Rotavirus vaccine impact and socioeconomic deprivation: an interrupted time-series analysis of gastrointestinal disease outcomes across primary and secondary care in the UK

Abstract Background Monovalent rotavirus vaccine, Rotarix (GlaxoSmithKline), was introduced in Kenya in July 2014 and is recommended to infants as oral doses at ages 6 and 10 weeks. A multisite study was established in 2 population-based surveillance sites to evaluate vaccine impact on the incidence of rotavirus-associated hospitalizations (RVHs). Methods Hospital-based surveillance was conducted from January 2010 to June 2017 for acute diarrhea hospitalizations among children aged <5 years in 2 health facilities in Kenya. A controlled interrupted time-series analysis was undertaken to compare RVH pre– and post–vaccine introduction using rotavirus-negative cases as a control series. The change in incidence post–vaccine introduction was estimated from a negative binomial model that adjusted for secular trend, seasonality, and multiple health worker industrial actions (strikes). Results Between January 2010 and June 2017 there were 1513 and 1652 diarrhea hospitalizations in Kilifi and Siaya; among those tested for rotavirus, 28% (315/1142) and 23% (197/877) were positive, respectively. There was a 57% (95% confidence interval [CI], 8–80%) reduction in RVHs observed in the first year post–vaccine introduction in Kilifi and a 59% (95% CI, 20–79%) reduction in Siaya. In the second year, RVHs decreased further at both sites, 80% (95% CI, 46–93%) reduction in Kilifi and 82% reduction in Siaya (95% CI. 61–92%); this reduction was sustained at both sites into the third year. Conclusions A substantial reduction in RVHs and all-cause diarrhea was observed in 2 demographic surveillance sites in Kenya within 3 years of vaccine introduction.

Download Full-text

Changes in soft drinks purchased by British households associated with the UK soft drinks industry levy: controlled interrupted time series analysis

BMJ ◽

10.1136/bmj.n254 ◽

2021 ◽

pp. n254 ◽

Cited By ~ 1

Author(s):

David Pell ◽

Oliver Mytton ◽

Tarra L Penney ◽

Adam Briggs ◽

Steven Cummins ◽

...

Keyword(s):

Time Series ◽

Confidence Interval ◽

Time Series Analysis ◽

Interrupted Time Series ◽

Soft Drinks ◽

Interrupted Time Series Analysis ◽

Series Analysis ◽

Market Research Company ◽

One Year ◽

The Uk

Abstract Objective To determine changes in household purchases of drinks and confectionery one year after implementation of the UK soft drinks industry levy (SDIL). Design Controlled interrupted time series analysis. Participants Members of a panel of households reporting their purchasing on a weekly basis to a market research company (average weekly number of participants n=22 183), March 2014 to March 2019. Intervention A two tiered tax levied on manufacturers of soft drinks, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g sugar/100 mL (high tier) are taxed at £0.24/L and drinks with ≥5 to <8 g sugar/100 mL (low tier) are taxed at £0.18/L. Drinks with <5 g sugar/100 mL (no levy) are not taxed. Main outcome measures Absolute and relative differences in the volume of, and amount of sugar in, soft drinks categories, all soft drinks combined, alcohol, and confectionery purchased per household per week one year after implementation of the SDIL compared with trends before the announcement of the SDIL. Results In March 2019, compared with the counterfactual estimated from pre-announcement trends, purchased volume of drinks in the high levy tier decreased by 155 mL (95% confidence interval 240.5 to 69.5 mL) per household per week, equivalent to 44.3% (95% confidence interval 59.9% to 28.7%), and sugar purchased in these drinks decreased by 18.0 g (95% confidence interval 32.3 to 3.6 g), or 45.9% (68.8% to 22.9%). Purchases of low tier drinks decreased by 177.3 mL (225.3 to 129.3 mL) per household per week, or 85.9% (95.1% to 76.7%), with a 12.5 g (15.4 to 9.5 g) reduction in sugar in these drinks, equivalent to 86.2% (94.2% to 78.1%). Despite no overall change in volume of no levy drinks purchased, there was an increase in sugar purchased of 15.3 g (12.6 to 17.9 g) per household per week, equivalent to 166.4% (94.2% to 238.5%). When all soft drinks were combined, the volume of drinks purchased did not change, but sugar decreased by 29.5 g (55.8 to 3.1 g), or 9.8% (17.9% to 1.8%). Purchases of confectionery and alcoholic drinks did not change. Conclusions Compared with trends before the SDIL was announced, one year after implementation, the volume of soft drinks purchased did not change. The amount of sugar in those drinks was 30 g, or 10%, lower per household per week—equivalent to one 250 mL serving of a low tier drink per person per week. The SDIL might benefit public health without harming industry. Trial registration ISRCTN18042742.

