The epidemiological impact of digital and manual contact tracing on the SARS-CoV-2 epidemic in the Netherlands: empirical evidence. (preprint)

Background. The Dutch government introduced the CoronaMelder smartphone application for digital contact tracing (DCT) to complement manual contact tracing (MCT) by Public Health Services (PHS) during the 2020-2022 SARS-CoV-2 epidemic. Modelling studies showed great potential but empirical evidence of DCT and MCT impact is scarce. Methods. We determined reasons for testing, and mean exposure-testing intervals by reason for testing, using routine data from PHS Amsterdam (1 December 2020 to 31 May 2021) and data from two SARS-CoV-2 rapid diagnostic test accuracy studies at other PHS sites in the Netherlands (14 December 2020 to 18 June 2021). Throughout the study periods, notification of DCT-identified contacts was via PHS contact-tracers, and self-testing was not yet widely available. Results. The most commonly reported reason for testing was having symptoms. In asymptomatic individuals, it was having been warned by an index case. Only around 2% and 2-5% of all tests took place after DCT or MCT notification, respectively. About 20-36% of those who had received a DCT or MCT notification had symptoms at the time of test request. Test positivity after a DCT notification was significantly lower, and exposure-test intervals after a DCT or MCT notification were longer, than for the above-mentioned other reasons for testing. Conclusions. Our data suggest that the impact of DCT and MCT on the SARS-CoV-2 epidemic in the Netherlands was limited. However, DCT impact might be enlarged if app use coverage is improved, contact-tracers are eliminated from the digital notification process to minimise delays, and DCT is combined with self-testing.

Impacts of the COVID-19 pandemic on future seasonal influenza epidemics (preprint)

Summary Seasonal influenza viruses typically cause annual epidemics worldwide infecting 5-15% of the human population 1 . However, during the first two years of the COVID-19 pandemic, seasonal influenza virus circulation was unprecedentedly low with very few reported infections 2 . The lack of immune stimulation to influenza viruses during this time, combined with waning antibody titres to previous influenza virus infections, could lead to increased susceptibility to influenza in the coming seasons and to larger and more severe epidemics when infection prevention measures against COVID-19 are relaxed 3,4 . Here, based on serum samples from 165 adults collected longitudinally before and during the pandemic, we show that the waning of antibody titres against seasonal influenza viruses during the first two years of the pandemic is likely to be negligible. Using historical influenza virus epidemiological data from 2003-2019, we also show that low country-level prevalence of each influenza subtype over one or more years has only small impacts on subsequent epidemic size. These results suggest that the risks posed by seasonal influenza viruses remained largely unchanged during the first two years of the COVID-19 pandemic and that the sizes of future seasonal influenza virus epidemics will likely be similar to those observed before the pandemic.

Evolution of COVID-19 symptoms during the first 9 months after illness onset (preprint)

BackgroundFew longitudinal data on COVID-19 symptoms across the full spectrum of disease severity are available. We evaluated symptom onset, severity and recovery up to nine months after illness onset. MethodsThe RECoVERED Study is a prospective cohort study based in Amsterdam, the Netherlands. Participants aged>18 years were recruited following SARS-CoV-2 diagnosis via the local Public Health Service and from hospitals. Standardised symptom questionnaires were completed at recruitment, at one week and month after recruitment, and monthly thereafter. Clinical severity was defined according to WHO criteria. Kaplan-Meier methods were used to compare time from illness onset to symptom recovery, by clinical severity. We examined determinants of time to recovery using multivariable Cox proportional hazards models. ResultsBetween 11 May 2020 and 31 January 2021, 301 COVID-19 patients (167[55%] male) were recruited, of whom 99/301(32.9%) had mild, 140/301(46.5%) moderate, 30/301(10.0%) severe and 32/301(10.6%) critical disease. The proportion of symptomatic participants who reported at least one persistent symptom at 12 weeks after illness onset was greater in those with severe/critical disease (81.7%[95%CI=68.7-89.7%]) compared to those with mild or moderate disease (33.0%[95%CI=23.0-43.3%] and 63.8%[95%CI=54.8-71.5%]). Even at nine months after illness onset, almost half of all participants (42.1%[95%CI=35.6-48.5]) overall continued to report [≥]1 symptom. Recovery was slower in participants with BMI[≥]30kg/m2 (HR 0.51[95%CI=0.30-0.87]) compared to those with BMI<25kg/m2, after adjusting for age, sex and number of comorbidities. ConclusionsCOVID-19 symptoms persisted for nine months after illness onset, even in those with mild disease. Obesity was the most important determinant of speed of recovery from symptoms.

Human coronavirus reinfection dynamics: lessons for SARS-CoV-2 (preprint)

In the current COVID-19 pandemic a key unsolved question is the duration of acquired immunity in recovered individuals. The recent emergence of SARS-CoV-2 precludes a direct study on this virus, but the four seasonal human coronaviruses may reveal common characteristics applicable to all human coronaviruses. We monitored healthy subjects over a time span of 35 years (1985-2020), providing a total of 2473 follow up person-months, and determined a) the time to reinfection by the same seasonal coronavirus and b) the dynamics of coronavirus antibody depletion post-infection. An alarmingly short duration of protective immunity to coronaviruses was found. Reinfections occurred frequently at 12 months post-infection and there was for each virus a substantial reduction in antibody levels as soon as 6 months post-infection.