ABSTRACT
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.
Subject(s)
COVID-19ABSTRACT
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.
Subject(s)
COVID-19ABSTRACT
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.
Subject(s)
Immune System Diseases , DeathABSTRACT
288 cases have been confirmed out of China from January 3 to February 13, 2020. We collected and synthesized all available information on these cases from official sources and media. We analyzed importations that were successfully isolated and those leading to onward transmission. We modeled their number over time, in relation to the origin of travel (Hubei province, other Chinese provinces, other countries) and interventions. We characterized importations timeline to assess the rapidity of isolation, and epidemiologically linked clusters to estimate the rate of detection. We found a rapid exponential growth of importations from Hubei, combined with a slower growth from the other areas. We predicted a rebound of importations from South East Asia in the upcoming weeks. Time from travel to detection has considerably decreased since the first importation, however 6 cases out of 10 were estimated to go undetected. Countries outside China should be prepared for the possible emergence of several undetected clusters of chains of local transmissions.
Subject(s)
COVID-19ABSTRACT
The novel coronavirus (2019-nCoV) epidemic has spread to 23 countries from China. Local cycles of transmission already occurred in 7 countries following case importation. No African country has reported cases yet. The management and control of 2019-nCoV introductions heavily relies on the public health capacity of a country. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of 2019-nCoV. We used data on air travel volumes departing from airports in the infected provinces in China and directed to Africa to estimate the risk of introduction per country. We determined the countries capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulation Monitoring and Evaluation Framework; and vulnerability, with the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing the most to their risk. Findings: Countries at the highest importation risk (Egypt, Algeria, Republic of South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, Kenya) have variable capacity and high vulnerability. Three clusters of countries are identified that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and Beijing, respectively. Interpretation: Several countries in Africa are stepping up their preparedness to detect and cope with 2019-nCoV importations. Resources and intensified surveillance and capacity capacity should be urgently prioritized towards countries at moderate risk that may be ill-prepared to face the importation and to limit onward transmission.