Dataset Information

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

ABSTRACT: OBJECTIVE:To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest. SETTING:The UK. PARTICIPANTS:National and regional influenza case estimates and retail sales from a major British supermarket. OUTCOME MEASURES:Weekly, seasonally adjusted sales of over-the-counter symptom remedies and non-pharmaceutical products; recommended as part of the advice offered by public health agencies; were compared with weekly influenza case estimates. Comparisons were made at national and regional spatial resolutions. We also compared sales to national measures of contemporaneous media output and public interest (Internet search volume) related to the pandemic. RESULTS:At a national scale there was no significant correlation between retail sales of symptom remedies and cases for the whole pandemic period in 2009. At the regional scale, a minority of regions showed statistically significant positive correlations between cases and sales of adult 'cold and flu' remedies and cough remedies (3.2%, 5/156, 3.8%, 6/156), but a greater number of regions showed a significant positive correlation between cases and symptomatic remedies for children (35.6%, 55/156). Significant positive correlations between cases and sales of thermometers and antiviral hand gels/wash were seen at both spatial scales (Cor 0.477 (95% CI 0.171 to 0.699); 0.711 (95% CI 0.495 to 0.844)). We found no significant association between retail sales and media reporting or Internet search volume. CONCLUSIONS:This study provides evidence that the British public responded appropriately to health messaging about hygiene. Non-prescription retail sales at a national level are not useful for the detection of cases. However, at finer spatial scales, in particular age-groups, retail sales may help augment existing surveillance and merit further study.

SUBMITTER: Todd S

PROVIDER: S-EPMC4010812 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

Todd Stacy S Diggle Peter J PJ White Peter J PJ Fearne Andrew A Read Jonathan M JM

BMJ open 20140429 4

<h4>Objective</h4>To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest.<h4>Setting</h4>The UK.<h4>Participants</h4>National and regional influenza case estimates and retail sales from a major British supermarket.<h4>Outcome measu ...[more]

PMID: 24780494

Similar Datasets

Project description:Following the emergence of 2009 pandemic influenza A virus subtype H1N1 (A[H1N1]pdm09) in the United States and Mexico in April 2009, A(H1N1)pdm09 spread rapidly all over the world. There is a dearth of information about the epidemiology of A(H1N1)pdm09 in Africa, including Morocco. We describe the epidemiologic characteristics of the A(H1N1)pdm09 epidemic in Morocco during 2009-2010, including transmissibility and risk factors associated with fatal disease.We implemented influenza surveillance for patients presenting with influenza-like illness (ILI) at 136 private and public clinics for patients with severe acute respiratory illness (SARI) at 16 regional public hospitals from June 2009 through February 2010. Respiratory samples and structured questionnaires were collected from all enrolled patients, and samples were tested by real-time reverse-transcription polymerase chain reaction for influenza viruses. We estimated the risk factors associated with fatal disease as well as the basic reproduction number (R(0)) and the serial interval of the pandemic virus.From June 2009 through February 2010, we obtained 3937 specimens, of which 1452 tested positive for influenza virus. Of these, 1398 (96%) were A(H1N1)pdm09. Forty percent of specimens from ILI cases (1056 of 2646) and 27% from SARI cases (342 of 1291) were positive for A(H1N1)pdm09. Sixty-four deaths occurred among laboratory-confirmed A(H1N1)pdm09 SARI cases. Among these cases, those who had hypertension (age-adjusted odd ratio [aOR], 28.2; 95% confidence interval [CI], 2.0-398.7), had neurological disorders (aOR, 7.5; 95% CI, 1.5-36.4), or were obese (aOR, 7.1; 95% CI, 1.6-31.1), as well as women of gestational age who were pregnant (aOR, 2.5; 95% CI, 1.1-5.6), were at increased risk of death. Across the country, elevated numbers of locally acquired infections were detected 4 months after the detection of the first laboratory-confirmed case and coincided with the expected influenza season (October-January) in Morocco. We obtained an R(0) estimate of 1.44 (95% CI, 1.32-1.56) and a mean serial interval (±SD) of 2.3 ± 1.4 days (95% CI, 1.6-3.0).Widespread but delayed community transmission of A(H1N1)pdm09 occurred in Morocco in 2009, and A(H1N1)pdm09 became the dominant influenza virus subtype during the 2009-2010 influenza season. The transmissibility characteristics were similar to those observed in other countries.

