Adapting Syndromic Surveillance Baselines After Public Health Interventions

Roger Antony Morbey; Alex James Elliot; Gillian Elizabeth Smith; Andre Charlett

doi:10.1177/0033354920959080

Adapting Syndromic Surveillance Baselines After Public Health Interventions

Roger Antony Morbey^*, Alex James Elliot, Gillian Elizabeth Smith, Andre Charlett

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods: We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results: Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion: Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

Original language	English
Pages (from-to)	737-745
Number of pages	9
Journal	Public Health Reports
Volume	135
Issue number	6
DOIs	https://doi.org/10.1177/0033354920959080
Publication status	Published - 1 Nov 2020

Bibliographical note

Funding Information:
The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research’s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE.

Funding Information:
The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research?s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE. The authors received no financial support for the research, authorship, and/or publication of this article.

Publisher Copyright:
© 2020, Association of Schools and Programs of Public Health.

Keywords

epidemiology
infectious disease
public health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/0033354920959080

Cite this

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title = "Adapting Syndromic Surveillance Baselines After Public Health Interventions",

abstract = "Background: Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods: We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results: Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion: Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.",

keywords = "epidemiology, infectious disease, public health",

author = "Morbey, {Roger Antony} and Elliot, {Alex James} and Smith, {Gillian Elizabeth} and Andre Charlett",

note = "Funding Information: The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research{\textquoteright}s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE. Funding Information: The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research?s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE. The authors received no financial support for the research, authorship, and/or publication of this article. Publisher Copyright: {\textcopyright} 2020, Association of Schools and Programs of Public Health.",

year = "2020",

month = nov,

day = "1",

doi = "10.1177/0033354920959080",

language = "English",

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journal = "Public Health Reports",

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AU - Elliot, Alex James

AU - Smith, Gillian Elizabeth

AU - Charlett, Andre

N1 - Funding Information: The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research’s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE. Funding Information: The authors acknowledge support from NHS 111 and NHS Digital; the contribution and support from the emergency department clinicians and staff members of the NHS trusts; the ongoing support of the Royal College of Emergency Medicine; the technical support provided by EMIS Health and L2S2 Ltd in developing the EDSSS; advanced and General Practitioner Out-Of-Hours and unscheduled care Syndromic Surveillance service providers who kindly agreed to participate in the EDSSS; and the help of the PHE Real-time Syndromic Surveillance Team, including Sue Smith, Paul Loveridge, Helen Hughes, Ana Soriano, and Sally Harcourt. A.J.E. and G.E.S. are supported by the National Institute of Health Research?s Health Protection Research Unit (NIHR HPRU) in Emergency Preparedness and Response. A.J.E. is supported by the NIHR HPRU in Gastrointestinal Infections. The views expressed are those of the authors and not necessarily those of the NHS, the National Institute of Health Research, the Department of Health, or PHE. The authors received no financial support for the research, authorship, and/or publication of this article. Publisher Copyright: © 2020, Association of Schools and Programs of Public Health.

PY - 2020/11/1

Y1 - 2020/11/1

N2 - Background: Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods: We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results: Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion: Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

AB - Background: Public health surveillance requires historical baselines to identify unusual activity. However, these baselines require adjustment after public health interventions. We describe an example of such an adjustment after the introduction of rotavirus vaccine in England in July 2013. Methods: We retrospectively measured the magnitude of differences between baselines and observed counts (residuals) before and after the introduction of a public health intervention, the introduction of a rotavirus vaccine in July 2013. We considered gastroenteritis, diarrhea, and vomiting to be indicators for national syndromic surveillance, including telephone calls to a telehealth system, emergency department visits, and unscheduled consultations with general practitioners. The start of the preintervention period varied depending on the availability of surveillance data: June 2005 for telehealth, November 2009 for emergency departments, and July 2010 for general practitioner data. The postintervention period was July 2013 to the second quarter of 2016. We then determined whether baselines incorporating a step-change reduction or a change in seasonality resulted in more accurate models of activity. Results: Residuals in the unadjusted baseline models increased by 42%-198% from preintervention to postintervention. Increases in residuals for vomiting indicators were 19%-44% higher than for diarrhea. Both step-change and seasonality adjustments improved the surveillance models; we found the greatest reduction in residuals in seasonally adjusted models (4%-75%). Conclusion: Our results demonstrated the importance of adjusting surveillance baselines after public health interventions, particularly accounting for changes in seasonality. Adjusted baselines produced more representative expected values than did unadjusted baselines, resulting in fewer false alarms and a greater likelihood of detecting public health threats.

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Adapting Syndromic Surveillance Baselines After Public Health Interventions

Abstract

Bibliographical note

Keywords

UN SDGs

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