Pathogen seasonality and links with weather in England and Wales: A big data time series analysis

This is the final version. Available on open access from BMC via the DOI in this record.Background: Many infectious diseases of public health importance display annual seasonal patterns in their incidence. We aimed to systematically document the seasonality of several human infectious disease pathogens in England and Wales, highlighting those organisms that appear weather-sensitive and therefore may be influenced by climate change in the future. Methods: Data on infections in England and Wales from 1989 to 2014 were extracted from the Public Health England (PHE) SGSS surveillance database. We conducted a weekly, monthly and quarterly time series analysis of 277 pathogen serotypes. Each organism's time series was forecasted using the TBATS package in R, with seasonality detected using model fit statistics. Meteorological data hosted on the MEDMI Platform were extracted at a monthly resolution for 2001-2011. The organisms were then clustered by K-means into two groups based on cross correlation coefficients with the weather variables. Results: Examination of 12.9 million infection episodes found seasonal components in 91/277 (33%) organism serotypes. Salmonella showed seasonal and non-seasonal serotypes. These results were visualised in an online Rshiny application. Seasonal organisms were then clustered into two groups based on their correlations with weather. Group 1 had positive correlations with temperature (max, mean and min), sunshine and vapour pressure and inverse correlations with mean wind speed, relative humidity, ground frost and air frost. Group 2 had the opposite but also slight positive correlations with rainfall (mm, > 1 mm, > 10 mm). Conclusions: The detection of seasonality in pathogen time series data and the identification of relevant weather predictors can improve forecasting and public health planning. Big data analytics and online visualisation allow the relationship between pathogen incidence and weather patterns to be clarified.Medical Research Council (MRC)National Institute for Health Research (NIHR)National Institute of Health Research (NIHR

Beyond climate change and health: Integrating broader environmental change and natural environments for public health protection and promotion in the UK

This is the final version of the article. Available from MDPI via the DOI in this record.Increasingly, the potential short and long-term impacts of climate change on human health and wellbeing are being demonstrated. However, other environmental change factors, particularly relating to the natural environment, need to be taken into account to understand the totality of these interactions and impacts. This paper provides an overview of ongoing research in the Health Protection Research Unit (HPRU) on Environmental Change and Health, particularly around the positive and negative effects of the natural environment on human health and well-being and primarily within a UK context. In addition to exploring the potential increasing risks to human health from water-borne and vector-borne diseases and from exposure to aeroallergens such as pollen, this paper also demonstrates the potential opportunities and co-benefits to human physical and mental health from interacting with the natural environment. The involvement of a Health and Environment Public Engagement (HEPE) group as a public forum of "critical friends" has proven useful for prioritising and exploring some of this research; such public involvement is essential to minimise public health risks and maximise the benefits which are identified from this research into environmental change and human health. Research gaps are identified and recommendations made for future research into the risks, benefits and potential opportunities of climate and other environmental change on human and planetary health.The research was funded in part by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Environmental Change and Health at the London School of Hygiene and Tropical Medicine in partnership with Public Health England (PHE), and in collaboration with the University of Exeter, University College London, and the Met Office (HPRU-2012-10016); the UK Medical Research Council (MRC) and UK Natural Environment Research Council (NERC) for the MEDMI Project (MR/K019341/1, https: //www.data-mashup.org.uk); the Economic and Social Research Council (ESRC) Project (ES/P011489/1); and the NIHR Knowledge Mobilisation Research Fellowship for Maguire

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses

Background: To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Methods: Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient’s specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient’s residence and the laboratory. Results: There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. Conclusion: The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory

Seasonality and the effects of weather on Campylobacter infections

This is the final version. Available on open access from BMC via the DOI in this recordAvailability of data and materials: The datasets on MEDMI are described at https://www.data-mashup.org.uk/data/data-library/ and include the SGSS infectious disease dataset. Permissions are required to access these datasets and users require an account to be set up as described at https://www.data-mashup.org.uk/data/accessing-data/.BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. RESULTS: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. CONCLUSIONS: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored

Seasonality and the effects of weather on Campylobacter infections

Background Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. Methods To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. Results The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. Conclusions The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored

Role of monocarboxylate transporters in human cancers : state of the art

Monocarboxylate transporters (MCTs) belong to the SLC16 gene family, presently composed by 14 members. MCT1-MCT4 are proton symporters, which mediate the transmembrane transport of pyruvate, lactate and ketone bodies. The role of MCTs in cell homeostasis has been characterized in detail in normal tissues, however, their role in cancer is still far from understood. Most solid tumors are known to rely on glycolysis for energy production and this activity leads to production of important amounts of lactate, which are exported into the extracellular milieu, contributing to the acidic microenvironment. In this context, MCTs will play a dual role in the maintenance of the hyper-glycolytic acidresistant phenotype of cancer, allowing the maintenance of the high glycolytic rates by performing lactate efflux, and pH regulation by the co-transport of protons. Thus, they constitute attractive targets for cancer therapy, which have been little explored. Here we review the literature on the role of MCTs in solid tumors in different locations, such as colon, central nervous system, breast, lung, gynecologic tract, prostate, stomach, however, there are many conflicting results and in most cases there are no functional studies showing the dependence of the tumors on MCT expression and activity. Additional studies on MCT expression in other tumor types, confirmation of the results already published as well as additional functional studies are needed to deeply understand the role of MCTs in cancer maintenance and aggressiveness

