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There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission., This work was generated using Copernicus Climate Change Service (C3S) and Copernicus Atmosphere Monitoring Service (CAMS) information [2020]. The authors would like to thank the European Centre for Medium-Range Weather Forecasts (ECMWF) that implements the C3S and CAMS on behalf of the European Union. D.R. was supported by a postdoctoral research fellowship of the Xunta de Galicia (Spain). A.G. was funded by the Medical Research Council-UK (Grant ID: MR/R013349/1), the Natural Environment Research Council UK (Grant ID: NE/R009384/1) and the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). R.L. was supported by a Royal Society Dorothy Hodgkin Fellowship. S.A. and S.M. were funded by the Wellcome Trust (grant 210758/Z/18/Z210758/Z/18/Z). The following funding sources are acknowledged as providing funding for the MCC Collaborative Research Network authors: J.K. and A.U. were supported by the Czech Science Foundation, project 18-22125S. S.T. was supported by the Shanghai Municipal Science and Technology Commission (Grant 18411951600). N.S. is supported by the NIEHS-funded HERCULES Center (P30ES019776). H.K. was supported by the National Research Foundation of Korea (BK21 Center for Integrative Response to Health Disasters, Graduate School of Public Health, Seoul National University). A.S., F.D.R. and S.R. were funded by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). Each member of the CMMID COVID-19 Working Group contributed to processing, cleaning and interpretation of data, interpreted findings, contributed to the manuscript and approved the work for publication. The following funding sources are acknowledged as providing funding for the CMMID COVID-19 working group authors. This research was partly funded by the Bill & Melinda Gates Foundation (INV-001754: M.Q; INV-003174: K.P., M.J., Y.L., J.L.; NTD Modelling Consortium OPP1184344: C.A.B.P., G.M.; OPP1180644: S.R.P.; OPP1183986: E.S.N.). BMGF (OPP1157270: K.E.A.). DFID/Wellcome Trust (Epidemic Preparedness Coronavirus research programme 221303/Z/20/Z: C.A.B.P.). EDCTP2 (RIA2020EF-2983-CSIGN: H.P.G.). ERC Starting Grant (#757699: M.Q.). This project has received funding from the European Union’s Horizon 2020 research and innovation programme—project EpiPose (101003688: K.P., M.J., P.K., R.C.B., W.J.E., Y.L.). This research was partly funded by the Global Challenges Research Fund (GCRF) project ‘RECAP’ managed through RCUK and ESRC (ES/P010873/1: A.G., C.I.J., T.J.). HDR UK (MR/S003975/1: R.M.E.). MRC (MR/N013638/1: N.R.W.; MR/V027956/1: W.W.). Nakajima Foundation (A.E.). This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care (16/136/46: B.J.Q.; 16/137/109: B.J.Q., F.Y.S., M.J., Y.L.; Health Protection Research Unit for Immunisation NIHR200929: N.G.D.; Health Protection Research Unit for Modelling Methodology HPRU-2012-10096: T.J.; NIHR200908: R.M.E.; NIHR200929: F.G.S., M.J.; PR-OD-1017-20002: A.R., W.J.E.). Royal Society (Dorothy Hodgkin Fellowship: R.L.; RP\EA\180004: P.K.). UK DHSC/UK Aid/NIHR (PR-OD-1017-20001: H.P.G.). UK MRC (MC_PC_19065—Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: A.G., N.G.D., R.M.E., S.C., T.J., W.J.E., Y.L.; MR/P014658/1: G.M.K.). Authors of this research receive funding from the UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care (T.J.). Wellcome Trust (206250/Z/17/Z: A.J.K., T.W.R.; 206471/Z/17/Z: O.B.; 208812/Z/17/Z: S.C.; 210758/Z/18/Z: J.D.M., J.H., N.I.B.; UNS110424: F.K.). No funding (A.M.F., A.S., C.J.V.-A., D.C.T., J.W., K.E.A., Y.-W.D.C.). LSHTM, DHSC/UKRI COVID-19 Rapid Response Initiative (MR/V028456/1: Y.L.). Innovation Fund of the Joint Federal Committee (01VSF18015: F.K.). Foreign, Commonwealth and Development Office/Wellcome Trust (221303/Z/20/Z: M.K.).

International audience; Background: The rapid increase in mobile telephone use has generated concern about possible health risks related to radiofrequency electromagnetic fields from this technology. Methods: An interview-based case-control study with 2708 glioma and 2409 meningioma cases and matched controls was conducted in 13 countries using a common protocol. Results: A reduced odds ratio (OR) related to ever having been a regular mobile phone user was seen for glioma (OR 0.81, 95% confidence interval (CI): 0.70, 0.94) and meningioma (OR 0.79; 95% CI 0.68, 0.91), possibly reflecting participation bias or other methodological limitations. No elevated OR was observed 10 or more years after first phone use (glioma: OR 0.98, 95% CI 0.76, 1.26; meningioma: OR 0.83, 95% CI 0.61, 1.14). Odds ratios were below 1.0 for all deciles of lifetime number of phone calls and nine deciles of cumulative call time. In the tenth decile of recalled cumulative call time, 1640 hours or longer, the odds ratio was 1.40 (95% CI 1.03, 1.89) for glioma, and 1.15 (95% CI 0.81, 1.62) for meningioma; but there are implausible values of reported use in this group. Odds ratios for glioma tended to be greater in the temporal lobe than in other lobes of the brain, but the confidence intervals around the lobe-specific estimates were wide. Odds ratios for glioma tended to be greater in subjects who reported usual phone use on the same side of the head as their tumour than on the opposite side. Conclusions: Overall, no increase in risk of glioma or meningioma was observed with use of mobile phones. There were suggestions of an increased risk of glioma at the highest exposure levels, but biases and error prevent a causal interpretation. The possible effects of long-term heavy use of mobile phones require further investigation.

