Title

A hybrid Shewhart chart for visualizing and learning from epidemic data

UMMS Affiliation

Department of Population and Quantitative Health Sciences

Publication Date

2021-12-04

Document Type

Article

Disciplines

Epidemiology | Infectious Disease | Statistics and Probability | Virus Diseases

Abstract

OBJECTIVE: As the globe endures the coronavirus disease 2019 (COVID-19) pandemic, we developed a hybrid Shewhart chart to visualize and learn from day-to-day variation in a variety of epidemic measures over time.

CONTEXT: Countries and localities have reported daily data representing the progression of COVID-19 conditions and measures, with trajectories mapping along the classic epidemiological curve. Settings have experienced different patterns over time within the epidemic: pre-exponential growth, exponential growth, plateau or descent and/ or low counts after descent. Decision-makers need a reliable method for rapidly detecting transitions in epidemic measures, informing curtailment strategies and learning from actions taken.

METHODS: We designed a hybrid Shewhart chart describing four 'epochs' ((i) pre-exponential growth, (ii) exponential growth, (iii) plateau or descent and (iv) stability after descent) of the COVID-19 epidemic that emerged by incorporating a C-chart and I-chart with a log-regression slope. We developed and tested the hybrid chart using international data at the country, regional and local levels with measures including cases, hospitalizations and deaths with guidance from local subject-matter experts.

RESULTS: The hybrid chart effectively and rapidly signaled the occurrence of each of the four epochs. In the UK, a signal that COVID-19 deaths moved into exponential growth occurred on 17 September, 44 days prior to the announcement of a large-scale lockdown. In California, USA, signals detecting increases in COVID-19 cases at the county level were detected in December 2020 prior to statewide stay-at-home orders, with declines detected in the weeks following. In Ireland, in December 2020, the hybrid chart detected increases in COVID-19 cases, followed by hospitalizations, intensive care unit admissions and deaths. Following national restrictions in late December, a similar sequence of reductions in the measures was detected in January and February 2021.

CONCLUSIONS: The Shewhart hybrid chart is a valuable tool for rapidly generating learning from data in close to real time. When used by subject-matter experts, the chart can guide actionable policy and local decision-making earlier than when action is likely to be taken without it.

Keywords

Shewhart control chart, covid-19 pandemic, statistical process control, statistical public reporting of healthcare data

DOI of Published Version

10.1093/intqhc/mzab151

Source

Parry G, Provost LP, Provost SM, Little K, Perla RJ. A hybrid Shewhart chart for visualizing and learning from epidemic data. Int J Qual Health Care. 2021 Dec 4;33(4). doi: 10.1093/intqhc/mzab151. PMID: 34865014. Link to article on publisher's site

Journal/Book/Conference Title

International journal for quality in health care : journal of the International Society for Quality in Health Care

Related Resources

Link to Article in PubMed

PubMed ID

34865014

Share

COinS