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Wuhan was the epicentre of the COVID-19 outbreak in China. We aimed to determine the seroprevalence and kinetics of anti-SARS-CoV-2 antibodies at population level in Wuhan to inform the development of vaccination strategies. In this longitudinal cross-sectional study, we used a multistage, population-stratified, cluster random sampling method to systematically select 100 communities from the 13 districts of Wuhan. Households were systematically selected from each community and all family members were invited to community health-care centres to participate. Eligible individuals were those who had lived in Wuhan for at least 14 days since Dec 1, 2019. All eligible participants who consented to participate completed a standardised electronic questionnaire of demographic and clinical questions and self-reported any symptoms associated with COVID-19 or previous diagnosis of COVID-19. A venous blood sample was taken for immunological testing on April 14–15, 2020. Blood samples were tested for the presence of pan-immunoglobulins, IgM, IgA, and IgG antibodies against SARS-CoV-2 nucleocapsid protein and neutralising antibodies were assessed. We did two successive follow-ups between June 11 and June 13, and between Oct 9 and Dec 5, 2020, at which blood samples were taken. Of 4600 households randomly selected, 3599 families (78·2%) with 9702 individuals attended the baseline visit. 9542 individuals from 3556 families had sufficient samples for analyses. 532 (5·6%) of 9542 participants were positive for pan-immunoglobulins against SARS-CoV-2, with a baseline adjusted seroprevalence of 6·92% (95% CI 6·41–7·43) in the population. 437 (82·1%) of 532 participants who were positive for pan-immunoglobulins were asymptomatic. 69 (13·0%) of 532 individuals were positive for IgM antibodies, 84 (15·8%) were positive for IgA antibodies, 532 (100%) were positive for IgG antibodies, and 212 (39·8%) were positive for neutralising antibodies at baseline. The proportion of individuals who were positive for pan-immunoglobulins who had neutralising antibodies in April remained stable for the two follow-up visits (162 [44·6%] of 363 in June, 2020, and 187 [41·2%] of 454 in October–December, 2020). On the basis of data from 335 individuals who attended all three follow-up visits and who were positive for pan-immunoglobulins, neutralising antibody levels did not significantly decrease over the study period (median 1/5·6 [IQR 1/2·0 to 1/14·0] at baseline vs 1/5·6 [1/4·0 to 1/11·2] at first follow-up [p=1·0] and 1/6·3 [1/2·0 to 1/12·6] at second follow-up [p=0·29]). However, neutralising antibody titres were lower in asymptomatic individuals than in confirmed cases and symptomatic individuals. Although titres of IgG decreased over time, the proportion of individuals who had IgG antibodies did not decrease substantially (from 30 [100%] of 30 at baseline to 26 [89·7%] of 29 at second follow-up among confirmed cases, 65 [100%] of 65 at baseline to 58 [92·1%] of 63 at second follow-up among symptomatic individuals, and 437 [100%] of 437 at baseline to 329 [90·9%] of 362 at second follow-up among asymptomatic individuals). 6·92% of a cross-sectional sample of the population of Wuhan developed antibodies against SARS-CoV-2, with 39·8% of this population seroconverting to have neutralising antibodies. Our durability data on humoral responses indicate that mass vaccination is needed to effect herd protection to prevent the resurgence of the epidemic. Chinese Academy of Medical Sciences & Peking Union Medical College, National Natural Science Foundation, and Chinese Ministry of Science and Technology. For the Chinese translation of the abstract see Supplementary Materials section.

Since the abolition of EU milk quotas in 2015, the Irish dairy industry has expanded with a 16.6% increase in calf births since 2011. Calf losses have major implications for the economic viability and sustainability of dairy enterprises. There is a paucity of literature on mortality in calves from birth to six months, particularly at a national herd level. Previous studies have tended to focus on herd size as a risk factor for calf mortality rather than the possible influence of herd expansion. The purpose of this study is to quantify any association between dairy herd expansion and the risk of being classified as a high or low calf mortality herd based on analysis of national dairy herd identification and movement records in Ireland from 2016-2020. In calves aged under 6 months, herds that expanded > 20% (OR 1.23 95% CI: 1.10-1.37, p < 0.001) and > 45% (OR 1.22, 95% CI:1.09-1.36, p = 0.001), were more likely to have > 10% herd calf mortality, compared to herds that did not increase in size. Newly established herds were more likely to have poor mortality outcomes (OR 2.44, 95% CI: 1.82-3.29, p < 0.001) compared to herds that did not increase in size. Herd expansion < 20% was not associated with mortality outcome. Herd ordinal location and herd size were significant risk factors for > 10% herd calf mortality. This study has demonstrated that herds that have expanded > 20% over five years and newly established herds were more likely to have poor mortality outcomes. It suggests that new entrants into dairy farming may benefit from targeted emphasis on herd health management. The results also highlight the value of national data as a tool to determine optimisation of farm interventions and surveillance and policy decisions to prioritise animal health and welfare.

We investigated what proportion of the population acquired severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whether the herd immunity threshold has been reached in 10 communities in Qatar. The study included 4,970 participants during June 21-September 9, 2020. Antibodies against SARS-CoV-2 were detected by using an electrochemiluminescence immunoassay. Seropositivity ranged from 54.9% (95% CI 50.2%-59.4%) to 83.8% (95% CI 79.1%-87.7%) across communities and showed a pooled mean of 66.1% (95% CI 61.5%-70.6%). A range of other epidemiologic measures indicated that active infection is rare, with limited if any sustainable infection transmission for clusters to occur. Only 5 infections were ever severe and 1 was critical in these young communities; infection severity rate of 0.2% (95% CI 0.1%-0.4%). Specific communities in Qatar have or nearly reached herd immunity for SARS-CoV-2 infection: 65%-70% of the population has been infected.