BACKGROUND: The aim of this study was to determine the extent to which pathology reporting of colorectal cancers notified to the New South Wales Central Cancer Registry during 2000 conformed to guidelines promulgated by the National Health and Medical Research Council. METHODS: De-identified reports for 2233 resected specimens of primary invasive colorectal carcinoma were coded according to a standardized system to compile information on 28 clinical and pathology features. An overall score for each report was calculated by computing the number out of 13 essential features specified in the guidelines for which data had been recorded explicitly and unambiguously in the report. RESULTS: The overall score ranged from 3 to 13 features with a mean of 9. No more than 7 features were reported explicitly in just less than one quarter of the reports and no more than 10 in three quarters. There were only 110 reports (4.9%) that included all features. Information on direct spread and nodal metastasis was well reported; resection margins less so. Many reports lacked information on metastases beyond the operative field, the involvement of deep or circumferential resection margins and tumour stage. CONCLUSION: In some respects pathology reports of resected colorectal cancer specimens displayed a high level of completeness. Some important features, however, were poorly described. Reporting could be improved if surgeons were to use a standardized form to convey clinical information to the pathologist and if pathologists were to report in a structured or synoptic format, explicitly recording the presence or absence of each feature in a standard list

OBJECTIVES: To investigate the risk of non-Hodgkin lymphoma (NHL) using a job-exposure matrix (JEM) to assess exposure to occupational magnetic fields at the power frequencies of 50/60 Hz. METHODS: The study population consisted of 694 cases of NHL, first diagnosed between 1 January 2000 and 31 August 2001, and 694 controls from two regions in Australia, matched by age, sex and region of residence. A detailed occupational history was given by each subject. Exposure to power frequency magnetic fields was estimated using a population-based JEM which was specifically developed in the United States to assess occupational magnetic field exposure. The cumulative exposure distribution was divided into quartiles and adjusted odds ratios were calculated using the lowest quartile as the referent group. RESULTS: For the total work history, the odds ratio (OR) for workers in the upper quartile of exposure was 1.48 (95% CI 1.02 to 2.16) compared to the referent (p value for trend was 0.006). When the exposure was lagged by 5 years the OR was 1.59 (95% CI 1.07 to 2.36) (p value for trend was 0.003). Adjusting for other occupational exposures did not significantly alter the results. CONCLUSIONS: These findings provide weak support for the hypothesis that occupational exposure to 50/60 Hz magnetic fields increases the risk of NHL

Since the middle of 20th century, epidemiology has been successfully elucidating the causes of human cancer and offering effective approaches to cancer prevention and control ([1][1]). In recent decades, substantial resources have been devoted to cancer epidemiologic studies without producing the

In an International Lymphoma Epidemiology Consortium pooled analysis, polymorphisms in 2 immune-system-related genes, tumor necrosis factor (TNF) and interleukin-10 (IL10), were associated with non-Hodgkin lymphoma (NHL) risk. Here, 8,847 participants were added to previous data (patients diagnosed from 1989 to 2005 in 14 case-control studies; 7,999 cases, 8,452 controls) for testing of polymorphisms in the TNF -308G>A (rs1800629), lymphotoxin-alpha (LTA) 252A>G (rs909253), IL10 -3575T>A (rs1800890, rs1800896), and nucleotide-binding oligomerization domain containing 2 (NOD2) 3020insC (rs2066847) genes. Odds ratios were estimated for non-Hispanic whites and several ethnic subgroups using 2-sided tests. Consistent with previous findings, odds ratios were increased for "new" participant TNF -308A carriers (NHL: per-allele odds ratio (OR(allelic)) = 1.10, P(trend) = 0.001; diffuse large B-cell lymphoma (DLBCL): OR(allelic) = 1.23, P(trend) = 0.004). In the combined population, odds ratios were increased for TNF -308A carriers (NHL: OR(allelic) = 1.13, P(trend) = 0.0001; DLBCL: OR(allelic) = 1.25, P(trend) = 3.7 x 10(-6); marginal zone lymphoma: OR(allelic) = 1.35, P(trend) = 0.004) and LTA 252G carriers (DLBCL: OR(allelic) = 1.12, P(trend) = 0.006; mycosis fungoides: OR(allelic) = 1.44, P(trend) = 0.015). The LTA 252A>G/TNF -308G>A haplotype containing the LTA/TNF variant alleles was strongly associated with DLBCL (P = 2.9 x 10(-8)). Results suggested associations between IL10 -3575T>A and DLBCL (P(trend) = 0.02) and IL10 -1082A>G and mantle cell lymphoma (P(trend) = 0.04). These findings strengthen previous results for DLBCL and the LTA 252A>G/TNF -308A locus and provide robust evidence that these TNF/LTA gene variants, or others in linkage disequilibrium, are involved in NHL etiology.