Download Full-text

OP31 Changes in household purchases of soft drinks up to one year after implementation of the UK soft drinks industry levy: a controlled interrupted time series analysis [ISRCTN18042742]

10.1136/jech-2020-ssmabstracts.31 ◽

2020 ◽

Author(s):

D Pell ◽

O Mytton ◽

M White ◽

J Adams

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Interrupted Time Series ◽

Soft Drinks ◽

Interrupted Time Series Analysis ◽

Series Analysis ◽

One Year ◽

The Uk

Download Full-text

Impact of the rotavirus vaccine in Valladolid, Spain: An interrupted time series analysis

Trials in Vaccinology ◽

10.1016/j.trivac.2016.04.005 ◽

2016 ◽

Vol 5 ◽

pp. 84-87 ◽

Cited By ~ 1

Author(s):

Alberto Pérez-Rubio ◽

Francisco Javier Luquero ◽

Maria Rosario Bachiller Luque ◽

Paz de la Torre Pardo ◽

José María Eiros Bouza

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Interrupted Time Series ◽

Rotavirus Vaccine ◽

Interrupted Time Series Analysis ◽

Series Analysis

Download Full-text

Impact of Withdrawal of the Analgesic Co-proxamol on Nonfatal Self-Poisoning in the UK

Crisis ◽

10.1027/0227-5910/a000063 ◽

2011 ◽

Vol 32 (2) ◽

pp. 81-87 ◽

Cited By ~ 16

Author(s):

Keith Hawton ◽

Helen Bergen ◽

Keith Waters ◽

Elizabeth Murphy ◽

Jayne Cooper ◽

...

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Marked Reduction ◽

Interrupted Time Series ◽

Withdrawal Period ◽

Interrupted Time Series Analysis ◽

Fatal Poisoning ◽

The Uk ◽

The Impact ◽

Withdrawal Phase

Background: In early 2005 the UK Committee on Safety of Medicines (CSM) announced gradual withdrawal of the analgesic co-proxamol because of its adverse benefit/safety ratio, especially its use for intentional and accidental fatal poisoning. Prescriptions of co-proxamol were reduced in the 3-year withdrawal phase (2005 to 2007) following the CSM announcement. Aims: To assess the impact of the CSM announcement in January 2005 to withdraw co-proxamol on nonfatal self-poisoning with co-proxamol and other analgesics. Methods: Interrupted time series analysis of general hospital presentations for nonfatal self-poisoning (five hospitals in three centers in England), comparing the 3-year withdrawal period 2005–2007 with 2000–2004. Results: A marked reduction in the number of episodes of nonfatal self-poisoning episodes involving co-proxamol was found following the CSM announcement (an estimated 62% over the period 2005 to 2007 compared to 2000 to 2004). There was no evidence of an increase in nonfatal self-poisoning episodes involving other analgesics (co-codamol, codeine, co-dydramol, dihydrocodeine, and tramadol) in relation to the CSM announcement over the same period, nor a change in the number of all episodes of self-poisoning. Limitations: Data were from three centers only. Conclusions: The impact of the policy appears to have reduced nonfatal self-poisoning with co-proxamol without significant substitution with other analgesics. This finding is in keeping with that for suicide.

Download Full-text

The Impact of Lockdown in England on Daily Confirmed Cases of COVID-19 and Related Deaths Compared to Sweden: A Comparative Interrupted Time Series Analysis

SSRN Electronic Journal ◽

10.2139/ssrn.3629457 ◽

2020 ◽

Author(s):

Moaath Mustafa Ali ◽

Yazan Samhouri ◽

Marwa Sabha ◽

Lynna Alnimer

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Interrupted Time Series ◽

Interrupted Time Series Analysis ◽

Series Analysis ◽

The Impact

Download Full-text

Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

BMC Health Services Research ◽

10.1186/s12913-021-06070-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Joanne Martin ◽

Edwin Amalraj Raja ◽

Steve Turner

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Emergency Admission ◽

Interrupted Time Series ◽

Interrupted Time Series Analysis ◽

Emergency Admissions ◽

Series Analysis ◽

Inpatient Services ◽

The Impact ◽

Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

Download Full-text