Food Use and Health Effects of Soybean and Sunflower Oils

This review provides a scientific assessment of current knowledge of health effects of soybean oil (SBO) and sunflower oil (SFO). SBO and SFO both contain high levels of polyunsaturated fatty acids (PUFA) (60.8 and 69%, respectively), with a PUFA:saturated fat ratio of 4.0 for SBO and 6.4 for SFO. SFO contains 69% C18:2n-6 and less than 0.1% C18:3n-3, while SBO contains 54% C18:2n-6 and 7.2% C18:3n-3. Thus, SFO and SBO each provide adequate amounts of C18:2n-6, but of the two, SBO provides C18:3n-3 with a C18:2n-6:C18:3n-3 ratio of 7.1. Epidemiological evidence has suggested an inverse relationship between the consumption of diets high in vegetable fat and blood pressure, although clinical findings have been inconclusive. Recent dietary guidelines suggest the desirability of decreasing consumption of total and saturated fat and cholesterol, an objective that can be achieved by substituting such oils as SFO and SBO for animal fats. Such changes have consistently resulted in decreased total and low-density-lipoprotein cholesterol, which is thought to be favorable with respect to decreasing risk of cardiovascular disease. Also, decreases in high-density-lipoprotein cholesterol have raised some concern. Use of vegetable oils such as SFO and SBO increases C18:2n-6, decreases C20:4n-6, and slightly elevated C20:5n-3 and C22:6n-3 in platelets, changes that slightly inhibit platelet generation of thromboxane and ex vivo aggregation. Whether chronic use of these oils will effectively block thrombosis at sites of vascular injury, inhibit pathologic platelet vascular interactions associated with atherosclerosis, or reduce the incidence of acute vascular occlusion in the coronary or cerebral circulation is uncertain. Linoleic acid is needed for normal immune response, and essential fatty acid (EFA) deficiency impairs B and T cell-mediated responses. SBO and SFO can provide adequate linoleic acid for maintenance of the immune response. Excess linoleic acid has supported tumor growth in animals, an effect not verified by data from diverse human studies of risk, incidence, or progression of cancers of the breast and colon. Areas yet to be investigated include the differential effects of n-6- and n-3-containing oil on tumor development in humans and whether shorter-chain n-3 PUFA of plant origin such as found in SBO will modulate these actions of linoleic acid, as has been shown for the longer-chain n-3 PUFA of marine oil

A systematic review of the incidence of schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology

BACKGROUND: Understanding variations in the incidence of schizophrenia is a crucial step in unravelling the aetiology of this group of disorders. The aims of this review are to systematically identify studies related to the incidence of schizophrenia, to describe the key features of these studies, and to explore the distribution of rates derived from these studies. METHODS: Studies with original data related to the incidence of schizophrenia (published 1965–2001) were identified via searching electronic databases, reviewing citations and writing to authors. These studies were divided into core studies, migrant studies, cohort studies and studies based on Other Special Groups. Between- and within-study filters were applied in order to identify discrete rates. Cumulative plots of these rates were made and these distributions were compared when the underlying rates were sorted according to sex, urbanicity, migrant status and various methodological features. RESULTS: We identified 100 core studies, 24 migrant studies, 23 cohort studies and 14 studies based on Other Special Groups. These studies, which were drawn from 33 countries, generated a total of 1,458 rates. Based on discrete core data for persons (55 studies and 170 rates), the distribution of rates was asymmetric and had a median value (10%–90% quantile) of 15.2 (7.7–43.0) per 100,000. The distribution of rates was significantly higher in males compared to females; the male/female rate ratio median (10%–90% quantile) was 1.40 (0.9–2.4). Those studies conducted in urban versus mixed urban-rural catchment areas generated significantly higher rate distributions. The distribution of rates in migrants was significantly higher compared to native-born; the migrant/native-born rate ratio median (10%–90% quantile) was 4.6 (1.0–12.8). Apart from the finding that older studies reported higher rates, other study features were not associated with significantly different rate distributions (e.g. overall quality, methods related to case finding, diagnostic confirmation and criteria, the use of age-standardization and age range). CONCLUSIONS: There is a wealth of data available on the incidence of schizophrenia. The width and skew of the rate distribution, and the significant impact of sex, urbanicity and migrant status on these distributions, indicate substantial variations in the incidence of schizophrenia