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medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.07.23.20154369


Cross-reactivity to SARS-CoV-2 from previous exposure to endemic coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and severity of COVID-19 disease. Here, we use a stochastic individual-based model to show that heterogeneities in individual exposure histories to endemic coronaviruses are able to explain observed age patterns of hospitalisation due to COVID-19 in EU/EEA countries and the UK, provided there is (i) a decrease in cross-protection to SARS-CoV-2 with the number of eHCoV exposures and (ii) an increase in potential disease severity with number of eHCoV exposures or as a result of immune senescence. We also show that variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates. Our findings call for further research on the role of cross-reactivity to endemic coronaviruses and highlight potential challenges arising from heterogeneous health care capacity and testing.

medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.07.22.20158352


The efficacy of digital contact tracing against COVID-19 epidemic is debated: smartphone penetration is limited in many countries, non-uniform across age groups, with low coverage among elderly, the most vulnerable to SARS-CoV-2. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact-survey and epidemiological information to describe the risk factors for exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.

medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.07.15.20154294


It is widely believed that the herd immunity threshold (HIT) required to prevent a resurgence of SARS-CoV-2 is in excess of 50% for any epidemiological setting. Here, we demonstrate that HIT may be greatly reduced if a fraction of the population is unable to transmit the virus due to innate resistance or cross-protection from exposure to seasonal coronaviruses. The drop in HIT is proportional to the fraction of the population resistant only when that fraction is effectively segregated from the general population; however, when mixing is random, the drop in HIT is more precipitous. Significant reductions in expected mortality can also be observed in settings where a fraction of the population is resistant to infection. These results help to explain the large degree of regional variation observed in seroprevalence and cumulative deaths and suggest that sufficient herd-immunity may already be in place to substantially mitigate a potential second wave.