Coronavirus disease (COVID-19)

Immunoassays targeting different SARS-CoV-2-specific antibodies are employed for seroprevalence studies. The degree of variability between immunoassays targeting anti-nucleocapsid (anti-NP; the majority) vs the potentially neutralising anti-spike antibodies (including anti-receptor-binding domain; anti-RBD), particularly in mild or asymptomatic disease, remains unclear.

We aimed to explore variability in anti-NP and anti-RBD antibody detectability following mild symptomatic or asymptomatic SARS-CoV-2 infection and analyse antibody response for correlation with symptomatology.

A multicentre prospective cross-sectional study was undertaken (April–July 2020). Paired serum samples were tested for anti-NP and anti-RBD IgG antibodies and reactivity expressed as binding ratios (BR). Multivariate linear regression was performed analysing age, sex, time since onset, symptomatology, anti-NP and anti-RBD antibody BR.

We included 906 adults. Antibody results (793/906; 87.5%; 95% confidence interval: 85.2–89.6) and BR strongly correlated (ρ = 0.75). PCR-confirmed cases were more frequently identified by anti-RBD (129/130) than anti-NP (123/130). Anti-RBD testing identified 83 of 325 (25.5%) cases otherwise reported as negative for anti-NP. Anti-NP presence (+1.75/unit increase; p < 0.001), fever (≥ 38°C; +1.81; p < 0.001) or anosmia (+1.91; p < 0.001) were significantly associated with increased anti-RBD BR. Age (p = 0.85), sex (p = 0.28) and cough (p = 0.35) were not. When time since symptom onset was considered, we did not observe a significant change in anti-RBD BR (p = 0.95) but did note decreasing anti-NP BR (p < 0.001).

SARS-CoV-2 anti-RBD IgG showed significant correlation with anti-NP IgG for absolute seroconversion and BR. Higher BR were seen in symptomatic individuals, particularly those with fever. Inter-assay variability (12.5%) was evident and raises considerations for optimising seroprevalence testing strategies/studies.

Cruise ships provide an ideal setting for transmission of SARS-CoV-2, given the socially dense exposure environment.

To provide a comprehensive review of COVID-19 outbreaks on cruise ships.

PubMed was searched for COVID-19 cases associated with cruise ships between January and October 2020. A list of cruise ships with COVID-19 was cross-referenced with the United States Centers for Disease Control and Prevention’s list of cruise ships associated with a COVID-19 case within 14 days of disembarkation. News articles were also searched for epidemiological information. Narratives of COVID-19 outbreaks on ships with over 100 cases are presented.

Seventy-nine ships and 104 unique voyages were associated with COVID-19 cases before 1 October 2020. Nineteen ships had more than one voyage with a case of COVID-19. The median number of cases per ship was three (interquartile range (IQR): 1–17.8), with two notable outliers: the Diamond Princess and the Ruby Princess, which had 712 and 907 cases, respectively. The median attack rate for COVID-19 was 0.2% (IQR: 0.03–1.5), although this distribution was right-skewed with a mean attack rate of 3.7%; 25.9% (27/104) of voyages had at least one COVID-19-associated death. Outbreaks involving only crew occurred later than outbreaks involving guests and crew.

In the absence of mitigation measures, COVID-19 can spread easily on cruise ships in a susceptible population because of the confined space and high-density contact networks. This environment can create superspreader events and facilitate international spread.

Serosurveys for SARS-CoV-2 aim to estimate the proportion of the population that has been infected.

This observational study assesses the seroprevalence of SARS-CoV-2 antibodies in Ontario, Canada during the first pandemic wave.

Using an orthogonal approach, we tested 8,902 residual specimens from the Public Health Ontario laboratory over three time periods during March–June 2020 and stratified results by age group, sex and region. We adjusted for antibody test sensitivity/specificity and compared with reported PCR-confirmed COVID-19 cases.

Adjusted seroprevalence was 0.5% (95% confidence interval (CI): 0.1–1.5) from 27 March–30 April, 1.5% (95% CI: 0.7–2.2) from 26–31 May, and 1.1% (95% CI: 0.8–1.3) from 5–30 June 2020. Adjusted estimates were highest in individuals aged ≥ 60 years in March–April (1.3%; 95% CI: 0.2–4.6), in those aged 20–59 years in May (2.1%; 95% CI: 0.8–3.4) and in those aged ≥ 60 years in June (1.6%; 95% CI: 1.1–2.1). Regional seroprevalence varied, and was highest for Toronto in March–April (0.9%; 95% CI: 0.1–3.1), for Toronto in May (3.2%; 95% CI: 1.0–5.3) and for Toronto (1.5%; 95% CI: 0.9–2.1) and Central East in June (1.5%; 95% CI: 1.0–2.0). We estimate that COVID-19 cases detected by PCR in Ontario underestimated SARS-CoV-2 infections by a factor of 4.9.

Our results indicate low population seroprevalence in Ontario, suggesting that public health measures were effective at limiting the spread of SARS-CoV-2 during the first pandemic wave.

The SARS-CoV-2 lineages carrying the amino acid change D614G have become the dominant variants in the global COVID-19 pandemic. By June 2021, all the emerging variants of concern carried the D614G mutation. The rapid spread of the G614 mutant suggests that it may have a transmission advantage over the D614 wildtype.

Our objective was to estimate the transmission advantage of D614G by integrating phylogenetic and epidemiological analysis.

We assume that the mutation D614G was the only site of interest which characterised the two cocirculating virus strains by June 2020, but their differential transmissibility might be attributable to a combination of D614G and other mutations. We define the fitness of G614 as the ratio of the basic reproduction number of the strain with G614 to the strain with D614 and applied an epidemiological framework for fitness inference to analyse SARS-CoV-2 surveillance and sequence data.

Using this framework, we estimated that the G614 mutant is 31% (95% credible interval: 28–34) more transmissible than the D614 wildtype. Therefore, interventions that were previously effective in containing or mitigating the D614 wildtype (e.g. in China, Vietnam and Thailand) may be less effective against the G614 mutant.

Our framework can be readily integrated into current SARS-CoV-2 surveillance to monitor the emergence and fitness of mutant strains such that pandemic surveillance, disease control and development of treatment and vaccines can be adjusted dynamically.

COVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.

To document and assess the COVID-19 mortality surveillance in Belgium.

We described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.

The participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.

Belgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of ‘COVID-19-related deaths’ in a context of limited testing capacity has provided timely information about the severity of the epidemic.

Many countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity.

We aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours.

We conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020.

Among the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%.

The lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.