Dataset Information

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

ABSTRACT: 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.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.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).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.

SUBMITTER: Cherrie MPC

PROVIDER: S-EPMC6114700 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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

Cherrie Mark P C MPC Nichols Gordon G Iacono Gianni Lo GL Sarran Christophe C Hajat Shakoor S Fleming Lora E LE

BMC public health 20180828 1

<h4>Background</h4>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.<h4>Methods</h4>Data on infections in England and Wales from 1989 to 2014 were extracted from the Public Health England (PHE) SGSS s ...[more]

PMID: 30153803

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Project description:BackgroundThe analgesic co-proxamol (paracetamol/dextropropoxyphene combination) has been widely involved in fatal poisoning. Concerns about its safety/effectiveness profile and widespread use for suicidal poisoning prompted its withdrawal in the UK in 2005, with partial withdrawal between 2005 and 2007, and full withdrawal in 2008. Our objective in this study was to assess the association between co-proxamol withdrawal and prescribing and deaths in England and Wales in 2005-2010 compared with 1998-2004, including estimation of possible substitution effects by other analgesics.Methods and findingsWe obtained prescribing data from the NHS Health and Social Care Information Centre (England) and Prescribing Services Partneriaeth Cydwasanaethau GIG Cymru (Wales), and mortality data from the Office for National Statistics. We carried out an interrupted time-series analysis of prescribing and deaths (suicide, open verdicts, accidental poisonings) involving single analgesics. The reduction in prescribing of co-proxamol following its withdrawal in 2005 was accompanied by increases in prescribing of several other analgesics (co-codamol, paracetamol, codeine, co-dydramol, tramadol, oxycodone, and morphine) during 2005-2010 compared with 1998-2004. These changes were associated with major reductions in deaths due to poisoning with co-proxamol receiving verdicts of suicide and undetermined cause of -21 deaths (95% CI -34 to -8) per quarter, equating to approximately 500 fewer suicide deaths (-61%) over the 6 years 2005-2010, and -25 deaths (95% CI -38 to -12) per quarter, equating to 600 fewer deaths (-62%) when accidental poisoning deaths were included. There was little observed change in deaths involving other analgesics, apart from an increase in oxycodone poisonings, but numbers were small. Limitations were that the study was based on deaths involving single drugs alone and changes in deaths involving prescribed morphine could not be assessed.ConclusionsDuring the 6 years following the withdrawal of co-proxamol in the UK, there was a major reduction in poisoning deaths involving this drug, without apparent significant increase in deaths involving other analgesics.

Dataset Information

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

Publications

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

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