Describing the indirect impact of COVID-19 on healthcare utilisation using syndromic surveillance systems

Abstract

Background: Since the end of January 2020, the coronavirus (COVID-19) pandemic has been responsible for a global health crisis. In England a number of non-pharmaceutical interventions have been introduced throughout the pandemic, including guidelines on healthcare attendance (for example, promoting remote consultations), increased handwashing and social distancing. These interventions are likely to have impacted the incidence of non-COVID-19 conditions as well as healthcare seeking behaviour. Syndromic Surveillance Systems offer the ability to monitor trends in healthcare usage over time.

Methods: This study describes the indirect impact of COVID-19 on healthcare utilisation using a range of syndromic indicators including eye conditions, mumps, fractures, herpes zoster and cardiac conditions. Data from the syndromic surveillance systems monitored by Public Health England were used to describe the number of contacts with NHS 111, general practitioner (GP) In Hours (GPIH) and Out-of-Hours (GPOOH), Ambulance and Emergency Department (ED) services over comparable periods before and during the pandemic.

Results: The peak pandemic period in 2020 (weeks 13-20), compared to the same period in 2019, displayed on average a 12% increase in NHS 111 calls, an 11% decrease in GPOOH consultations, and a 49% decrease in ED attendances. In the GP In Hours system, conjunctivitis consultations decreased by 64% and mumps consultations by 31%. There was a 49% reduction in attendance at EDs for fractures, and there was no longer any weekend increase in ED fracture attendances, with similar attendance patterns observed across each day of the week. There was a decrease in the number of ED attendances with diagnoses of myocardial ischaemia.

Conclusion: The COVID-19 pandemic drastically impacted healthcare utilisation for non-COVID-19 conditions, due to a combination of a probable decrease in incidence of certain conditions and changes in healthcare seeking behaviour. Syndromic surveillance has a valuable role in describing and understanding these trends.

Keywords: Coronavirus; Epidemiology; Healthcare utilisation; Pandemic; Syndromic surveillance; Viral.

Fig. 1

Number of cases and deaths from SARS-CoV-2 in England between January to May 2020. This graph shows the epidemiological curve of lab-confirmed cases and deaths (recorded within 28 days of positive test) due to SARS-CoV-2 in England (30/01/2020–24/05/2020), showing the introduction of non-pharmaceutical interventions at three significant dates, which are used as reference points in subsequent Figs. 2, 3, 4, 5, 6 [9]

Fig. 2

Overall total numbers of contacts in four different syndromic surveillance systems. These graphs show the daily (dotted line) and 7-day moving average (solid line) a) total number of attendances at emergency departments, b) total number of calls to NHS 111 as rate per 100,000 population, c) total number of calls to 999 for an ambulance, and d) total number of contacts with GP Out-of-Hours services

Fig. 3

Numbers of contacts for eye conditions in three different syndromic surveillance systems. These graphs show the daily (dotted line) and 7-day moving average (solid line) a) number of GP In Hours consultations for ‘conjunctivitis’ per 100,000 population, b) number of GP Out-of-hours contacts for ‘eye irritation’ as a percentage of contacts with a Read code and c) number of calls per 100,000 population to NHS 111 for ‘eye problems’

Fig. 4

Numbers of contacts in GP In Hours syndromic system for two indicators. These graphs show the number of consultations per 100,000 population using GP In Hours daily syndromic surveillance data (dotted line) and 7-day moving average (solid line) for clinical presentation of a) Herpes Zoster and b) Mumps

Fig. 5

Number of attendances at emergency departments with a diagnosis of fracture by day and hour. These graphs show the a) number of daily (dotted line) and 7-day moving average (solid line) number of attendances at emergency departments and, for the period of ‘peak lockdown’ highlighted in blue (23/03/2020–24/05/2020 compared to 25/03/2019–26/05/2019), the b) daily mean number of attendances by hour of day, day of week (indicated by colour) in males in 2019 (dotted) compared to 2020 (solid) and c) daily mean number of attendances by hour of day, day of week (indicated by colour) in females in 2019 (dotted) compared to 2020 (solid)

Fig. 6

Numbers of contacts for chest-pain syndromes in three different syndromic surveillance systems. These graphs show daily syndromic surveillance data (dotted line) and 7-day moving average (solid line) for a) number of attendances with ‘Myocardial Ischaemia’ at emergency departments b) number of calls to 999 for an ambulance due to ‘Chest Pain’, and c) number of GP Out-of-Hours contacts for ‘Chest Pain / Myocardial Infarction’ as a percentage of contacts with a Read code