27 March 2020 – Policy Brief

Analysis of Swiss Epidemic as of 27 March 20

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Executive summary​

At 3 PM yesterday the Federal Office of Public Health (FOPH) shared line-listed data of the confirmed daily COVID-19 cases in Switzerland by canton, age and sex, and the daily number of negative tests for the whole country. The FOPH asked the academic community to address four questions. The expert panel undertook descriptive analyses and modelling to address the questions, to which we provide answers below.

Question 1. How should the epidemic curve be interpreted? Increasing, decreasing, stable trend?

The data provided are not themselves the epidemic curve, which would include all SARS-CoV-2 infections, but rather only the confirmed COVID-19 cases. The main difficulty in making inferences is the intrinsic biology of the virus, which means that the confirmed cases today reflect transmission 2-3 weeks ago. Furthermore, due to delays in updating the number of reported cases, the last three days should be interpreted with caution.

From the observed data, it is too early to infer either the trend of the epidemic curve or the magnitude of the effect of the control measures implemented since 13 March. A transmission model, developed for this report, also shows that, with the available data, the future trajectory of the epidemic in Switzerland is still uncertain. The uncertainty implies that we need to be prepared for the continued growth of the epidemic. Addition of data from new cases in the immediate future will considerably improve our ability to predict the effectiveness of the interventions and of the final size of the epidemic.

Question 2. Do you think that the data allow to evaluate the effect of the measures taken, and if so, how? If not why?

The data shared by FOPH are a vital information source that should make it possible to estimate the intervention effectiveness, but this will require at least a week’s more data. Additional parameters, including more complete data on the date of onset of symptoms in confirmed cases, would make it possible to  stimate the trends with more confidence and to determine the impact of the control measures sooner. Variations in testing rates may be masking some of the trends in the data. These trends would be clearer if the numbers of negative test results were available disaggregated by canton and ideally, age and sex. The analysis by canton indicates that the most intense outbreaks are in a small number of cantons and that, in much of Switzerland, it might still be possible to avert a major outbreak by intensive case finding, contact tracing and isolation, if this strategy is implemented very soon with a stateof-the-art information system.

Question 3. What can be learned from the data despite these quality problems?

Data collection and curation is clearly challenging, and we are unsure what specific quality problems are referred to here. Despite the inevitable noise in the data and delays in reporting, our initial analyses highlight several important trends:

  • The rate of confirmed cases per 10,000 population varies substantially by canton.
  • The average age of confirmed cases has increased as the epidemic has developed. This trend is compatible with a pattern of initial cases being imported or detected by contact tracing, and later cases being ascertained in the clinic, when community transmission became established.
  • The mean age of confirmed cases has remained constant since March 3, implying that eligibility criteria in the later increase in testing did not expand.
  • There is evidence for an age-gender interaction. In younger age groups, women account for a larger proportion of confirmed cases, and in the older age groups confirmed cases are predominantly male. This pattern cannot be further interpreted without data on the distribution of testing by age and sex.
  • The proportion of tests with a positive result appears to be increasing. This pattern is consistent with incomplete ascertainment in case detection. This is of concern because of the potential for continued transmission, despite social distancing measures. 

Question 4. What would be your reply if you were asked how this epidemic will evolve in the near futur especially with regard to the capacities in the medical system?

The observed data and model predictions show that future course of the epidemic remains uncertain. We must prepare for the case where the epidemic grows to levels that will severely strain the capacity of our health system. The panel currently lacks data on which to base judgements on the adequacy of the supply of ICU beds, ventilators, protective clothing, or trained and uninfected staff. The question does not specify which capacities are referred to.

Disclaimer: The answers to the four questions are based on interpretation of descriptive analyses and modelling that were conducted under extreme time pressure. The findings of the analyses are subject to change. Changes in the findings could affect the interpretation.

Main Report

Background on panel assembly and structure of the report

At 3 PM on March 26th, Brigitte Meier from the Federal Office of Public Health (FOPH) shared line-listed data of the confirmed daily COVID-19 cases in Switzerland, from 24/02/2020 – 25/03/2020, by canton, age and sex, and data summarizing the daily number of negative tests for the whole country. These data were shared with a request for feedback sent both to the mailing list of the Swiss School of Public Health (SSPH+) and the ETH Domain COVID-19 Taskforce. At 6 PM an additional variable was added to a subset of the data; the date of onset of symptoms. The deadline for feedback was 9 AM on March 27. 

An ad-hoc panel of experts from ETH Zurich / ETH Domain COVID-19 Taskforce, Swiss Tropical and Public Health Institute (Swiss TPH), and the Institute of Social and Preventive Medicine, University of Bern (ISPM Bern) met in a virtual space to provide timely feedback on the shared data, and considered responses to the questions from FOPH. 

This document is the response of this panel to the questions raised by Brigitte Meier, structured as follows: in part 1 (pages 3-10), we present preliminary analyses and modelling of the data provided by FOPH, highlighting some key insights from these data. All data analyses were carried out by the team at ISPM Bern. In part 2 (pages 11-13), we address each of the four questions posed by the FOPH, based on the limited analyses that we were able to conduct in the short time frame. A short outlook is provided. 

Part 1. Descriptive analyses 

The data comprised two parts, confirmed positive tests and negative tests. The original individual line-listed dataset for confirmed cases with five variables: date of test (Falldatum), date of reporting (Eingangdatum), canton, age and sex. The data summarize 11,207 cases. The data were generally complete, with few missing data for sex (457 cases; 4.1%) or age (35; 0.3%). The additional variable, date of symptom onset, was available for 1130 cases (10.0% of all cases).  
Note: the observed reported data are a subset of the true case count as the percentage of reported cases for Switzerland has been estimated at 38% (28% – 51%) (https://cmmid.github.io/topics/covid19/severity/global_cfr_estimates.html).
Figure 1: shows the numbers of reported cases of COVID-19 over time, in relation to the number of SARS-CoV-2 tests. The daily number of tests peaked on March 18, 2020. The continuing increase in the proportion of positive tests, even after the daily number of tests has decreased, suggests that testing is reaching the target groups, but does not identify all cases.
Figure 1. Top panel: numbers of reported cases (positive SARS-CoV-2 test result) and number of negative results by date of test. Bottom panel: test positivity by date of test
The SARS-CoV-2 epidemic in Switzerland varies geographically, with the four cantons of VD, TI, ZH and GE accounting for 58% of cases. Several cantons have fewer than 50 cases (AR, GL, NW, OW, SH, UR). Figure 2a and Figure 2b show that, while the numbers of confirmed COVID-19 cases are highest in VD, GE, TI and ZH, the rate of cases per 10,000 is the highest in TI, BS, GE, VD. The cantonal data appear to show different trends in case numbers (Figure 2a) and rates per 10,000 population (Figure 2b), although the instability in the daily rate is noted. For example, rates appear to show continuing daily increases in cantons BS, GE, TI but not in BE, BL or OW (Figure 2b). In-depth interpretation of these data would require data on the daily number of tests done in each canton.
Figure 2a. Number of reported COVID-19 cases by date of test and canton

Figure 2b. Rate per 10,000 of reported COVID-19 cases, by date of test and canton