Project description:BackgroundPrediction of timing for the onset and peak of an influenza pandemic is of vital importance for preventive measures. In order to identify common spatiotemporal patterns and climate influences for pandemics in Sweden we have studied the propagation in space and time of A(H1N1)pdm09 (10,000 laboratory verified cases), the Asian Influenza 1957-1958 (275,000 cases of influenza-like illness (ILI), reported by local physicians) and the Russian Influenza 1889-1890 (32,600 ILI cases reported by physicians shortly after the end of the outbreak).MethodsAll cases were geocoded and analysed in space and time. Animated video sequences, showing weekly incidence per municipality and its geographically weighted mean (GWM), were created to depict and compare the spread of the pandemics. Daily data from 1957-1958 on temperature and precipitation from 39 weather stations were collected and analysed with the case data to examine possible climatological effects on the influenza dissemination.ResultsThe epidemic period lasted 11 weeks for the Russian Influenza, 10 weeks for the Asian Influenza and 9 weeks for the A(H1N1)pdm09. The Russian Influenza arrived in Sweden during the winter and was immediately disseminated, while both the Asian Influenza and the A(H1N1)pdm09 arrived during the spring. They were seeded over the country during the summer, but did not peak until October-November. The weekly GWM of the incidence moved along a line from southwest to northeast for the Russian and Asian Influenza but northeast to southwest for the A(H1N1)pdm09. The local epidemic periods of the Asian Influenza were preceded by falling temperature in all but one of the locations analysed.ConclusionsThe power of spatiotemporal analysis and modeling for pandemic spread was clearly demonstrated. The epidemic period lasted approximately 10 weeks for all pandemics. None of the pandemics had its epidemic period before late autumn. The epidemic period of the Asian Influenza was preceded by falling temperatures. Climate influences on pandemic spread seem important and should be further investigated.

Project description:BackgroundDuring 2019, an epidemic of equine influenza (EI) occurred in Europe.ObjectivesTo describe the epidemiology of the 2019 EI epidemic within Great Britain (GB).Study designRetrospective descriptive study of laboratory confirmed EI cases.MethodsEpidemiological data were obtained from veterinary surgeons referring samples for EI virus testing. Where available, data on confirmed cases and their wider resident population on EI-infected premises were collated and described. On a national level, spatial and temporal representations, consisting of choropleth maps and epidemic curves, described the spread of EI. EI-infected premises-level factors associated with the first of two epidemic phases were investigated using ordinary logistic regression analysis.ResultsThere were 412 confirmed cases and 234 EI-infected premises, with the first of two epidemic phases occurring between January and April, followed by a second phase through to August. The median age of confirmed cases was 5 years and Sports horses (24%) and Cobs (16%) made up the highest proportions by general horse type and breed. Among confirmed cases 72% were unvaccinated and 18% were vaccinated against EI. New horses arriving within 2 weeks of a confirmed case were reported by 42% of EI-infected premises. Investigation of EI-infected premises biosecurity measures indicated that 23% quarantined new arrivals, 37% had isolation facilities and 57% of resident horses were vaccinated. EI-infected premises were more likely in the first than second epidemic phase to be classified as professional, have a vaccinated confirmed case and EI confirmed in a newly arrived animal.Main limitationsData were collected at a single time point for each EI-infected premises with no follow ups performed.ConclusionsDuring 2019, EI-infected premises generally had low levels of population vaccine coverage and implemented limited preventive biosecurity measures, particularly linked to horse movements. Without substantial improvements in infectious disease prevention and control, the GB equine population remains at risk of future EI epidemics.

Project description:BackgroundTicks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored epidemiological and geo-referenced data from > 7 million electronic health records (EHRs) from cats and dogs collected by the Small Animal Veterinary Surveillance Network (SAVSNET) in Great Britain (GB) between 2014 and 2021 to assess the factors affecting tick attachment in an individual and at a spatiotemporal level.MethodsEHRs in which ticks were mentioned were identified by text mining; domain experts confirmed those with ticks on the animal. Tick presence/absence records were overlaid with a spatiotemporal series of climate, environment, anthropogenic and host distribution factors to produce a spatiotemporal regression matrix. An ensemble machine learning spatiotemporal model was used to fine-tune hyperparameters for Random Forest, Gradient-boosted Trees and Generalized Linear Model regression algorithms, which were then used to produce a final ensemble meta-learner to predict the probability of tick attachment across GB at a monthly interval and averaged long-term through 2014-2021 at a spatial resolution of 1 km. Individual host factors associated with tick attachment were also assessed by conditional logistic regression on a matched case-control dataset.ResultsIn total, 11,741 consultations were identified in which a tick was recorded. The frequency of tick records was low (0.16% EHRs), suggesting an underestimation of risk. That said, increased odds for tick attachment in cats and dogs were associated with younger adult ages, longer coat length, crossbreeds and unclassified breeds. In cats, males and entire animals had significantly increased odds of recorded tick attachment. The key variables controlling the spatiotemporal risk for tick attachment were climatic (precipitation and temperature) and vegetation type (Enhanced Vegetation Index). Suitable areas for tick attachment were predicted across GB, especially in forests and grassland areas, mainly during summer, particularly in June.ConclusionsOur results can inform targeted health messages to owners and veterinary practitioners, identifying those animals, seasons and areas of higher risk for tick attachment and allowing for more tailored prophylaxis to reduce tick burden, inappropriate parasiticide treatment and potentially TBDs in companion animals and humans. Sentinel networks like SAVSNET represent a novel complementary data source to improve our understanding of tick attachment risk for companion animals and as a proxy of risk to humans.

Dataset Information

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

Publications

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets