARBOOK, 1976, for further explanation of the data's limitations. Certain countries have modified reporting procedures which are presented in both the footnotes and the technical notes accompanying the tables in the Yearbook. There is no way to identify these problems using only the machine-readable data.In order to eliminate unnecessary repetition of identifying information, data were merged so that each record now contains all the data for a country for one particular year. In this process, breakdowns of deaths by ethnic group and/or urban/rural classification were omitted since only a few countries provided such information. Each record now contains the data for the number of deaths from each cause of death for male, female, and total.While the data appear to be in a rectangular matrix, such is not the case. This occurs because different versions of the abbreviated list are referenced in different data years. The lack of a rectangular data matrix does little to restrict the manageability of the dataset. See codebook for examples.While the data have been reformatted and documented by ICPSR staff, there has been no attempt to verify the accuracy and consistency of the data received from the U.N. Statistical Office.

To date, most of the evidence suggests that smoking is negatively associated with testing positive for SARS-CoV-2. However, evidence has several methodological limitations. Using an outpatient sample population, we analyzed the association of testing positive for SARS-CoV-2 and smoking considering comorbidities, socioeconomic and demographic factors. Baseline data were obtained from a cohort during the first wave of the pandemic in Geneva, Switzerland (March-April 2020). RT-PCR tests were carried out on individuals suspected of having SARS-CoV-2 according to the testing strategy at that time. Logistic regressions were performed to test the association of smoking and testing positive for SARS-CoV-2 and further adjusted for comorbidities, socioeconomic and demographic factors. The sample included 5,169 participants; 60% were women and the mean age was 41 years. The unadjusted OR for testing positive for SARS-CoV-2 was 0.46 (CI: 0.38–0.54). After adjustment for comorbidities, socioeconomic and demographic factors, smoking was still negatively associated with testing positive for SARS-CoV-2 (OR: 0.44; CI: 0.35–0.77). Women (OR: 0.79; CI: 0.69–0.91), higher postal income (OR: 0.97; CI: 0.95–0.99), having respiratory (OR: 0.68; CI: 0.55–0.84) and immunosuppressive disorders (OR: 0.63; CI: 0.44–0.88) also showed independent negative associations with a positive test for SARS-CoV-2. Smoking was negatively associated with a positive test for SARS-CoV-2 independently of comorbidities, socioeconomic and demographic factors. Since having respiratory or immunosuppressive conditions and being females and healthcare workers were similarly negatively associated with SARS-CoV-2 positive testing, we hypothesize that risk factor-related protective or testing behaviors could have induced a negative association with SARS-CoV-2.