Herd immunity, where a pathogen can no longer efficiently spread in a population, is achieved when a large proportion of the population becomes immune, making the spread of infection from person to person unlikely and protecting those without immunity. Despite the global spread of SARS-CoV-2, the failure of virus- and vaccine-induced immunity to prevent transmission, combined with the emergence of antigenically distinct variants, has made herd immunity to SARS-CoV-2 unachievable thus far. Where does this leave us?Herd immunity to SARS-CoV-2 has not materialized. In this Comment, David Goldblatt discusses the underlying reasons and their implications.

Broadly neutralizing antibodies against HIV can be rapidly generated by immunizing cows.

Herd immunity is a key concept for epidemic control. It states that only a proportion of a population needs to be immune (through overcoming natural infection or through vaccination) to an infectious agent for it to stop generating large outbreaks. A key question in the current COVID-19 pandemic is how and when herd immunity can be achieved and at what cost.During the current COVID-19 pandemic, the concept of herd immunity has become a topic of much debate. This Comment examines the factors that determine it, discusses how far we have come and considers what it will take to reach herd immunity safely.

Background: The viral main protease (M[sup.pro]) of SARS-CoV-2 has been recently proposed as a key target to inhibit virus replication in the host. Therefore, molecules that can bind the catalytic site of M[sup.pro] could be considered as potential drug candidates in the treatment of SARS-CoV-2 infections. Here we proposed the application of a state-of-the-art analytical platform which combines metabolomics and protein structure analysis to fish-out potential active compounds deriving from a natural matrix, i.e., a blueberry extract. Methods: The experiments focus on finding MS covalent inhibitors of M[sup.pro] that contain in their structure a catechol/pyrogallol moiety capable of binding to the nucleophilic amino acids of the enzyme’s catalytic site. Results: Among the potential candidates identified, the delphinidin-3-glucoside showed the most promising results. Its antiviral activity has been confirmed in vitro on Vero E6 cells infected with SARS-CoV-2, showing a dose-dependent inhibitory effect almost comparable to the known M[sup.pro] inhibitor baicalin. The interaction of delphinidin-3-glucoside with the M[sup.pro] pocket observed was also evaluated by computational studies. Conclusions: The HRMS analytical platform described proved to be effective in identifying compounds that covalently bind M[sup.pro] and are active in the inhibition of SARS-CoV-2 replication, such as delphinidin-3-glucoside.

Vaccination protects individuals directly and communities indirectly by reducing transmission. We aimed to determine whether information about herd immunity and local vaccination coverage could change an individual’s vaccination plans and concern about influenza. We surveyed Minnesota residents ≥18 years during the 2016 Minnesota State Fair. Participants were asked to identify the definition of herd immunity, to report their history of and plans to receive influenza vaccine, to report their concern about influenza, and to estimate the reported influenza vaccination coverage in their county. After providing educational information about herd immunity and local vaccination rates, we reassessed vaccination plans and concerns. We used logistic regression to estimate predicted percentages for those willing to be vaccinated, for concern about influenza, and for changes in these outcomes after the intervention. We then compared those individuals with and without prior knowledge of herd immunity, accounting for other characteristics. Among 554 participants, the median age was 57 years; most were female (65.9%), white (91.0%), and non-Hispanic/Latino (93.9%). Overall, 37.2% of participants did not know about herd immunity and 75.6% thought that the influenza vaccination coverage in their county was higher than it was reported. Those not knowledgeable about herd immunity were significantly less likely than those knowledgeable about the concept to report plans to be vaccinated at baseline (67.8% versus 78.9%; p = 0.004). After learning about herd immunity and influenza vaccination coverage, the proportion of those not knowledgeable about herd immunity who were willing to be vaccinated increased significantly by 7.3 percentage points (p = 0.001). Educating participants eliminated the significant difference in the proportion planning to be vaccinated between these two groups (80.1% of those knowledgeable and 75.1% of those who were not initially knowledgeable became willing; p = 0.148). Education about herd immunity and local vaccination coverage could be a useful tool for increasing willingness to vaccinate, generating benefits both to individuals and communities.

It has been suggested, without rigorous mathematical analysis, that the classical vaccine-induced herd immunity threshold (HIT) assuming a homogeneous population can be substantially higher than the minimum HIT obtained when considering population heterogeneities. We investigated this claim by developing, and rigorously analyzing, a vaccination model that incorporates various forms of heterogeneity and compared it with a model that considers a homogeneous population. By employing a two-group vaccination model in heterogeneous populations, we theoretically established conditions under which heterogeneity leads to different HIT values, depending on the relative values of the contact rates for each group, the type of mixing between the groups, the relative vaccine efficacy, and the relative population size of each group. For example, under biased random mixing assumption and when vaccinating a given group results in disproportionate prevention of higher transmission per capita, we show that it is optimal to vaccinate that group before vaccinating the other groups. We also found situations, under biased assortative mixing assumption, where it is optimal to vaccinate more than one group. We show that regardless of the form of mixing between the groups, the HIT values assuming a heterogeneous population are always lower than the HIT values obtained from a corresponding model with a homogeneous population. Using realistic numerical examples and parametrization (e.g., assuming assortative mixing together with vaccine efficacy of 95% and the value of the basic reproduction number, R0, of the model set at R0= 2.5), we demonstrate that the HIT value generated from a model that considers population heterogeneity (e.g., biased assortative mixing) is significantly lower (40%) compared with a HIT value of 63% obtained if the model uses homogeneous population.